INFO1105_Data structure_2012 Semester 2_w05

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INFO1105_Data structure_2012 Semester 2_w11(1)

INFO1x05Tutorial11Graph Algorithms Exercise1:Draw an adjacency list and adjacency matrix representation of the undirected graph shown in the ﬁgure below.Exercise2:Suppose we represent a graph G having n vertices and m edges with the edge list structure.Why, in this case,does the insertVertex method run in O(1)time while the removeVertex method runs in O(m)time?Exercise3:Let G be a graph whose vertices are the integers1through8,and let the adjacent vertices of each vertex be given by the table below:vertex adjacent vertices1(2,3,4)2(1,3,4)3(1,2,4)4(1,2,3,6)5(6,7,8)6(4,5,7)7(5,6,8)8(5,7)Assume that,in a traversal of G,the adjacent vertices of a given vertex are returned in the same order as they are listed in the table above.1.Draw G.2.Give the sequence of vertices of G visited using a DFS traversal starting at vertex1.3.Give the sequence of vertices visited using a BFS traversal starting at vertex1.Exercise4:George claims he has a fast way to do path compression in a tree-based partition union-ﬁnd structure, starting at a node v.He puts v into a list L,and starts following parent pointers.Each time he encounters a new node,u,he adds u to L and updates the parent pointer of each node in L to point to u’s parent.Show that George’s algorithm runs inΩ(h2)time on a path of length h.Exercise5:Describe,in pseudocode,how to perform path compression on a path of length h in O(h)time in a tree-based union-ﬁnd structure.Exercise6:You have been employed as a surveyer for the Archipelago of Setland.You are given a list of all the towns in Setland,and a list of the pairs of towns connected directly by a road.For example:Towns=[t0,t1,t2,t3,t4,t5,t6,t7]Roads=[(t0,t1),(t0,t2),(t5,t4),(t3,t4),(t3,t5),(t6,t7)] Every island has at least two towns and one road,and there are no roads built across water.Design an algorithm in pseudocode that uses union-ﬁnd to count the number of islands.Exercise7:Write a class implementing a simpliﬁed graph ADT that has only methods relevant to undirected graphs and does not include update methods,using the adjacency matrix structure.Your class should include a constructor method that takes two collections(for example,sequences)-a collection V of vertex elements and a collection E of pairs of vertex elements-and produces the graph G that these two collections represent.Exercise8:Implement the simpliﬁed graph ADT described in the previous exercise,using the adjacency list structure.。

Academic Word List sublists

Sublists of the Academic Word ListEach word in italics is the most frequently occurring member of the word family in the Academic Corpus.For example, analysis is the most common form of the word family analyse. 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assignassignedassigningassignmentassignmentsassignsreassignreassignedreassigningreassignsunassigned attachattachedattachesattachingattachmentattachmentsunattachedauthorauthoredauthoringauthorsauthorshipbondbondedbondingbondsbriefbrevitybriefedbriefingbrieflybriefscapablecapabilitiescapabilityincapablecitecitationcitationscitedcitingcitescooperatecooperatedcooperatescooperatingcooperationcooperativecooperativelyco-operateco-operatedco-operatesco-operationco-operativeco-operativelydiscriminatediscriminateddiscriminatesdiscriminatingdiscriminationdisplaydisplayeddisplayingdisplaysdiversediverselydiversificationdiversifieddiversifiesdiversifydiversifyingdiversitydomaindomainsediteditededitingeditioneditionseditoreditorialeditorialseditorseditsenhanceenhancedenhancementenhancesenhancingestateestatesexceedexceededexceedingexceedsexpertexpertiseexpertlyexpertsexplicitexplicitly federalfederationfederations feefeesflexibleflexibilityinflexibleinflexibility furthermore gendergenders 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structures

Accessing Structure Members
There are two methods to access structure members. The first method is to access a structure member by structure name.
Method 1.
Using structure variable name, dot operator (.) and the name of the member field.
struct Student s; s.id = 101;
Example: (Accessing structure members by structure name)
struct Student { int id; char name[32]; }; ... struct Student s;
s is a variable of struct Student type with two members id and name.
2) Declaring a structure without using a tag ቤተ መጻሕፍቲ ባይዱame.
Or
struct Student { int id; char name[32]; }; ... typedef struct Student student_t; ... student_t s; // struct Student s;
student_t is the type of struct Student.
s.id); ); and name\n”);
s.id); );
Accessing Structure Members (Cont.)

OperationsManagementWilliamStevenson,10thed.a.）

POM102:P RODUCTION /O PERATIONS M ANAGEMENTCOURSE SYLLABUSCourse Catalog: POM 102Course Title: Quantitative Methods & Production/Operations ManagementDepartment: Department of Quantitative Methods and Information TechnologySchool: John Gokongwei School of ManagementSchool Year: SY 2012-2013Semester: Junior Term Abroad First SemesterCredit: 3 Units [Major Subject]A. Course DescriptionThis course aims to provide the student with an analytical approach to the economic problems of planning and deploying human resources, materials, plus facilities and equipment to generate goods and/or services for the marketplace. Course emphasis will be on the application of the analytical tools to address critical issues related to strengthening the competitive position of the enterprise, such as: product or service design, process engineering and work systems design, management of technology and innovation, environment-friendly design, capacity planning, plant location and facilities layout, logistics and supply chain management, total quality management, operations scheduling, and performance management.B. Course ObjectiveBy the end of this course, the student should be able to understand and appreciate the basic concepts of Production/Operations Management; know its importance in the success of the business; and learn the major POM concepts, quantitative tools and techniques that are used in tactical and strategic decisions. Other main objectives will include:• To understand the role and contribution of operations towards achieving competitive advantage in the marketplace.• To understand the relationship between operations and other business functions, such as Marketing, Finance, Accounting, and Human Resources.• To understand and apply systematic approaches (qualitative and quantitative) in designing and managing operationsC. Textbook and Readings Requirements:Required Readings Operations ManagementWilliam Stevenson, 10th ed.Supplementary Readings a.)Operations ManagementJay Heizer and Barry Render, 2008, 9th Edition b.)Operations ManagementRoberta Russell and Bernard Taylor, 2011, 7th Edition c.)Operations ManagementLee Krajewski and Larry Ritzman, 7th ed.D. Course Outline (not in order in which they will be discussed)Qualitative Topics Quantitative TopicsChapter 1: Introduction to Operations ManagementChapter 2: Competitiveness, Strategy & ProductivityChapter 3: Forecasting Forecasting MethodsChapter 4: Product and Service Design ReliabilityChapter 5: Capacity Planning Linear ProgrammingChapter 6: Process Selection and Facilities Layout Line Balancing, ProcessLayoutsChapter 7: Design of Work SystemsChapter 8: Location Planning and Analysis Factor Rating, TransportationModelChapter 9: Management of Quality Statistical Process ControlChapter 10: Quality Control Acceptance SamplingChapter 11: Supply-Chain ManagementChapter 12: Inventory Management Inventory ModelsChapter 13: Aggregate Planning Aggregate Planning StrategiesChapter 14: Material Requirements Planning (MRP) MRP AlgorithmChapter 15: Lean OperationsChapter 16: Short-Term Scheduling Scheduling AlgorithmChapter 17: Project Management PERT – CPM ModelsChapter 18 Waiting Lines Waiting Line Models*** Different books have different Chapter numbers, so Focus on the Topic, not the Chapter numbers.E. Course Requirements & Grade EquivalentsRequirements Long Exams (3-5) Final Group Project: Partial Papers (3) & Final Paper Final Presentation Total: Weight 75% 15% 10% 100% Final Grade Equivalents3.76 –4.00 A3.31 – 3.75 B+2.81 –3.30 B2.31 – 2.80 C+1.81 –2.30 C1.00 – 1.80 DBelow 1.00 FF. Classroom Policies1.Attendance: The course will meet twice a week. The highly accelerated pace of this courserequires students to accept a great deal of responsibility for achieving their own learning outcomes.While in class, students are expected to actively participate in discussions and group activities, and not just listen to lecture. Outside class time, students are expected to spend hours of preparation which will include reading assignments, homework preparations, research, and group meetings.2.Class Participation: Each learner is expected to actively participate in discussions on theassumption that each brings a wide range of experiences to the learning process. Active participation may include asking thoughtful questions, being willing to consider new ideas, helping the class understand complex ideas, having a cooperative attitude and a sense of humor, and helping others comprehend the material. However, consideration of other students is strongly encouraged to avoid dominating class discussions.3.Written Assignments: An important component of this course is the completion of writtenassignments by students. All written work is expected to meet college level basic writing skills.Case Studies are the primary method to evaluate student progress in this course. Learners are encouraged to apply case materials to their project papers.4.Presentations: Presentations on assigned case studies and applications papers will be made in thisclass. Students will be required to prepare written analyses of each assigned case and will also be required to present in class. Presentations made are to be professional in nature. The presentations should be well organized, with the topic thoroughly covered with all Case Study questions answered. Handouts and visual aids are to be professional looking and appropriate for the material to be covered. Presentations should not exceed the time given by the faculty.5.ACADEMIC INTEGRITY POLICY: Every student is responsible to know the standards ofconduct and expectations of academic integrity that apply to undertakings. Academic dishonesty will not be tolerated and will result in the maximum penalty as defined in the Student Handbook:1.Cheating during exams2.Submitting spurious reports copied from pervious materials other than his/her own.3.Copying another student’s work including assignments and reports4.Receiving assistance from anyone else with take-home quizzes.5.PlagiarismG. The Group Project: Operations Plan•Each group is required to submit partial project papers to serve as periodic updates of their progress in completing the Operations Plan. These project papers will begraded.•The final written paper should follow the format discussed in class. There will be a mock defense (classroom presentation of the Operations Plan) prior to the final oralpresentation. The final oral presentation will be graded by an outside panel ofjudges.•Each student will be asked to force rank their group members at the end of the semester. Grades for group work will be adjusted upward or downward to accountfor each individual’s relative contribution to the group effort.H. Final Start-up Operations Paper1.You are tasked to develop a business plan for a new product or service, with emphasis on eachtopics discussed in Operations Management.2.Be sure you have the contacts that will help you in your operations startup project.3.****************************************4.For this semester’s operations plan, you are doing a startup business with a capitalization of 5Million initial asset investment.5.Be guided with the due dates for the submission of your partial papers and final paper.6.Mock presentations will be on June 18-22, 2012. Final presentation will be on the 1st week ofJuly.I. Due Dates:Partial Paper Contents Due Date PartialPaper # 1 Product Design, Process Design, Demand Forecasting May 7Partial Paper # 2 Capacity Planning, Location Planning, Facilities Layout, HumanResource Mgt. May 21First Draft Quality Mgt, Supply Chain, Inventory Mgt, Scheduling, Costing June 4Final Paper July 2 *** Submit hardcopy and softcopy (*******************& ****************)on or before 4pm for all Partial Papers and Final Paper***J.Internet Sources:1.) Log in to either/group/mgt2014 or /group/lm2014 and join the group. This will be our official yahoo group for the entire batch of Mgt Standard or Legal Management students. This is where I will make all my announcements for your batch.2.)Log in to /group/pom102-104and join the group. Just type inyour name and once verified, I will allow you to join the group.3.)You can access and download the Power Point slides and other Opman stuffs from Yahoo Mail.Login name: POM102104Password: ateneoThe teacher reserves the right to raise a student’s grade if in his judgment, a particularstudent’s overall performance, behavior and character merits this recognition. Theteacher, of course, has no right to pull down any student’s grade point achievement.Good Luck and Enjoy the Semester!!Michael C. Tan, MBAInstructor, JGSOM, QMIT DepartmentBS Mgt & LM Program DirectorEmail:****************,*******************Cellnumber*************POM 102/104: Start-up Operations Management Paper Outline•Very Brief Industry Background -- (Just a SUMMARY! Not included in the Opman Panel grading.No need to complete all the details.)1.Industry Analysis – Major players and developmental trends.2.Target Market - Can you describe the customer base in such terms as age, income, lifestyle, orsimilar dimensions? What is the projected growth in the primary customer base over the nextfive years? What is the frequency of the purchase? Are brands important to the customers?petition Analysis - Who are the primary competitors, and what are their market shares?What are the operations and marketing strategies of the various competitors?•Product / Service Design -- What are the products or the services you will offer? (Describe in full details!!) Why did you choose that product? (Do market research!!) How “unique” is your product/service? Describe the life-cycle of your product/service.•Demand Forecasting - Indicate what you are forecasting. (product or service) Discuss methodology.Present research data from Surveys, Population Data, Foot Counting, & Benchmarking. Analyze your data. Check for behaviors and patterns like trend, seasonality & variations. Finally, present your forecast.•Location Planning1.Location Requirements (What are the factors that you are looking for your location? Explain.)2.Choices of Location (Provide a very detailed address and sketch of your location, if possible,pictures of the locations).3.Factor Rating Method in arriving the decision.4.Explain fully the discrepancies in each score for each location for each factor.•Process Design -- Do a Make or Buy Analysis for each step of the process and provide BASIS for deciding to Make or Buy. Explain the detailed processes from opening to closing including employee involvement. Provide a detailed process flow chart.•Capacity Planning -- What is your limiting capacity? How flexible is your capacity?1.Provide some pictures of the machines or equipment used. For each machine: Explain the simpleuse of that machine in your production process. Give your suppliers and their quotations of the prices. What is your choice among the suppliers? Why? --Be sure to give explanations why you choose that particular machine or equipment. Identify the capacity of your chosen type/brand/model of that machine.2.From the processes involved, identify your limiting capacity. Do capacity planning.pute your design, effective & actual capacity estimates.4.Match actual capacity with demand forecast. Evaluate.5.If capacity utilization percentage is high, how can you expand capacity?•Facilities Layout -- Describe your layout and provide BASIS. (The reader should be able to visualize your layout without looking at your floor plan. Be sure to have the RESTROOMS and the FIRE EXITS in your layout.) Provide Facilities Layout Floor Plan with proper scaling.•Design of Work Systems - Who is your most important employee and how do you recruit, train and retain him (from being pirated)?1.Identify the workforce needed (Simple Org Chart). Give detailed job design.2.Explain selection process, recruitment process and training process.3.Explain compensation package. Indicate performance management system.4.Explain the current working conditions.•Supply Chain Management - Identify your prospective suppliers and provide BASIS why you chose them. How does the company manage the flow of information and materials from suppliers through production and distribution to end-users?•Inventory Management - How many days’ supply is your safety stock of finished goods/ work in process/raw materials inventory?1.Identify all the inventories maintained. ( raw materials, work-in-process, finished products)2.Replenishment parameters (lead time, buffer stock, order policy)? Procurementmethods/practices?3.Identify the needed safety stock. (Be sure to show all your explanations or computations.)What is your service level?4.Inventory Counting System? Discuss inventory control.•Aggregate Planning: Make an aggregate plan based on your preferred strategy.•Materials Requirements Planning:Make an MRP table for your products. Provide explanation on the details used for computation.•Scheduling: Prepare GANTT Charts for pre-operational and operational scheduling.•Total Quality Management: How do you check the quality of your product/service? Identify dimensions and determinants of quality. Discuss the impact of quality on costing. Discuss method of inspection. How do you maintain your machines in good condition? Discuss waste disposal system.•Financial Statements / Costing -- Were you able to produce the same quality product (like your competitor) at a lower cost? Compute the initial outlay and total expenses for the first year of operations.Compute initial investment, break-even analysis and detailed computation of cost.If possible, compute income statement and do capital budgeting analysis.Group I_____________________________________ Group II_____________________________________Group 1 Group 2 CONTENT ( Operations Strategy ) 75 %1.Product & Service Design ( 9 points )•Was the product user-friendly? Was the service customer-friendly?•Was the proposed product/service design “manufacturable” or “feasible”?2.Forecasting ( 9 points )•Did the group gather adequate and appropriate external data to serve as the basisfor their forecast? Did the group use the proper forecasting technique? Were theforecasts achievable or realistic?3.Location Planning ( 8 points )•Did the group choose the appropriate location for the business?•Did they use the appropriate criteria in selecting their proposed location?4.Process Design ( 9 points )•Did the group have a clear understanding of the whole process of theirproduct/service design? Was the proposed production process efficient? Did thegroup select the optimal process design?5.Capacity Planning ( 9 points )•Was the capacity planning accurate? Would capacity be able to produce theprojected forecast? Was there any difference between the forecast and thecapacity? Did the group make any adjustment in the capacity (like doingovertime work or having additional workforce) to ensure production?6.Facilities Layout ( 8 points )•Would the workplace layout produce efficient production results? Was the spacemaximized? Were the facilities properly placed in the layout?7.Design of Work Systems & Scheduling ( 8 points )•Was the number of workers enough to be able to operate the whole business?Were workers given enough compensation and benefits? Were workers trained tobecome efficient?8.Inventory Management & Aggregate Planning & Materials Requirements Planning (5 pts. )•Did the group have efficient inventory management? Was the system efficientenough to avoid stock outs and overstocking of finished goods/ work in process/raw materials inventory?9.Quality Control ( 5 points )•Was the group able to tackle quality control issues adequately? Were the qualitycontrol measures appropriate?10.Financial Statements ( 5 points )•Was the group able to estimate the production costs? Is this business aworthwhile investment?PRESENTATION 25 %1.PRESENTATION STYLE & COMMUNICATION SKILLS (15 points )•Were the visual aids used appropriate to their concept? Was there teamworkbetween the members of the group? Was the presentation clear and consistent?Was the thought/message organized logically? Was the presentation doneprofessionally?2. ORAL DEFENSE (10 points )•Did all the members of the group reflect an adequate understanding of theirproject? Was the group able to adequately respond to the issues raised by thepanelists?TOTAL RAW SCORE: ( 100 POINTS )LETTER GRADE EQUIVALENT:。

