A New Collaboration Design Method Based on
临床研究统计学SOP(英文原稿+中文翻译)
Standard Operating Procedure:StatisticsPurposeThis standard operating procedure (SOP) describes the statistical procedures involved in clinical research conducted within the University of Birmingham (UoB).ScopeThis SOP applies to all clinical research where the UoB is sponsor or takes on sponsor responsibilities for the statistical procedures. Where clinical research is (co-)sponsored by another institution, this procedure should be followed as far as possible, and in line with the contractual agreement between the UoB and the other institution. This SOP also applies to clinical research approved by a UoB Research Ethics Committee (REC) that is required to follow the UoB Principles of Good Clinical Practice (GCP) for Clinical Research (UoB-GCP-POL-001). This SOP may be used as a guidance document in all other cases.Implementation planThis SOP will be implemented directly after its effective date for all clinical trials and any clinical studies that are in set up. For existing clinical research that is already set up and in the recruitment phase (or further) at the time of implementation, this SOP will be implemented within three months of the effective date. StakeholdersNote that where the UoB takes on the sponsor responsibility for statistics, the UoB will delegate the majority of these duties to the chief investigator (CI) and/or to a clinical trials unit (CTU), who may delegate these duties further to their research team(s). All delegation of duties will be documented e.g. using either the CI declaration and/or the Clinical Trials Task Delegation Log (UoB-SPO-QCD-001).☐CI: The CI may delegate activities to members of their research team, although evidence of CI involvement and approval is still expected and may not be delegated where ‘no delegation allowed’ is indicated. This SOP will state where delegation is possible. For clinical research approved by a UoB REC, the role of CI may be referred to as the principal investigator (PI), or the supervisor for the postgraduate research student. ☐Statistician: The statistician must possess the relevant statistical knowledge and experience. This may be the CI (or delegate) where they have sufficient knowledge and experience to advise on and/or perform the required statistical elements of the clinical research.Statistical advisor: Where a statistical advisor is utilised, they may contribute to some, but not all, aspects of the clinical research design, conduct, analysis and reporting. The statistical advisor may take on the responsibility of the ‘statistician’ for specific statistical aspects of the clinical research that they willperform and will adhere to the relevant sections of this SOP.Background and rationaleFor the purposes of this SOP the terms ‘clinical research’ or ‘project’ will cover clinical trials of investigational medicinal products (CTIMPs), other interventional trials (e.g. surgical trials, device trials and non-CTIMP trials, and any other projects deemed to be ‘interventional’ by the sponsor), clinical studies.The purpose of this document is to describe the statistical procedures involved in clinical research conducted within the UoB. Statistics is a fundamental component of clinical research. The design, conduct, analysis of the resultant data and reporting must be scientifically sound in order to ensure that the results are reliable, minimise bias, and address the research question.The statistician takes responsibility for the statistical methods, which may include (but not limited to): the design of the clinical research, protocol development, case report form (CRF) development, database design, input into the data management process, development of the statistical analysis plan (SAP), research project conduct, performance of interim analyses and the final analyses, interpretation of the results and contribution to the publication(s).* A statistical advisor may take on the responsibility of the ‘statistician’ for specific statistical aspects of the clinical research that they will perform as documented in a memorandum of understanding or collaboration agreement.Identify statistical support1.The CI (or delegate) will seek appropriate advice on project design and statistical methodology at the initialconceptualisation of the clinical research (e.g., at the grant application phase).o This may be the CI where they have sufficient knowledge and experience to take on the statistician’s role as detailed below under ‘statistician’. In the small number of cases, where statistical review fordetermining the sample size is not deemed necessary, the CI (or delegate) will provide suitablejustification for this in the protocol e.g. with reference to other published research using a similarsample size.o Where appropriate, the CI (or delegate) will include appropriate funding for statistical support in the grant application.o The CI may choose to work with a statistical advisor to contribute to some, but not all, aspects of the project design, conduct, analysis and reporting. The statistical advisor may take on the responsibility of the ‘statistician’ for specific statistical aspects of the clinical research that they will perform asdetailed below.2.The CI (or delegate) will ensure that where the statistical advisor is not, or will not be, a member of theresearch team, their responsibilities are clearly detailed in an agreement.o For internal staff, this will be set out in a non-legally binding memorandum of understanding (e.g. CTU statistician advising an independent Investigator)o For staff working in different organisations, this will be set out in a legally binding collaboration agreement (e.g. statistician from another organisation).3.The CI (or delegate) will file evidence that the statistician and/or statistical advisor possesses relevantstatistical knowledge and experience to fulfil their role in the project. See the Training SOP (UoB-TRN-SOP-001).o It is expected that for clinical trials undertaken to support marketing authorisation applications, or large clinical trials where their publications may change prescribing practice or the standard care, an appropriate qualified and experienced statistician should take responsibility for the statistical aspects of the clinical trial.4.The CI (or delegate) will document the level of ongoing input required from a statistician. For example, thismay be documented in the protocol, a project-specific risk assessment, or local policies/processes. Project design and protocol development5.Where applicable to the project, the CI (or delegate) will seek input from a statistician on the followingaspects of the research:o research design (e.g. observational, randomised clinical trial, inclusion of a feasibility/pilot study) o formulating clinical research objectiveso suitability of outcome measures for meeting the objectives of the clinical researcho methods to minimise biaso sample sizeo randomisationo stratification/minimisation variableso blindingo statistical stopping guidelines (e.g. futility, superiority)o analysis methods (final and interim)o the clinical research reporting requirement for registries. See also the Project Closure SOP (UoB-CLO-SOP-001).6.The CI (or delegate) will maintain documented evidence of the statistician’s involvement inproject/protocol design as applicable (e.g. emails, meeting minutes, comments on proposals/protocols).o It is recommended that a second check of the statistical section of the protocol is performed prior to finalisation, in particular to check the sample size calculation (if performed), and where appropriate this should be performed by a second statistician.SAP development7.The trial statistician will document the pre-specified statistical methodology for the project, either directlyin the protocol and/or in a separate document, typically referred to as a SAP, which will be version-controlled. See also Protocol Template (CTIMPs)(UoB-ESD-QCD-001) and Protocol Template (non-CTIMPs and studies) (UoB-ESD-QCD-002).8.The statistician will, as a minimum, include the following details for the primary and secondary outcomes(or equivalent terms) in the SAP:o how the outcome will be measuredo appropriate statistical method(s) which will be used to analyse the data.9.Where appropriate, the statistician will include details on these, and other, analytical aspects in the SAP:o handling missing datao handling protocol deviationso adjustments for multiple testing or multiple comparisonso pre-specified sub-groupso rules for calculation of derived variableso use of baseline data as co-variates in adjusted analysiso levels of confidence/ statistical significanceo sensitivity analyseso treatment interactions, particularly for factorial clinical trials.10.The statistician will approve (each version of) the SAP, and the CI (or delegate) will retain documentationof this approval (e.g., emails, meeting minutes). It is expected that the first version of the SAP is in place prior to:o data collection for an open label projecto unblinding the data for a blinded project.CRF design and data management activities11.Where appropriate (as per the risk assessment), the CI (or delegate) will document the statistician’sinvolvement in developing the CRF, where this is being used to collect data, and the clinical research database. See the Case Report Form Development SOP (UoB-CRT-CRF-SOP-001).o It is expected for CTIMPs that the statistician will review and formally approve the final version of the CRF, and any amendments which then impact on data items. However, this procedure (whereappropriate) could also be applied in non-CTIMPs/clinical studies to support best practices.12.Where appropriate (as per the risk assessment), the CI (or delegate) will document the statistician’sinvolvement in data management activities. See also the Data Management SOP (UoB-DMA-SOP-001).o If applicable, it is recommended that the statistician will review the validation process (validation specification), which describes the checks to be performed as part of the data validation plan.13.The CI (or delegate) will work with the statistician to document all protocol non-compliances and collatethem prior to statistical analysis (where appropriate, prior to unblinding).14.The statistician will review all significant protocol non-compliances for assessment of the impact on theanalysis.Amendments15.The CI (or delegate) will highlight amendments to the project that are likely to have an impact on thedesign and analysis of the clinical research, and the statistician will review and document these (asappropriate as per the risk assessment). This includes:o review of the impact of the amendment on CRFs and project systemso review of the impact of the amendment on the SAPo whether the amendment introduces any risk of bias.16.Where changes to the project necessitates an update to the SAP, the statistician will amend the SAPensuring appropriate version control is employed and changes justified.Statistical programming, analysis and publication17.Where appropriate, the CI (or delegate) will perform quality checks, data cleaning and data validation priorto analysis. For clinical trials, see the Data Management SOP (UoB-DMA-SOP-001) for further details. 