structure 使用说明

Documentation for structure software:Version2.3Jonathan K.Pritchard aXiaoquan Wen aDaniel Falush b123a Department of Human GeneticsUniversity of Chicagob Department of StatisticsUniversity of OxfordSoftware from/structure.htmlApril21,20091Our other colleagues in the structure project are Peter Donnelly,Matthew Stephens and Melissa Hubisz.2Theﬁrst version of this program was developed while the authors(JP,MS,PD)were in the Department of Statistics,University of Oxford.3Discussion and questions about structure should be addressed to the online forum at structure-software@.Please check this document and search the previous discus-sion before posting questions.Contents1Introduction31.1Overview (3)1.2What’s new in Version2.3? (3)2Format for the dataﬁle42.1Components of the dataﬁle: (4)2.2Rows (5)2.3Individual/genotype data (6)2.4Missing genotype data (7)2.5Formatting errors (7)3Modelling decisions for the user73.1Ancestry Models (7)3.2Allele frequency models (12)3.3How long to run the program (13)4Missing data,null alleles and dominant markers144.1Dominant markers,null alleles,and polyploid genotypes (14)5Estimation of K(the number of populations)155.1Steps in estimating K (15)5.2Mild departures from the model can lead to overestimating K (16)5.3Informal pointers for choosing K;is the structure real? (16)5.4Isolation by distance data (17)6Background LD and other miscellania176.1Sequence data,tightly linked SNPs and haplotype data (17)6.2Multimodality (18)6.3Estimating admixture proportions when most individuals are admixed (18)7Running structure from the command line197.1Program parameters (19)7.2Parameters inﬁle mainparams (19)7.3Parameters inﬁle extraparams (21)7.4Command-line changes to parameter values (25)8Front End268.1Download and installation (26)8.2Overview (27)8.3Building a project (27)8.4Conﬁguring a parameter set (28)8.5Running simulations (30)8.6Batch runs (30)8.7Exporting parameterﬁles from the front end (30)8.8Importing results from the command-line program (31)8.9Analyzing the results (32)9Interpreting the text output339.1Output to screen during run (34)9.2Printout of Q (34)9.3Printout of Q when using prior population information (35)9.4Printout of allele-frequency divergence (35)9.5Printout of estimated allele frequencies(P) (35)9.6Site by site output for linkage model (36)10Other resources for use with structure3710.1Plotting structure results (37)10.2Importing bacterial MLST data into structure format (37)11How to cite this program37 12Bibliography371IntroductionThe program structure implements a model-based clustering method for inferring population struc-ture using genotype data consisting of unlinked markers.The method was introduced in a paper by Pritchard,Stephens and Donnelly(2000a)and extended in sequels by Falush,Stephens and Pritchard(2003a,2007).Applications of our method include demonstrating the presence of popu-lation structure,identifying distinct genetic populations,assigning individuals to populations,and identifying migrants and admixed individuals.Brieﬂy,we assume a model in which there are K populations(where K may be unknown), each of which is characterized by a set of allele frequencies at each locus.Individuals in the sample are assigned(probabilistically)to populations,or jointly to two or more populations if their genotypes indicate that they are admixed.It is assumed that within populations,the loci are at Hardy-Weinberg equilibrium,and linkage equilibrium.Loosely speaking,individuals are assigned to populations in such a way as to achieve this.Our model does not assume a particular mutation process,and it can be applied to most of the commonly used genetic markers including microsatellites,SNPs and RFLPs.The model assumes that markers are not in linkage disequilibrium(LD)within subpopulations,so we can’t handle markers that are extremely close together.Starting with version2.0,we can now deal with weakly linked markers.While the computational approaches implemented here are fairly powerful,some care is needed in running the program in order to ensure sensible answers.For example,it is not possible to determine suitable run-lengths theoretically,and this requires some experimentation on the part of the user.This document describes the use and interpretation of the software and supplements the published papers,which provide more formal descriptions and evaluations of the methods.1.1OverviewThe software package structure consists of several parts.The computational part of the program was written in C.We distribute source code as well as executables for various platforms(currently Mac,Windows,Linux,Sun).The C executable reads a dataﬁle supplied by the user.There is also a Java front end that provides various helpful features for the user including simple processing of the output.You can also invoke structure from the command line instead of using the front end.This document includes information about how to format the dataﬁle,how to choose appropriate models,and how to interpret the results.It also has details on using the two interfaces(command line and front end)and a summary of the various user-deﬁned parameters.1.2What’s new in Version2.3?The2.3release(April2009)introduces new models for improving structure inference for data sets where(1)the data are not informative enough for the usual structure models to provide accurate in-ference,but(2)the sampling locations are correlated with population membership.In this situation, by making explicit use of sampling location information,we give structure a boost,often allowing much improved performance(Hubisz et al.,2009).We hope to release further improvements in the coming months.loc a loc b loc c loc d loc eGeorge1-914566092George1-9-964094Paula110614268192Paula110614864094Matthew2110145-9092Matthew2110148661-9Bob210814264194Bob2-9142-9094Anja1112142-91-9Anja111414266194Peter1-9145660-9Peter1110145-91-9Carsten2108145620-9Carsten211014564192Table1:Sample dataﬁle.Here MARKERNAMES=1,LABEL=1,POPDATA=1,NUMINDS=7, NUMLOCI=5,and MISSING=-9.Also,POPFLAG=0,LOCDATA=0,PHENOTYPE=0,EX-TRACOLS=0.The second column shows the geographic sampling location of individuals.We can also store the data with one row per individual(ONEROWPERIND=1),in which case theﬁrst row would read“George1-9-9145-96664009294”.2Format for the dataﬁleThe format for the genotype data is shown in Table2(and Table1shows an example).Essentially, the entire data set is arranged as a matrix in a singleﬁle,in which the data for individuals are in rows,and the loci are in columns.The user can make several choices about format,and most of these data(apart from the genotypes!)are optional.For a diploid organism,data for each individual can be stored either as2consecutive rows, where each locus is in one column,or in one row,where each locus is in two consecutive columns. Unless you plan to use the linkage model(see below)the order of the alleles for a single individual does not matter.The pre-genotype data columns(see below)are recorded twice for each individual. (More generally,for n-ploid organisms,data for each individual are stored in n consecutive rows unless the ONEROWPERIND option is used.)2.1Components of the dataﬁle:The elements of the inputﬁle are as listed below.If present,they must be in the following order, however most are optional(as indicated)and may be deleted completely.The user speciﬁes which data are present,either in the front end,or(when running structure from the command line),in a separateﬁle,mainparams.At the same time,the user also speciﬁes the number of individuals and the number of loci.2.2Rows1.Marker Names(Optional;string)Theﬁrst row in theﬁle can contain a list of identiﬁersfor each of the markers in the data set.This row contains L strings of integers or characters, where L is the number of loci.2.Recessive Alleles(Data with dominant markers only;integer)Data sets of SNPs or mi-crosatellites would generally not include this line.However if the option RECESSIVEALLE-LES is set to1,then the program requires this row to indicate which allele(if any)is recessive at each marker.See Section4.1for more information.The option is used for data such as AFLPs and for polyploids where genotypes may be ambiguous.3.Inter-Marker Distances(Optional;real)the next row in theﬁle is a set of inter-markerdistances,for use with linked loci.These should be genetic distances(e.g.,centiMorgans),or some proxy for this based,for example,on physical distances.The actual units of distance do not matter too much,provided that the marker distances are(roughly)proportional to recombination rate.The front end estimates an appropriate scaling from the data,but users of the command line version must set LOG10RMIN,LOG10RMAX and LOG10RSTART in theﬁle extraparams.The markers must be in map order within linkage groups.When consecutive markers are from diﬀerent linkage groups(e.g.,diﬀerent chromosomes),this should be indicated by the value-1.Theﬁrst marker is also assigned the value-1.All other distances are non-negative.This row contains L real numbers.4.Phase Information(Optional;diploid data only;real number in the range[0,1]).This isfor use with the linkage model only.This is a single row of L probabilities that appears after the genotype data for each individual.If phase is known completely,or no phase information is available,these rows are unnecessary.They may be useful when there is partial phase information from family data or when haploid X chromosome data from males and diploid autosomal data are input together.There are two alternative representations for the phase information:(1)the two rows of data for an individual are assumed to correspond to the paternal and maternal contributions,respectively.The phase line indicates the probability that the ordering is correct at the current marker(set MARKOVPHASE=0);(2)the phase line indicates the probability that the phase of one allele relative to the previous allele is correct(set MARKOVPHASE=1).Theﬁrst entry should beﬁlled in with0.5toﬁll out the line to L entries.For example the following data input would represent the information from an male with5unphased autosomal microsatellite loci followed by three X chromosome loci, using the maternal/paternal phase model:102156165101143105104101100148163101143-9-9-90.50.50.50.50.5 1.0 1.0 1.0where-9indicates”missing data”,here missing due to the absence of a second X chromo-some,the0.5indicates that the autosomal loci are unphased,and the1.0s indicate that the X chromosome loci are have been maternally inherited with probability1.0,and hence are phased.The same information can be represented with the markovphase model.In this case the inputﬁle would read:102156165101143105104101100148163101143-9-9-90.50.50.50.50.50.5 1.0 1.0Here,the two1.0s indicate that theﬁrst and second,and second and third X chromosome loci are perfectly in phase with each other.Note that the site by site output under these two models will be diﬀerent.In theﬁrst case,structure would output the assignment probabilities for maternal and paternal chromosomes.In the second case,it would output the probabilities for each allele listed in the inputﬁle.5.Individual/Genotype data(Required)Data for each sampled individual are arranged intoone or more rows as described below.2.3Individual/genotype dataEach row of individual data contains the following elements.These form columns in the dataﬁle.bel(Optional;string)A string of integers or characters used to designate each individualin the sample.2.PopData(Optional;integer)An integer designating a user-deﬁned population from which theindividual was obtained(for instance these might designate the geographic sampling locations of individuals).In the default models,this information is not used by the clustering algorithm, but can be used to help organize the output(for example,plotting individuals from the same pre-deﬁned population next to each other).3.PopFlag(Optional;0or1)A Booleanﬂag which indicates whether to use the PopDatawhen using learning samples(see USEPOPINFO,below).(Note:A Boolean variable(ﬂag)isa variable which takes the values TRUE or FALSE,which are designated here by the integers1(use PopData)and0(don’t use PopData),respectively.)4.LocData(Optional;integer)An integer designating a user-deﬁned sampling location(orother characteristic,such as a shared phenotype)for each individual.This information is used to assist the clustering when the LOCPRIOR model is turned on.If you simply wish to use the PopData for the LOCPRIOR model,then you can omit the LocData column and set LOCISPOP=1(this tells the program to use PopData to set the locations).5.Phenotype(Optional;integer)An integer designating the value of a phenotype of interest,foreach individual.(φ(i)in table.)(The phenotype information is not actually used in structure.It is here to permit a smooth interface with the program STRAT which is used for association mapping.)6.Extra Columns(Optional;string)It may be convenient for the user to include additionaldata in the inputﬁle which are ignored by the program.These go here,and may be strings of integers or characters.7.Genotype Data(Required;integer)Each allele at a given locus should be coded by a uniqueinteger(eg microsatellite repeat score).2.4Missing genotype dataMissing data should be indicated by a number that doesn’t occur elsewhere in the data(often-9 by convention).This number can also be used where there is a mixture of haploid and diploid data (eg X and autosomal loci in males).The missing-data value is set along with the other parameters describing the characteristics of the data set.2.5Formatting errors.We have implemented reasonably careful error checking to make sure that the data set is in the correct format,and the program will attempt to provide some indication about the nature of any problems that exist.The front end requires returns at the ends of each row,and does not allow returns within rows;the command-line version of structure treats returns in the same way as spaces or tabs.One problem that can arise is that editing programs used to assemble the data prior to importing them into structure can introduce hidden formatting characters,often at the ends of lines,or at the end of theﬁle.The front end can remove many of these automatically,but this type of problem may be responsible for errors when the dataﬁle seems to be in the right format.If you are importing data to a UNIX system,the dos2unix function can be helpful for cleaning these up.3Modelling decisions for the user3.1Ancestry ModelsThere are four main models for the ancestry of individuals:(1)no admixture model(individuals are discretely from one population or another);(2)the admixture model(each individual draws some fraction of his/her genome from each of the K populations;(3)the linkage model(like the admixture model,but linked loci are more likely to come from the same population);(4)models with informative priors(allow structure to use information about sampling locations:either to assist clustering with weak data,to detect migrants,or to pre-deﬁne some populations).See Pritchard et al.(2000a)and(Hubisz et al.,2009)for more on models1,2,and4and Falush et al.(2003a)for model3.1.No admixture model.Each individual comes purely from one of the K populations.The output reports the posterior probability that individual i is from population k.The prior probability for each population is1/K.This model is appropriate for studying fully discrete populations and is often more powerful than the admixture model at detecting subtle structure.2.Admixture model.Individuals may have mixed ancestry.This is modelled by saying that individual i has inherited some fraction of his/her genome from ancestors in population k.The output records the posterior mean estimates of these proportions.Conditional on the ancestry vector,q(i),the origin of each allele is independent.We recommend this model as a starting point for most analyses.It is a reasonablyﬂexible model for dealing with many of the complexities of real populations.Admixture is a common feature of real data,and you probably won’tﬁnd it if you use the no-admixture model.The admixture model can also deal with hybrid zones in a natural way.Label Pop Flag Location Phen ExtraCols Loc1Loc2Loc3....Loc LM1M2M3....M Lr1r2r3....r L-1D1,2D2,3....D L−1,LID(1)g(1)f(1)l(1)φ(1)y(1)1,...,y(1)n x(1,1)1x(1,1)2x(1,1)3....x(1,1)LID(1)g(1)f(1)l(1)φ(1)y(1)1,...,y(1)n x(1,2)1x(1,2)2x(1,2)3....x(1,2)Lp(1)1p(1)2p(1)3....p(1)LID(2)g(2)f(2)l(2)φ(2)y(2)1,...,y(2)n x(2,1)1x(2,1)2x(2,1)3....x(2,1)LID(2)g(2)f(2)l(2)φ(2)y(2)1,...,y(2)n x(2,2)1x(2,2)2x(2,2)3....x(2,2)Lp(2)1p(2)2p(2)3....p(2)L ....ID(i)g(i)f(i)l(i)φ(i)y(i)1,...,y(i)n x(i,1)1x(i,1)2x(i,1)3....x(i,1)LID(i)g(i)f(i)l(i)φ(i)y(i)1,...,y(i)n x(i,2)1x(i,2)2x(i,2)3....x(i,2)Lp(3)1p(3)2p(3)3....p(3)L ....ID(N)g(N)f(N)l(N)φ(N)y(N)1,...,y(N)n x(N,1)1x(N,1)2x(N,1)3....x(N,1)LID(N)g(N)f(N)l(N)φ(N)y(N)1,...,y(N)n x(N,2)1x(N,2)2x(N,2)3....x(N,2)Lp(L)1p(L)2p(L)3....p(1)LTable2:Format of the dataﬁle,in two-row format.Most of these components are optional(see text for details).M l is an identiﬁer for marker l.r l indicates which allele,if any,is recessive at each marker(dominant genotype data only).D i,i+1is the distance between markers i and i+1.ID(i) is the label for individual i,g(i)is a predeﬁned population index for individual i(PopData);f(i)is aﬂag used to incorporate learning samples(PopFlag);l(i)is the sampling location of individual i (LocData);φ(i)can store a phenotype for individual i;y(i)1,...,y(i)n are for storing extra data(ignoredby the program);(x i,1l ,x i,2l)stores the genotype of individual i at locus l.p(l)i is the phase informationfor marker l in individual i.3.Linkage model.This is essentially a generalization of the admixture model to deal with“ad-mixture linkage disequilibrium”–i.e.,the correlations that arise between linked markers in recently admixed populations.Falush et al.(2003a)describes the model,and computations in more detail.The basic model is that,t generations in the past,there was an admixture event that mixed the K populations.If you consider an individual chromosome,it is composed of a series of“chunks”that are inherited as discrete units from ancestors at the time of the admixture.Admixture LD arises because linked alleles are often on the same chunk,and therefore come from the same ancestral population.The sizes of the chunks are assumed to be independent exponential random variables with mean length1/t(in Morgans).In practice we estimate a“recombination rate”r from the datathat corresponds to the rate of switching from the present chunk to a new chunk.1Each chunkin individual i is derived independently from population k with probability q(i)k ,where q(i)kis theproportion of that individual’s ancestry from population k.Overall,the new model retains the main elements of the admixture model,but all the alleles that are on a single chunk have to come from the same population.The new MCMC algorithm integrates over the possible chunk sizes and break points.It reports the overall ancestry for each individual,taking account of the linkage,and can also report the probability of origin of each bit of chromosome,if desired by the user.This new model performs better than the original admixture model when using linked loci to study admixed populations.It achieves more accurate estimates of the ancestry vector,and can extract more information from the data.It should be useful for admixture mapping.The model is not designed to deal with background LD between very tightly linked markers.Clearly,this model is a big simpliﬁcation of the complex realities of most real admixed popu-lations.However,the major eﬀect of admixture is to create long-range correlation among linked markers,and so our aim here is to encapsulate that feature within a fairly simple model.The computations are a bit slower than for the admixture model,especially with large K and unphased data.Nonetheless,they are practical for thousands of sites and individuals and multiple populations.The model can only be used if there is information about the relative positions of the markers(usually a genetic map).ing prior population information.The default mode for structure uses only genetic information to learn about population structure.However,there is often additional information that might be relevant to the clustering(e.g.,physical characteristics of sampled individuals or geographic sampling locations).At present,structure can use this information in three ways:•LOCPRIOR models:use sampling locations as prior information to assist the clustering–for use with data sets where the signal of structure is relatively weak2.There are some data sets where there is genuine population structure(e.g.,signiﬁcant F ST between sampling locations),but the signal is too weak for the standard structure models to detect.This is often the case for data sets with few markers,few individuals,or very weak structure.To improve performance in this situation,Hubisz et al.(2009)developed new models that make use of the location information to assist clustering.The new models can often provide accurate inference of population structure and individual ancestry in data sets where the signal of structure is too weak to be found using the standard structure models.Brieﬂy,the rationale for the LOCPRIOR models is as ually,structure assumes that all partitions of individuals are approximately equally likely a priori.Since there is an immense number of possible partitions,it takes highly informative data for structure to 1Because of the way that this is parameterized,the map distances in the inputﬁle can be in arbitrary units–e.g.,genetic distances,or physical distances(under the assumption that these are roughly proportional to genetic distances).Then the estimated value of r represents the rate of switching from one chunks to the next,per unit of whatever distance was assumed in the inputﬁle.E.g.,if an admixture event took place ten generations ago,then r should be estimated as0.1when the map distances are measured in cM(this is10∗0.01,where0.01is the probability of recombination per centiMorgan),or as10−4=10∗10−5when the map distances are measured in KB(assuming a constant crossing-over rate of1cM/MB).The prior for r is log-uniform.The front end tries to make some guesses about sensible upper and lower bounds for r,but the user should adjust these to match the biology of the situation.2Daniel refers to this as“Better priors for worse data.”conclude that any particular partition of individuals into clusters has compelling statistical support.In contrast,the LOCPRIOR models take the view that in practice,individuals from the same sampling location often come from the same population.Therefore,the LOCPRIOR models are set up to expect that the sampling locations may be informative about ancestry. If the data suggest that the locations are informative,then the LOCPRIOR models allow structure to use this information.Hubisz et al.(2009)developed a pair of LOCPRIOR models:for no-admixture and for admix-ture.In both cases,the underlying model(and the likelihood)is the same as for the standard versions.The key diﬀerence is that structure is allowed to use the location information to assist the clustering(i.e.,by modifying the prior to prefer clustering solutions that correlate with the locations).The LOCPRIOR models have the desirable properties that(i)they do not tend toﬁnd struc-ture when none is present;(ii)they are able to ignore the sampling information when the ancestry of individuals is uncorrelated with sampling locations;and(iii)the old and new models give essentially the same answers when the signal of population structure is very strong.Hence,we recommend using the new models in most situations where the amount of available data is very limited,especially when the standard structure models do not provide a clear signal of structure.However,since there is now a great deal of accumulated experience with the standard structure models,we recommend that the basic models remain the default for highly informative data sets(Hubisz et al.,2009).To run the LOCPRIOR model,the user mustﬁrst specify a“sampling location”for each individual,coded as an integer.That is,we assume the samples were collected at a set of discrete locations,and we do not use any spatial information about the locations.(We recognize that in some studies,every individual may be collected at a diﬀerent location,and so clumping individuals into a smaller set of discrete locations may not be an ideal representation of the data.)The“locations”could also represent a phenotype,ecotype,or ethnic group. The locations are entered into the inputﬁle either in the PopData column(set LOCISPOP=1), or as a separate LocData column(see Section2.3).To use the LOCPRIOR model you must ﬁrst specify either the admixture or no-admixture models.If you are using the Graphical User Interface version,tick the“use sampling locations as prior”box.If you are using the command-line version,set LOCPRIOR=1.(Note that LOCPRIOR is incompatible with the linkage model.)Our experience so far is that the LOCPRIOR model does not bias towards detecting structure spuriously when none is present.You can use the same diagnostics for whether there is genuine structure as when you are not using a LOCPRIOR.Additionally it may be helpful to look at the value of r,which parameterizes the amount of information carried by the locations. Values of r near1,or<1indicate that the locations are rger values of r indicate that either there is no population structure,or that the structure is independent of the locations.•USEPOPINFO model:use sampling locations to test for migrants or hybrids–for use with data sets where the data are very informative.In some data sets,the user mightﬁnd that pre-deﬁned groups(eg sampling locations)correspond almost exactly to structure clusters,except for a handful of individuals who seem to be misclassiﬁed.Pritchard et al.(2000a)developed a formal Bayesian test for evaluating whether any individuals in the sample are immigrants to their supposed populations,or have recent immigrant ancestors.Note that this model assumes that the predeﬁned populations are usually correct.It takes quite strong data to overcome the prior against misclassiﬁcation.Before using the USEPOPINFO model,you should also run the program without population information to ensure that the pre-deﬁned populations are in rough agreement with the genetic information.To use this model set USEPOPINFO to1,and choose a value of MIGRPRIOR(which isνin Pritchard et al.(2000a)).You might choose something in the range0.001to0.1forν.The pre-deﬁned population for each individual is set in the input dataﬁle(see PopData).In this mode,individuals assigned to population k in the inputﬁle will be assigned to cluster k in the structure algorithm.Therefore,the predeﬁned populations should be integers between 1and MAXPOPS(K),inclusive.If PopData for any individual is outside this range,their q will be updated in the normal way(ie without prior population information,according to the model that would be used if USEPOPINFO was turned oﬀ.3).•USEPOPINFO model:pre-specify the population of origin of some individuals to assist ancestry estimation for individuals of unknown origin.A second way to use the USEPOPINFO model is to deﬁne“learning samples”that are pre-deﬁned as coming from particular clusters.structure is then used to cluster the remaining individuals.Note:In the Front End,this option is switched on using the option“Update allele frequencies using only individuals with POPFLAG=1”,located under the“Advanced Tab”.Learning samples are implemented using the PopFlag column in the dataﬁle.The pre-deﬁned population is used for those individuals for whom PopFlag=1(and whose PopData is in(1...K)).The PopData value is ignored for individuals for whom PopFlag=0.If there is no PopFlag column in the dataﬁle,then when USEPOPINFO is turned on,PopFlag is set to1 for all individuals.Ancestry of individuals with PopFlag=0,or with PopData not in(1...K) are updated according to the admixture or no-admixture model,as speciﬁed by the user.As noted above,it may be helpful to setαto a sensible value if there are few individuals without predeﬁned populations.This application of USEPOPINFO can be helpful in several contexts.For example,there may be some individuals of known origin,and the goal is to classify additional individuals of unknown origin.For example,we might collect data from a set of dogs of known breeds (numbered1...K),and then use structure to estimate the ancestry for additional dogs of unknown(possibly hybrid)origin.By pre-setting the population numbers,we can ensure that the structure clusters correspond to pre-deﬁned breeds,which makes the output more interpretable,and can improve the accuracy of the inference.(Of course,if two pre-deﬁned breeds are genetically identical,then the dogs of unknown origin may be inferred to have mixed ancestry.Another use of USEPOPINFO is for cases where the user wants to update allele frequen-cies using only a subset of the individuals.Ordinarily,structure analyses update the allele frequency estimates using all available individuals.However there are some settings where you might want to estimate ancestry for some individuals,without those individuals aﬀecting the allele frequency estimates.For example you may have a standard collection of learning samples,and then periodically you want to estimate ancestry for new batches of genotyped 3If the admixture model is used to estimate q for those individuals without prior population information,αis updated on the basis of those individuals only.If there are very few such individuals,you may need toﬁxαat a sensible value.。

软件工程2012SEModule1

Yang Chunting 2012 Semester 1 yangctzust@ Module 1 Slide 4
SOFTWARE
IBM Rational Rose Microsoft Project 2010: Project Standard、Project Professional、Project Server and Project Web Access Sybase PowerBuilder.
Yang Chunting 2012 Semester 1
yangctzust@ Module 1
Slide 8
About software engineering
What are the costs of software engineering? What are software engineering methods? What is CASE (Computer-Aided Software Engineering) What are the attributes of good software? What are the key challenges facing software engineering?
Yang Chunting 2012 Semester 1
yangctzust@ Module 1
Slide 9
What is software?
Computer programs and associated documentation such as requirements, design models and user manuals. Software products may be developed for a particular customer or may be developed for a general market. Software products may be

INFO1105_Data structure_2012 Semester 2_w12_stud (1)

INFO1x05Tutorial12Graph Algorithms Exercise1:Compute a topological ordering for the directed graph shown below:Exercise2:Can we use a queue instead of a stack as an auxiliary data structure in the topological sorting algorithm shown below?Why or why not?Algorithm1Topological sort1:procedure T OPOLOGICAL S ORT( G)2:S←an initially empty stack.3:for all u in G.vertices()do4:Let incounter(u)be the in-degree of u.5:if incounter(u)=0then6:S.push(u)7:end if8:end for9:i←110:while!S.isEmpty()do11:u←S.pop()12:Let u be vertex number i in the topological ordering.13:i←i+114:for all outgoing edge(u,w)of u do15:incounter(w)←incounter(w)−116:if incounter(w)=0then17:S.push(w)18:end if19:end for20:end while21:end procedureExercise3:A simple undirected graph is complete if it contains an edge between every pair of distinct vertices. What does a depth-ﬁrst search tree of a complete graph look like?Exercise4:Recalling the deﬁnition of a complete graph from the previous exercise,what does a breadth-ﬁrst search tree of a complete graph look like?Exercise5:Draw a simple connected directed graph with8vertices and16edges such that the in-degree and out-degree of each vertex is2.Show that there is a single(nonsimple)cycle that includes all the edges of your graph,that is,you can trace all the edges in their respective directions without ever lifting your pencil.(Such a cycle is called an Euler tour.)Exercise6:Repeat the previous problem and then remove one edge from the graph.Show that now there is a single(nonsimple)path that includes all the edges of your graph.(Such a path is called an Euler path.)Exercise7:Computer networks should avoid single points of failure,that is,network nodes that can disconnect the network if they fail.We say a connected graph G is biconnected if it contains no vertex whose removal would divide G into two or more connected components.Give an O(n+m)-time algorithm for adding at most n edges to a connected graph G,with n≥3vertices and m≥n−1edges,to guarantee that G is biconnected.Exercise8:A graph G is bipartite if its vertices can be partitioned into two sets X and Y such that every edge in G has one end vertex in X and the other in Y.Design and analyse an efﬁcient algorithm for determining if an undirected graph G is bipartite(without knowing the sets X and Y in advance). Exercise9:Bob loves foreign languages and wants to plan his course schedule for the following years.He is interested in the following nine language courses:LA15,LA16,LA22,LA31,LA32,LA126,LA127, LA141,and LA169.The course prerequisites are:LA15:(none)LA16:LA15LA22:(none)LA31:LA15LA32:LA16,LA31LA126:LA22,LA32LA127:LA16LA141:LA22,LA16LA169:LA32.Find the sequence of courses that allows Bob to satisfy all the prerequisites.Exercise10:Implement a topological sorting algorithm.。

1. The Art of UNIX Programming, Eric S. Raymond, Addison-Wesley, 2004.

COP 4604 UNIX System ProgrammingSection 001/Spring 2007Course Description:This is a second computer operating systems course that will give students a closer look at various functions of a computer operating system from a programmer's perspective. To gain insight into the implementation of an operating system, students will be required to do a term project byprogramming in C at least one of the major functions of an operating system.Textbook:Advanced Programming in the UNIX Environment, 2nd ed., W. Richard Stevens, Stephen A.Raqo, Addison Wesley, 2005.References:1.The Art of UNIX Programming, Eric S. Raymond, Addison-Wesley, 2004.2.UNIX Systems Programming: Concurrency, Communication, and Threads, Kay Robbins andSteven Robbins, Prentice Hall, 2003.3.Linux: The Textbook, Syed Sarwar, Robert Koretsky, and Syed Sarwar,Addison-Wesley, 2002.4.Interprocess Communications in Linux: The Nooks and Crannies, John Gray, Prentice Hall,2003.5.UNIX Network Programming, Volume 1: The Sockets Networking APIs, 3rd ed., W. RichardStevens, Bill Fenner, and Andrew M. Rudoff, Prentice Hall, 2004.6.LINUX & UNIX Programming Tools: A Primer for Software Developers, Syed Sarwar andKhaled Al-Saqabi, Addison Wesley, 2003.7.Embedded Linux: Hardware, Software, and Interfacing, Craig Hollabaugh, Addison Wesley,2002.8.The Design of the UNIX operating System, Maurice Bach, Prentice Hall, 1986.9.The Design and Implementation of the 4.4 BSD Operating System, Marshall McKusick, KeithBostic, Michael Karels and John Quarterman, Addison-Wesley, 1996.10.UNIX Internals: The New Frontiers, Uresh Vahalia, Prentice Hall, 1996.11.UNIX for Programmers and Users, Graham Glass & King Ables, 3rd ed., Prentice Hall, 2003.12.Other relevant materials by netsurfing.Instructor: Dr. Sam Hsu, S&E 404; Tel: 561/297-3728; Fax: 561/297-2800Email: sam@; WWW: /~samOffice hours: T, R: 9:00am-12:00noon; other times by appointmentCourse objectives:To develop an understanding of the various components of the UNIX/Linux operating systems froma system programmer’s perspective including both the shell and programming interfaces. Todevelop the ability to use a variety of components of the system library. More specifically,1.To learn the major characteristics of the Unix Operating System2.To learn the concepts of I/O redirection3.To be able to do file I/O4.To be able to write programs that create processes and execute other programs5.To learn how signals work and to handle signals in programs6.To learn inter-process communications, such as pipes, semaphores, shared memory, etc.7.To be able to do system programming at system-call level.Prerequisites:1.COP 3530 Data Structures and Algorithm Analysis2.COP 4610 Computer Operating Systems3.Good C programming skills4.Experience with using a UNIX operating systemPlease note: There will be a substantial amount of C programming in this course. If you are not well prepared for this, you should consider other alternative courses.Major topics:1. IntroductionHistoryStandards2. Files and directoriesFile and directory structuresPermissionsSequential and random file accessAccessing directoriesI/O redirections3. ProcessesProcess modelProcess environmentProcess creation and terminationProcess controlProcess times4. SignalsSignal conceptsCatching and handling signalsSignal system calls5. Interprocess communicationProcess synchronization and communication conceptsPipesNamed pipesSemaphoresShared memory6. Terminal I/OGetting and setting terminal attributesCanonical and noncanonical modesNonblocking I/OPseudo terminals7. ThreadsThread conceptsThread environmentThread invocation and synchronization8. Socket programmingIntro to socketsTCP/IP architectureClient/server programmingHomework & exams:Reading assignments will be given on a weekly basis. There will be several programmingassignments in C. One of them will be your term project. There will be three exams. Details about homework assignments and exams will be discussed in class later.Grading:Homework assignments 20%project 20%TermExams 60%Your final grade will be based on the scores you have earned from your homework assignments, term project, and exams, compared to the performance of other students in the class.Notes:All assignments are due at the beginning of the class on the assigned due date. No late assignment will be accepted without advance permission or a very convincing reason with relevantdocumentation. Debugging assistance for programming assignments will be given only when the program logic is clear, or enough documentation is accompanied such that debugging can become a pleasant process. You may work on any UNIX system to which you have access. However, all final versions of your work must be able to run on our CSE SUN workstations. Submission of homework assignments will be done electronically either via the instructor’s Web page or by accessing the following URL directly. Follow the screen prompts./~hwsam/student/index.html.All work in this course must be INDIVIDUAL effort unless otherwise specified.。

INFO1105_Data structure_2012 Semester 2_quiz3_1

Review Test Submission: Quiz 3∙Question 11 out of 1 pointsGiven the following function R, what is returned by R(4)?public static int R(int n) { if (n <= 1) { return 2; }if (n % 2 == 0) { return R(n-1)+2; } else { return 2*R(n-2); } }[Blank1]Specified Answer for: Blank1 6Correct Answers for: Blank1 6∙Question 21 out of 1 pointsAn initially empty queue Q has performed a total of 15 enqueue operations, 10 front operations, and 15 dequeue operations, 5 of which generatedEmptyQueueExceptions, which were caught and ignored. What is the current size ofQ?AnswerSelected Answer:5Correct Answer:5∙Question 31 out of 1 pointsAn initially empty queue Q has performed a total of 10 enqueue operations, 10 front operations, and 10 dequeue operations. What is the current size of Q?AnswerSelected Answer:Correct Answer:∙Question 40 out of 1 pointsConsider a full binary tree implemented using the array as discussed in thelectures. For the tree show below, assume that the root of the tree is storedat index 1 of its array representation. At what index is the node "d" stored? AnswerSelected Answer:4Correct Answer:5∙Question 51 out of 1 pointsAt which nodes of a min-heap can an entry with the smallest key be stored?AnswerSelected Answer:The root nodeCorrect Answer:The root node∙Question 60 out of 1 pointsSelect all statements that are true for a heap T storing seven entries with distinctkeys.AnswerSelectedAnswers: There exists a preorder traversal of T that produces the keys inincreasing order.CorrectAnswers: There exists a preorder traversal of T that produces the keys inincreasing order.There exists a postorder traversal of T that produces its keys indecreasing order.∙Question 70 out of 1 pointsConsider performing a binary search on 64 elements. How many comparisons do weneed in the worst case to find the required element? AnswerSelected Answer:5Correct Answer:7∙Question 80 out of 1 pointsConsider performing a binary search on 4 elements. How many comparisons do weneed in the worst case to find the required element?AnswerSelected Answer:2Correct Answer:3∙Question 90 out of 1 pointsConsider the pseudocode shown below. What does it do?some_method(Tree T)h = 0for each vertex v in T doif v is an external node in T thenh = max(h, depth(T, v))return hAnswerSelected Answer:Computes the depth of node vCorrect Answer:Computes the height of the tree T∙Question 101 out of 1 pointsCheck all that apply (assume worst case performance).AnswerSelectedAnswers: Insertion into a heap has a worst case time complexity of O(log n)Sorting with a binary heap takes O(n log n) assuming an optimalimplementation of a heap.CorrectAnswers: Insertion into a heap has a worst case time complexity of O(log n)Sorting with a binary heap takes O(n log n) assuming an optimalimplementation of a heap.。

micro_2012S1_final

<Year 2012 Spring Semester>
<Microeconomics: Final Exam>
(2012. 6. 19.) * Answer the questions after reading them carefully. * Please note that: (i) Answers should be written in English. (ii) Answers should be in the form of complete sentences so that the meaning is clear. (iii) Answers should be legible. (iv) When a graph is drawn, it is recommended to indicate all the information in the graph so that the meaning is clear. (v) It is recommended to show all the process for deriving answers when the calculation is needed. (vi) It is not allowed to use a calculator. (vii) Total score is 80.
6.
[6
points]

A
competitive
firm
has
the
following
short-run
cost
function:
. (1) Average variable cost is falling as output rises if output is less than and rising as output rises if output is greater than . what is the value of ? (2) The firm will supply zero output if the price is less than _____. (3) The smallest positive amount that the firm will ever supply at any price is ______.

Course Title Code

National Institute of Technology CalicutB. Tech. Degree Programme in Computer Science & EngineeringCurriculum(2003 admission Onwards)First Semester Contact hours per week Sl. No Course Title Code L G PCredits Category1 Mathematics I MA101T 3 1 0 4 BS2 Physics I SH101T3 0 0 3 BS3 Engineering Mechanics I ZZ101T 2 1 0 3 ES4 Engineering Graphics I ZZ103D 1 0 3 3 TA5 Chemistry SH103C 2 0 2 3 BS6 Professional Communication SH106T 3 0 0 3 HL7 Mechanical Engineering Workshop/ Civil Engineering Workshop ME103L/C E101L 0 0 2 1 TA8 Ph. Edn.(1Cr.),Value Education (1Cr.) National Service Scheme (1Cr.).OT - - - 3* -Total - 14 2 7 23 - Second SemesterContact hours per week Sl.No Course Title Code L G PCredits Category1 Mathematics II MA102T 3 1 0 4 BS2 Physics II SH102C 2 0 23 BS3 Engineering Mechanics II ZZ102T 2 1 0 3 ES4 Engineering Graphics II ZZ104D 1 0 3 3 TA5 Basic Electrical Engineering EE101T 2 1 0 3 ES6 Basic Electronics Engineering EC101T 2 1 0 3 ES7 Introduction to computingCS102T 2 1 0 3 ES 8 Mechanical Engineering Workshop/ Civil Engineering WorkshopME103L/ CE101L 0 0 2 1 TATotal - 16 6 7 23 -Contact hours per week Sl. No Course Title Code L G PCredits Category1 Mathematics III MA201T 3 1 0 32 Electrical Circuits and Systems EE217T3 1 0 33 Electronic Circuits and Systems EC219T 3 1 0 34 Program Design CS210T 3 1 0 35 Logic Design CS211T 3 1 0 36 Data Structures and Algorithms CS213T 3 1 0 37 Electronics Lab EC216L 0 0 3 18 Programming Lab CS217L 0 0 3 1Total - 18 6 6 20Fourth Semester Contact hours per week Sl.No Course Title Code L G PCredits Category1 Mathematics IV MA202T 3 1 0 32 Theory of ComputationCS221T 3 1 0 3 3 Discrete Computational StructuresCS212T 3 1 0 3 4 Computer Systems Software CS223T 3 1 0 35 Computer Hardware Design CS224T 3 1 0 36 Computer Organization CS225T 3 1 0 37 Data Structures Lab CS226L 0 0 3 18 Digital Systems Lab CS227L 0 0 3 1Total - 18 6 6 20 Fifth SemesterContact hours per week Sl.NoCourse Title Code L G P Credits Category 1 Software Engineering CS301T3 1 0 3 2 Communication and Information TheoryCS312T 3 1 0 3 3 Operating Systems CS313T 3 1 0 34 Principles of Programming LanguagesCS314T 3 1 0 3 5 Computational Combinatorics CS222T 3 1 0 36 Environmental Studies ZZ301Z 3 1 0 37 Hardware Lab CS316L 0 0 3 18 Operating Systems Lab CS326L 0 0 3 1Total - 18 6 6 20Contact hours per week Sl. No Course Title Code L G PCredits Category1 Principles of Management ME401T 3 1 0 32 Compiler Construction CS311T3 1 0 33 Computer Architecture CS321T 3 1 0 34 Computer Networks CS322T 3 1 0 35 Database Management Systems CS323T 3 1 0 36 Elective3 1 0 3 7 Compiler Lab CS317L 0 0 3 18 Networks & DBMS Lab CS327L 0 0 3 19 Mini Project/ Industrial Training CS398P/ CS399P 0 0 0 0 3 3 1** 1**Total - 18 6 9 21Seventh SemesterContact hours per week Sl.No Course Title Code L G PCredits Category1 EconomicsSH301T 3 1 0 3 2 Design and Analysis of AlgorithmsCS421T 3 1 0 3 3 Elective 3 1 0 34 Elective3 1 0 3 5 Elective3 1 0 3 6 Seminar CS497S 0 0 3 17 Project CS498P 0 0 3 38 Programming Paradigms Lab CS416L 0 0 3 1Total - 18 6 6 20Eighth SemesterContact hours per week Sl.No Course Title Code L G PCredits Category1 Computational Intelligence CS422T 3 1 0 32 Elective3 1 0 3 3 Elective3 1 0 34 Elective3 1 0 3 5 Elective3 1 0 3 6 Project CS499P 0 0 5 5Total - 15 5 5 20Semester (B.Tech) CreditsI 23 II 23 III 20 IV 20 V 20 VI 21 VII 20 VIII 20 Total Credits 167* Three courses of one credit each, to be credited before completing six semesters of the programme.** One of Mini Project and Industrial Training is compulsory. Candidates are free to credit both.Electives:1. CS332T Advanced Data Structures2. CS333T Object Oriented-Analysis & Design3. CS334T Web Programming4. CS431T Advanced Database Management Systems5. CS432T Multimedia System Design6. CS341T Distributed Computing7. CS343T Embedded System Design8. CS441T Advanced Computer Architecture9. CS351T Network Security10. CS352T Coding Theory11. CS353T Mobile Communication Systems12. CS354T Electronic Commerce13. CS356T Mobile Computing14. CS361T Image Processing15. CS362T Pattern Recognition16. CS364T Natural Language Processing17. CS371T Logic for Computer Science18. CS372T Number Theory & Cryptography19. CS373T Computational Complexity20. CS471T Advanced topics in Algorithms21. CS472T Quantum Computation22. CS473T Algorithms for VLSI Design23. CS331T Computer Graphics & Multimedia SystemsCS102T: INTRODUCTION TO COMPUTINGPrerequisite: NilAlgorithm discovery and design, analysis of algorithms, Boolean functions and logicaloperations, Karnaugh map, Quine-McClusky algorithm, computer organization, assemblers and assembly languages, operating systems, object oriented programs, HTML, compilation,Turing machine, databases, computer networks, Internet and WWW, computing security. References:1. G. M. Schneider and J. L. Gersting, An Invitation to Computer Science, 2/e, ThomsonPublishing, 1999.2. T. L. Floyd, Digital Fundamentals, 3/e, Universal Book Stall, New Delhi, 1986.3. A. W. Bierman, Great Ideas in Computer Science, 2/e, MIT Press, 1997EE217T – ELECTRICAL CIRCUITS & SYSTEMSPrerequisite: EE101TElectric Circuit Parameters, Sinusoidal and Steady State Analysis, Lap Lace TransformAnalysis of Simple Electric Circuits, Review of Electric Network Theorems, Network Graph Theory, Introduction to Control Systems, Open Loop & Closed Loop Control Systems, Principles of Electromechanical Energy Conversion, Electric Machines, Introduction to Power Supply System, Static Power Supply Devices.Reference:Hayt and Kemmerly, Engineering Circuit Analysis, McGraw Hill.EC219T – ELECTRONIC CIRCUITS & SYSTEMSPrerequisite: EC101TBipolar junction Transistor, Biasing, Small signal Amplifiers, Classification of amplifiers, Field Effect Transistors, Power Amplifiers, Feedback in Amplifiers, Oscillators, Operational Amplifiers, analog computation, active filters, A/D converters, Multivibrators, Schmitt trigger, Miller & Bootstrap Time base generators, 555 Timer circuits, Logic families Reference:J. Millman and C. Halkias, Integrated Electronics: Analog and Digital Circuits and systems,Tata McGraw Hill, New Delhi, 1972.CS210T : PROGRAM DESIGNPrerequisite: NilProblem solving, elegance in program design, program testing and documentation, controlstructures, functions, arrays, pointers and strings, classes and data abstraction, inheritance, virtual functions and polymorphism, input/output, exception handling, file processing, class string and string stream processing.References:1. Juliet P., Program Design, 4/e, Prentice Hall India, 2000.2. Dietel H. M. and Deitel P. J., C++, How to Program, 3/e, Pearson Education, 2001.CS211T LOGIC DESIGNPrerequisite: CS102TNumber Systems and codes, Boolean algebra, Boolean functions and logical operations,Karnaugh map, Quine-McClusky algorithm, Combinational Logic, adders, comparators, decoders and encoders, multiplexers, ROMs, PLAs, Fault diagnosis and tolerance, programmable logic arrays, c ounters and shift registers, Clock mode sequential machines Reference:N. N. Biswas, Logic Design Theory, Prentice Hall of India, New Delhi, 1993.CS213T – DATA STRUCTURES & ALGORITHMSPrerequisite: CS102TReview of data types, Data abstraction, Time and space complexity of algorithms,Recursion, linear data structures: Stacks, queues, lists, Non linear Structures: Graphs, trees, sets, Searching, Sorting, Bubble sort, insertion Sort, selection sort. nlogn sorts,quick sort, heap sort, merge sort. External sort, merge files.Reference:Aho A.V., Hopcroft J.E., and Ullman J.D., Data Structures and Algorithms, Pearson Education, New Delhi, 1983.EC216L – ELECTRONICS LABElectronics Workshops, diode characteristics, UJT and UJT relaxation oscillator, transistor characteristics, wave shaping circuits, Series voltage regulator, Frequency response of CE amplifier, measurement of input and output impedance, oscillator, Op Amp.Reference:lman and C. Halkias, Integrated Electronics: Analog and Digital Circuits and systems, Tata McGraw Hill, New Delhi, 1972.CS217L – PROGRAMMING LABPrerequisite: CS102THCF (Euclid’s algorithm) and LCM of given numbers, Conversion of numbers from binary to decimal, hexadecimal, octal and back, evaluation of functions like e x, sin x, cos x etc. for a given numerical precision using Taylor’s series, testing whether a given number is prime, string manipulation programs, Matrix operations, Files.References:1. H. Schildt, C: The Complete Reference, 4/e, Tata McGraw Hill, 2000.2. T. H. Cormen, C. E. Lieserson, R. L. Rivest, Introduction to Algorithms, PHI, 1998CS221T – THEORY OF COMPUTATIONPrerequisite: CS102TBasic concepts of Languages, Automata and Grammar, Regular Languages, Kleene's theorem, Pumping Lemma, Context Free Languages, Pushdown Automata. Turing Machines: TM Computations, Church Turing Thesis, Decidability, Redecidability. Computational Complexity: classes P and NP - NP-Completeness - ReductionsReference:Michael Sipser, Introduction to the theory of Computation, Thomson Learning, Singapore, 2001CS212T DISCRETE COMPUTATIONAL STRUCTURESPrerequisite: NilReview of set theory, Logic, laws of logic, rules of inference, relations and Functions, partial ordering, equivalence relations, lattices, Boolean algebra, groups, cyclic groups, Cosets and Lagrange's Theorem, linear codes, Rings, the integer modulo n, polynomial rings, finite fields.Reference:Grimaldi R. P., Discrete and Combinatorial Mathematics, 4/e, Pearson Education, New Delhi, 1999.CS223T – COMPUTER SYSTEMS SOFTWAREPrerequisite: CS213TSystem software machine architecture, RISC machines, Assemblers, Assembler design,Loaders and linkers, Macro Processors, Device Drivers, Disk Device Driver Access Strategies, Operating System Overview , Operating System Design Options, Windows 2000 & UNIXoverview.Reference:L. L. Beck, System software - An introduction to Systems Programming, 3/e, Addison-Wesley, 1999.CS224T – COMPUTER HARDWARE DESIGNPrerequisite: CS211TPC hardware, Interfaces, operating system, BIOS, and memory organization. 8086/8088 Hardware specification, Features of Pentium IV processor, Microprocessor architecture, Addressing modes, Programming the microprocessor, using assembly language with C/C++, Memory interface, I/O interface, Interrupts, DMA, Bus interface: ISA bus, EISA and VESA buses, PCI bus.Reference:B. B. Brey, The Intel Microprocessors 8086 to Pentium: Architecture, Programming and Interface, 6/e, Pearson Education, 2003.CS225T – COMPUTER ORGANISATIONPrerequisite: CS211TComputer abstraction and technology, measuring performance, Instructions, Computer arithmetic, constructing an ALU, multiplication and division, floating point representation and arithmetic, processor, Memory hierarchy: caches, virtual memory, Input/output, buses.Reference:D. A. Patterson and J. L. Hennessy, Computer Organisation and Design: The Hardware/ Software Interface, 2/e, Harcourt Asia Pte Ltd (Morgan Kaufman), Singapore, 1998.CS226L – DATA STRUCTURES LABStack and Queue, Searching Methods, Sorting, Binary Search Tree, Infix Expression Evaluation, graph Search Algorithm, Minimal Spanning Tree,Shortest Path Algorithm, Disjoint Set operations, Applications of Heap.CS227L – DIGITAL SYSTEMS LABTTL characteristics, Half and full adders, Digital comparator, parity generator, flipflops, Shift register, counter, multivibrator, frequency divider using 555 .CS301T - SOFTWARE ENGINEERINGPrerequisite: CS213TSoftware process, software requirements, requirements engineering processes,system models, Software prototyping , formal specification, architectural design, object-oriented design, Dependability verification and validation, software testing, software, Software project management, software cost estimation, quality, configuration.References:1. Ian Sommerville, Software Engineering, 6/e, Pearson Education Asia, 2003.2. Pressman R. S., Software Engineering, 5/e, McGraw Hill, 2003CS312T COMMUNICATION & INFORMATION THEORYPrerequisite: EC219TNoise in communication systems, PAM, PPM, PWM, PCM, delta modulation, digital modulation, information theory, channel capacity, Coding Theory, Introduction to convolutional codes.References:1. Kolimbiris H., Digital Communication Systems, Pearson Education, 2001.2. Bose R., Information Theory, coding & Cryptography, Tata McGraw-Hill, 2002.3. Taub H. and Schilling D. L, Principles of Communication Systems, 2/e, McGrawHill, 1986CS313T - OPERATING SYSTEMSPrerequisite: CS223TProcess description and control, Threads, SMP and Microkernels, Deadlock and starvation, Memory management, Virtual memory, Scheduling, Multiprocessor and real-time scheduling, Input-Output, files and Security, File management, Computer Security References:1. William Stallings, Operating systems- Internals and design principles, 4/e, PHI Pvt. Ltd.,New Delhi, 2002.2. Nutt G.J, Operating systems- A modern perspective, Addison Wesley, 1999.CS 314T PRINCIPLES OF PROGRAMMING LANGUAGESPrerequisite: CS213TSyntax and semantics of programming languages. Imperative programming: Block structure, Scope rules, Principle of abstraction, Parameter passing mechanisms. Functional programming: Functions, Recursion, Types, Data abstraction, Polymorphism, Untyped and simply-typed Lambda calculus and extensions.References:1. Sethi R., Programming Languages: Concepts and Constructs, 2/e, Addison-Wesley, 19952. Benjamin C. Pierce, Types and Programming Languages. MIT Press, 2002CS222T COMPUTATIONAL COMBINATORICSPrerequisite: CS212TCounting, permutations, combinations, combinations with repetition. The principle of inclusion and exclusion, derangements, pigeonhole principle. Generating Functions, Recurrence Relations, Graphs, Euler trails and circuits, planar graphs, Hamilton paths and cycles, graph colouring, Polya's Enumeration, Trees, weighted trees. Optimization and Matching, transport networks.Reference:Grimaldi R. P., Discrete and Combinatorial Mathematics, 5/e, Addison Wesley, 2002.CS316L – HARDWARE LABIdentification of components/cards and PC assembling from components, 8086 Assembly language programming (non-recursive and recursive) TSR Prog: Disk I/O, Keyboard - stepper motor – Display – ADC/DAC – Interfacing, Wave form generation.References:1. Messmer H. P., The Indispensable PC Hardware Book, 3/e, Addison Wesley.2. Hall D.V., Microprocessors and Interfacing, 2/e, Tata McGraw Hill.CS 326L OPERATING SYSTEMS LABEnhance the primitive NACHOS operating Systems with the following capabilities:1. Load Module -Implementation of Read(), Write(), Open() and Close() system calls.2. Multiprogramming- Implementation of Fork, Wait, Exec and Exit,3. T ranslation L ookaside B uffer (TLB)4. File System5. Synchronization-Semaphore, Locks and Conditional Variables6. Networking-Nachos MailboxReference:Gary J. Nutt, Operating Systems, Pearson Education, 3/e, 2004.CS311T - COMPILER CONSTRUCTIONPrerequisite: CS221TPhases of a compiler, lexical analysis, lexical analyzer generators, Syntax analysis, Syntax-directed translation, run-time environments, symbol tables, Intermediate code generation, introduction to code optimization, code generation.References:1. Aho A.V., Sethi R. & Ullman J.D., Compilers Principles, Techniques and Tools, AddisonWesley, 1986.2. Appel A.W., Modern Compiler Implementation in Java, Cambridge University Press, 2/e,2002.CS321T: COMPUTER ARCHITECTUREPrerequisite: CS225TPerformance evaluation, Processor architecture, pipelining, pipeline hazards, issues in pipelined processor implementation. Instruction level parallelism, hardware and compiler support for branch prediction, out-of-order Instruction issue, speculative execution and other techniques for high-performance. Instruction and data cache organizations, multilevel caches, parallel memory systems, Support for virtual memory. Multiple processor systems, Interconnection networks, shared memory system, memory models, cache coherence. References:1. Hennesy J. L. & Patterson D. A., Computer Architecture: A Quantitative approach, 3/e,Harcourt Asia Pte Ltd. (Morgan Kaufman), Singapore, 2003.2. Patterson D. A. & Hennesy J. L., Computer Organisation and Design: The Hardware/Software Interface, 2/e, Harcourt Asia Pte Ltd (Morgan Kaufman), Singapore3. Hwang K., Advanced Computer Architecture: Parallelism, Scalability andProgrammability, McGraw Hill, Singapore, 1993.CS322T COMPUTER NETWORKSPrerequisite: CS312TPhysical layer, Link layer services, error detection and correction, Ethernet, hubs, bridges, switches, wireless links, Transport layer services, UDP and TCP, Network layer services, routing, IP, Internet, Application layer protocols, Network Security, Protocols, Firewalls. References:1. Peterson L.L. & Davie B.S., Computer Networks, A systems approach, 3/E, HarcourtAsia, 2003.2. Keshav S., An Engineering Approach to Computer Networking, Pearson Education, 2000.3. Andrew S. Tanenbaum, Computer Networks, 3/E, PHI, 1996.CS323T - DATABASE MANAGEMENT SYSTEMSPrerequisite: CS213TDatabase System Concepts and Architecture, Data Modeling using ER model, Relational datamodel, Relational algebra and Relational calculus, SQL, Relational database design using ER to relational mapping, Database design theory and Methodology, Data storage, Indexing andphysical design, Transaction processing concepts.References:1. Elmasri & Navathe, Fundamentals of Database Systems, 4rd Edition, Addison Wesley2. Ramakrishnan R. & Gehrke J., Database Management Systems, 2/e, McGraw Hill3. O'neil P. & O'neil E., Database Principles, Programming, and Performance, 2/e,Harcourt Asia, Morgan KaufmanCS 317L COMPILER LABGeneration of lexical analyzer using tools such as LEX, Generation of parser using toolssuch as YACC, Creation of Symbol tables, Creation of type checker, Generation of intermediate code, Generation of machine code.Reference:Halub A. I., Compiler Design in C, Prentice Hall IndiaCS 327 L NETWORKS AND DBMS LABPart 1 – NetworksLab 1- Implementation of PC to PC file transfer using serial port and MODEM. Lab 2, 3 -Software Simulation of Medium Access Control protocols - 1) Go Back N, 2) Selective Repeat and 3) Sliding Window. Lab 4 - Implementation of a subset of Simple Mail Transfer Protocol using UDP - Lab 5, 6 - Implementation of a subset of File Transfer Protocol using TCP/IP. Lab 7 - Implementation of “finger” utility using Remote Procedure Call (RPC). Lab 8 - Generation and processing of HTML forms using CGI.Part 2 – DBMSLab 1 - Implementation of B tree and B+ tree . Lab 2 - Implement a database stored in an RDBMS accessible through a web browser. Lab 3 - Minibase [ Expected time: 3 weeks]In this part students have to implement a simplified single-user relational database system, called MINIBASE. The MINIBASE project involves writing code for both the logical layer and the physical layer of a Database Management System. Refer the Minibase homepage for more information (/coral/minibase/ minibase.html). The goal is not just to have a functional DBMS, but to have a DBMS where the individual components can be studied and implemented by students.References:1. Stevans W. Richard, Unix Network Programming, PHI2. Comer D.E., Internetworking with TCP/IP, Vol. 1,2 & 3, PHI3. Campione et. al M., The Java Tutorial Continued, Addison Wesley4. Douglas E Comer., Hands-on Networking with Internet Technologies, Pearson Education5. Elmasri, Navathe, Fundamentals of Database Systems, 4th Edition, Pearson EducationCS398P MINI PROJECTEach student group (not more than 5 members in a group) is expected to develop a complete software product using software engineering techniques. The product is to be installed and should have user manuals. A detailed report is also to be submitted. The students may be accessed individually and in groups.CS399P INDUSTRIAL TRAININGEach student is expected to undertake with help from the Department of Training andPlacement, Internship in the field of Computer Science and Engineering by undergoing training of at least one-month duration in reputed industries/research centers in thecountry. The industrial training is expected to be undertaken during the semester recess. The student should write a final report on this training and should make an oral presentation before an evaluation committee.CS421T DESIGN AND ANALYSIS OF ALGORITHMSPrerequisite: CS213TSpace and Time Complexities. Asymptotic notations and complexity classes. Algorithm Design Paradigms: Brute Force, Divide and Conquer, Decrease and Conquer, Transform and Conquer, Dynamic, Greedy. Back Tracking, Branch and Bound, Approximation Algorithms. Space-Time Trade-offs.References:1. Anany Levitin, Introduction to the Design & Analysis of Algorithms, Pearson Education.20032. Cormen, Leiserson, Rivest and Stein, Introduction to Algorithms, Second Edition. PHI.2002.3. Aho, Hopcroft and Ullman, The Design and Analysis of Algorithms, Seventh IndianReprint, Pearson Education, 2002.CS331T COMPUTER GRAPHICS & MULTIMEDIA SYSTEMSPrerequisite: CS213TBasic raster graphics algorithms for drawing 2D primitives - 2D transformations - Input devices and interactive techniques - 3D graphics - 3D transformations. Introduction to multimedia - multimedia hardware - multimedia software. Multimedia building blocks - audio - images and graphics - animation techniques. Data compression - basic compression techniques like JPEG, H.261, MPEG and DVI - multimedia database systems. References:1. Foley J. D., Van Dam A., Feiner S. K., & Hughes J. F., Computer Graphics Principles andPractice, Second Edition, Addison Wesley2. Ralf Steinmetz & Klara Nahrstedt, Multimedia: Computing, Communications andApplications, Pearson Education3. Koegel Buford J. F., Multimedia System, Addison WesleyCS 497S SEMINAREach student is expected to present a seminar on a topic of current relevance in computer science and engineering – they have to refer papers from standard journals like ACM, IEEE, JPDC, IEE etc. – at least three cross references must be used – the seminar report must not be the reproduction of the original paper.CS498P PROJECTThis project is for a duration of two semesters. Each student group(not more than 5 members in a group) is expected to develop a complete product. The design and development may include hardware and /or software. First part of the project is mainly for the design of the product. An interim report is to be submitted at the end of the semester. The assessment may be made individually and in groups.CS416L PROGRAMMING PARADIGMS LABTower of Hanoi - recursive and non-recursive, Eight Queens Knight's tour ExpressionEvaluation. These problems are solved in procedural, object oriented, functional and logic paradigms. Specific problems suitable for the above paradigms are also given. A scriptinglanguage is also introduced.CS422T - COMPUTATIONAL INTELLIGENCEPrerequisite: CS213TArtificial Intelligence, Structures and Strategies for state space search, Knowledge representation, AI Representational Schemes, Machine Learning, The Genetic algorithm, Genetic Programming, Rule based Expert Systems, Introduction to Natural Language Processing, Languages and Programming Techniques for AI.References:1. Luger G. F., Artificial Intelligence- Structures and Strategies for Complex ProblemSolving, 4/e, Pearson Education2. Elain Rich & Kevin Knight, Artificial Intelligence, 2/e, Tata McGraw Hill3. Steven. L. Tanimotto, The Elements of Artificial Intelligence, Computer Science PressWinston P H, LISP, Addison WesleyCS499P PROJECTThis is the second part of the project. This part is for the development, testing, and installation of the product. The product should have user manuals. A detailed report is to be submitted at the end of the semester. The assessment may be made individually and in groups.CS 332T ADVANCED DATA STRUCTURESPrerequisite: CS213TA review of elementary data structures. Hash tables - different implementations - collision handling. Binary Search Trees - Red-Black Trees - AVL Trees - optimal binary tree. B-Trees. Binomial and fibonacci heaps. Datastructure for representing disjoint sets.Data structure choice and justification for some practical Applications.References:1. Cormen, Leiserson, Rivest and Stein, Introduction to algorithms, Second Edition, PHI,2002.2. Niklaus Wirth, Algorithms + Data structures = Programs, PHI, 1994CS 333T OBJECT ORIENTED ANALYSIS AND DESIGNStructural Modeling – UML Models – Behavioral and Architectural Models – Design Patterns – Object Oriented Testing Methodologies - Components.References:1. Page Jones M., Fundamentals of Object Oriented Design in UML, Pearson Education, 2000.2. Booch G., Rumbaugh J. & Jacobsons I., The Unified Modeling Language User Guide,Addison Wesley, 2000.3. Bahrami A., Object Oriented System Development, McGraw Hill, 2000.CS 334T: WEB PROGRAMMINGPrerequisite: CS213T & CS322TInternet and WWW, HTML, Paintshop, Photoshop, FrontPage, JavaScript/Jscript, Dynamic HTML, multimedia, e-commerce security, web servers, SQL, ADO and RDS, Active server pages, CGI and Perl, XML, Servlets .References:1. H. M. Deitel, P. J. Deitel and T. R. Nieto, Internet and World Wide Web: How ToProgram, Pearson Education, 2000.2. Current LiteratureCS431T ADVANCED DATABASE MANAGEMENT SYSTEMSPrerequisite: CS323TOverview of relational database concept - object oriented database - overview of CORBA standard for distributed objects, Distributed database concepts - overview of client - server architecture and its relationship to distributed database, Deductive database - basic inference mechanism for logic programs - data warehousing and data mining - database on World Wide Web - multimedia database - mobile database - geographic information system - digital libraries, Oracle and microsoft access - basic structure of the oracle system, database structures and its manipulation in oracle - programming oracle applications - oracle tools - an overview of microsoft access features and functionality of access - distributed databases in oracle.References :1. Elmasri & Navathe, Fundamentals of Database Systems, 3/e, Addison Wesley2. Ramakrishnan R. & Gehrke J., Database Management Systems, 2/e, McGraw Hill3. O'neil P. & O'neil E., Database Principles, Programming and Performance, 2/e, HarcourtAsia (Morgan Kaufman)4. Silberschatz, Korth H. F. & Sudarshan S., Database System Concepts, Tata McGraw Hill5. Theory T. J., Database Modelling and Design, 3/e, Harcourt Asia (Morgan Kaufman)CS432T: MULTIMEDIA SYSTEM DESIGNPrerequisite: CS213TIntroduction, compression and decompression, data and file format standards, multimedia I/O technologies, storage and retrieval technologies, architectural and telecommunications considerations, multimedia application design, multimedia authoring and user interface, hypermedia messaging, distributed multimedia systems.References:1. P. K. Andleigh and K. Thakrar, Multimedia System Design, , Prentice Hall India, 1996.2. Current Literature.CS341T: DISTRIBUTED COMPUTINGPrerequisite: CS313TOperating system fundamentals - distributed system concepts and architectures - major design issues - distributed computing environments (DCE)Concurrent processes and programming - threads and processes - client server model - time services - language mechanisms for synchronization - concurrent programming languages Interprocess communication and coordination - message passing communication - request/reply communication - transaction communication - name and directory services - distributed mutual exclusion - leader electionDistributed process scheduling - static process scheduling, dynamic load sharing and balancing - distributed process implementation - real-time scheduling - concepts of distributed file systems - distributed shared memory - distributed computer security。