18.The statistician will ensure that user-written code/macros and programs used during the analysis processare fit for purpose (validated). This will be on a risk-based approach with the detail and level of checking varying depending on the item begin checked. For example, output related to the primary objective of the clinical research should be checked.19.It is expected that hardcoding during the analysis process is avoided. In extreme circumstances where hardcoding is considered necessary, the statistician will retain documentation of its use and provide clear justification for this. For example, use of hard coding in free text fields for adverse event data.20.Once data collection has been completed, the CI (or delegate) will lock the data from any further changes.This includes the procedures for unlocking the data for extreme circumstances where changes to the data are required. For qualitative data, an example of this may include converting transcripts to PDF or printing and signing finalised versions of the transcripts. For clinical trials, see the Data Management SOP (UoB-DMA-SOP-001) for further details.21.The statistician will ensure an appropriate audit trail in the statistical analysis process, in order to allow thedata analysis to be reconstructed from start to finish. An appropriate audit trail means that the finalclinical research results for publication/reports can be traced back to the statistical program output and the datasets used. For example, a table of results including mean difference and 95% confidence interval should be verifiable against information that shows who undertook the analysis, and how and when this analysis occurred. This can be documented, for example, by email or a printout that has been signed and dated.22.The statistician will apply version control to all outputs of the statistical process.23.For clinical trials, where appropriate, the statistician will perform interim analyses at the intervals specifiedin the protocol (e.g. for data monitoring committee (DMC) meetings) and following the SAP.o For this, a frozen copy (snapshot) of the dataset will be made for analyses, ensuring the frozen dataset is preserved so that the analysis can be reproduced if required at a later date.o Where a decision is taken to cancel interim analysis (e.g. due to insufficient participant numbers), this must be documented.o If the project is blinded, and interim unblinded analysis is required, ensure the clinical research team cannot gain access to unblinded data or the randomisation schedule. See the Randomisation andBlinding SOP(UoB-RND-SOP-001) for further information.24.During final analysis, the statistician will ensure statistical packages remain unchanged e.g. by disablingautomatic updates. Where updates have occurred e.g. if analysis undertaken over a period of time, these packages may require re-validation (see point 18 above).25.The statistician will perform and document checks to ensure that the output of the statistical analysisprocess is accurate, and ensure that the SAP has been followed.26.The statistician will prepare the analytical section of project reports (e.g. DMC, end of project report,reports to other third parties e.g. ethics, funder etcetera).27.The statistician will review publications (including DMC reports) prior to submission, ensuring the resultshave been correctly transferred into the publication and that they accurately reflect the analysis data, and retain evidence of this review. For randomised clinical trials, the statistician will follow The CONSORT (Consolidated Standards of Reporting Trials) Statement guideline for publication. Also see Extensions of the CONSORT Statement for “non-standard” randomised clinical trial with specific designs, data andinterventions.o For clinical trials, it is expected that all significant non-compliances that occurred during the trial and how these contributed to the analysis, and any changes to the planned statistical analysis withjustification for these changes are reported.Essential documentation and archiving28.The CI (or delegate) will retain adequate documentation to allow verification that data has been accuratelyhandled and reported in accordance with the UoB Principles of GCP for Clinical Research (UoB-GCP-POL-001). This includes (but is not limited to):o a SAP (where separate from the protocol)o an audit trail (see previous section for details).29.The CI (or delegate) will archive documentation related to statistical processes with the rest of thestudy/trial master file (S/TMF) at the end of the clinical research. See the Archiving SOP (UoB-ARC-SOP-001) for further information.List of expected outputs☐Documented evidence that the statistician has the relevant statistical knowledge and experience to perform the required tasks.☐Roles and responsibilities of the statistician are documented, with evidence of the level of ongoing input required and contracts and agreements to be in place (where appropriate).☐Evidence of the statistician involvement in the project design and protocol development. Where appropriate (as per the risk assessment), documented evidence of the statistician involvement in CRF design, clinical research database and data management activities.☐Evidence of a process to record and collate all protocol non-compliances and documented evidence that all significant protocol non-compliances have been reviewed by the statistician.☐Evidence of the pre-specified statistical methodology for the project in the protocol or in a separate document (SAP). As a minimum, it will detail how the primary and secondary outcomes will be measured and what statistical method(s) will be used.☐Documented evidence of the statistician’s approval of (each version of) the SAP.☐Where amendments to the project are likely to have an impact on the design and analysis of the clinical research: evidence that the impact of these have been reviewed by the statistician, with any changes justified and appropriate version control applied.☐Evidence of quality check, data cleaning and data validation processes. For clinical trials, this will be in accordance with the Data Management SOP (UoB-DMA-SOP-001).☐Evidence that the data has been locked (or a snapshot has been created) prior to the start of the statistical analysis. For clinical trials, this will be in accordance with the Data Management SOP (UoB-DMA-SOP-001). ☐An audit trail in the statistical analysis process in order to allow the data analysis to be reconstructed from start to finish, with appropriate version control applied.☐Evidence of appropriate checks by the statistician to ensure the outputs of the statistical analysis process is accurate.☐Evidence that the SAP has been followed.☐Evidence that the statistician has reviewed publications prior to submission.☐Evidence that the documentation related to statistical processes has been stored as per the Archiving SOP (UoB-ARC-SOP-001).Related documents☐UoB-ARC-SOP-001 Archiving☐UoB-CLO-SOP-001 Project Closure☐UoB-CRT-CRF-SOP-001 Case Report Form Development☐UoB-DMA-SOP-001 Data Management☐UoB-GCP-POL-001 UoB Principles of GCP for Clinical Research☐UoB-RND-SOP-001 Randomisation and Blinding☐UoB-SPO-QCD-001 Clinical Trials Task Delegation Log☐UoB-TRN-SOP-001 TrainingUoB QMS documents can be found on the CRCT website. Internal work instructions can be obtained from the CRCT (XXX) and/or from the RGT (XXX).References and frameworks☐The CONSORT (Consolidated Standards of Reporting Trials) Statement guideline☐Extensions of the CONSORT Statement☐Medicines and Healthcare products Regulatory Agency (MHRA). Good Clinical Practice Guide, London: The Stationery Office, 2012.Abbreviations and definitions:See also the Glossary of Terms.标准操作程序:统计学目的本标准操作程序(SOP)描述了在伯明翰大学(UoB)内进行的临床研究中涉及的统计程序。
现代机械工程专业英语
Lesson 1 Engineering Drawings1.assembly drawing 转配图2.balloon 零件序号3.detail drawing 零件图4.view 视图5.full-section view 全剖视图6.Broken-sectional view 局部视图7.Convention 惯例,规范8.Cutting-plane 剖切图9.Sketch drawing 草图10.Interchangeable 可互换的11.Craftsman 工匠,工人12.Tolerance 公差13.Procurement 采购,获得14.Exploded drawing 分解示图15.Pattern maker 模型工,翻铸工16.Machinist 机械师,机工Lesson 2 mechanics1.mechanics 力学2.Acceleration 加速度3.Deformation 变形4.Stress 应力5.Sub discipline 分支学科6.Static 静力学7.Dynamics 动力学8.Mechanics of material材料力学9.Fluid mechanics 流体力学10.Kinematics 运动学11.Continuum mechanics连续介质力学12.static equilibrium 静力平衡13.Newton’s first law14.Susceptibility 敏感性15.Newton’s second law of motion16.Yield strength 屈服强度17.ultimate strength 极限强度18.Failure by bucking 屈曲破坏19.Stiffness 刚度20.Young’s modulus 杨氏模量21.Macroscopic 宏量22.Microscopic 微量putational fluid dynamics (CFD)计算流体力学24.trajectory 轨道25.Astrophysics 天体物理学26.Celestial 天空的27.Robotics 机器人学28.Biomechanics 生物力学29.Rigid body 刚体Lesson 3 Engineering Materials1.polymer 聚合物2.Ceramics 陶瓷3.Stiff 硬的,刚性的4.Fracture 断裂,折断5.Transparent 透明的,显然的6.Lustrous 有光泽的7.Delocalized 不受位置限制的8.Ferrous 铁的,含铁的9.Nonferrous 不含铁的,非铁的10.Tailored 定制的,特制的11.Hardness 硬度12.Tensile strength 抗拉强度13.Toughness 韧性14.Quenching 淬火15.Tempering 回火16.Stainless 不锈的17.Shield 防护,屏蔽,遮挡Lesson4 Mechanical Design1.mechanism 机构,机械2.Thermal 热量,热的3.Switch 开关4.Cam 凸轮5.Valve 阀门6.Beam 梁7.Phenomena 现象8.Screw 螺钉,螺杆9.Fasteners 紧固件10.Spring 弹簧11.Gear 齿轮12.Durability 耐用性13.Femur 股骨14.Quadriceps 四头肌15.Optimization method 最优化方法16.Stiffness 硬度17.Stock 原料,备品18.Noninterference 互不干扰Lesson5 machinery component1.pulley 滑轮,带轮2.Torque 扭矩,转(力)距3.Sheave 滑轮车,槽轮4.Disassembly 拆卸分解5.Stock 棒料,库存6.Woodruff key 半圆键,月牙键7.Axle 轮轴,车轴8.Spline 花键,用花键连接9.Bushing 轴瓦,轴衬10.Involute spline 渐开线花键11.Spindle 主轴,轴12.Groove 沟,槽;刻沟,刻槽13.Residual stress 残余应力14.Coupling 联轴器15.Distortion 变形,绕曲16.Misalignment 未对准(线),非对中17.Referred to as 把。
Collaboration, Automation, and Cognitive Aids Technologies to Solve Complex Transportation
Collaboration, Automation, and Cognitive Aids Technologies to Solve Complex Transportation Problems Deepa ManiUniversity of Missouri, Columbia1205 University Avenue #327Columbia, MO 65201Dm4x9@ABSTRACTIt has always been the endeavor of scientists and engineers to develop systems that could mimic the human brain and adapt themselves to complex situations in order to arrive at a solution to the problem at hand in an efficient and effective manner. These systems would not only be capable of action but also of thought. Heuristic and algorithmic technologies are needed for the automation of cognitive activities. There is a need to develop tools, which are capable of assessing a situation at hand, alerting the human part of the system to various concerns and providing advice on possible responses, and possibly proceed towards solving the problem. This paper deals with the development of a human-machine optimal automated transportation system. In this paper it is proposed to develop specific algorithms to predict and avoid traffic congestion and collision. Two such tools that can be used with each other to produce optimal results are the Global Positioning System (GPS) and the Kalman filter. The Kalman filter is an algorithm, which can be used to predict the future state of a system based on the past information. This could be useful when we are dealing with typically, the problem of collision. A Kalman filter could be designed to give an accurate estimate of the future state of a highway or an intersection based on the data collected for that particular highway or intersection by GPS. The goal is to successfully use data fusion algorithms specifically like GPS and Kalman filters to improve the safety and efficiency of transportation systems particularly with respect to collision avoidance.Key words: automated transportation system—global positioning system—Kalman filter Proceedings of the 2003 Mid-Continent Transportation Research Symposium, Ames, Iowa, August 2003. © 2003 by Iowa State University. The contents of this paper reflect the views of the author(s), who are responsible for the facts and accuracy of theINTRODUCTIONIt has always been the endeavor of scientists and engineers to develop systems that could mimic the human brain and adapt themselves to complex situations in order to arrive at a solution to the problem at hand in an efficient and effective manner. These systems would not only be capable of action but also of thought. Heuristic and algorithmic technologies are needed for the automation of cognitive activities. There is a need to develop tools, which are capable of assessing a situation at hand, alerting the human part of the system to various concerns and providing advice on possible responses, and possibly proceed towards solving the problem.One of the most complex problems facing all the big cities of the world alike is that of traffic congestion and unwanted incidents of collision. There is an ever-growing demand for new highway systems as a result of the exponentially increasing vehicle population. This growing problem has to be taken into account seriously, not only by governments, but also by private sector. A solution to the problem here lies not in creating more and more assets but in the smart management of existing assets.Hence, design of smart vehicles and highway systems and efficient management of automated systems can definitely alleviate the existing problem of traffic congestion and help in collision avoidance.The objective of this proposal is to develop a human-machine automation system and identify the level of automation that would optimize the performance levels of both, the human and the machine. It is also intended through this project to delve into the prospect of the successful use of data fusion algorithms specifically like GPS and Kalman filters to improve the safety and efficiency of transportation systems particularly with respect to collision avoidance.LITERATURE REVIEWA thorough study of all the concepts dealing with automation and smart human-machine technologies will be undertaken for this research. All the previous work will be analyzed and improvisations, if any will be suggested. The literature review carried out till date is summarized below.Intelligent Vehicle/Highway SystemThe Intelligent Vehicle/Highway system is an intelligent transportation system, in which vehicles and highways will exchange information through a two-way communication system. The automated highways will have a set of lanes on which vehicles with specialized sensors and wireless communication systems could travel under computer control at closely spaced intervals.This type of arrangement is called Platoons. The vehicles could continuously exchange information with other vehicles and traffic-control centers about speed, acceleration, braking, obstacles, road conditions, etc. Sensor data can be processed and sent back to each vehicle guaranteeing a continuous exchange of information.The highway system will know the destinations and planned routes of individual vehicles. In that way the system can coordinate traffic flow more efficiently, reduce speed fluctuations, monitor unsafe vehicle operation and traffic shock waves, maximize highway capacity and minimize avoidable traffic congestion. In addition, the system will respond rapidly to changing highway conditions.The vehicles might use several types of devices to sense its environment, such as magnetometers, visual sensors, infrared sensors, laser sensors, accelerometers, etc. Each vehicle has to have a powerful computer to process sensory data and the information that come from the traffic-control centers.Devices and systems such as Global Positioning System (GPS), Automatic Vehicle Monitoring (AVM), Incident Management System (IMS), Intelligent Transportation System (ITS), Vehicle Navigation System (VNS), and Driver Assistance System (DAS) can all be lumped under Intelligent Vehicle/Highway System (IVHS).Collision AvoidanceCollision Avoidance System (CAS) denotes the first step towards accomplishing fully automated highways. However, the development and near-term implementation of CAS is driven by the system’s role in preventing rear-end vehicle collisions.The development of CAS represents a change of focus in dealing with the consequences of accidents. Traditionally the emphasis has been on injury mitigation for those involved in a collision, for example by providing stronger vehicle frames, seat belts, and airbags. Starting with the development of antilock brakes, the focus has now shifted to collision avoidance. Most CASs are currently in experimental stage; before they can be implemented on a wide-scale basis; several technical and political questions need to be answered.A collision avoidance system operates, generally, through a sensor installed at the front end of a vehicle, which constantly scans the road ahead for vehicles or obstacles. When found, the system determines whether the vehicle is in imminent danger of crashing, and if so, a collision avoidance maneuver is undertaken. Most CASs are non-cooperative, that is, detection is independent of whether other vehicles on the road are equipped with collision avoidance devices.An alternative technology relies on vehicle-to-vehicle communications to exchange information on vehicles’ presence, location, lane of travel, and speed among other factors. In addition to the front-end sensor, vehicles require a rear-end transponder as well, since communication, and therefore detection, only occurs among equipped vehicles.Criteria to Activate the Collision Avoidance SystemTime-to-collision criterion: the system decides whether a collision is likely to occur at prevailing speeds and distances, within a certain time interval. In a car-following scenario, the time-to-collision is the time taken for the two vehicles to collide if they maintain their present speed and heading.Worst-case scenario:the system infers that the vehicle preceding the CAS equipped vehicle could brake at full braking power at any time. Basically, it operates on a “critical headway distance” that is, the minimum distance necessary for the CAS-equipped vehicle to come to a stop in the event of the leading car abruptly brakes.Collision Avoidance ManeuversHeadway distance control:the system alerts the drivers when their cars are following the leading car too closely. Some systems include automatic speed control, in such a way; the car could automatically reduce its speed in order to maintain a safe headway with the leading vehicle.Hazard warning:the system alerts the driver of an object (moving or stationary) within its projected path, so that the driver has enough time to avoid collision.Automatic vehicle control: the system controls the vehicle’s brakes and steering wheel, and applies them automatically when it determines it is necessary.Warning DevicesVisual head-up displays:warnings are displayed on the windshield in the driver’s fields of view, so that their content can be assimilated in conjunction with the driving scene ahead. These displays are intended to minimize distraction from driving tasks, in addition to ensuring that warning does not go undetected. Audio/Voice signals: in comparison to visual signals, auditory signals appear to be less intrusive on driving tasks. They are also insensitive to external conditions such as poor light, bad weather, or a dirty windshield. Two different auditory warnings have been developed: speech (synthesized voice) or non-speech (buzzer) displays.Haptic devices: they provide redundant information via alternative sensory modalities, given that the primary visual or auditory channel may be degraded or overburdened. Research suggests that one possibility is to increase the force needed to push the gas pedal.Kalman filters: First reported in ASME’s Journal of Basic Engineering by R.E.Kalman (1960), this positional estimation algorithm has been widely used for a variety of optimization tasks. Transportation systems employing Kalman filtering use discrete-time algorithms to remove noise from sensor signals in order to better determine the present and future positions of a target.Kalman filtering produces fused data that estimate the smoothed values of position, velocity, and acceleration at a series of points in a trajectory.Although no set of sensors can pinpoint a target with complete accuracy, the tolerance of each sensor’s positional fix accuracy can be known and assigned. So Kalman filtering can be used to define a region of space within which an object is located. The narrower these spatial limits are kept, the better the estimation algorithm can perform.The Kalman filter estimates a process by using a form of feedback control. The filter estimates the process state at some time and then obtains feedback in the form of (noisy) measurements. As such, the equations for the Kalman filter fall into two groups: time update equations and measurement update equations. The time update equations are responsible for projecting forward (in time) the current state and error covariance estimates to obtain the “a priori” estimates for the next time step. The measurement update equations are responsible for the feedback—i.e. for incorporating a new measurement into the “a priori” estimate to obtain an improved “a posteriori” estimate.The time update equations can also be thought of as predictor equations, while the measurement update equations can be thought of as corrector equations. Indeed the final estimation algorithm resembles that of a predictor-corrector algorithm for solving numerical problems.FIGURE 1. Kalman Filter CycleThe Kalman filter is a recursive, linear filter. At each cycle, the state estimate is updated by combining new measurements with the predicted state estimate from previous measurements.FIGURE 2. Kalman Filter Operation (1)Global positioning system (GPS): A global positioning system employs a network of Earth-orbiting satellites to calculate a subject’s position and then transmit that information to the subject’s GPS receiver. The GPS has 3 parts: the space segment consists of 24 satellites, each in its own orbit 11,000 miles above the Earth. The user segment consists of the receivers. The control segment consists of ground stations (five of them located around the world) that make sure the satellites are working properly.Each GPS satellite transmits data that indicates its location and the current time. All GPS satellites synchronize operations so that these repeating signals are transmitted at the same instant. The signals, moving at the speed of light, arrive at a GPS receiver at slightly different times because some satellites are further away than others. The distance to the GPS satellites can be determined by estimating the amount of time it takes for their signals to reach the receiver. When the receiver estimates the distance to at least four GPS satellites, it can calculate its position in three dimensions. Ground stations are used to precisely track each satellite's orbit. A GPS receiver knows the location of the satellites, because that information is included in satellite transmissions. By estimating how far away a satellite is, the receiver also knows it is located somewhere on the surface of an imaginary sphere centered at the satellite. It then determines the sizes of several spheres, one for each satellite. The receiver is located where these spheres intersect.GPS accuracy: The accuracy of a position determined with GPS depends on the type of receiver. Most hand-held GPS units have about 10-20-meter accuracy. Other types of receivers use a method called Differential GPS (DGPS) to obtain much higher accuracy. DGPS requires an additional receiver fixed at a known location nearby. Observations made by the stationary receiver are used to correct positions recorded by the roving units, producing an accuracy of greater than 1 meter.Data fusion process: The data generated by a GPS could be passed through a Kalman filter which would forecast future traffic condition. A Pattern matching software could be used to match the current traffic situation with the historical situations. A Knowledge–Based Expert System (KBES) could then be used to identify abnormal traffic conditions, and if possible qualitatively suggest corrections early enough to avoid any incidents.FIGURE 3. GPS FlowchartAn integrated GPS receiver and inertial navigator use a Kalman filter to improve overall navigation performanceRESEARCH APPROACHDevelopmental StagesStage I: to equip vehicles and highways with GPS receivers and transmitters to allow exchange of data between them as well as with the Traffic Information Centers (TIC).Stage II:To design a Kalman filter specifically to process the data generated by the Global Positioning System and accurately predict the future traffic condition. The most challenging aspect of this step would be to define the initial state i.e., to determine the state equations that effectively represent the traffic model, to be able to extract the data that will be needed to predict the future states.Stage III: Developing software capable of identifying similar situations in past appearing in the present data. The software developed could be trained in such a way that, it in collaboration with a database has the capability of identifying events and categorizing them.Stage IV: Development of specific expert system to recognize anomalous traffic conditions. This system should not only identify the abnormal traffic conditions but it should also give a qualitative account of the condition.FIGURE 4. Diagrammatic Representation of the ProcessSUMMARYThe challenge is to ensure that new information, safety, and automation technologies are integrated to create human-centered intelligent vehicles that can advance safety, surface transportation efficiency, and economic competitiveness. It is my opinion that by developing human-centered smart systems the demands on present-day transportation syatems can be met effectively. It is through human-centered automation, the most efficient method of data-analysis and decision-making can be achieved. Technological change, however, is constant. Even as one set of technologies are envisioned, the envelope of possibilities expands. The latest innovations in information and computer technology, for example, are focusing on the development of neural links that will allow commands to be given with muscle impulses, eye movements, and brain waves, creating an almost symbiotic relationship between humans and machines. The vision of a human-centered intelligent vehicle, therefore, is not fixed but will continuously evolve in the wake of continuing technological breakthroughs. However, for transporation systems, putting people at the center of technology, will remain paramount.REFERENCES1. Bahowick, T.J. “The Kalman Filter.” Report given at the University of Washington, 1990. Adapted from S.M. Bozic Digital and Kalman Filtering: An Introduction to Discrete Time-Filtering and Optimum Linear Estimation. Edward Arnold Publishers, London, 1979.。