2012 summer soilmech3

Chapter 2 Soil Classification System Chap. 3 The Water in a Soil
3.1 The Water in a Soil < Influence Factors > (1) Density Dense ~ Loose (2) Consistency Solid ~ liquid (3) Strength High ~ Low
[1 Organic Soil type]
(1)Pt
Chapter 2 Soil Classification System
2.5 The others 1) AASHTO Classification System American Association of State Highway and Transportation Officials 2) CAA Classification System Civil Aeronautics Administration System 3) Group Index (1 ~ 20) G.I. = 0.2a + 0.005ac + 0.01bd G.I. >> Poor Soil for Sub- Grade and Sub- Base of Road
Chapter 2 Soil Classification System
1) Free Water(Gravitational moisture)
● ●
Flow : Surface water Underground water water level in underground: not horizontal
Chapter 2 Soil Classification System

Research Student

Clustering and Grid Computing : Age of CrisisNiraj UpadhayayaResearch StudentCEMS.UWE, Bristol.________________________________________________________________________ Abstract: Clustering has evolved as a mature technique and developed in to grid computing. With increasing complexity of today’s world, processing power offered by grid computing has become great help to solve complex problems. However cluster computing is going through an age of crisis. This crisis has come due to the fact that it is useful but still efficiency is much below the expected limits. In this paper problems related to efficiency of Cluster / Grid computing are discussed with suggestion regarding possible solutions.________________________________________________________________________1.Growth in processing capacity and clustering technologyFrom basic research to weather questions and aerodynamic problems for airplane manufacturers, science and industry are looking for answers that can only come from years of computing time using the world's fastest computers. According to Dan Reed, director of the National Center for Supercomputing Applications (NCSA), "There's no upper bound on the level of performance that today's researchers want and need. If we had a petaflops (a machine capable of 1,000 trillion floating point operations per second) on the floor, researchers would clamor for access, and it would be saturated in a few days."Gordon Moore (Cofounder of Intel) predicted in 1965 that processing capacity 9 Basically he talked about transistor density in chip) would double every 18 months.As a fact growth in processor technology has outsmarted even this prediction, and processing capacity is doubling almost every 14 months. With increased processor efficiency, commodity computing has become more effective and powerful. This in turn has resulted in the growth of cluster computing as even more powerful andaffordable computing architecture. Now there are 137 Cluster supercomputers in top 500 supercomputers (Top 500 June 2003) , and they are not at bottom of the list but evenly distributed across it. The third most powerful computer in the world as on date is a Linux based supercomputer comprising 2304 processor giving peakperformance of 11 T Flops.This capability at affordable cost has brought a revolution in the world ofcomputing. Supercomputing has become now part of a common person. For example Google the popular search engine of Internet, is a big cluster itself comprising of15,000 commodity Linux system, distributed across 6 data centers, giving total processing capacity of 15 T Flops.2.Power at the cost of efficiencyWith above statistics it appears that everything in the world of cluster /grid supercomputing is going quite well. The reality however is far from this. All this processing power of clustering is harnessed at a price and that is efficiency. As a fact this problem is plaguing the processor technology itself, where the available performance of processors is far below than possible peak performance of the architecture.This problem can be understood by the example that a Pentium 4 processor running at 3200MHz can give theoretical peak performance of(1fpu)*(2flops/cycle)*(3.2 GHz) = 6040 MFLOP/sAt this theoretical peak simple mathematical operations like Y=AX+Y where three operands (24 bytes) needed for 2 flops demands a bandwidth of 9060 MW/s.However theoretical peak of memory considering bus speed of 800 MHz is32bit * 800 =2560 MB/s = 320 MW/sIt clearly shows that if we achieve theoretical peak of processor and memory, the memory will be 30 times slower than the demand of processing. This makes whole system run slower than expected. It can be clearly seen here that instead of processor , memory bandwidth is becoming bottleneck in computing. In parallel computing like clusters and grids this situation becomes more acute. It will further growing to be worse considering growing rate of disparity in the speed of development of processor and memory technology.3.Other major reasons of concernDisparity between memory and processor technology is just one of the major issues to be tackled by grid computing. There are other areas of growing concern as well.a. Complexity of programming on these machines was underestimated.Initially there was PVM than MPI came. Now we have several libraries to help programmers, programming in cluster domain. Clusters are generally used to solve massive critical kind of problems. In such domain using these libraries not only makes the code more cumbersome but difficult to debug and maintain. Moreover no separate architectural paradigm was evolved for programming on cluster computers. It further makes the task of programmer more difficult.b. Lack of reliability in commodity hardware.The commodity hardware, which was thought the basis of cluster hardware architecture, making it economically attractive is becoming area of concern. Such hardware is less reliable and failure rate though low when calculated percentage wise, affects seriously when making a cluster of more than 1000 nodes. In case programmers are not aware of this issue of possible failure of a few nodes all the time, they may create a program, which will not work at all in some cases and works erroneously in most of the cases.c. No medium and long term research activity on applications, algorithms, middleware, programming model etc.Lot of research has been done to create new models and schemes of clustering, but hardly any research is being done in improvement of cluster computing efficiency. It has resulted in a scenario, where we have lot of techniques but none of these has been perfected. Unfortunately still more stress is being given to finding new way of clustering, rather than perfecting existing methods.d. Cluster has become hardware domain and there is tendency to depend on hardware to solve software related problems as well.In the area of cluster computing for many years, problems related to software were searched in hardware domain. This methodology was flawed since conception, as we know that solution of any problem lies in problem domain itself. It was initially thought that higher speed of network will solve all the problems, but it did not. Similarly more stress was given to hardware architecture, rather than software architecture of applications running on clusters. Now when solutions obtained through such shortcuts have already been proved far from satisfactory, there is growing feeling that most of the problems related to clusters are to be resolved in software domain.e. Challenges for applications, libraries and tools are formidable with T Flops level and almost insurmountable at P Flops.As we increase the number of processors to get more processing power, scalability becomes a big issue. Scalability and cache coherency does not go hand in hand. Creating and maintaining distributed software memory (DSM) with such big clusters is therefore becoming more and more difficult. Further share memory programming methods do not scale to large number of CPUs.f. Problems with General Purpose Kernels (GPK)A major reason of performance drop in cluster computing is that, a few general-purpose kernels are handling a large mass of applications, requiring different and diverse resource allocation pattern. These kernels are simply not designed to handle very special needs of such massively parallel applications. If we add the factor that most of cluster supercomputers handle one or very few application, it clearly shows that instead of tuning application to kernel, there is need to go in reverse direction and tune or even create kernel specifically suited to applications.Further most of the kernel give preference to processor scheduling over memory scheduling, with memory bandwidth becoming bottleneck, this preference order needs to reversed, specially in case of cluster /grid computing. General-purpose kernels are failing to deliver optimally tuned performance, and redesigning special kernels from scratch is only answers to work with long time objectives.g. Lagging compiler technologyToday hardware technology is evolving at such a fast rate that, it is difficult to keep pace with it. It becomes very evident by the fact that there are hardly any applications to take benefits of additional instruction sets offered by improving processor technology. Compilers are simply lagging too far behind to take benefit of evolving instruction sets. Incorporating these additional facilities in compiler is must to design very large, critical and distributed software suitable to run on clusters. However it is simply not happening.4.So where lies the solutionThis crisis can be handled in two ways short term and long term. Short-term mantra to solve this is performance tuning. This can be done individually on each kernel for each application, or we can resort to not yet very reliable automatic performancetuning tools. In first case, for each kernel we have to identify and generate space of algorithms and search the fastest one by actually running them. Space of algorithms here means, instruction mix and order, memory access pattern, data structure andmathematical formulations. Tests need to be done for each kernel and architecture, and both at compile time and run time.Other short-term solutions are to make numerical software more adaptive, exploratory and intelligent. Adaptivity is key here, so that applications can use the resources effectively. Further there is need to eliminate determinism in numerical computing. After all it is not reasonable to ask for exactness in numerical computation. This however will reduce reproducibility of the result. In a way we can say that, in case if we want to introduce determinism and extreme reproducibility in numerical software, it is coming at very high cost of the performance.Reproducibility, fault tolerance, performance and adaptivity are all diverse aims and balance is indeed a difficult task, which gets more complicated in the scenarios of general purpose kernels.Long term SolutionsThe dark side of computer cluster is the fact that they perform poorly on application that requires large shared memory. To overcome this there is growing need to research in the areas of ultra high performance hardware-software architectures, including new programming paradigms, kernels, user interfaces and above all peta-scale distributed databases.Another long-term solution is to have more mature and effective auto performance tuning tools for parallel applications. Here the objective is to create an environment for dynamic automatic tuning of distributed applications that facilitates design and development of distributed applications, takes care of performance optimization of application during it’s execution. Fortunately automatic tuning schemes like kappa-pi, HPCS, Active Harmony are showing promise in this direction.Redesigning kernel with new architectural goal of better memory management and more tenability is very important if cluster computing efficiency has to be increased to an acceptable level in peta flop computing scenario.5.ConclusionCluster / Grid computing has become a tool which is affordable and scalable to solve complicated, processor intensive and parallel problems. Like any technology, cluster computing is maturing with time. This is leading to higher expectation from users, researchers especially in terms of performance. In spite of providing benefits of largeprocessing power, clusters are inherently very inefficient and there is urgent need to improve the efficiency. Software performance on cluster has to be improved using tools in software domain. Better performance tuning of application, kernel and stress on better utilization of memory bandwidth or few possible solutions to remove this performance bottleneck.6. References and Bibliography1.G. Fox, M. Pierce, D. Gannon, M. Thomas, Overview of Grid ComputingEnvironments, GGF Document Series.2.Ian Foster, The Grid: A New Infrastructure for 21st Century Science (Reprint),Physics Today /pt/vol-55/iss-2/p42.html3.Ian Foster, Carl Kesselman, Jeffrey M. Nick, Steven Tuecke, The Physiology ofthe Grid: An Open Grid Services Architecture for Distributed SystemsIntegration (Draft 2.9), 22nd June 2002.4.David De Roure, Nicholas Jennings, Nigel Shadbolt and Mark Baker, "ResearchAgenda for the Semantic Grid: A Future e-Science Infrastructure", Technical Paper, 19th February 2002. (pdf, html, background).5.Rajkumar Buyya and Manzur Murshed, GridSim: A Toolkit for the Modelingand Simulation of Distributed Resource Management and Scheduling for Grid Computing, The Journal of Concurrency and Computation: Practice andExperience (CCPE), 1-32pp, Wiley Press, May 2002 (to appear).6.I. Foster, C. Kesselman, S. Tuecke, The Anatomy of the Grid: EnablingScalable Virtual Organizations , January 20017.Rajkumar Buyya, Mark Baker, Grid Computing, Grid 2000: First IEEE/ACMInternational Workshop, Bangalore, India, December 17, 2000: Proceedings 8.R.J. Allan , Survey of Computational Grid, Meta-computing and NetworkInformation Tools, Daresbury Technical Report, Computational Science and Engineering Department, CLRC Daresbury Laboratory, Daresbury, Warrington, UK, 20th June 20009.Abramson D., Giddy J., and Kotler L., High Performance Parametric Modelingwith Nimrod/G: Killer Application for the Global Grid? International Parallel and Distributed Processing Symposium (IPDPS), IEEE Computer SocietyPress, 200010.Rajkumar Buyya, Steve Chapin, David DiNucci, Architectural Models forResource Management in the Grid, The First IEEE/ACM InternationalWorkshop on Grid Computing (GRID 2000), Springer Verlag LNCS Series,Germany, Dec. 17, 2000, Bangalore, India.11.Klaus Krauter, Rajkumar Buyya, and Muthucumaru Maheswaran, A Taxonomyand Survey of Grid Resource Management Systems, Technical Report:Manitoba and Monash Universitities, 2000.。

数据库系统概念(database system concepts)英文第六版 PPT 第六章

Database System Concepts - 6th Edition
6.8
©Silberschatz, Korth and Sudarshan
Union Operation
Notation: r s Defined as:
r s = {t | t r or t s}
©Silberschatz, Korth and Sudarshan
Cartesian-Product Operation – Example
Relations r, s:
r x s:
Database System Concepts - 6th Edition
6.12
©Silberschatz, Korth and Sudarshan
Project Operation
Notation:

A , A , , A 1 2 k
(r )
where A1, A2 are attribute names and r is a relation name.
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INFO5001_System Analysis & Modelling_2013 Semester 2_INFO_5001Week7_html

INFO5001System Analysis and ModellingSemester 2, 2013Lecture 7, Introduction to HTML (part 2)Based on Internet & WWW Ch2Introduction ❝HTML5 (HyperText Markup Language 5)-markup language that specifies the structure and content of documentsthat are displayed in web browsers❝We introduce some basics, then cover more sophisticated HTML5 techniques such as:-tables, which are particularly useful for structuring information fromdatabases (i.e., software that stores structured sets of data)-forms for collecting information from web-page visitors-internal linking for easier page navigation-meta elements for specifying information about a documentEditing HTML5›We’ll create HTML5 documents by typing HTML5 markup text in a text editor (such as Notepad, TextEdit, vi, emacs) and saving it with the .html or .htm filename extension.›Computers called web servers store HTML5 documents.›Clients (such as web browsers running on your local computer or smartphone) request specific resources such as HTML5 documents from web servers.First HTML5 Example›Figure 2.1 is an HTML5 document named main.html›This first example displays the message Welcome to HTML5!in the browser.Linking ›A hyperlink references or links to other resources, such as HTML5 documents and images.›Web browsers typically underline text hyperlinks and color them blue by default.Linking (Cont.)❝The strong element indicates that the content has high importance. Browsers typically render such text in a bold font.❝Links are created using the a(anchor) element.❝Attribute href(hypertext reference)specifies a resource’s location, such as-a web page or location within a web page-a file-an e-mail address❝When a URL does not indicate a specific document on the website, the web server returns a default web page. This page is oftencalled index.html, but most web servers can be configured touse any file as the default web page for the site.❝If the web server cannot locate a requested document, it returns an error indication to the web browser (known as a 404 error), and the browser displays a web page containing an error message.Linking (Cont.)Hyperlinking to an E-Mail Address-Anchors can link to an e-mail address using a mailto:URL-When a user clicks this type of anchored link, most browsers launch the default e-mail program (e.g., Mozilla Thunderbird, Microsoft Outlook or Apple Mail) to enable the user to write an e-mail message to the linkedaddress.Images (Cont.)Void Elements❝Some HTML5 elements (called void elements) contain only attributes and do not mark up text (i.e., text is not placed betweena start and an end tag).❝You can terminate void elements (such as the img element) by using the forward slash character (/) inside the closing right angle bracket (>) of the start tag.❝For example, lines 15–16 of Fig. 2.6 could be written as follows: <img src = "jhtp.png" width = "92" height = "120"alt = "Java How to Program book cover" />Images (Cont.)Using Images as Hyperlinks❝By using images as hyperlinks, you can create graphical web pages that link to other resources.❝In Fig. 2.7, we create five different image hyperlinks.❝Clicking an image in this example takes the user to a corresponding web page—one of the other examples in this chapter.Forms›HTML5 provides forms for collecting information from users.›Figure 2.14 is a simple form that sends data to the web server for processing.Forms (Cont.)method Attribute of the form ElementA form is defined by a form element-Attribute method specifies how the form’s data is sent to the webserver.-Using method = "post" appends form data to the browser request,which contains the protocol (HTTP) and the requested resource’s URL.-The other possible value, method = "get", appends the form datadirectly to the end of the URL of the script, where it’s visible in thebrowser’s Address field.-The action attribute of the form element specifies the script to whichthe form data will be sentForms (Cont.)action Attribute of the form Element-The action attribute of the form element specifies the script to which the form data will be sent.-Since we haven’t introduced server-side programming yet, we set this attribute to for now.-input elements that specify data to provide to the script that processes the form (also called the form handler).-An input’s type is determined by its type attribute.Forms (Cont.) Hidden Inputs❝Forms can contain visual and nonvisual components.❝Visual components include clickable buttons and other graphical user interface components with which users interact.❝Nonvisual components, called hidden inputs, store any data that you specify, such as e-mail addresses and HTML5 document file names that act as links.Forms (Cont.) text input Element❝The text input inserts a text field into the form, which allows the user to input data.❝The label element provides users with information about the input element’s purpose❝The size attribute specifies the number of characters visible in the text field.❝Optional attribute maxlength limits the number of characters input into a text field.Forms (Cont.) submit and reset input Elements❝The submit input element is a button.-When the submit button is pressed, the form’s data is sent to the location specified in the form’s action attribute.❝The value attribute sets the text displayed on the button.❝The reset input element allows a user to reset all form elements to their default values.Forms (Cont.) Additional Form Elements❝Figure 2.15 contains a form that solicits user feedback about a website.❝The textarea element inserts a multiline text area into the form.❝The number of rows is specified with the rows attribute, and the number of columns (i.e., characters per line) with the cols attribute.❝Default text can be specified in other input types,such as text fields, by using the value attribute.2.11 Forms (Cont.)›The password input inserts a password box into a form.-Allows users to enter sensitive information, such as credit card numbers and passwords, by “masking” the information input with another character, usually asterisks.-The actual value input is sent to the web server, not the asterisks thatmask the input.Forms (Cont.)❝The checkbox input element enables users to select and option.-When the checkbox is selected, a check mark appears in thecheckbox. Otherwise, the checkbox is empty-checkbox es can be used individually and in groups.checkbox es that are part of the same group have the samename❝radio buttons are similar to checkbox es, except that only one radio button in a group can be selected at any time.-All radio buttons in a group have the same name attribute butdifferent value attributes.❝The select input provides a drop-down list of items.-The name attribute identifies the drop-down list.-The option element adds items to the drop-down list.Internal Linking ›The a tag can be used to link to another section of the same document by specifying the element’s id as the link’s href.›To link internally to an element with its id attribute set, use thesyntax #id.41meta Elements ›One way that search engines catalog pages is by reading the meta element’s contents.-The name attribute identifies the type of meta element-The content attribute-Of a keywords meta element: provides search engines with a list ofwords that describe a page, which are compared with words in searchrequests-Of a description meta element: provides a three-to four-linedescription of a site in sentence form, used by search engines to catalogyour site. This text is sometimes displayed as part of the search result47。

sex and the internet

C YBER P SYCH O LOG Y & B EHAV IOR Volume 3, Number 2, 2000Mary Ann Liebert, Inc.Sex and the Internet: A Survey Instrument to AssessCollege Students’ Behavior and AttitudesPATRICIA GOODSON, Ph.D.,1DEBORAH MCCORMICK, Ph.D.,2and ALEXANDRAEVANS, Ph.D.3ABSTRACTDue to the paucity of empirical data on college students’ perceptions and behavior when searching the Internet for sexuality-related information, the purpose of this article is to pre-sent the development, psychometric properties, and initial validation results of an instrument designed to measure these factors. The questionnaire, based on Social Cognitive Theory, con-tained three scales to measure attitudes of students toward use of the Internet for (a) obtain-ing sexuality-related information, (b) establishing personal connections, and (c) for sexual en-tertainment/arousal. Each of these three scales consisted of two subscales, measuring expectancies and expectations for the above functions. The subscales demonstrated a high de-gree of internal consistency (alphas ranging from .76 to .95) and appropriate temporal stabil-ity (rs .69 to .78). A Principal Components analysis of the subscales yielded a factor struc-ture of six factors, accounting for 68.8% of the total variance. Importance of the instrument for sexuality research as well as its limitations are alsopresented.INTRODUCTIONPE OP LE H A V E A LW A Y Sbeen quick to adoptnew innovations in technology in order to satisfy their interest in and curiosity about sexual matters. The Internet is the most recent in a long line of technological inventions—from the printing press to video cameras and cassettes—that have been utilized for the pur-pose of allowing exploration of sexuality-re-lated topics.1Several of the Internet’s charac-teristics, such as easy access, affordability andanonymity,2render this form of technologyespecially powerful and unique for the ex-ploration of sexuality.“Sex” is presently the number one search term used on the Internet.3,4According to the market research firm Relevant Knowledge,more than 9.6 million people (or 15% of all Web users) accessed one of the ten most popular cy-bersex sites during April 1998. Industry sources report that sex-related searches make up 10–20% of requests by visitors to search sites on the Web. Sex is not only the number oneThis article was presented at the Western Region Annual Conference of The Society for the Scientific Study of Sexu-ality, San Francisco, CA, April 22, 1999.1Texas A&M University, Department of Health and Kinesiology, College Station, TX.2Northern Arizona University, Department of Health, Physical Education and Nutrition, Flagstaff, AZ.3The University of Texas at Austin, Department of Kinesiology and Health Education, Austin, TX.search topic on the Web but also one of its largest revenue-producers.3,5On the positive side, the Internet is func-tioning as a useful tool to promote sexuality ed-ucation,6,7however, many are disturbed by the proliferation of pornographic websites and chat rooms that include activities that may not only be offensive but also illegal. The issue of “sex on the Internet” has now become a topic of heated debate and controversy, as it touches upon matters of freedom of speech, education, and protection of youth.8Despite the widespread availability of sexu-ality-related websites, very little has been doc-umented regarding users’ behavior (What do they do?) and attitudes (What do they believe?) when it comes to searching the Internet for sex-uality-related topics. Documentation is scarce, for instance, regarding what types of informa-tion (or entertainment) users seek when online; how users feel about searching for sex-related subjects; how non-users perceive those who log on for sexual purposes, etc. A search of more than a dozen databases (including ERIC, PsychInfo, and Sociological Abstracts among others) using the search terms “sex/sexuality and Internet,” “virtual sex,” and “cybersex” re-vealed only one empirical study of the behav-ior of Internet users for sexual pursuits, carried out by Cooper and his colleagues.9In this study, authors documented from a sample of volunteer users of the Internet (N 9,177) “Who goes online for sexual pursuits, where they go, and whether it seems to be caus-ing problems in their lives” (Ref. 9, p. 156). Findings revealed expected gender differences in response rates (male respondents outnum-bered females by a ratio of 6:1) as well as for several of the studies’ variables, such as going online for sexual pursuits from home or office computers, and preferred online media (most men preferring sites with visual erotica and women choosing chat rooms). The study com-pared high, moderate, and low users (cate-gorized according to hours spent online for sex-ual purposes) and focused on assessing pat-terns of use along with reported distress caused by online behavior. Sixty-one percent of re-spondents admitted changing their age when online, but only 5% reported assuming a dif-ferent gender; 70% said they keep secret how much time they spend on Internet sexual pur-suits, and most respondents reported that their sexual experiences online were “satisfying but not particularly arousing.” Authors concluded that high usage of the Internet for sexual pur-suits caused distress only in a small percentage of their sample. Additionally, they examined the implications of these findings for treatment and prevention of mental health problems.9 While Cooper’s study represents a much needed step in the process of documenting on-line behavior related to sexuality, it is limited by the nature of its sample: only respondents over 18 who indicated they had logged on to a sexual site at least once were invited to com-plete the non-randon survey. Care was taken to demonstrate that the sample of volunteers for this study was similar to a random sample of visitors to the website, and sim-ilar to a sample of 9.6 million visitors of adult sexual websites. The study is also limited by the nature of its dependent variable: online sex-ual pursuits. It remains unclear what is the de-finition given to “sexual pursuits” (Is this mainly sexual entertainment, or does it include seeking sexuality-related information?).Given the paucity of information on this topic, the purpose of this article is to present the development of an instrument designed to assess college students’ perceptions and be-havior when searching the Internet for sexual-ity-related matters. Our instrument (see Ap-pendix) represents an important contribution to this new field of inquiry because it is de-signed to document behaviors and attitudes of both users and non-users of the Internet while investigating three different aspects of college students’ use of the Internet for sexuality mat-ters: information-seeking, relationship build-ing and maintenance, and sexual arousal/en-tertainment. A combination of age, education, interest in sexuality, computer literacy, and availability makes college students a particu-larly attractive target population for Internet information dissemination, communication, and commerce.10,11Below we describe the de-velopment of the instrument, its psychometric properties, initial validation results and limita-tions.THEORETICAL FRAMEWORKSocial Cognitive Theory (SCT) was chosen as the framework for the construction of our ques-tionnaire and collection of data.12,13Even though examination of Internet and E-mail users’ behavior and attitudes is a rather nascent pursuit, the practice and views of users of other media have been extensively scrutinized. This is especially true regarding sexuality-related media impact. The study of the effects of pornography consumption upon violent sexual behavior, for instance, has consistently used SCT for its theoretical framework, alongside aggression and excitation transfer theo-ries.14,15,16Such preference for SCT probably owes to this theory’s non-simplistic view of media im-pact. Whereas most of the early research on pornography effects was based on a “monkey-see-monkey-do” theory of media influence, SCT proposes that the media’s effects are nec-essarily mediated by the consumer’s cognitive abilities, reinforcement history and outcome expectations regarding the images he/she con-sumes.17In addition to its use in investigations of the effects of pornography, SCT has also been used to explain the social diffusion of prod-ucts, ideas, and values through mass com-munication.18Acknowledging that there are multiple pathways through which the media may affect human behavior and attitudes, SCT provides useful intrapersonal, behav-ioral and environmental constructs (such as observational learning, symbolic modeling, self-beliefs of efficacy, outcome expectations and expectancies, among others) for under-standing media influence on learning about sexuality. Moreover, SCT allows not only an appropriate theoretical understanding of hu-man learning, but also of the social interac-tions that function as environmental contexts within which learning occurs.19Our study focuses only on selected SCT constructs (see discussion below). Further studies on the topic of Internet and sexuality information/entertainment would do well to explore and test those concepts we have not addressed.METHODSDevelopment of itemsOur purpose was to develop a survey in-strument for documenting college students’ at-titudes and behavior when using the Internet for three main functions: (a) obtaining infor-mation related to sexuality (for school, work-related projects, or personal information); (b) establishing and maintaining relationships (such as using E-mail or participating in chat groups); and (c) sexual gratification (sexual arousal and/or entertainment). These three uses mirror the predominant uses of the Inter-net for general purposes.20The first step in compiling an item pool con-sisted of asking undergraduate students en-rolled in two health classes at The University of Texas at San Antonio (UTSA) to brainstorm a list of potential questions. Once these student-generated questions were obtained, our second step consisted of categorizing the questions ac-cording to selected constructs from Social Cog-nitive Theory. Student-generated questions fell under the categories of (a) situations (subjects; perception of their environments); (b) expecta-tions (outcomes related to specific uses of the Internet for sexuality-related purposes); (c) ex-pectancies (value subjects place on the out-comes defined above); (d) emotional arousal (the emotions generated by using the Internet for sexual gratification); and (e) behavior (sub-jects’ actual search practices/patterns).After organizing the questions into these cat-egories we added several demographic items including one aimed at controlling for prior ex-posure to human sexuality classes, where searches on the Internet may be required as class assignments.Content validityConsensual validity.To ensure consensual va-lidity for each of the sections of the questionnaire, a draft of the instrument was sent to experts in the fields of sexuality and/or electronic com-munications.21These experts were asked to pro-vide feedback related to the relevance of each item, the appropriateness of item wording and potential gaps in the content beingcovered.Pre-survey evaluation of items.Following rec-ommendations that survey questions be evalu-ated prior to use in a full-scale study through focus group discussion, intensive individual interviews, and field pretesting,22a version of the questionnaire (revised according to experts’comments) was submitted to a focus group of UTSA students.The focus group consisted of students from the Division of Education at UTSA. Students were asked to answer the items on the questionnaire, immediately prior to the meeting. Due to the sen-sitive nature of the topic, they were instructed to role-play as they answered the questions. Five potential “roles” or “characters” were presented to the group (e.g., someone who uses the Inter-net for research on human sexuality only; some-one who searches for sexually explicit materials; someone who does not use the Internet at all) and each participant chose one character to role-play while answering the questionnaire. All an-swers, then, reflected how this character would potentially answer the questions being posed in the instrument (not how the student him/herself would choose to answer). The main purpose of the focus group was to detect possible ambigu-ous wording of questions or of response alter-natives, as well as to check for the flow of ques-tions (including the use of skips and filters). Despite inherent limitations, we chose to conduct only one focus group session due to the absence of problems encountered by either the group of experts or these focus group participants.Intensive individual interviews.In order to de-termine whether the questions were being un-derstood by respondents in the intended man-ner, a revised version of the questionnaire (based on the suggestions made during the fo-cus group) was then submitted to six students who met individually with one of the authors. These intensive interviews assessed students’understanding of each question, strategies em-ployed for choosing answers, and identifica-tion of sensitive questions (those that might not be answered truthfully by respondents).Questionnaire structure and scalesBehavior items.The questionnaire to be field tested consisted of eight sections: A through H (the final version maintained this same struc-ture). Section A consisted of demographic in-formation (age, ethnicity, marital status, reli-gious preference, religiosity, academic status and having had a sexuality class), and sections B through E contained several items designed to assess different behaviors employed by stu-dents while using the Internet for accessing sex-related topics. Section B, for instance, contained items related to frequency and history of use of the Internet/E-mail; location from which stu-dents access the net (campus computer lab; home computer; personal computer at work; friend/relative’s computer) as well as reasons for not using the Internet or E-mail (e.g., “I feel intimidated by this technology”; “It is incon-venient for me because I don’t have time to go to the campus computer lab”). Section C con-tained items focusing on types of sex-related information usually searched for, and whether these searches were for class/work assign-ments or for personal information.Section D consisted of questions designed to gauge if students use E-mail to keep in touch with family and friends, if they’ve developed new friendships over the E-mail/Internet, if they participate in chat groups and whether they disclose personal information online that they would not disclose in a face-to-face inter-action. We also wanted to learn whether stu-dents might present themselves, online, with a different persona and, when this occurred, which aspects of their identity were re-created (such as changing gender, age, sexual orienta-tion, physical appearance and availability sta-tus).Seven items in section D were included to as-sess if students had ever met face-to-face with individuals they first met online and their per-ceived impact of online friendships on their off-line relationships with their partners (e.g., “Has your partner ever expressed jealousy over the relationships you have developed online?”).Behavior items in section E were designed to capture college students’ patterns of behavior when using the Internet for sexual entertain-ment/arousal; this section contains 13 items such as “I have subscribed to sexually explicit websites (paid for registering).” Additionally, six items were included asking students about masturbation, cybersex, and use of alcoholanddrugs while viewing sexually explicit materi-als on the net (e.g., “I like to use stimulants (drugs) while having cybersex with my online partner(s)”).Emotional arousal and general views.Section F contains 11 items gauging respondents’ emo-tional arousal when viewing sexually explicit materials over the Internet. Examples of items include: “When I view sexually explicit mate-rials on the Internet I have a general feeling of excitement and anticipation” and “I am con-cerned that my cyber trail will be followed (could be caught later).”As only respondents who answered, in sec-tion E, that they had accessed sexually explicit materials on the Internet (either accidentally or intentionally) answered the attitude questions in that section, section G was designed to cap-ture the beliefs of all respondents who used the Internet (even if not for sexual entertainment) about cybersex and college students’ general behavior regarding sex on the Internet. This section contains nine items such as : “Cybersex can be considered real sex”; “Cybersex is an al-ternative way to practice safer sex,” and “Per-sons who engage in cybersex are weird.”A final section—section H—contains eight items gauging if respondents were in favor of or against regulation of public access to sexu-ally explicit materials on the Internet (e.g., “Are you in favor or against public libraries block-ing access to sexually-explicit websites whose primary purpose is sexual entertainment/ arousal?”).Attitude scales and subscales.Within sections C, D, and E, 30 items were designed to mea-sure both expectations and expectancies re-garding the use of the Internet for obtaining sexuality-related information (Items C5 through C14), to establish personal connections (items D23 through D30), and for sexual entertain-ment/arousal (items E21 through E32). As per-sonal attitudes are determined by behavioral beliefs (expectations) and evaluation of behav-ioral outcomes (expectancies),23,24an overall at-titude score was obtained through a linear com-bination of the items in the expectation and expectancy scales (by multiplying the expecta-tion score for each outcome by the corre-sponding expectancy score and then summing these multiplied scores across all items of the scales). This linear combination yielded three attitude scales: attitudes towards information-seeking; attitudes toward personal connec-tions, and attitudes toward sexual entertain-ment. The items for each expectation and expectancy subscale are presented in Table 1.Item responses were scored on a Likert-type 5-point scale. For expectations, responses ranged from 1 (Strongly disagree) to 5 (Strongly agree). Higher scores on the expectation scales indicate positive beliefs about specific out-comes related to use of the Internet for the three functions described above. For expectancies, scale responses ranged from 1 (not important at all) to 5 (extremely important). Higher scores on the expectancies scales indicate a high value placed upon the use of the Internet for the three proposed purposes. For the combined attitude scores, high values represent a more favorable attitude.Field pretestingThe next step in validating the question-naire’s attitude scales was field pretesting of all items. Pretesting was carried out in three phases, as described below.Phase 1—Reliability testing.For an assess-ment of the subscales’ internal consistency and evaluation of items to be retained for the final version, questionnaires were distributed to 207 students (38% males and 62% females; 55% se-niors) enrolled in undergraduate health classes at UTSA during the Spring semester, 1998. Half of the sample was White (50.7%) and over a third were Mexican American/Hispanic/ Latino (36.2%—hereafter referred to as His-panics); students’ mean age was 25.5 years (SD 6.22), with a range of 18–57 years. Sixty-six percent of students were single and 23% were married. This distribution closely resem-bles UTSA’s student profile (54.8% of students enrolled in the Fall of 1997 were female; 55.8% of students are aged 23 and older; 42.4% are Hispanic).25The sample was almost equally split among students who had had a human sexuality course either in high school or incol-T A B LE 1.M EA N S , S TA N D A RD D E VIA TIO N S , I TE M -T O TA L C O R RE LA TIO N S A N D C RO N BA C H A L PH AFO RE XPEC T AT IO N A N D E X PEC TA N C Y I TEM S (P H A SE 3—A G GR EG A TED D A TA )Item-TotalMSDrUse of the Internet to search for sexuality-related information ExpectationsC5.I have learned about sexuality-related topics by using the Internet. 2.87 ing the Internet to learn about sexuality allows me to remainanonymous while searching for information.3.48 ing the Internet to learn about sexuality minimizes my embarrassement.3.36 1.13.48C8.I find the sexuality-related information available on the Internet to be accurate. 3.170.84.52C9.The Internet is a good way for anyone to learn about sexuality-related topics. 3.15 1.08.51Scale16.053.86Internal consistency (Cronbach)ExpectanciesHow important is it to you that . . .C10.You can learn about sexuality-related topics by using the Internet? 3.07 1.11.64C11.You have a way of searching for sexuality-related information while3.41 1.14.65remaining anonymous?C12.You do not feel embarrassed when learning about sexuality-related topics? 3.29 1.21.64C13.You have access to accurate information about human sexuality?3.90 1.05.56C14.Other people have a way of learning about sexuality-related topics using the3.61 1.00.62Internet?Scale17.294.26Internal consistency (Cronbach)Use of the Internet/E-mail to establish personal connections/relationships ExpectationsD23.The Internet is an alternataive way/place to meet new people.3.19 1.08.63D24.People can develop meaningful relationships over the Internet/E-mail. 2.65 1.00.72D25.The Internet provides a way of developing emotionally supportive2.700.95.68relationships.D26.The Internet/E-mail is an alternative way/place for meeting potential2.20 1.11.57sexual partners.Scale10.763.36Internal consistency (Cronbach)ExpectanciesHow important is it to you that . . .D27.An alternative way/place for meeting new people is available?2.47 1.12.70D28.People can develop meaningful relationships over the Internet/E-mail? 2.260.96.79D29. A way of developing emotionally supportive relationships is available? 2.59 1.10.68D30.An alternative way/place for meeting potential on-line sexual partners1.770.89.62is available?Scale9.113.41Internal consistency (Cronbach)Use of the Internet for sexual entertainment/arousal ExpectationsSexually explicit materials on the Internet . . .E21.Are a way of learning new sexual techniques. 2.87 1.08.68E22.Help improve my sexual relationships off-line. 2.48 1.03.75E23.Are a way of fulfilling my sexual fantasies. 2.46 1.15.78E24.Stimulate my sexual fantasies. 2.64 1.23.83E25.Make me sexually aroused. 2.67 1.20.83E26.Satisfy my curiosity about sex. 2.58 1.13.73Scale15.73 5.76Internal consistency (Cronbach)ExpectanciesHow important is it to you to use the Internet . . .E27.To learn new sexual techniques?2.150.99.82E28.To improve your sexual relationships off-line? 2.15 1.06.78E29.To fulfill your sexual fantasies? 2.09 1.04.90E30.To stimulate your sexual fantasies? 2.17 1.09.89E31.To become sexually aroused?2.04 1.00.88E32.To satisfy your curiosity about sex? 2.24 1.07.79Scale12.855.60Internal consistency (Cronbach).76N 243.82.83N 465.85N 465.92N 191.95lege and those who had not (54% had taken a semester-long course). Eighty percent of the students said they used E-mail, and 85% used the Internet (only 22% of students, however, declared using it 2–3 times a week, or daily; most accessed the Internet less than once a week).Cronbach’s alpha coefficient was calculated for each of the expectation and expectancy sub-scales and ranged from .78 (expectations re-lated to use of the Internet to search for sexu-ality-related information) to .95 (expectancies related to using the Internet for sexual enter-tainment/arousal—Table 1). As a factor analy-sis of the scales’ items would render unstable solutions due to the small sample size (not all 207 respondents answered the questions for all three scales), corrected item-total correlations were observed for potential deletion of non-useful items. None of the items yielded an item-total correlation smaller than .50 (our elimina-tion criterion) and, therefore, none of the scale items were deleted after this first phase of test-ing.Phase 2—Temporal stability of scales.Even though none of the scale items were deleted, we did eliminate a couple of the behavior items presenting substantial missing data or yielding irrelevant information (e.g., “Do you surf the Internet just for fun?” and “Do you share an E-mail/Internet password with someone else?”). Following deletion of these few behavioral items, a revised version of the questionnaire was distributed to 106 UTSA students enrolled in health promotion classes during the Summer of 1998.Again, most of the phase two students were female (70%), with a mean age of 26 years (SD 6.98). The ethnic split was 46% White and 44% Hispanic. Only 22% were married (64% were single) and 67% were seniors. Thirty-seven percent had taken a semester-long sexuality course either in high school or col-lege. Seventy-seven percent said they used E-mail and 89% said they used the Internet. The majority of Internet users declared using it less than once a week (63%).In phase 2, students were asked to fill out the questionnaire and then re-take it 2 weeks later. Temporal stability of the expectation and ex-pectancy subscales was assessed through cor-relation of students’ scores. Test-retest correla-tions for each of the subscales ranged from .69 to .78 (all correlations were significant at the .01 level). Most of the scales were equally reliable for males and females. However, the scale mea-suring expectancies toward using the Internet for sexuality-related information was, in this sample, more reliable for females (r.83) than for males (r.60); the same pattern was pre-sent in the expectancies toward using the In-ternet to establish personal connections and re-lationships, where the test-retest correlation for females was .76 and .68 for males (all correla-tions were significant at the .01 level of proba-bility, with reduced sample sizes ranging from 16 to 28 cases for males and 18 to 64 for fe-males).Phase 3—Factor analysis.Concomitant with the test-retest phase, we asked for faculty vol-unteers to distribute the questionnaire to their students. Our objective was to increase the sample size in order to perform a factor analy-sis of the expectation and expectancy items. An additional 193 subjects responded to the ques-tionnaire during this phase. These students were similar to the previous samples; most were female (57%); 46% were Hispanic and 44% White, with a mean age of 24.5 years (SD 4.96). Most were single (63%), seniors (62%), and 63% had not taken a semester-long sexu-ality education course either in high school or college.Given that the scale items remained identi-cal during all phases of the study, that the ad-ministration of the questions during phases 1, 2, and 3 were very close in time (late Spring and early first Summer sessions) as well as pro-cedurally similar, and that the samples were demographically equivalent across all phases, we aggregated respondents for the factor analysis, resulting in a final sample size of 506 subjects.Originally, the items for the expectation and expectancy subscales were designed to repre-sent six aspects of attitudes: expectations and expectancies related to using the Internet for sexuality-related information; expectations and expectancies related to using the Internet to es-tablish personalconnections/relationships,。