关于小组合作的英语作文
关于小组合作的英语作文Effective group collaboration is essential in both academic and professional settings. When individuals work together towards a common goal, they can leverage their diverse skills and perspectives to produce higher-quality outcomes than they could achieve individually. However, group work also presents unique challenges that must be navigated carefully. In this essay, I will discuss the key benefits and potential pitfalls of group collaboration, as well as strategies for ensuring successful group projects.One of the primary advantages of group collaboration is the ability to draw upon a range of knowledge and expertise. In any given group, members will likely have different educational backgrounds, work experiences, and areas of specialization. By pooling these varied skillsets, the group can tackle complex problems from multiple angles and develop more comprehensive and innovative solutions. For example, in a student group project to design a new product, an engineering student could contribute technical expertise on product design and functionality, a business student could provide insights on market analysis and financial viability, and acommunications student could help with branding and marketing. Together, the group can create a final product that is not only well-engineered, but also commercially viable and effectively marketed.In addition to diversifying the knowledge base, group collaboration also facilitates the exchange of ideas and perspectives. When individuals with different backgrounds and thought processes come together, it can spark new ways of thinking and lead to breakthroughs that may not have occurred in isolation. The process of discussing, debating, and refining ideas within a group setting can uncover flaws or blind spots that a single person may have overlooked. This collaborative ideation can result in more well-rounded and creative solutions.Furthermore, group work can enhance productivity and efficiency. By dividing tasks and responsibilities among members, the group can accomplish more in less time than if each individual were working alone. This is particularly beneficial in fast-paced, high-stakes environments where timely delivery of results is crucial. Moreover, the mutual accountability and support within a group can help maintain momentum and ensure that deadlines are met.However, group collaboration is not without its challenges. One of the primary obstacles is the potential for interpersonal conflicts and communication breakdowns. Differences in communication styles,work preferences, and personalities can sometimes lead to misunderstandings, disagreements, and resentment among group members. This can hinder the group's ability to work cohesively and effectively.Another common issue in group work is the uneven distribution of effort and contribution. It is not uncommon for some members to carry a disproportionate share of the workload, while others may contribute minimally or even free-ride on the efforts of their peers. This can breed resentment, undermine morale, and ultimately jeopardize the quality of the group's output.Additionally, group collaboration can be hindered by logistical challenges, such as scheduling conflicts, geographical dispersal of members, and technological barriers to effective communication and coordination. These practical obstacles can make it difficult for the group to meet regularly, stay aligned on goals and deadlines, and maintain a sense of collective purpose.To address these challenges and ensure successful group collaboration, it is essential to establish clear guidelines, roles, and responsibilities from the outset. This includes defining the group's objectives, setting realistic timelines, and agreeing on protocols for decision-making, conflict resolution, and task allocation. Effective communication is also key, with regular check-ins, progress updates,and opportunities for feedback and input from all members.It is also important for group members to cultivate interpersonal skills, such as active listening, empathy, and compromise. By fostering an environment of mutual respect, trust, and openness, the group can navigate differences and disagreements more constructively. Additionally, group members should be willing to hold each other accountable and provide constructive feedback to ensure that everyone is contributing their fair share.Finally, the use of collaborative technologies, such as project management software, cloud-based document sharing, and video conferencing, can greatly facilitate group coordination and productivity, especially in cases where members are geographically dispersed.In conclusion, group collaboration offers numerous benefits, including the ability to leverage diverse expertise, foster innovative thinking, and enhance productivity. However, it also presents unique challenges that must be carefully navigated. By establishing clear guidelines, fostering effective communication and interpersonal skills, and leveraging collaborative technologies, groups can maximize the advantages of collective work and minimize the potential pitfalls. Ultimately, the success of group collaboration depends on thewillingness of members to work together, communicate openly, and commit to the shared goals of the group.。
设想一家公司设计自己的产品英语作文
设想一家公司设计自己的产品英语作文Designing products is an essential part of creating a successful business. When a company takes the time to design their own products, they have the opportunity to differentiate themselves from competitors, create unique solutions for their customers, and build a strong brand identity. In this essay, we will explore the process of designing products for a company and the benefits that come from this approach.The first step in designing products for a company is to identify the target market and understand their needs and preferences. By conducting market research, a company can gain insights into what their customers are looking for in a product and how they can meet those needs. This information can then be used to brainstorm ideas for new products that will resonate with the target market.Once a company has a clear understanding of the target market, they can begin to design their products. This process involves creating prototypes, conducting testing, and iterating on the design until it meets the desired specifications. At this stage, it is important to involve key stakeholders, such as customers, employees, and designers, to ensure that the product is well-received and meets the needs of the target market.One of the key benefits of designing products for a company is the ability to create unique solutions for customers. By customizing products to meet the specific needs of the target market, a company can differentiate themselves from competitors and stand out in a crowded marketplace. This can lead to increased customer loyalty, repeat business, and positive word-of-mouth marketing.Another benefit of designing products for a company is the opportunity to build a strong brand identity. By creating products that are aligned with the company's values, mission, and aesthetic, a company can establish a unique identity that sets them apart from competitors. This can help to build brand recognition, attract new customers, and foster a sense of trust and loyalty among existing customers.In conclusion, designing products for a company is a crucial step in building a successful business. By understanding the needs of the target market, creating unique solutions, and building a strong brand identity, a company can differentiate themselves from competitors, attract new customers, and build a loyal customer base. Through careful planning, collaboration, and innovation, a company can design products that meet the needs of their customers and drive long-term success.。
介绍新加坡国立大学英语作文
介绍新加坡国立大学英语作文Singapore National University is one of the most prestigious universities in Asia and has a strong reputation for academic excellence. Located in the heart of Singapore, this renowned institution offers a diverse range of undergraduate and postgraduate programs, catering to students from all over the world. In this essay, I will provide an in-depth introduction to Singapore National University, highlighting its academic offerings, campus life, and the unique opportunities it presents to students.Established in 1905, Singapore National University has a long and illustrious history as a center of higher education. The university's origins can be traced back to the founding of the Straits Settlements and Federated Malay States Government Medical School, which later evolved into the present-day Faculty of Medicine. Over the decades, the university has expanded its academic offerings, establishing new faculties and schools to cater to the ever-changing needs of the global economy.Today, Singapore National University is renowned for its world-class education and cutting-edge research. The university is organized into 17 schools and faculties, each of which offers a wide range ofundergraduate and postgraduate programs. These include the Faculty of Arts and Social Sciences, the Faculty of Engineering, the Faculty of Science, the School of Business, and the School of Design and Environment, among others. Each faculty is led by renowned scholars and researchers who are at the forefront of their respective fields, ensuring that students receive a truly exceptional educational experience.One of the standout features of Singapore National University is its commitment to interdisciplinary learning. The university encourages its students to explore a diverse range of subjects and to think critically about the interconnections between different fields of study. This approach not only helps students develop a well-rounded knowledge base but also prepares them for the increasingly complex challenges of the modern world.In addition to its academic excellence, Singapore National University is also renowned for its vibrant campus life. The university's sprawling 150-hectare campus is a hub of activity, with a wide range of clubs, societies, and student organizations catering to a variety of interests and passions. From sports teams and performing arts groups to community service initiatives and entrepreneurship clubs, there is something for everyone at Singapore National University.The university also boasts state-of-the-art facilities that support bothacademic and extracurricular pursuits. These include modern lecture halls and seminar rooms, well-equipped laboratories and research facilities, a comprehensive library system, and world-class sports and recreational amenities. The campus also features a diverse range of dining options, providing students with a wide selection of cuisines to choose from.One of the most unique aspects of Singapore National University is its commitment to global engagement. The university has established partnerships with leading institutions around the world, offering students the opportunity to participate in exchange programs, study abroad initiatives, and international research collaborations. This exposure to diverse cultures and perspectives not only enhances the educational experience but also helps students develop the skills and mindset needed to succeed in the increasingly globalized world.Moreover, Singapore National University is renowned for its strong ties to industry and the local community. The university works closely with businesses, government agencies, and non-profit organizations to ensure that its programs are relevant and responsive to the needs of the workforce and society. This collaboration also provides students with valuable opportunities for internships, project-based learning, and professional networking.In conclusion, Singapore National University is a truly exceptional institution that offers a world-class education and a vibrant campus experience. With its commitment to academic excellence, interdisciplinary learning, global engagement, and community partnership, the university is well-positioned to prepare students for the challenges and opportunities of the 21st century. Whether you are interested in the arts, sciences, business, or engineering, Singapore National University is an institution that is sure to inspire and challenge you on your educational journey.。
工业工程毕业设计参考文献
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组织学习与企业创新产出外文文献翻译中英文2020
外文文献翻译原文及译文(节选重点翻译)组织学习与企业创新产出外文文献翻译中英文文献出处:International Journal of Innovation Studies,Volume 4, Issue 1, March 2020, Pages 16-26译文字数:6000 多字英文Influence of organization learning on innovation output in manufacturingfirms in KenyaIsaac Gachanja, Stephen Nga’nga’, Lucy Kiganane AbstractKnowledge entrepreneurship is increasingly becoming important in driving innovation for high levels of competitiveness. The purpose of this study was to investigate the relationship between Organization Learning (OL) and Innovation Output (IO) for improved performance in manufacturing firms in Kenya. The theoretical underpinnings on this study are the Schumpeter’s (1934) innovation theory of and the Gleick (1987) complexity theory. The methodology used was mixed method research because it provides a more holistic understanding of a thematic area. The research design that was used is cross-sectional design because it allows for making observations on different characteristics that exist within a group at a particular time. The target population was manufacturing firms across the country. Multi-stage sampling strategy was used to sample 303 respondents from 101 firms. Primary and secondary data were used to collect both qualitative and quantitative data. The questionnaire, interview schedule and a checklist of key informants were used to collect data. Content validity was used to ascertain the credibility of the research procedure and internal consistency techniquewas used to test for reliability. Correlation and linear regression were used to determine the relationship between OL and IO. Work disruptions were avoided by making prior arrangements and appointments. The findings indicate that OL has a significant influence on IO. It is recommended that lifelong learning, management support and risk tolerance should be encouraged to improve creativity. High creativity is important in raising the capacity to integrate internal and external knowledge for greater levels of IO. Further research should be carried out to find how customers and suppliers information can be utilized to enriched OL.Keywords: Organization learning, Innovation output, Competitiveness, Lifelong learning, Risk tolerance1. IntroductionInnovation utilizes knowledge which is important in raising creativity and capacity development for enterprise prosperity. Many countries have developed their National Innovation Systems (NIS) and have a comprehensive innovation policy framework, but most firms have not leveraged on these opportunities to raise their Innovation Output (IO). This has been contributed by the disjointed relationship between research institutions and industry. The situation has been brought about by multiplicity of new institutions that have become a barrier to knowledge sharing and thus firms are shying away from intense collaboration withresearch institutions and universities which has led to declining knowledge absorption, creation and diffusion which are key components of innovation performance (Cornell University, INSEAD & WIPO, 2015). The situation can be addressed by rallying firms to develop their knowledge capacities by focusing on Organization Learning (OL) for greater IO.Previous researchers have not managed to unravel the puzzle of how to transform knowledge into innovation output that improves competitiveness in the manufacturing sector. This has been partly attributed to by the failure of incorporating local knowledge in the innovation process (Sambuli & Whitt, 2017). The complexity of blending internal and external knowledge and reconfiguring new insight for greater innovation has also not been adequately addressed in Kenya. Furthermore, the linkages within the innovation system are weak and the manufacturing sector has the highest abandoned innovation activities at about 40% (Ongwae, Mukulu, & Odhiambo, 2013). The quagmire of striking a balance between sharing knowledge, guarding against knowledge leakages, diffusion of tension and mistrust that emanates from the competition while interacting with the NIS to improve IO has not been resolved. The study will attempt to address these gaps by investigating the influence of OL on IO.The objective of the study is therefore to examine the influence ofOL on IO in manufacturing firms in Kenya. The null hypothesis is that OL has no significant influence on IO in manufacturing firms in Kenya while the alternative hypothesis is that OL has a significant influence on IO. The hypothesis will be subjected for a test. The study will contribute to the value of OL on the firms’ competitiveness. It will provide insights on how firms can blend internal and external knowledge in the process of OL to improve IO which contributes to their competitive advantage.2. Literature reviewThis section begins with review of previous empirical work on OL and IO. Theoretical underpinnings are then discussed leading to a development of conceptual framework.2.1. Innovation outputInnovation output is the end product of an innovation activity. The end products of innovation are; new products, new process, new enterprise and new markets. Andreeva and Kianto (2011) believe that IO is the degree to which enterprises develop novelty in terms of processes, management and marketing. Innovation output can therefore be defined as the increase in novel products, creative processes, and development of new ventures and discovery of new markets.Innovation output depicts the result of an innovation effort. It can be measured as the summation of increased new products as a result of innovation, patents acquired, new innovation process and uniqueenterprises created to cater for innovation activities. Innovation output can be enhanced by improving the innovation capacity of a firm.Innovation capacity is paramount in realizing and identifying the need for change, thus leading to new ideas. It provides the capability of seizing up opportunities (Teece, 2009) leading into a new business configuration which helps in attaining and maintaining high competitive levels (Saenz & Perez-Bouvier, 2014). Innovation capacity can be optimized through OL which leads to continuous improvement in firm performance particularly in the manufacturing sector. Manufacturing firms are faced with myriad of challenges such as; the ever-changing taste and preferences of customers, rapid change in technology, increasing competitions, dynamic operating environment and changing global trends. This calls for OL for firms to adequately navigate in the turbulence.2.2. Organization LearningOrganization Learning is one of the key aspects of knowledge entrepreneurship which is crucial in determining innovation output. Desai (2010) defined OL as the process of acquiring, absorbing, sharing, modifying and transferring knowledge within an entity. The context in which OL is used in this study is a mechanism for discovering new ways of improving operations through knowledge acquisition, absorption, sharing and transfer for improved performance. The salient feature that distinguishes OL from learning organization is its diversity andextensiveness. This forms the bases of generating internal knowledge that is peculiar to an Organization.The capacities developed in OL provide an opportunity for the integration of internal and external knowledge. This requires collective input and knowledge sharing (Granerud & Rocha, 2011). Organization learning therefore involves development of internal knowledge capacities that integrates external knowledge from other organizations within and without the sector. This is beneficial to the firm because it allows continuous improvement, adaptability and value addition Granerud and Rocha (2011) argues that OL is the foundation from which the base of improved practices is laid.Organization Learning can be measured in different ways. Jain and Moreno (2015) posited that the factors attributing to OL are; collaboration, teamwork, performance management, autonomy and freedom, reward, recognition and achievement orientation. The Global Innovation Index utilizes Knowledge absorption, creation, impact and diffusion which can be measured by the level of royalties, patents, number of new firms, royalties and license fees receipts or web presence respectively in measuring OL (Cornell University, INSEAD & WIPO, 2016). Tohidi and Jabbari (2012) believe that the strategic elements of OL are experimentation, knowledge transfer, developing learning capacity, teamwork and problem-solving. Chiva and Alegre (2007) are ofthe opinion that development of learning capacity can be enhanced by empowerment to generate new ideas, managerial commitment to support creativity, continued learning, openness and interaction with external environment and risk tolerance.The study thus adopted and improved on the measures of OL used by Chiva and Alegre (2007) and Tohidi and Jabbari (2012) because the parameters are more comprehensive in measuring OL. This was done by incorporating openness and knowledge integration on OL. The measures that were used to measure OL in this study are therefore; liberty of experiment, empowerment to generate new ideas, managerial commitment to support creativity, knowledge transfer and integration, openness and interaction with external environment, continued learning and risk tolerance.Nevertheless, absorptive capacity is important in OL because it improves the ability of the human resource within the firm to acquire and assimilate new and external knowledge for improved performance. Supportive Learning Environment (SLE) increases the absorptive capacity of the firm thus enhancing OL while a turbulent learning environment lowers the OL (Cohen & Levinthal, 1990). The SLE therefore moderates the influence of OL on IO. The SLE provides a conducive atmosphere for employee to engage each other and with the management freely and constructively which may lead to review of firmsoperations and processes (Garvin, Edmondson, & Gino, 2008).The appropriate SLE promotes OL and enhances the innovative ability of a firm. The parameters for measuring SLE are availability of accelerators and incubators, trade organization support and business services (Majava, Leviakangas, Kinnumen, Kess, & Foit, 2016). These parameters facilitates dynamic networking within an economy and accelerates technological spill over which is important in boastering innovation.2.3. Relationship between organization leaning and innovation outputThere have been several attempts to highlight the relationship between OL and IO. To begin with, Hung, Lien, Yang, Wu, and Kuo (2011) found that an analysis