基于j2se的学生信息管理系统【呕心沥血整理版】

齐齐哈尔大学综合实践（论文)题目基于j2se的学生信息管理系统学院通信与电子工程学院专业班级通信工程102班学生姓名邴笑然指导教师于泓博成绩2013年11 月24 日齐齐哈尔大学综合实践（论文）摘要随着信息技术在管理上越来越深入而广泛的应用,管理信息系统的实施在技术上已逐步成熟。

管理信息系统是一个不断发展的新型学科，任何一个单位要生存要发展,要高效率地把内部活动有机地组织起来,就必须建立与自身特点相适应的管理信息系统。

本文介绍了在windows环境下开发一个管理信息系统的过程。

通过分析某一学校学生管理的不足,创建了一套行之有效的计算机管理学生的方案。

文章介绍了学生管理信息系统的系统分析部分，包括可行性分析、业务流程分析等;系统设计部分主要介绍了系统功能设计和数据库设计及代码设计；系统实现部分说明了几个主要模块的算法，本系统界面友好，操作简单,比较实用.关键词:信息管理系统；学生管理；流程分析；系统设计I齐齐哈尔大学综合实践（论文）AbstractAs information technology in management more and more in—depth and extensive application, the implementation of the management information system has gradually mature in technology。

Management information system is a continuous development of new disciplines，any one unit to survive to development，to efficiently organize the internal activity organically, we must set up corresponding to their own characteristics of management information system。

Semester-Thesis_TPM-Emulator for Linux

Semester ThesisA Software-based TPM Emulatorfor LinuxMario StrasserDepartment of Computer ScienceSwiss Federal Institute of Technology ZurichSummer Semester2004Supervisors:Paul E.SevinçProf.Dr.David BasinAbstractThe Trusted Computing Group(TCG)has produced several speciﬁcations for trusted computing such as for a security chip,called Trusted Platform Module(TPM),and for related software inter-faces(TCG Software Stack Speciﬁcation(TSS)).Although a TPM is probably going to be part of more and more state-of-the-art personal comput-ers,there are and will always be situations where a TPM is unavailable or unaccessible.Further-more,the TCG and the TPM in particular are controversial and disputed matters.Therefore,the goal of this semester thesis was not to show that TPMs are either good or bad,but to implement a software-based TPM emulator for Linux to give people the means to easily explore TPMs for educational and experimental purposes.In the course of this semester thesis,about50out of120(∼42%)TPM commands have been implemented and for the remaining,appropriate function-stubs have been provided.Additionally, a complete TCG Device Driver Library(TDDL)to access the TPM has been created to provide future applications with a suitable and standardized device interface.Despite the limited function-ality,almost all available TPM applications work well with the current emulator implementation as the most important and frequent commands are already supported.Currently,the TPM emu-lator has been successfully tested by the developers as well as by two other people and on three different Linux platforms.Contents1Introduction11.1Motivation and Goals (1)1.2Tasks (1)1.3Typographic Conventions (2)1.4Outline (2)1.5Acknowledgments (2)2Trusted Computing and Trusted Platform Module Basics32.1Trusted Computing (3)2.2Trusted Platform Module (4)3Installation and Usage113.1TPM Emulator (11)3.2TCG Device Driver Library (13)4Implementation of the TPM Emulator194.1Concept (19)4.2Structure (19)4.3Naming and Coding Conventions (20)4.4License and Copyright (20)4.5Kernel Module/Interface (21)4.6TPM Data Structures (21)4.7Internal Data (23)4.8Marshaling and Unmarshaling (25)4.9Authorization (27)4.10Cryptographic Functions (28)4.11Initialization,Self-Test,and Shutdown (29)4.12Command Execution (30)4.13Command Summary (31)4.14TCG Device Driver Library (38)IV CONTENTS5Conclusion395.1Summary (39)5.2Outlook (39)A FIPS Tests41A.1Statistical Random Number Generator Tests[FIPS140] (41)A.2SHA-1Test Vectors[FIPS180] (42)A.3HMAC Test Vectors[RFC2202] (42)B Source and Documentation Files45B.1CD-ROM Content (45)B.2TPM Emulator Package (45)B.3TDDL Package (46)Chapter1IntroductionWhat I cannot create I do not understand.–R.Feynman1.1Motivation and GoalsThe Trusted Computing Group(TCG)[TCGBG]–successor of the Trusted Computing Platform Alliance(TCPA)–has produced several speciﬁcations for trusted computing such as for a security chip,called Trusted Platform Module(TPM)or Fritz-Chip1,and for related software interfaces (TCG Software Stack Speciﬁcation(TSS))[TPMPart1,TPMArch,TSS11].Although a TPM is probably going to be part of more and more state-of-the-art personal com-puters,there are and will always be situations where a TPM is unavailable or unaccessible.Fur-thermore,the TCG and the TPM in particular are controversial and disputed matters.Therefore, the goal of this semester thesis was not to show that TPMs are either good or bad(whatever this means),but to implement a software-based TPM emulator for Linux to give people the means to easily explore TPMs for educational and experimental purposes.Linux was chosen as the target platform for two main reasons:First,almost all currently available TPM-based applications and projects(e.g.,IBM’s TPM utilities[IBMSW],tcgLinux[IBMTL]or the enforcer project[DCEF])run under Linux.Second,we are more familiar with device-driver development under Linux than under any other operating system.1.2Tasks•Implementation of a software-based TPM emulator for Linux by means of a Linux kernel module.•Implementation of an appropriate TCG Device Driver Library(TDDL)to access the emu-lator.•Making the device interface of the emulator compatible to IBM’s device driver[IBMSW].•At least supporting Linux kernel release2.4.1Named after the famous US-senator Fritz Hollings who supports the ideas of the TCG very much.2Chapter1-Introduction 1.3Typographic Conventions•Functions,variables,and constants are set in a mono-spaced typewriter font:function(),data,CONSTANT.•Shell commands are marked with a leading#:#ls*.c•Code snippets and listings contain colored and highlighted keywords and are printed in a smaller font:/*listing example*/for(int i=0;i<10;i++)...1.4OutlineThis report is structured as follows:Chapter two gives a brief introduction into Trusted Comput-ing and highlights the capabilities of the Trusted Platform Module(readers already familiar with these topics might skip this chapter).In chapter three,the installation and usage of the TPM em-ulator as well as of the dedicated device driver library are explained.Chapter four,describes the implementation of the TPM emulator.Note that this chapter only points out the most important implementation and design issues and decisions.For a more detailed description we refer to the documented source code and[TPMPart1,TPMPart2,TPMPart3].In chapterﬁve,we conclude by giving a summary and a short outlook of future work.1.5AcknowledgmentsI would like to extend my gratitude to all people who made this semester thesis possible.First of all I would like to thank my supervisors Prof.Dr.David Basin and Paul E.Sevinç.A special thank you goes to Achim D.Brucker and Michael Näf for supplying me with the neces-sary hardware and software.Furthermore,I would like to thank Jeff Kravitz and David Safford from the IBM Watson Research Center for sharing information about their TPM libraries and examples with me,as well as Omen Wild from Dartmouth College and Jesus Molina from the University of Maryland for testing the emulator.Chapter2Trusted Computing and Trusted Platform Module BasicsA common mistake people make when trying to design something completely foolproof is to un-derestimate the ingenuity of complete fools.–D.AdamsWalking on water and developing software from a speciﬁcation are easy if both are frozen.–E.Berard2.1Trusted ComputingThe following chapter gives a brief overview of trusted computing and TPMs.The interested reader is referred to[TPMPart1,TPMPart3,TPMArch,TPMNew,TCPHP]for a complete and comprehensive description.2.1.1Trusted PlatformA Trusted(Computing)Platform(TP)is a platform that is trusted by local users and remote entities including users,software and web sites.To enable a user to trust such a platform,a relationship of trust must be established between the user and the computing platform so that the user believes that an expected boot process,a selected operating system,and a set of selected security functions in the computing platform have been properly installed and operate correctly.The user makes his or her own judgment on whether or not he or she trusts the relationship.2.1.2Roots of TrustThe so called Roots of Trust(RT)are components within a TP that must be trusted because mis-behavior might not be detected.They provide at least functionality for measurement,storing,and reporting of characteristics that affect the trustworthiness of the monly there is one root of trust for each capability:a Root of Trust for Measurement(RTM),a Root of Trust for Storage(RTS),and a Root of Trust for Reporting(RTR).In the trusted platform speciﬁed by the Trusted Computing Group(TCG),the Trusted Platform Module(TPM)acts as the RTS as well as the RTR whereas the Core Root of Trust for Measurement4Chapter2-Trusted Computing and Trusted Platform Module Basics (CRTM)is most often part of the BIOS.2.2Trusted Platform ModuleThe Trusted Platform Module is a hardware component that provides four major classes of func-tions:1.Cryptographic functions:(P)RNG,SHA-1,HMAC,RSA.2.Secure storage and reporting of hash values representing a speciﬁc platform conﬁguration.3.Protected key and data storage.4.Initialization and management functions.In addition,the following auxiliary functions exist:•Monotonic counters and timing-ticks•Non-volatile storage•Auditing•Delegation2.2.1Cryptographic FunctionsIt should be mentioned that the TPM is not a cryptographic accelerator.There are no speciﬁed minimum throughput requirements for any of the cryptographic functions.Random Number GeneratorThe Random Number Generator(RNG)is the source of randomness in the TPM.It is used for the generation of nonces,keys and the randomness in signatures.The TPM speciﬁcation allows for both true hardware-based and for algorithmic pseudo random-number generators.SHA-1EngineA SHA-1[FIPS180]message digest engine is primarily used for computing message or data signa-tures and for creating key blobs.The hash interfaces are also exposed outside the TPM to support measurement during the boot phases.HMAC EngineThe HMAC[RFC2104]calculation provides two pieces of information to the TPM:proof of knowledge of the authorization data(shared secret key K)and integrity of the message M.The used algorithm implementation uses SHA-1as the hash function and a padding ipad(opad)con-sisting of64repetitions of byte0x36(0x5C).In the following formula⊗denotes the bitwise xor-operation and concatenation:HMAC(K,M)=SHA-1(K⊗opad SHA-1(K⊗ipad M))2.2.Trusted Platform Module5Figure2.1:Schematic representation of a Trusted Platform ModuleRSA EngineThe RSA asymmetric algorithm is used for digital signatures and for encryption.The PKCS #1standard[PKCS1]provides the implementation details for digital signature,encryption,and data formats.The RSA key generation engine is used to create signing keys and storage keys.A TPM must support up to2048-bit RSA keys,and certain keys must have at least a2048-bit modulus.There is no requirement concerning how the RSA algorithm is to be implemented.TPM manufacturers may use Chinese Remainder Theorem(CRT)implementations or any other method.2.2.2Platform IntegrityPlatform Conﬁguration Register(PCR)A Platform Conﬁguration Register(PCR)is a160-bit storage location for discrete integrity mea-surements in form of SHA-1digests.There are a minimum of16PCR registers which are all inside the shielded location of the TPM.The correlation of PCR registers to speciﬁc measure-ments is speciﬁed in[TPMPC](see table2.1on the following page).To allow the storage of an unlimited number of measurements in a speciﬁc PCR register,its new value is dependent on both its old value and the new value to be added:PCR[i]←SHA-1(i PCR[i] new value to add)As a result,updates to PCRs are not commutative.For example,measuringﬁrst A then B is not the same as measuringﬁrst B then A.Furthermore,subsequent updates to a PCR cannot be determined without knowledge of the previous PCR values or all previous input messages provided to a PCR register since the last reset.Integrity MeasurementIntegrity measurement is the process of obtaining metrics that reﬂect the integrity of a platform, storing them,and putting digests of those metrics in the PCRs.Examples for such metrics are the6Chapter2-Trusted Computing and Trusted Platform Module BasicsPCR Index PCR Usage0CRTM,BIOS,and Platform Extensions1Platform Conﬁguration2Option ROM Code3Option ROM Conﬁguration and Data4IPL Code(usually the MBR)5IPL Code Conﬁguration and Data6State Transition and Wake Events7Reserved for future usageTable2.1:PCR usage on PC platforms.opcode of the operating system or the BIOS conﬁguration settings.The philosophy of integrity measurement,storage,and reporting is that a platform may be permitted to enter any state,in-cluding undesirable or insecure states,but that it cannot lie about states that it was or was not in.Starting with the CRTM,there is a bootstrapping process by which a series of trusted subsystem components measure the next component in the chain and record the value in a PCR register(e.g., CRTM→BIOS→MBR→OS→Application).By these means,software is measured and recorded before it is executed.The recordings cannot be undone until the platform is rebooted. Integrity ReportingIntegrity reporting is used to determine a platform’s current conﬁguration state.The reports are digitally signed,using therefore created Attestation Identity Keys(AIK),to authenticate the PCR values as created by a trusted TPM.To ensure anonymity,different AIKs should be used with different parties.Attestation that a speciﬁc AIK really belongs to a trusted platform without dis-closure of the actual TPM identity can either be done by using a trusted third party(privacy CA) or by means of Direct Anonymous Attestation(DAA)[HPDAA].The latter has the advantage that it avoids a possible linkage of the several AIK by the privacy CA.2.2.3Protected Key and Data StorageKey StorageThe Root of Trust for Storage(RTS)protects keys and data entrusted to the TPM.Due to size limitations,only a small amount of volatile memory,where keys are held while performing signing and decryption operations,is provided.Inactive keys are encrypted using an adequate storage key (SK),often referred to as the keys parent key(seeﬁgure2.2on the next page).The so called Storage Root Key(SRK)acts as the root of this key hierarchy and cannot be removed from the TPM.However,a new SRK may be created as part of the take-ownership process.This has the side-effect that data objects controlled by the previous SRK are no longer accessible.2.2.Trusted Platform Module7Figure2.2:Key storage hierarchy.Further,the TPM can also be used to create new signing or storage keys that can either be bound to it or marked as migratable.In addition to the speciﬁc key parameters(key length,usage,authoriza-tion data,etc.)the keys parent key has also to be speciﬁed.A new created key is not automatically loaded into the TPM but encrypted using the given parent key and returned to the user.Hence,it has to be explicitly loaded before usage.Data ProtectionThe TPM speciﬁcation deﬁnes four classes of data protection:Binding,Sealing(Sealed-Binding), Signing,and Sealed-Signing.Due to the limited data size that can be directly protected(∼210 bytes with a2048-bit RSA key)not the conﬁdential data itself but a symmetric key which is used to(de-)encrypt the data is typically protected.Binding Binding is the operation of encrypting data using a public key.The data is only recov-erable by decrypting it with the corresponding private key.If the private key is managed by the TPM as a non-migratable key,only the TPM that created the key may use it.Hence,the data might be seen as bound to a particular TPM.However,as it is possible to create migratable private keys that are transferable between multiple TPM devices,binding has no special signiﬁcance beyond encryption.Sealing Sealing takes binding one step further inasmuch as the data are not only encrypted but also bound to a speciﬁc platform conﬁguration.Sealing associates the encrypted data with a set of PCR-register values and a non-migratable asymmetric key.The TPM only decrypts the data when the platform conﬁguration matches the speciﬁed PCR-register values.Sealing is a powerful feature of the TPM as it provides assurance that the protected data is only recoverable when the platform is in a speciﬁc conﬁguration.Signing Signing of a data digest is only possible with signing only keys.These keys cannot be used for encryption and therefore avoid that a malicious user can encrypt an accordingly prepared data object and misuse it as a valid signature.Sealed-Signing Signing operations can also be linked to PCR registers to ensure that the plat-form that signed the data meets a speciﬁc conﬁguration.When a veriﬁer demands that a signature must include a particular set of PCR registers,the speciﬁed registers are added to the data and included into the computation of the signature.8Chapter2-Trusted Computing and Trusted Platform Module Basics 2.2.4Initialization and management functionsOpt-InTPM modules are shipped in the state the customer desires.This ranges from disabled and deac-tivated to fully enabled;ready for an owner to take possession.TPM OwnershipTaking ownership of a TPM is the process of inserting a shared secret into a TPM’s shielded-location.Proving knowledge of this authentication value proves that the calling entity is the TPM owner.The owner of the TPM has ultimate administrative control,in particular it can enable or disable the TPM,create AIKs and set policies for the TPM.There is no mechanism to recover a lost TPM owner authentication value.Recovery from a lost or forgotten authentication value involves removing the old value and installing a new one,thereby invalidating all information associated with the previous value.The semantics of platform ownership are tied to the root of trust for storage(RTS).During the process of taking ownership,a new Storage Root Key(SRK)and a new(unique)TPM proof-value are created.It follows that objects owned by a previous owner will not be inherited by the new owner and must(if still needed)be explicitly transferred.AuthorizationThe purpose of the authorization protocols and mechanisms is to prove to the TPM that the ini-tiator of a command has permission to execute it and to access the involved data objects.For instance,they are used to establish platform ownership,restrict key usage,and to apply access control to(opaque)objects.The proof comes from the knowledge of a shared secret,the so called authorization data.The TPM treats knowledge of the authorization data as complete proof,no other checks are necessary.There are three protocols to proof the knowledge of a speciﬁc piece of authorization data.The Object-Independent Authorization Protocol(OIAP)supports multiple authorization sessions for arbitrary entities whereby each entity has to be authorized individually.The Object-Speciﬁc Au-thorization Protocol(OSAP)supports an authorization session for a single entity only,but has the advantage that the authorization data has to be used only once during the whole session.The Delegate-Speciﬁc Authorization Protocol(DSAP)supports the delegation of owner or entity au-thorization.New authorization information is inserted by the Authorization Data Insertion Protocol(ADIP) during the creation of an entity.The Authorization Data Change Protocol(ADCP)and the Asym-metric Authorization Change Protocol(AACP)allow the changing of the authorization data for an entity.The protocols use a rolling nonce paradigm that is,they require that a nonce from one side is in use only for one message and its reply.For instance,a TPM’s nonce which is returned as part of its command reply is part of the next command request.This mechanism is used to prevent reply as well as man-in-the-middle attacks.2.2.Trusted Platform Module9 2.2.5Auxiliary FunctionsMonotonic CountersMonotonic counters provide an ever-increasing incremental value which is designed to not wear out in theﬁrst7years of operation(with an increment once every5seconds).A TPM must support a minimum of at least4concurrent counters.Non Volatile StorageThe TPM contains a protected and shielded non-volatile storage area.Its main purpose is to provide the manufacturers and owners with a area for storing protected information.The TPM owner,when deﬁning the area to use,will set the access and use policy for the area.He can set authorization values,delegations,PCR values and other controls(e.g.,whether and how often data might be written to this area).The TPM does not control,edit,validate or manipulate in any manner the information in the non-volatile store.It is merely a storage device that enforces the speciﬁed access rules.AuditingTo give the TPM owner the ability to determine that certain operations on the TPM have been executed,auditing of commands is possible.The audit value is a digest held internally to the TPM and externally as a log of all audited commands.The internal digest is only used to detect manipulations of the external log and does not contain any actual log information.It is in the responsibility of the TPM owner to specify which commands generate an audit event and to change the selection at any time.Delegation ModelThe TPM owner is an entity with a single super user privilege to control the TPM.Thus,if a TPM requires some kind of management,the TPM owner must perform that task himself or reveal his privilege information to another entity.This other entity thereby obtains the privilege to operate all TPM controls,not just those intended by the owner.Therefore,the owner often must have greater trust in the other entity than is strictly necessary to perform an arbitrary task.The delegation model addresses this issue by allowing delegation of individual TPM owner privileges(the right to use individual owner authorized TPM commands)to individual entities.2.2.6Command StructureTPM commands(responses)are byte arrays which consist of three main parts:a request(response) header,some command-speciﬁc input(output)parameters,and an optional authorization trailer. Presence or absence of the authorization trailer depends on the used command(response)type, deﬁned by the tagﬁeld.If it is set to TPM_TAG_RQU_COMMAND,no authorization data is avail-able,if it is set to TPM_TAG_RQU_AUTH1_COMMAND,only auth1is present,and if it is set to TPM_TAG_RQU_AUTH2_COMMAND,both auth1and auth2are given.Integer values which are larger than one byte are encoded in network byte-order and might have to be converted into the local byte-order of the host platform.Since version1.2of the TPM10Chapter2-Trusted Computing and Trusted Platform Module Basicstag command or response type(normal,(double)authorized)size size of the whole command(including header and trailer)ordinal command number(actual function to execute)result return code(zero on success,an error code otherwise)Figure2.3:TPM command sructurespeciﬁcation commands can also be sent from and to the TPM in an encrypted form using the transport encryption command.Chapter3Installation and UsageCaptain Kirk:“You ought to sell an instruction and maintenance manual with this thing.”Cyrano Jones:“If I did,what would happen to man’s search for knowledge?”–Star Trek,The Trouble with Tribbles(1967)3.1TPM Emulator3.1.1ConﬁgurationKernel ReleasePer default,the module is compiled and installed for the currently running kernel release,as in-dicated by’uname-r’.To compile and install the module for an alternative(installed)kernel release,the variable RELEASE in the main makeﬁle(Makefile)has to be adapted accordingly. GNU MP SupportBy deﬁning the variable USE_GMP in the main makeﬁle to point to the static GNU MP library (libgmp.a),some of its highly optimized core functions(mpz_*,mpn_*)are linked against the module.Otherwise,if USE_GMP is not deﬁned,the generic GNU MP sources shipped with the emulator are used.Although linking the module against the GMP library results in a larger module,it is recommended because of the signiﬁcant performance gain.Example:USE_GMP:=/usr/lib/libgmp.a3.1.2InstallationFirst unpack the archive,then compile and install it:#tar xvzf tpm_emulator-X.Y.tar.gz#cd tpm_emulator-X.Y#make#make install12Chapter3-Installation and Usage The automatic installation procedure(make install)consists of the following steps:First,a TPM device with major number10and minor number224as well as the directory to store the persistent TPM data(/var/tpm/)are created.Afterwards,the TPM kernel module is copied into the misc directory of the dedicated kernel release and its dependencies are updated.3.1.3Loading the ModuleThe startup mode of the TPM emulator(see[TPMPart1,section7.3])can be deﬁned with a module parameter called startup that can either be set to clear,save(default)or deactivated. If the emulator is started in mode save and fails to load a previously stored TPM state it will go into a fail-stop mode and has to be reloaded to be usable again.Therefore,startup should be set to clear theﬁrst time the emulator module is loaded.#modprobe tpm_emulator startup="clear"3.1.4Example Programs from IBMIBM provides a TPM device driver for their ThinkPads as well as some example applications [IBMSW].Unfortunately,the current release contains some minor byte-order conversion bugs and thus a patch has to be applied before the examples can be used with the emulator.#tar xvzf tpm-1.1b.tar.gz#cd TPM#patch-p1<tpm-1.1b.patch#cd libtcpa/#make#cd../examples/#makeIn the following,it is shown how these tools can be used to test the TPM emulator’s capabilities. For a more detailed description and explanation of the library and tools we refer to the package documentation as well as to an article in the Linux Journal[IBMLJ]written by the authors of the software.For aﬁrst veriﬁcation of whether the TPM emulator has been loaded correctly or not,the tcpa_-demo application can be used.#./tcpa_demoIn case of errors or unexpected behavior,the extensive logging output of the module might be a good starting point to localize the problem source.#tail-f/var/log/messages|grep tpm_emulatorTaking OwnershipIn order to use the TPM emulator one has to perform the take-ownership command when the module is loaded for theﬁrst time.The process includes the insertion of owner authorization data and the creation of the storage root key(SRK).#./takeown<owner password><SRK password>3.2.TCG Device Driver Library13 Key Generation and Key LoadingThe programs createkey and loadkey allow the generation and loading of a RSA signing key,respectively.In the following example the SRK–whose key handle is always0x40000000–is used as the parent key.The speciﬁed key name is only used by the programs as aﬁle name to store the returned key-blob and its dedicated public key;it has no TPM speciﬁc relevance.#./createkey40000000<key name><key password>#./loadkey40000000<SRK password><key name>loaded key<key name>,returned handle<key handle>File Signing and VeriﬁcationOnce a signing key has been installed,it can be used to verify the integrity ofﬁles by signing their content digest.#./signfile<key handle><key password><data file><sig file> #./verifyfile<sig file><data file><key name>.pemData SealingIn addition to signing,two more programs for sealing and unsealingﬁles are provided.It should be noted that signing keys cannot be used for encryption but only for signing.In particular,if the previously generated signing key were used for sealing,this would cause an invalid key usage ex-ception.In addition to the key password,an additional data password has to be deﬁned.Unsealing is only possible if both the key password and the data password are known.#./sealfile<key handle><key password><data password>\<input file><seal file>#./unsealfile<key handle><key password><data password>\<seal file><output file>Key EvictionIf the loaded keys are no longer needed,they can be evicted using the./evictkey tool.#./evictkey<key handle>3.2TCG Device Driver LibraryThis section gives a short overview of the TCG Device Driver Library(TDDL)for the TPM emulator.For a detailed speciﬁcation of the mentioned functions,constants,and error codes we refer to[TSS11].3.2.1ConﬁgurationPer default,the TDDL library is installed into/usr/local/lib and the TDDL headerﬁle into /usr/local/include,respectively.To use different installation locations(e.g.,/usr/lib。