of OL and IO model showed the goodness of fit and a significantly positive relationship, thus promoting a culture of sharing and trust which is necessary for enterprise success. However, there is a gap in linking learning process and IO in empirical studies (Lau & Lo, 2015). The study addressed this gap by demonstrating the aspects of OL that influences IO and which do not. Calisir, Gumussoy, and Guzelsov (2013) found that open-mindedness in OL has a positive association with innovation output. Open-mindedness is one of the measures of OL which is incorporated in this study as openness. Zhou, Hu, and Shi (2015) found that OL significantly influences innovationoutput. Furthermore, Ghasemzadeh, Nazari, Farzaneh, and Mehralian (2019) found a significant influence of OL on IO. This study replicated those studies in manufacturing firms in Kenya. The study was anchored on two theories.2.4. Theoretical underpinningsThe first theory that is relevant in this study is Schumpeter’s (1934) theory of innovation. The theory is of the view that the transformation of the economy comes through innovations which bring about creative destructions which lead to improved performance. The dimensions of this theory are the creation of novelties which includes new products, new process, new enterprises, new raw materials and new markets. However, the theory failed to address the required organizational capacity to innovate. This necessitated the adoption of a theory that has a more holistic approach and takes cognizant of the OL as an input in the innovation process. This can be addressed by interrogation of complexity theory.The second theory that is related to this study is Gleick (1987) complexity theory. The theory recognizes the intricacies involved in developing innovation capacity. It advocates for an emergent learning that transcends from the industrial era to the knowledge era that produces ideas that provide complex interplay of different interactions. The complex interactions of internal and external knowledge bring about OLwhich is crucial in enhancing IO. This led to the development of a conceptual framework.3. MethodologyCross-sectional design was used because it helps in making observations on characteristics that exist within a group. The target population was 828 manufacturing firms. The sampling frame was the listed companies in Kenya Association of Manufacturer as of 2018.The multi-stage sampling strategy was used. Purposive sampling was used select the major industrial counties in Kenya. Random sampling was then applied to sample 101 firms from the major industrial counties according to their proportionate representation in terms of location and sub-sector. Purposive sampling was later used to select 3 respondents who were from the sampled 101 firms. The respondents comprised of section heads from operations, marketing and innovation. The total sample size of the respondent was therefore 303. Primary and secondary data were used to collect both qualitative and quantitative data. The questionnaire with Likert scale items o OL and IO, interview schedule and a checklist of key informants were used to collect data.The items which could have had a VIF of more than 10 could be deleted since that is the recommended upper limit (Creswell, 2014), but in this case no item was deleted since the VIF were less than 10. This test was important in authenticating the findings.Validity of the data collected was tested through content validity method. This is where the criteria used to access quality regarding the procedure and results to enhance credibility, transferability, dependability and conformability was addressed by constructing the measuring scale in line with the literature and pre-testing the research instruments during piloting. The questionnaire was designed in line with the constructs and parameters of OL and IO as brought out in literature review.4. Results and discussionsThis implies more new products were manufactured as opposed to other forms of novelty. This means that the general form of innovation in manufacturing firms in Kenya is the creation of new products relative to other forms of innovations such as new processes and enterprises. However, the maximum number of new product was 13 while those that were patented were only 5. It means that majority of new products were not patented. Manufacturing firms should therefore strive to register their patent rights to avoid escalation of counterfeits.The notable new products brought about by innovation were; nitrocellulose paints, hydro-pool, computerized painting machines, nova legs, sodium hypo-chloride, Clorox bleach, adjustable pallet racking and castellated beam for constructing cranes. New products had also a higher standard deviation as compared to other forms of novelty. This implies that there was a widespread of new products created within themanufacturing firms hence a low level of uniformity in new products created and thus a low degree of homogeneity across the firms.This implies that there were innovation activities that generated innovation output. It means that the outcome of innovation activities was observable and can be quantified. The standard deviation of 6.2 implies that there was a widespread within the manufacturing firms. This means that there was a low level of uniformity in innovation output across manufacturing firms and thus a low degree of homogeneity in the sample.This implies that there were more novelties created in the plastics and rubber sub-sector than any other. It means that on average, there were more new products, patents, new process and new enterprises created in the textile and apparels sub-sector. The highest standard deviation of 7.250 was recorded in vehicle assemblers and accessories sub-sector. This implies that the spread of novelties was widest in vehicle assemblers and accessories than other sub-sectors. This means that there was a high variety of IO produced and thus a low level of uniformity in novelties in vehicle assemblers and accessories sub-sector and thus low degree of homogeneity.The highest innovation output in the plastics and rubber sub-sector implies that the sector has more innovation activities as compared to other sub-sector, but innovation efforts were concentrated more on new products. The highest innovation intensity in the food and beverages sub-sector means that there were concerted innovation efforts that were spread across the four novelties and thus diversified IO. This is important because diversified innovation mitigates the risk of over reliance on single or few innovations that may that can be rendered absolute with emergence of other superior innovations.The study has thus established that OL has a significant influence on IO in manufacturing firms in Kenya. Manufacturing firms should, therefore, inculcate a culture of OL for grater IO for improved competitiveness. The findings are consistent with those of Hung et al. (2011) who found that OL have a significant influence on IO. Manufacturing firms should, therefore, embrace OL for utilization of scarce resources to provide value and provide society solutions sustainably. The findings are also in tandem with those Of Calisir et al. (2013) who found that firms with an Organizational practice that promote OL have higher value and IO levels. Higher IO is an indicator that a firm is generating novelties according to the changing needs of the market and hence the likelihood of being competitive leading to improved performance. The findings also concur with those of Hofstetter and Harpez (2015) who found that OL has an immense influence on firm’s IO. Increased IO can lead to improved competitiveness of a firm within the industry, in the economy, the region and the global market. The findings are also in line with Cassiman and Veugelers (2006); Chen,Vanhaverbeke, and Du (2016); Radicic and Balavac (2019); Antonelli & Fassio, 2016 who found that internal and external learning has a positive influence on IO. It is therefore imperative that OL is promoted in the manufacturing sector in Kenya for greater outcomes in IO for enhanced competitiveness locally and internationally.5. Conclusions and recommendationsIt is concluded that the various aspects of OL which include; liberty of experimentation, empowerment to generate new ideas, managerial commitment to support creativity, risk tolerance, knowledge transfer and integration, openness and interaction with the external environment and continuous learning contributes to development of new products, patents acquired, new process and new enterprises. It is also observed that SLE has a significant moderating effect between OL and IO.Management in manufacturing sector should, therefore, nurture and encourage OL for greater IO. Leaders in manufacturing firms should provide freedom to their employees to come up with new ideas and support them to try them out while at the same time be patient to accommodate failures that come with trials. They should also be receptive to divergent viewpoints, encourage problem solving and knowledge transfer. Leaders in manufacturing firms should also set up a robust Research and Development (R&D) by developing the policies that will enhance assimilation of external with internal knowledge for highercapacity to innovate. Policy makers and other relevant stakeholders such as government agencies, research institutions and investor lobby groups and associations should work jointly to address the bottlenecks in SLE.The study enriches the theoretical understanding of how OL influences IO by contributing to new knowledge on how manufacturing firms can improve their competitiveness in Kenya and other parts of sub Saharan Africa.It is recommended that lifelong learning should be encouraged because it improves creativity and develops the capacity to integrate internal and external knowledge which increases the level of IO. Management should also create an enabling culture for promoting creativity and risk tolerance to enhance IO. Manufacturing firms in Kenya should also set clear policies on R&D to enhance OL for increased innovation activities and thus higher IO.Further research should be carried to determine ways in which customers and suppliers information can be utilized to enrich OL. Customers and suppliers are major stakeholders in manufacturing firms. Their input in OL is essential in improving the IO. Further study should also be carried out to examine how networking influences IO. The challenges of mitigating the risks that comes with experimentation and failure tolerance is also a futile ground for further study.组织学习对肯尼亚制造业公司创新产出的影响艾萨克·加尚嘉,史蒂芬·纳加,露西·基加纳摘要知识企业家精神对于推动创新以提高竞争力具有越来越重要的作用。
企业英文缩写大全
企业英文缩写大全5S : 整理(SEIRI)、整頓(SEITON)、清掃(SEISO)、清潔(SEIKETSU)及身美(SHITSUKE)五種行為ABC : 作業製成本制度(Activity-Based Costing)ABB : 實施作業制預算制度(Activity-Based Budgeting)ABM : 作業製成本管理(Activity-Base Management)APS : 先進規畫與排程系統(Advanced Planning and Scheduling)ASP : 應用程式服務供應商(Application Service Provider)ATP : 可承諾量(Available To Promise)AVL : 認可的供應商清單(Approved Vendor List)BOM : 物料清單(Bill Of Material)BPR : 企業流程再造(Business Process Reengineering)BSC : 平衡記分卡(Balanced ScoreCard)BTF : 計畫生產(Build To Forecast)BTO : 訂單生產(Build To Order)CPM : 要徑法(Critical Path Method)CPM : 每一百萬個使用者會有幾次抱怨(Complaint per Million)CRM : 客戶關係管理(Customer Relationship Management)CRP : 產能需求規劃(Capacity Requirements Planning)CTO : 客制化生產(Configuration To Order)DBR : 限制驅導式排程法(Drum-Buffer-Rope)DMT : 成熟度驗證(Design Maturing Testing)DVT : 設計驗證(Design Verification Testing)DRP : 運銷資源計畫(Distribution Resource Planning)DSS : 決策支援系統(Decision Support System)EC : 設計變更/工程變更(Engineer Change)EC : 電子商務(Electronic Commerce)ECRN : 原件規格更改通知(Engineer Change Request Notice)EDI : 電子資料交換(Electronic Data Interchange)EIS : 主管決策系統(Executive Information System)EMC : 電磁相容(Electric Magnetic Capability)EOQ : 基本經濟訂購量(Economic Order Quantity)ERP : 企業資源規劃(Enterprise Resource Planning)FAE : 應用工程師(Field Application Engineer)FCST : 預估(Forecast)FMS : 彈性製造系統(Flexible Manufacture System)FQC : 成品品質管制(Finish or Final Quality Control)IPQC : 制程品質管制(In-Process Quality Control)IQC : 進料品質管制(Incoming Quality Control)SPC : 統計制程管制(Statistic Process Control)TOC : 限制理論(Theory of Constraints)TPM : 全面生產管理Total Production ManagementTQC : 全面品質管制(Total Quality Control)TQM : 全面品質管理(Total Quality Management)WIP : 在製品(Work In Process)ABC Absolute Best Cost (is a procurement strategy to secure thebest costs for a part)AFR Annual Failure ReturnETD Estimated time of departure 估計出發時間ETA Estimated time of arriveAMO After Market OptionsWWAN (Wireless Wide Area Network) 是指傳輸範圍可跨越國家或不同城市之間的無線網路AN The product line code for MCD COMMERCIAL regionsAPJ Asia Pacific and JapanAPL Approved Partner ListFPC PCB" 柔性電路板(柔性RMAPCB): 簡稱"軟板", 又稱"柔性線路板", 也稱"軟性線路板、撓性線路板"或"軟性電路板、撓性電路板","FPCB, Flexible and Rigid-Flex". APO Advanced Planning OptimizationASN Advance Shipment NoticeASP Average Selling PriceATP Acknowledge to Production (order acknowledgement methodology) AUP Average Unit Price (sometimes used interchangeably with ASP)AV Refers to the Marketing Feature level of the BOM (2nd level). Is unique by family/platform/business modelAVL Approved Vendor ListAVLC Available Vendor List CandidateBCPL Blind Corporate Price List - When a product becomes "orderable" for the customerBDD Business Desktop Division - Is now defunct - the HP legacy busines desktop groupBOM Bill of MaterialBPN Business Products North America (Pre-Merger HP term for North America region…sometimes referred to as PPMD)BRD Business Requirements DocumentBRP Business Revenue PlanBT Build TriggerBTCO Build to Customer OrderBTO Build to OrderBTS Build-to-stock (situation where you ask factory to build units and stock FGI at their site before orders arrive)CDS Compal Direct ShipCFZ Code FreezeCIR Consumer IR(OEIC) 光電子集成電路CM Contract ManufacturersCNY Chinese New YearCO Customer Order (a term used in ICON - it is how daily demand is input into ICON) OR Change OrderCOA Certificate of Authenticity - most commonly refers to the Microsoft licensing label that is used on our PCsCRT 阴极射线管(Cathode Ray Tube)的显示器COGS Cost of Goods Sold (usually represented as a percentage of revenue) COS Cost of SalesCPB Company Performance BonusCPC Consumer PC Division - refers to the consumer desktop division based in Cupertino, CaliforniaCPL Corporate Price ListCPMO Region: China (refers to both their operations region and their regional manufacturing site)CPP Commodity Purchase PlanCPU Central Processing UnitCT Commodity TrackingCTO Configure to OrderCWSP Confirmed Weekly Shipment PlanDB Design BuildDC Distribution CenterDIB Drop in BoxDO Design Objective (Project or PLC Milestone - Establish Objectives of a project or new part)DoD Department of DefenseDOS Days of SupplyDR Delivery Request (An order placed by the region on the ODM for delivery)DRCD Driver CDDSM Demand Supply MatchingDSP Depot-Specific Supply Chain - ICON term to describe where/how a product is distributed in the MRP toolFW Firm wareECO Enterprise Core ObjectsECO Engineering Change OrderECR Engineering Change RecordEMEA Europe, Middle-East and Africa (is the Europe region)EOL End of LifeEPC Electronic Product Code (RFID technology provider)ESG Enteriprise Systems GroupEDID Extended Display Identification DATA,即扩展显示识别数据EURP End-User Replaceable PartsFCS First Customer ShipFCT Factory Cycle Time (measures the time it takes the factory to produce and ship the product once they have the ually measured in days) FDD Floppy Disk DriveFLC Factory Learning CurveFPU Factory Produce Unit (IPG term)FTO Flexible Time-off (HP term for vacation time)GBU General Base Unit (Pre-merger HP) OR…General Business Unit (new HP)GFI Go For Intro (PLC and project milestone - indicates this project is ready to start implementation)GPS Global Procurement ServicesHDD Hard Disk DriveHDCP (High-bandwidth Digital Content Protection)HOI HP-Owned InventoryHPD HP DirectHPS HP ServicesI/L Investigation to Lab (PLC milestone - freezes product definition)IDC Inventory Driven CostsIDP Individual Development PlanIDS International Direct ShipOOC Out of characterIES Inventec ChinaIPO International Procurement Organization - now called GPS in some entitiesIQDC Integrated Quality Data CollectionIUR IXXXX Unit RequestPP SAMPLE SP : 指產品的打樣制作;Sample PhasePP :指產品小批量試做;Production PhaseMP :指產品進入大量生產Mass PhaseIWT Inter Warehouse Transfer (a term used in ICON that gives the value of the demand plan per sku)KMAT Configurable Material (SAP term)KV The product line code for MCD RETAIL regionsKWL Keyboard Warning LabelLADO Region: Latin America (Latin America Distribution Organization) LCD Liquid Crystyal DisplayLCPL Live Customer Product List - product number and pricing visibleLi-ION Lithion-Ion: Battery technologyLT Lead TimeLTB Last Time Buy - is used when a component/product is going to become EOLMADP Most Accurate Demand PlanMAP Material Availability Plan OR Mobile Attainment Plan (used by Marketing Ops to outline the volumes we want to ship from a revenue standpoint)MAS Material Availbility Split - HP internal term to refer to our tool/process to support material availability visibility to the regionsMCD Mobile Computing Division (pre-merger HP Mobile Computing Division)MDL Module - is a MCD feature naming convention for Floppy Disk Drive or Optical Disk DriveMF Marketing ForecastMIR Mail In RebateMIT Multimedia Integration TestMOH Manufacturing OverheadMP Mass ProductionMR Manufacturing Release (PLC milestone - beginning of volume production)MRD Marketing Requirements DocumentMRP Materials Requirement PlanningMSP Master Shipment PlanMTD Month to DateMV Manufacturing ValidationNA Another name for North America COMMERCIALNACC North America Consumer Computing - refers to the NA consumer regionNAM North America RegionNB NotebookNiMH Nickel-Metal Hydride: Battery technology (boy…this is old!)NPI New Product IntroductionNRP Net Requirement PlanOCT Order Cycle TimeODD Optical Disk DriveODM Original Design ManufacturerOEM Original Equipment ManufacturerOH On-Hand (usually refers to inventory)OP Order ProcessingOPEC Oem Product data management External Collaboration for PSGOS Operating SystemOSS Outsourced serviceOT OvertimeOTS Observation Tracking SystemPCB Printed Circuit BoardPCBA Printed Ciruit Board AssemblyPDD Program Definition DocumentsPDG Product Data GenerationPDM BOM Data Warehouse System (Product Data Management) 產品資料管理系統PL Product LinePLC Product Life CyclePMC Pre-Merger CompaqPMH Pre-Merger Hewlett-PackardPMP Process Management PlanPNOP Part number on PartPO Purchase order订单pxe 網絡啟動模式POD Print On DemandTPM Total Productive Management全面生產管理POR Plan of Record (a general "roadmap" of a product that indicates estimated product forecast, features, etc.)PPMD Region: North America (Personal Information Products Manufacturing & Distribution) or BPN (see above)PRISM Preinstall Reengineering Initiative of Software Manufacturing PSDA Region: Asia PacificPSDE Region: EuropePSG Personal Systems GroupPTRPTT Post, Telegraph and Telephone AuthorityPV Product ValidationPWSP Preliminary Weekly Shipping PlanQBR Quarterly Business ReviewR10 SCITS Material Availability report (is at subassembly level)R11 SCITS Open Orders at the ODMR12 SCITS Shipments from the factoryR16 SCITS Factory BOMR5 SCITS Inventory reportRACDRACD Region Applicatioin CDRAD Reseller Arrival DatesRAM Random Access MemoryRAR Regional Allocation RulesRASRCD Recovery Compact Disc (Includes Windows, etc.)RCTO Regional Configure to Order - describes the SC postponement model where regionally-managed factories configure notebook unitsRDP Regional Demand PlanRFS Required for SetupRICAR Regional Inventory Cost Allocation Rules (used for allocating inventory costs back to the regions)RMN Regulatory Model NumberRMA Return(ed) Material AuthorizationROW Rest of WorldRQM Release Qual MatrixRSBT Radically Simple Better Together (Marketing Value Proposition for HP products)RSL Recommended Spares ListRSN Regional Supply Netting (solution until SNP)RT MCD code name for the US retail regionRTF Read This FirstRTP Release to Production - describes an order management methodology where orders are released only to available supplySA Subassembly (is the 3rd level of the BOM) and is the level at which regional DSM occursSCBO Supply Chain Business Operations (formerly PSDE, Europe region) SCITS Supply Chain Information Transfer Standard - the standard we use to transfer data between ODM, regions and GBUSCM Support Configuration MatrixSI System IntegrationSKU Stock-Keeping Unit (HP classic uses sku to refer to a model number) SKU Store Keeping UnitSLA Service Level AgreementSMB Small-Medium BusinessSMBC Small-Medium Business and ConsumerSMI Supplier Managed InventorySMT Surface Mounted Technology (used in motherboard preparation) SNP APO Module: Supply Network PlanningSOI Supplier-Owned InventorySR Ship Release (What the delivery engineers must do before a sku can be ordered by the regions)SRP SKU Reengineering ProcessST Sell-ThroughSVTP System Validation Test PlanSWMR Software Manufacturing Release (?)TAC Transfer at Cost - often refers to units we sell internally (for new employee equipemnt setup, etc)TAT Turn Around TimeTCE Total Customer ExperienceUAT User Acceptance TestUCUDF Unit Configuration User Defined Format, pre-CompeqUI User InterfaceVAR Value-Added ResellerVCM Variable Contribution MarginVMI Vendor Managed InventoryWDP Weekly Demand Plan (the same as Weekly Shipping Plan)WIF "What-if" demand - used primarily by NACC to describe their uncommitted demand scenarioWOS Weeks of SupplyWPTR Worldwide Product Tracking Record, pre-HPWSP Weekly Shipping PlanWWF Worldwide FulfillmentWWP Worldwide PlanningWWSNRS World Wide Serial Number Repository。
英语作文-设计服务行业创新设计理念引领产品升级与改进
英语作文-设计服务行业创新设计理念引领产品升级与改进In the dynamic realm of design services, innovation is the cornerstone that drives continual product enhancement and improvement. As consumer expectations evolve and technological advancements accelerate, the design service industry faces the perpetual challenge of staying ahead through innovative design concepts.Effective innovation in design services begins with a deep understanding of customer needs and market trends. By integrating these insights, designers can proactively identify opportunities for improvement and develop creative solutions that resonate with consumers. This customer-centric approach not only enhances product functionality but also improves user experience, setting a solid foundation for sustained market competitiveness.Moreover, embracing technological advancements plays a pivotal role in shaping the future of design services. Technologies such as artificial intelligence, augmented reality, and advanced modeling software empower designers to explore new possibilities and streamline the design process. For instance, AI algorithms can analyze user data to predict design preferences, while augmented reality enables clients to visualize prototypes in real-world settings, facilitating more informed decision-making and accelerating product development cycles.Furthermore, sustainability has emerged as a crucial consideration in modern design practices. By adopting eco-friendly materials, implementing energy-efficient manufacturing processes, and promoting recyclability, design services can minimize environmental impact and align with global sustainability goals. This eco-conscious approach not only meets regulatory requirements but also resonates with environmentally aware consumers, enhancing brand reputation and fostering long-term customer loyalty.Collaboration across disciplines is another catalyst for innovation in the design service industry. By fostering partnerships with experts in diverse fields such asengineering, psychology, and material science, designers can leverage cross-disciplinary insights to tackle complex challenges and push the boundaries of traditional design paradigms. Such collaborative efforts often result in breakthrough innovations that address multifaceted consumer needs and preferences.Moreover, continuous learning and skill development are essential for design professionals to stay abreast of industry trends and evolving technologies. Ongoing education programs, workshops, and professional certifications enable designers to expand their knowledge base, acquire new skills, and embrace emerging design methodologies. This commitment to learning not only enhances individual competencies but also cultivates a culture of innovation within design firms, driving collective progress and excellence.In conclusion, the design service industry is undergoing a transformative evolution fueled by innovative design concepts. By prioritizing customer insights, embracing technological advancements, championing sustainability, fostering collaboration, and committing to continuous learning, design services can effectively lead product upgrades and improvements. This proactive approach not only positions companies as market leaders but also ensures that they remain agile and responsive in an increasingly competitive landscape. As the industry continues to evolve, the relentless pursuit of innovation will undoubtedly redefine the future of design services, shaping experiences and exceeding expectations in profound ways.。