ACADEMIC CALENDAR 2011-2012

ACADEMIC CALENDAR 2011-2012Tuesday 16 August 2011Start of the registration period for 2011-2012Wednesday 21 September – Sunday 25 September 2011 Orientation Days for International StudentsMonday 26 September 2011Opening ceremony of the academic year 2011-2012 Tuesday 27 September 2011 Start of classes in the first semester of 2011-2012Friday 23 December 2011 End of classes in the first semesterMonday 26 December 2011 till Sunday 8 January 2012 Christmas and New Year holidaysMonday 09 January 2012 – Sunday 15 January 2012Exam preparation. No classesMonday 16 January 2012 – Saturday 04 February 2012 First semester examsThursday 2 February 2012 Patron’s Feast Day – university offices will be closed! Monday 06 February 2012 – Sunday 12 February 2012 Mid-year break. No classesThursday 9 February 2012 – Sunday 12 February 2012 Orientation Days for International StudentsMonday 13 February 2012Start of classes in the second semesterMonday 2 April 2012 – Sunday 15 April 2012 Easter holidaysSaturday 26 May 2012End of classes in the second semesterMonday 28 May 2012 – Sunday 10 June 2012 Exam preparation. No classesMonday 11 June 2012 – Saturday 7 July 2012 Second semester examsThursday 16 August 2012 Start of the registration period for 2012-2013Monday 20 August 2012 – Saturday 15 Sept. 2012 Examination retakes for failed students 2011-2012 Monday 24 September 2012 Start of the academic year 2012-2013INTRODUCTORY DUTCH COURSESAt the request of the International Office, the Leuven Language Institute organises ‘Dutch for Foreign Students’ courses. These are introductory Dutch language courses and they are only open to Erasmus students. On presentation of the Erasmus-student card these courses are offered free.•The course lasts 3 months and is meant for beginning students in order to activate communication through conversational exercises. It is a practical course based on the principles of Dutch grammar. The aim is to makestudents acquainted with the vocabulary of every-day life.Students who already have a basic or advanced level of Dutch can gain entry to one of the higher levels of the regular courses if they pass the placement test. In total, 5 basic levels and 1 perfection level of Dutch are taught. The level 1 to 5 modules can be taken either intensively (12 hours/week) or over a more extended period (6 hours/week). The perfection level 6 is only offered at a pace of 4 hours/week.Besides the courses throughout the academic year,the ILT also offers a full-time intensive summer course in Dutch language and culture. The course consists of 80 hours and takes place from Friday 29 July 2011 till Friday 26 August 2011 (20 hours a week). The course is open to undergraduates and graduates of all areas of study who wish to improve their knowledge of and communicative skills in Dutch. The communicative approach is used in all 5 levels. Besides the theoretical courses, many conversational exercises and complementary activities are planned (lectures, cultural happening, trip etc.). The course is intended for students of different levels, from beginners to intermediate and advanced. The tuition fee is € 300 for all students.For the latest information, please visit the ILT website: http://ilt.kuleuven.be/WHAT EXCHANGE STUDENTS SHOULD BRINGEEA-students (EEA: E uropean E conomic A rea: 27 countries of European Union plus Iceland, Norway and Liechtenstein)1. your identity card or passport2. the official forms that prove you are affiliated with a health insurance in your home country and which is valid inBelgium (EHIC: European Health Insurance Card)3. proof that you are registered as a student at your home university4. your “letter of admission”non-EEA students1. your passport, with “Authorisation for provisional sojourn“ (student visa) if required (for stays longer than 3 months)2. for those who do not require a student visa: a proof of solvency or proof of scholarship3. proof that you are registered as a student at your home university4. your “letter of admission”EEA- and non-EEA-students: please read the information about insurances and health care in our brochure “Living in Leuven” which can also be found on http://www.kuleuven.be/admissions/pdf/living.pdfExchange Programmes: Key dataFull legal name of the Institution Katholieke Universiteit LeuvenERASMUS code B LEUVEN01Rector Marc WaerAddress Naamsestraat 22 box 5000Postal code and town 3000 LeuvenCountry BelgiumWebsite http://www.kuleuven.be/englishINTERNATIONAL OFFICEName Elke Timmermans, Institutional CoordinatorAddress International OfficeInternational Policy UnitNaamsestraat 63 box 5410Postal code and town 3000 LeuvenCountry BelgiumTelephone +32 (0)16 32 37 67Fax +32 (0)16 32 37 73Email Elke.Timmermans@int.kuleuven.beHOUSINGGeneral information regarding private and university accommodation in Leuven for (exchange) students can be found on http://www.kuleuven.be/accommodation/index.htm.Non-Subsidized ResidencesThe K.U.Leuven has reserved about 200 of its 1200 non-subsidized university residence rooms to house international students taking part in the Erasmus exchange programs. These rooms are randomly located amongst rooms for Flemish students or other international students and they are spread over seven residences across the City of Leuven. You can find more information concerning these rooms and an application form on the following website:http://admin.kuleuven.be/erasmus-residences. Practical arrangments (date of arrival, what to do on arrival, checking in etc) can be made directly with the landlord.Private marketThe majority of exchange students are referred to the private housing market, as the offer of rooms in university residences is limited. On our general website you will read that it’s impossible to arrange permanent private housing before your arrival in Leuven! Because of the wide variety in prices, comfort, surface area etc…, it is really too risky to make a choice from abroad, without having viewed at least a few rental units personally. According to the Belgian law, a contract, once signed, cannot be terminated before it expires. For those reasons we never send contact information or address lists by e-mail to students who are not in Leuven yet.We strongly advise (exchange) students to come to Leuven a few days before the start of the courses, in order to arrange their permanent housing. This room hunt will take from a few days up to one week. In the mean time, you can stay in a guesthouse. We strongly recommend students to book temporary guesthousing themselves, quite a few weeks in advance. Guesthousing can be found on: http://www.kuleuven.be/accommodation/guesthousing/index.html.Attention, September is the most difficult time to find both temporary and permanent housing!Upon arrival in Leuven, students are welcome at the Housing Service, located at Van Dalecollege, Naamsestraat 80 in Leuven. The Housing Service is open every weekday between 9-12am and 2-5pm. We will provide information on and assist in finding permanent accommodation.Exchange students staying for a full academic year will be referred to the university database of privately rented student houses.Exchange students staying for one semester will receive a list of Flemish students who sublet their room to an international student while they are studying abroad themselves, or while they are in training on another location.The list for the 1st semester is available from the middle of July. Please note that from July onwards, the supply of sublettings reduces very fast. Therefore we advise you to come during July or August.The list for the 2nd semester is available from the middle of December. Unlike students who stay in Leuven during the 1st semester, students who come for the 2nd semester can also negotiate directly with landlords. Landlords who still have rooms available in January will generally conclude a contract that ends together with the academic year.You can only consult the addresses (both from the database and the lists) locally at the Housing service. It is not possible to apply for those lists or to consult the database from abroad.Single room: furnished, kitchen and bathroom to share with other students in the house. Blankets, sheets and pillows are NOT provided! Average price: between €270 and €300 /month.Studio: private kitchen and bathroom, furnished. Blankets, sheets and pillows are NOT provided! Average price: between €400 and €500 /month.。

05_TestRequMaster1_2_Rev1_1_020808

AS-International AssociationActuator Sensor Interface(AS-Interface®)Test Requirements MasterVersion 1.2, Revision 1.1Apr. 05, 2002ConfidentialFor internal use of the members only or for companies which have bought the documentation from the AssociationTest Requirements Master 1.2 Rev. 1.1AcceptanceThese test requirements have been accepted by the Technical Commission of the AS International Association in its meeting on April 10, 2002 and by the Management Committee in its meeting on May 14, 2002.File date: August 8th, 2002Test Requirements for AS-Interface MasterContents:A. General (1)1. Basic tests (4)2. Simplified test (4)3. Additional tests (4)4. Precedence (4)B. Test instructions (4)1. Test instruction: Current consumption (5)2. Test instruction: Noise emission AS-i master (8)3. Test instructions: Impedance and symmetry measurement (11)4. Test instruction: Power-on behaviour (21)5. Test instruction: Burst test (25)6. Test instruction: Analogue part (31)7. Test instruction: Voltage cutoff (34)8. Test instruction: Logical start-up behaviour (37)9. Test instruction: Logical behaviour in normal operation (40)10. Test instruction: Analogue profile (43)11. Test instruction: Functions in accordance with PICS (45)12. Test instruction: Time response (49)13. Test instruction: Security of data (52)C. Forms for technical reports (56)Annex: (77)Test Requirements Master 1.2 Rev. 1.1A. General1. Basic testsThese test requirements for the AS-Interface master describe the minimum extent of a basic test to be carried out on the AS-i master to section 4.4 (2) of the Certification Guidelines (ZRL) for AS-i products.AS-i masters forming a part of a higher-level system, e.g. couplers (gateways) to higher-level bus systems or masters with integrated host functions (AS-i control) are also tested in accordance with these test requirements if applicable. Host functions shall be accessible or realised in the higher-level system in accordance with these test requirements.If an AS-i power supply is integrated in the AS-i master, the master is additionally subject to the test requirements for AS-i power supplies.If the AS-i master contains components already tested and approved by the AS-i Association these components will not be tested again (section 4.4 (3) of the ZRL).All standard AS-i components used for testing purposes shall be AS-i certified.2. Simplified testSimplified tests to section 4.5 ZRL shall use parts of these test requirements if applicable.3. Additional testsIn special cases the test laboratory is entitled to execute additional tests beyond these test requirements in accordance with the valid specification or shall demand them from the manufacturer.4. PrecedenceIn the case of discrepancies between these test requirements and the AS-i specifications the complete specification takes precedence.instructionsB. TestAll tests described in these test requirements shall have an accuracy of 1% unless stated otherwise, and shall be documented accordingly in the test protocols.For test purposes, the connection between the master and the AS-i shall be made by means of a split plug.All logical tests shall be recorded via AS-i bus monitor. All recordings of the monitor are saved as a file on a diskette which shall be part of the test report. In the case of errors in the logical tests a printout of the monitor recordings shall be made additionally. To protect the files from corruption, a check sum shall be put on the contents of the files. The directory listing contents and check sum shall be enclosed with the test report.1. Test instruction: Current consumptionReference: Specification AS-i master (chapter 7 of the Complete Specification),Master profiles,Test requirements for AS-i power supplies1.1 GeneralThe test requirements allow measurement of the current consumption of an AS-i master. These test requirements become obsolete if the master has an integrated AS-i power supply. In that case, however, all tests of the test requirements for AS-i power supplies have to be additionally fulfilled by the master.The manufacturer shall provide the following information:1. current data sheet,used2. profile1.2 Test circuitFigure 1 shows the required test circuit.Figure 1: Test circuit for current consumption test1.3 Measuring and test equipment·AS-i reference network·AS-i data decoupling network· ammeter· oscilloscope·test circuit to figure 1·variable power supply1.4 Test procedure1. Set up test circuit to figure 12. Operate the master to be tested in normal operation3. Check the master functions at the following DC voltages on the AS-i-line: 31.6V,26.5V, 23.5V, 21.5V and again at 23.5V4. Check the maximum current consumption1.5 EvaluationThe maximum current consumption as stated by the manufacturer shall not be greater than the value stated in the data sheet or than the requirements of the specification.The function test at the operating voltage limits shall correspond to the data stated in the data sheets and the applicable specifications, i.e. at DC voltages on the AS-i line of 31.6V, 26.5Vmaster activity is detected by means of an oscilloscope directly on the AS-i line.Test recordingsDate:Tested by:Test laboratory:Test report no.:ofPage:Current consumptionTest piece code: ___________________Network configurationMaster: __________________________Power supply: __________________________ Data decoupling: ___________________ Slaves: __________________________Measured values:Voltage U /(V) 31.6 26.5 23.5 21.5 23.5Current I / (mA)Communication yes/no yes/no yes/no yes/no yes/nomax. current consumption: ______mA < current stated in data sheet:yes/noResult:Test passed: Yes / No Signature: _________________Test Requirements Master 1.2 Rev. 1.1 2. Test instruction: Noise emission AS-i masterReference: Specification AS-i master (chapter 7 of the Complete Specification),2.1 GeneralThis test instruction allows the measurement of the noise emission of an AS-i master in a power-fail state on the AS-i network.2.2 Test circuitFigure 1 shows the required test circuit.Figure 1: Test circuit noise emission AS-i masterThe change in current consumption in a master should only cause a noise voltage £ 50mVss on the AS-i line in the frequency range between 10kHz and 500kHz. The voltage on the AS-i line is measured by means of an oscilloscope via a bandpass (see figure 2, see spice simulation in the appendix to the test requirements for impedance and symmetry measurement). The oscilloscope is to be operated in the mode Envelope, Peak Detection on at a cut-off frequency > 10 MHz. The FET probe is to be terminated with an impedance of 50 Ohm. The test circuit is to be screened from noise so that the measured maximum noise voltage without the master is smaller than 15 mV. For this purpose, the cable length between master and AS-i equivalent line (see figure 3) is to be limited to max. 20 cm. The master is to be operated in the power-fail state (direct voltage on the AS-i line of 21 V).50 Ohm or AS-i 10 … 1MOhm 10 … 30 pFFigure 2: bandpass 10kHz ... 500kHzR = 0,125O hmL = 1,25 µHC=700 p FFigure 3: equivalent circuit of the 10m AS-i equivalent line2.3. Measuring and test equipment·AS-i power supply·oscilloscope with FET probe (50 Ohm output impedance)· bandpass·test circuit to figure 12.4 Test procedure1. Apply a voltage of 21 V to the AS-i line2. Measure the noise voltage without the master by means of the oscilloscope over 60seconds3. Connect the master4. Check the power-fail state of the master5. Measure the noise voltage with the master on the AS-i line by means of an oscilloscopeover 60 secondsThe measurements shall have an accuracy of 5%.2.5 EvaluationThe noise voltage on the AS-i line must not be increased by more than 50 mVss by the master in the power-fail state.Test Requirements Master 1.2 Rev. 1.1 Test recordingsDate:by:TestedTest laboratory:Test report no.:Page:of Noise emission AS-i masterTest piece code: ___________________Network configurationMaster: __________________________Power supply: _________________________Measured values:Noise voltage:without master: _______mVsswith master: _______mVss difference: ______ £ 50mVss : yes / noTest criteria: In the power-fail state the noise voltage of the master on the AS-i line must not exceed 50 mVss!Result:Test passed: Yes / No Signature: _________________3. Test instructions: Impedance and symmetry measurementReference: Specification AS-i master (chapter 7 of the Complete Specification),3.1. Impedance measurement3.1.1 GeneralThe impedance measurement of the master is to be performed in the "ready state" under laboratory conditions.An AC signal U~ with Ri £20 Ohm is to be superimposed on the AS-i DC voltage. This AC voltage and the resulting AC current I~ of the master are to be measured3.1.2 Test circuitFigure 1 shows the test circuit for the impedance measurement. The operation of the master in switch position "test" has been purposefully selected as asymmetrical, i.e. metal parts of the master must not be grounded. Switch S1 allows a switching of AC ground (switch position shown: AS-i- = GND).The AC input current I~ is measured by means of the current probe. The input impedance is calculated as follows:| Z | = | U~ | / | I~ |The distance to the AS-i master shall be 20 cm.The DC voltage is to be set to 21V to put the master in the offline state.3.1.3 Measuring and test equipment·power supply (universal)· signal generator· current probe·test circuit (IMP_SYM) to figure 1for point 3.2 (symmetry measurement)· FET probe· HF voltmeter· bandpassFigure 1: Test circuit impedance measurement (IMP_SYM)3.1.4 Test procedure·Switch S1: position "AS-i- = GND"·Determine the AC current I~ at U~ = 6 Vss·The measurement is to be carried out as described in chapter 7.2.1.1 of the Complete Specification.The accuracy of the measurements shall be within 3%.3.1.5 EvaluationThe evaluation is to be carried out as described in chapter 7.2.1.1 of the Complete Specification and must not exceed the limit values stated there.3.1.6 DC resistanceThe DC resistance between ASI+, ASI- and all metallic parts of the master with the exception of outer connections shall be ³ 250 kOhm.3.2. Symmetry measurement:3.2.1 General:Figure 2: Master connection for symmetry measurementThe partial impedances Z1 and Z2 respectively form a voltage divider at measurement point M. This measurement point may be the metallic housing or a metallic mounting plate. The measurement point shall be connected to the external supplies of the master or the host respectively.In the off-load state the currents through Z1 and Z2 are identical.For an asymmetry of 10% this means10.190.02121£=£Z Z U U r r .r U 1r: voltage between M and ASI+ for ASI+ = GNDU 2: voltage between M and ASI- for ASI- = GND3.2.3 Test circuit:Figure 3: Test circuit symmetry measurement of the AS-i master50 Ohm or AS-i10 … 1MOhm 10 … 30 pFFigure 4: bandpass 10 kHz ... 500 kHzThe test circuit corresponds to the one of the impedance measurement (compare figures 1 and 2). With the test circuit in figure 3 the voltage drops U1 of ASI+ to M and U2 of ASI- to M are determined by means of a FET probe (Ri=1MOhm//2pF) with AC coupling Ck ³1nF at an output impedance of 50 Ohm and an HF voltmeter (frequency range up to 300 kHz, Ri=10MOhm//30pF). The capacitance Ckomp=Cfet is to be taken into account in the circuit to compensate for the probe capacitance.By means of calibrating C 3, |U1| = |U2| = UE/2 can be achieved and the capacitances of C 1 and C 2 can be determined independent of Z.A possible measurement error of the HF voltmeter in higher frequency ranges is eliminated by means of the ratio |U1| / |U2|.The appendix shows the frequency response of the bandpass from a SPICE simulation with different combinations of the terminating resistor.3.2.4 Test procedure· Set a measurement voltage Ue of 2.0 Veff displayed on the evaluation meter at afrequency of 160 kHz· Determine |U1| and |U2| at a frequency of 300 kHz without C 3 · Check the condition10.190.02121£=£Z Z U U r r .· If this condition is met, determine at frequencies of 50kHz, 100kHz, 125kHz, 160kHz,200kHz, 300kHz and check if this condition is met.· for ASI+ = GND determine the frequency response of |U1| · for ASI- = GND determine the frequency response of |U2| · define the ratio |U1| / |U2| as stated in point 2.1 (General)·If the condition10.190.02121£=£Z Z U U r ris not met:· Add C3 between ASI+ and M or ASI- and M respectively, depending on the voltage testand calibrate until you reach |U1| = |U2| = UE/2 at a measurement frequency of 300kHz · Determine C3The accuracy of the measurements shall be within 3%.3.2.5 Evaluation / symmetry criteriaOne of the following conditions shall be met:1. 10.190.02121£=£Z Z U U r r or2.90.080.021££U U r r or 20.110.21££U U r 1r with C 3 £ 15 pF or3. 80.021£U U r r or 2120.1U U r r £ with C 3 £ 30 pFTest recordingsDate: Tested by: Test laboratory: Test report no.: Page: ofImpedance and symmetry measurementNetwork configurationMaster: _________________________ Test circuit: IMP_SYMImpedance measurement:R min L min C maxlimits5k W3mH 400pF measurementsTest criteria: R meas > R min ; L meas > L min ; C meas < C maxDC resistance (R ³ 250 kOhm): ASI+ - M: _______ ASI- - M: _______Symmetry measurement:f / (kHz) 50 100 125 160 200 300 |U1| / (V)|U2| / (V)|U1 / |U2||U1| / |U2| = ________ , C3=______ pFOne of the following conditions shall be met: 1.10.190.02121£=£Z Z U U r r2.90.080.021££U U r r or 20.110.21££U U r 1r withC 3 £ 15 pF or 3.80.021£U U r r or 2120.1U U r r £ with C 3 £ 30 pFSymmetry sufficient? yes/noResult:_________________ Yes/No Signature:passed:TestAppendix: Frequency responses bandpass with different terminating impedances4. Test instruction: Power-On behaviourReference: Specification ASI master (Chapter 7 of the Complete Specification),4.1 GeneralBy testing the Power-ON behaviour, the switch-on delay time t E of the ASI master and its current consumption shall be tested. The settings of the oscilloscope can be seen on the oscillograms.AS-i masters with integrated AS-i power supply must have an internal voltage supply which is accessible and can be interrupted for this test so that the external AS-i supply can be connected.4.2 Measuring and test equipment· power supply with AS-i data decoupling network· oscilloscope· constant current source (KONST_I)4.3 On-delay4.3.1 GeneralThe offline flag of the master is reset (normal operation). In the initial state the master is not connected with the AS-i line (switch S is open). The master shall communicate with the slaves for min. one second after switch S has been closed. The oscilloscope shall be triggered by the rising edge of the supply voltage on the AS-i line. The start of communication is shown on the oscilloscope via peak detection on and DC coupling.4.3.2 Test circuitFigure 1: Test circuit: On-delayFigure 2: Oscillogram on-delay (example)4.3.3 EvaluationThe time t E is to be determined from the oscillogram. It shall be longer than 1.00s. The accuracy of the measurements shall be within 3%.4.4 Current consumption4.4.1 GeneralIf the master is supplied (see circuit figure 4) with a current corresponding to the total current consumption as stated in the data sheet + 12.5mA (to be set with an accuracy of ± 2.5 mA), the master shall have reached an operating voltage of 26.5V within one second after closing switch S in figure 4. The final operating voltage value to be reached shall be 30V at the output of the circuit with a set constant current.4.4.2 Test circuitFigure 3: Block circuit diagram current consumption measurement of the AS-i master++--Trigger output30V in the stationary state Figure 4: Constant current source with trigger output (KONST_I)Figure 5: Oscillogram current consumption (example)4.4.3 EvaluationThe time t shall be determined from the oscillogram to figure 5. It shall be smaller than 1s. The accuracy of the measurement shall be within 3%.Test recordingsDate:by:TestedTest laboratory:Test report no.:ofPage:Power-On behaviourTest piece code: __________________Network configurationMaster: _________________________Power supply: ______________________ Data decoupling: _____________________Test circuit: KONST_IMeasured values:On-delay t E: ______ s > 1s: yes / noCurrent consumption t : __________ s < 1s: yes / noThe oscillograms are to be added to the appendix.Result:Test passed: Yes / No Signature: _________________5. Test instruction: Burst testReference: Specification AS-i master (Chapters 7 and 8 of the Complete Specification),5.1 GeneralThe test shall be performed with fast transient bursts in form of pulse groups. The interferences are injected on the AS-i line by means of a capacitive coupling clamp. The test shall be made with the following data:·level 3 for data lines·test voltage 1 kV·pulse rate 5 kHz·burst length 15 ms·burst period 300 ms.The following requirements are to be met to minimise the environmental influence on the test results:·ambient temperature: 15° C to 35° C·relative humidity: 45% to 75%·air pressure: 680 hPa to 1060 hPaFigure 1 shows the curve of the transient interferences.Figure 1: Overall curve of the transient interference5.2 Test circuit (principle)Figure 2 shows the test circuit (principle) for the burst test of the AS-i master. Figure 3 shows the circuit diagram of the filter to be used to protect the slaves from burst pulses.K a p . 5.2.2Figure 3: Test installation burst tester (BURST_T)The master operates an AS-i network (see figure 2, consisting of the first 90m of the reference network, see test instruction "Operation on the reference network" from the test requirements for AS-i-slaves and and a burst tester at measurement point 1 of the reference network, see figure 3) in the cyclic normal operation with active data exchange. The burst tester includes 2 AS-i slaves (addresses 1 and 2) and a data strobe evaluation for these two slaves, i.e. all data strobe pulses of slaves 1 and 2 are recorded, the timing is defined for the undisturbed case and the timing violation in the case of bursts is recorded. If the time defined in undisturbed operation is exceeded by more than 100 µs, this indicates an error. In the case of double pulses at slave 1 the time measurement refers to the first pulse.The reference measurements (no faults in the case of burst) require ferrite cores (define number and position) for decoupling (filter).Burst pulses of the burst generator are injected via a capacitive coupling clamp.Measurements are taken over a longer period of time (e.g. 2 min, but for a minimum of 100,000 cycles).5.3 Test installationFigure 4 shows the test installation for the burst test.10 cm above the grounded metal plateFigure 4: Test installation burst test5.4 Measuring and test equipment· burst generator·capacitive coupling clamp·20 m AS-i line (burst setup)· filter·part of the AS-i reference network (90m)·burst tester (BURST_T)·AS-i power supply5.5 Test procedure·The AS-i slaves shall be protected from the effects of burst pulses by means of filters. ·The master shall be grounded according to IEC 801 part 4. The master shall be mounted as described in the data sheet. Supplied mounting material shall be used. Measurements shall be carried out at a distance of 10cm from the metal plate for all designs.·10m AS-i line shall be mounted s-shaped at 10cm above the grounded metal plate; the remaining 10m shall be used to connect the AS-i slaves of the reference network protected by filters and the burst tester.· A test voltage of 1kV shall be set at the burst generator.·The tests shall be made with both burst polarities.·The test period shall be 2 min.5.6 EvaluationThe errors caused by the master to be tested shall be evaluated.To calculate the error rate caused by the system without the master, a test with insensitive reference master (symmetrical design) is performed.5.6.1 Calculation of the maximum error rateBased on the assumption that each AS-i message is disturbed during the burst period of 15 ms each we get a maximum percentage of disturbed messages of (see figure 1):15 ms / 300 ms = 5% = Nmax .5.6.2 Measurement of the actual error rate using a reference masterThe reference master is set up with the lowest possible stray capacitance to mass. It is assumed that no error in the network will occur during operation without burst.5.7 TestThe master shall be installed ready for operation (see data sheet) and – if applicable – connected to mass (ground).Under the influence of the burst pulses the number of exceeded timings of the data strobe pulses between slaves 1 and 2 is measured5.8 EvaluationThe limit value according to specification defines: "Max. every 30th message shall be distorted".This means that:Nmess £ Nmax ·1 30Nmess £16 %has to be met.Test criteria: The number of exceeded timings must not exceed 1 %. 65.9 Enhanced test5.9.1 Test voltage 2kVThe test master shall be installed ready for operation and – if applicable – connected to mass (ground). Refer to the installation notes in the data sheet or the instructions in the box.A test voltage of 2kV shall be set at the burst generator. The test period shall be 2 min.For this test one of the AS-i line shall be grounded at the power supply (protective earth). The functional earth of the power supply shall be removed.5.9.2 EvaluationAt a voltage of 2kV it has to be ensured that no errors occur, in particular:· no RESET,·no destruction of the master during the test.Test recordingsDate: Tested by: Test laboratory: Test report no.: Page: ofBurst test to IEC 801, part 4Test piece code: __________________________ Test piece type: ____________________________ Switching state: ___________________________ Burst generator type: _______________________ Coupling clamp type: ________________________ Mass reference surface: ______________________ Ambient temperature: _______________ Relative humidity: ________________ Air pressure: ________________Network configurationSlaves: __________________Power supply: ___________________ Test level: 3 (1kV)Burst duration: 15ms, burst period 300ms, spike frequency 5kHz Test duration (> 1min): ______________ Test condition: Nmess £ 1/6 % + Nref Test circuit: BURST_TTest results:Test at 1kV:Polarity Nref 1/6 % + Nref Nmess at a distance of 10 cmTest passed:positive yes / no negativeyes / noTest at 2kV:positive polarity negative polarity yes no yes no RESET destructionResult:Test passed: Yes / No Signature: _________________6. Test instruction: Analogue partReference Specification AS-i master (Chapter 7 of the Complete Specification),profiles,Master6.1 GeneralThis test instruction will assess the analogue part of the master.A manufacturer declaration is to guarantee a bit time of the master transmitter of 6µs ±0.1% .6.2 Measuring and test equipment· AS-i master·AS-i power supply· 2 pcs. 4O modules as slaves 1 and 2·AS-i monitor (e.g. SINEC S1 – PC card (CP 2413) with monitor program SCOPE S1, version 1.0), with a capacitive load on the AS-i line of C monitor≤ 0.4 nF·equivalent network (29 slaves, 300 Ohm||(3 nF-C monitor))·data decoupling with HF ground6.3 Test circuit1m (+/-0,1m)99m (+/- 1m)Laboratorypower supply39 OhmFigure 2: Data decoupling and HF groundThe AS-i line (99m) shall be mounted s-shaped (length: 2.50m, distance 0.1m). The data decoupling network shall be made up of a core EF 25 consisting of 2 parts, material N27(Siemens, order nos.: B 66 317-G-X127 and B 66 317-G-X127, see data sheet) with 1mm total air gap, equipped with a bifilar winding of 16.5 windings, wire diameter 0.8mm, wound parallel and the parallel resistor of 39R 1%. The equivalent circuit Zn (copy of an impedance of 29 slaves) is to consist of the parallel wiring of 10 pcs. 3.3kOhm 1% metal film resistors and a capacitance of 3nF 2% (The equivalent circuit Zn includes the impedance of the AS-i monitor, i.e. Zn = 330W || (3nF-C monitor) || monitor).6.4 Test procedureTest 1:1. Set up the test installation as shown in figure 1,2. Set slave 1 on address 21 and slave 2 on address 13. Slave 1 shall be polled by the master with data message ("0xA"), slave 2 with datamessage ("0x0")4. After the error rate has been measured via the monitor, the positions of slaves 1 and2 shall be changed and test shall be repeatedTest 2:1. The test installation shall be changed by removing the 99m AS-i line between slaves 1and 2 and the equivalent network Zn, i.e. slave 2, the AS-i monitor and slave 1 shall be connected at a distance of 1m from the master2. Set slave 1 on address 21 and slave 2 on address 13. Slave 1 shall be polled by the master with data message ("0xA"), slave 2 with datamessage ("0x0")4. The error rate shall be measured via monitor6.5 EvaluationThe monitor shall show an error rate of £ 0.5% for all tests.The error rate shall be defined as the number of master request /slave response combinations for slave 1 not correctly detected by the master, referred to a total number of master requests to slave 1.Test recordingsDate:by:TestedTest laboratory:Test report no.:ofPage:Analogue partTest piece code: ___________________AS-i master: ______________________Power supply: _________________________Test results:Test 1:correct? yes/no Error rate measurement 1: _____% £0.5%correct? yes/no Error rate measurement 2: _____% £0.5%Test 2:correct? yes/no Error rate measurement: _____% £0.5%Result:Test passed: Yes / No Signature: _________________7. Test instruction: Voltage cutoffReference: Specification AS-i master (chapter 7 of the Complete Specification),profiles,Master7.1 GeneralThe reaction of the master to voltage cutoff on the AS-i line of 1ms and a reduced voltage on the AS-i line from approx. 23.5V to 14.5V shall be tested.7.2 Measuring and test equipment· AS-i master·AS-i power supply·AS-i bus monitor· generator· oscilloscope7.3 Test circuitFigure 1 shows the basic principle of the test installation to check the reaction of the master to voltage cutoffs as well as the reduction of the DC voltage on the AS-i line. The connectedslave puts the master in the normal operation mode.7.4 Test procedure:1. Interrupt the voltage on the AS-i line for 0.6 ms with a repetition frequency of < 1Hzand check the AS-i messages by means of the bus monitor.2. Interrupt the voltage on the AS-i line for 2.1ms with a repetition frequency of <1Hz andcheck the AS-i messages by means of the bus monitor.3. Check the transmitting amplitude of the master at an AS-i-DC voltage of 23.5V4. Reduce the DC voltage on the AS-i line from 23.5V to 14.5V.Check AS-i message sequence "RESET_Slave" to all slaves by the master by means of a bus monitor and check their transmitting amplitude and subsequent offline operation of the master.7.5 Evaluation。

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Data Structures
Page 2 of 4
INFO1x05 Trees
Exercise 4: Binary tree coordinates (INFO1105 and INFO1905)
Consider a binary tree T where each node has a pair of (x, y ) coordinates in the plane. The x-axis represents the order produced by inorder traversal. The y -axis is the height, i.e., the y coordinate is the height of a node in T . Write a method in BinaryTree.java that computes the node coordinates and outputs a binary tree to a ﬁle in the dot format. For example, the following dot ﬁle (sample.dot) deﬁnes three nodes a, b, and c positioned at (2, 0), (0, −2) and (0, 2) respectively (the coordinates are in inches by default). There are two edges (a, b) and (a, c): graph { a [pos="2,0!"]; b [pos="0,-2!"]; c [pos="0,2!"]; a -- b; a -- c; } Once you have a dot ﬁle, you can visualise your binary tree using the following command to produce a PNG ﬁle: dot -Kfdp -Tpng -o sample.png sample.dot
Exercise 3: (INFO1105 and INFO1905)
Give an O(n)-time algorithm for computing the depth of all the nodes of a tree T , where n is the number of nodes of T .
Exercise 2: (INFO1105)
We can deﬁne a binary tree representation T for an ordered general tree T as follows (see Figure 1): • For each node u of T , there is an internal node u of T associated with u. • If u is an external node of T and does not have a sibling immediately following it, then the children of u in T are external nodes. 1
a
b
c
Figure 2: sample.png
Exercise 5: (INFOห้องสมุดไป่ตู้905)
Describe a nonrecursive method for performing an inorder traversal of a binary tree in linear time that does not use a stack.
INFO1x05 Trees • If u is an internal node of T and v is the ﬁrst child of u in T , then v is the left child of u in T . • If node v has a sibling w immediately following it, then w is the right child of v in T . Given such a representation T of a general ordered tree T , answer each of the following questions: 1. Is a preorder traversal of T equivalent to a preorder traversal of T ? 2. Is a postorder traversal of T equivalent to a postorder traversal of T ? 3. Is an inorder traversal of T equivalent to one of the standard traversals of T ? If so, which one?
A
B
A
E
C
B
C
D
F
D
E
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G
G
(a) T
(b) T
Figure 1: Representation of a tree with a binary tree: 1a tree T ; 1b binary tree T for T . The dashed edges connect nodes of T that are siblings in T .
(1)
This traversal is known as the level order traversal.
Data Structures
Page 4 of 4
INFO1x05
Tutorial 5
Trees
Exercise 1: (INFO1105 and INFO1905)
1. Show a tree with n elements achieving the worst-case running time for the following algorithm: Algorithm 1 Calculates the depth of a tree 1: procedure DEPTH(Tree T , node v ) 2: if v is the root of T then 3: return 0 4: else 5: return 1+DEPTH(T , w), where w is the parent of v in T 6: end if 7: end procedure Also, show a tree that achieves the best-case running time. 2. Let T be a tree with more than one node. Is it possible that the preorder traversal of T visits the nodes in the same order as the postorder traversal of T ? If so, give an example; otherwise, argue why this cannot occur. Likewise, is it possible that the preorder traversal of T visits the nodes in the reverse order of the postorder traversal of T ? If so, give an example; otherwise, argue why this cannot occur. 3. Draw a (single) binary tree T such that • Each internal node of T stores a single character • A preorder traversal of T yields EXAMFUN • An inorder traversal of T yields MAFXUEN.
Data Structures
Page 3 of 4
INFO1x05 Trees
Exercise 6: (INFO1905)
Let T be a binary tree with n nodes (T may be realised with an array list or a linked structure). Give a linear-time algorithm that uses the methods of the BinaryTree interface to traverse the nodes of T by increasing values of the level numbering function p(v ) deﬁned as follows: 1, 2p(u), p(v ) = 2p(u) + 1, if v is the root of T if v is the left child of node u if v is the right child of node u