Creo 中常用术语缩写的说明信息
文档- CS72633文档详细信息标题有关Pro/ENGINEER 和Creo 中常用术语缩写的说明信息说明∙有关Pro/ENGINEER 和Creo 中常用术语缩写的说明信息∙ Glossary abbreviates detail explanation∙例如 AFX, B-rep, CMM, FMX, HDIC, IMM, MBD, PCX, PMI, WEDM等等适用于∙Pro/ENGINEER 所有版本∙Creo Elements/Pro 所有版本∙Creo Parametric 所有版本原因解决方案ESR External Simplified Representation 外部简化表示FAO Fatigue Advisor Option 疲劳分析顾问FRT Feature Recognition Tool 特征识别工具FEM Finite Element Mode 有限元模式FMX Flexiable Modeling Extension 柔性建模扩展F-rep or FREP Facet RepresentationGCRI GRANITE-based Cross-ReleaseInteroperabilityGRANITE 的跨版本互操作性GD&T Geometric Dimensions and Tolerances 几何尺寸和公差GEA Geometric Element Analysis 几何元素分析GEM Geometric Element Modeling 几何元素建模GEO Geometric Element Optimization 几何元素优化GTOL Geometric Tolerance 几何公差GUI Graphical User Interface 图形用户界面HDIC Heterogeneous Design In ContextHeterogeneous Design In ContextHPGL Hewlett-Packard Graphics LanguageIDD Imported Data DoctorIDF Intermediate Data FormatIGES Initial Graphics Exchange SpecificationIMM Injection Molding Machine 注射成型机ISDX Interactive Surface Design Extension 交互式曲面LCS Local Coordinate System 局部坐标系LDA Large Displacement Analyse 大变形分析LMX Legacy Migration Extension 继承迁移扩展NC Numerical Control 数字控制NURBS Non-uniform Rational Basis SplineMAX Manikin Analysis ExtensionMBD Model Based DefinitionMDO Mechanism Dynamics Option 机构动态扩展MDX Mechanism Design Extension 机构设计扩展MPA Multi-Pass Adaptive 多通道自适应OIT Order Independent TransparencyPAX Plastic Advisor Extension 塑料顾问扩展PCB Printed Circuit Board 印刷电路板。
掌握扎实的基础知识的重要性英文作文
掌握扎实的基础知识的重要性英文作文全文共3篇示例,供读者参考篇1The Importance of Mastering Solid Foundation KnowledgeIn any field of study or profession, having a strong foundation of knowledge is essential for success and growth. This is especially true in today's rapidly changing and competitive world, where the ability to adapt and learn new skills is crucial. Whether you are a student, a professional, or someone seeking personal development, mastering solid foundation knowledge is key to achieving your goals and advancing in your chosen path.First and foremost, a solid foundation of knowledge provides a framework for further learning and understanding. Just like a building needs a strong foundation to support its structure, having a strong base of knowledge allows you to build upon it with more advanced concepts and skills. Without a solid foundation, you may struggle to grasp complex ideas and make connections between different areas of knowledge.Furthermore, mastering basic concepts and principles helps you develop critical thinking and problem-solving skills. When you have a deep understanding of fundamental principles, you are better equipped to analyze and solve problems in creative and innovative ways. This ability to think critically and approach problems from different angles is highly valued in any profession and can set you apart from others.In addition, having a solid foundation of knowledge enables you to communicate effectively and collaborate with others. When you are well-versed in the basics of your field, you can engage in meaningful discussions, exchange ideas, and work together to achieve common goals. Effective communication and collaboration are key skills in today's interconnected world and can greatly enhance your personal and professional relationships.Moreover, mastering solid foundation knowledge can give you a competitive edge in the job market. Employers value candidates who have a strong understanding of the fundamentals of their field and can apply their knowledge in practical settings. By demonstrating your expertise in basic concepts and principles, you can showcase your potential for growth and success in your chosen career path.Finally, mastering solid foundation knowledge is essential for lifelong learning and personal development. In today'sfast-paced world, new technologies, trends, and ideas emerge constantly, and it is crucial to stay updated and adapt to change. By building a solid foundation of knowledge, you can create a solid base from which to explore new areas of interest, expand your skills, and continue your journey of learning and growth.In conclusion, mastering solid foundation knowledge is essential for success and growth in any field of study or profession. By developing a deep understanding of basic concepts and principles, you can build a framework for further learning, develop critical thinking skills, communicate effectively, and gain a competitive edge in the job market. Moreover, having a strong foundation of knowledge empowers you to adapt to change, embrace new challenges, and continue your journey of lifelong learning and personal development. So, invest in mastering solid foundation knowledge today and pave the way for a brighter and more fulfilling future.篇2The Importance of Mastering Solid Basic KnowledgeIntroductionIn today's fast-paced and competitive world, having a strong foundation of basic knowledge is crucial for success. Whether in academics, professional life, or personal development, a solid understanding of fundamental concepts is essential. In this essay, we will explore the significance of mastering basic knowledge and how it can positively impact various aspects of our lives.AcademicsIn the field of academics, possessing a solid grasp of foundational concepts is essential for building upon higher-level skills and knowledge. Subjects such as mathematics, language arts, and science all rely on a strong understanding of basic principles. Without a firm foundation, students may struggle to grasp more complex topics and may fall behind their peers. By mastering basic knowledge early on, students can set themselves up for success in their academic pursuits.Professional LifeIn the professional world, having a strong foundation of basic knowledge can open up a world of opportunities. Employers value employees who possess a deep understanding of core concepts in their field, as it demonstrates their dedication and competence. Whether in STEM fields, humanities, orbusiness, having a solid base of knowledge can help individuals excel in their careers and stand out among their colleagues.Personal DevelopmentBeyond academics and professional life, mastering basic knowledge can also enrich one's personal development. Whether it's understanding the fundamentals of health and nutrition, financial literacy, or even basic life skills, having a strong foundation of knowledge can empower individuals to make informed decisions and lead fulfilling lives. By equipping themselves with essential knowledge, individuals can navigate the complexities of the modern world with confidence and clarity.ConclusionIn conclusion, mastering solid basic knowledge is essential for success in various aspects of life. Whether in academics, professional life, or personal development, a strong foundation of fundamental concepts can serve as a springboard for growth and achievement. By investing time and effort into acquiring and understanding basic knowledge, individuals can position themselves for success and make meaningful contributions to society.篇3The Importance of Mastering Solid FundamentalsIntroductionIn any field of study or profession, having a strong foundation of basic knowledge is essential for success. This holds true in both academic and practical contexts, as a solid understanding of core concepts forms the basis upon which more advanced learning and skills can be built. In this essay, we will explore the importance of mastering solid fundamentals in various areas, and why it is crucial for individuals to invest time and effort in acquiring and refining their basic knowledge.Importance in EducationIn the field of education, the significance of mastering solid fundamentals cannot be overstated. A student who has a thorough grasp of basic concepts in subjects such as mathematics, science, language, and history is better equipped to tackle more complex topics and challenges. For example, in mathematics, understanding basic arithmetic operations, fractions, and algebraic equations is crucial for solvinghigher-level problems in calculus and trigonometry. Similarly, in science, grasping foundational principles such as the laws ofphysics or the scientific method is essential for conducting experiments and drawing valid conclusions.Moreover, having a strong foundation in basic knowledge not only enables students to excel in their academic endeavors but also sets them up for success in their future careers. Employers often value candidates who possess a solid understanding of fundamental concepts in their respective fields, as these individuals are better equipped to adapt to new challenges and apply their knowledge in practical settings.Importance in Professional DevelopmentIn the professional world, the importance of mastering solid basics extends beyond education and into various industries and occupations. For instance, in the field of software development, having a thorough understanding of programming languages, algorithms, and data structures is essential for building robust and efficient applications. Without a solid foundation in these fundamental concepts, developers may struggle to write clean and maintainable code, leading to errors and inefficiencies in their projects.Similarly, in fields such as finance, engineering, and healthcare, professionals must possess a strong grasp of basic principles and techniques to perform their jobs effectively. Forexample, a financial analyst who lacks knowledge of accounting principles and financial markets may struggle to make accurate projections or investment decisions. Likewise, an engineer who is unfamiliar with fundamental concepts in mechanics or thermodynamics may struggle to design and optimize complex systems.Overall, mastering solid fundamentals in one's chosen field is critical for professional growth and success. By continually refining and expanding their basic knowledge, individuals can stay ahead of the curve and remain competitive in today's rapidly changing job market.Practical BenefitsAside from the academic and professional advantages of mastering solid fundamentals, there are also practical benefits to be gained from having a strong foundation of basic knowledge. For example, individuals who possess a solid understanding of personal finance principles are better equipped to manage their money, invest wisely, and plan for their future. Similarly, individuals who are proficient in basic cooking techniques and nutrition principles can prepare healthy and delicious meals for themselves and their families.Furthermore, having a solid grasp of fundamental concepts in areas such as communication, problem-solving, and critical thinking can also enhance one's everyday life. By honing these essential skills, individuals can navigate social interactions, resolve conflicts, and make informed decisions in various aspects of their personal and professional lives.ConclusionIn conclusion, mastering solid fundamentals is essential for success in education, professional development, and everyday living. By investing time and effort in acquiring and refining basic knowledge, individuals can build a strong foundation upon which to develop more advanced skills and expertise. Whether in academia, the workplace, or daily life, possessing a thorough understanding of core concepts is crucial for achieving personal growth and fulfillment. As such, it is imperative for individuals to prioritize the mastery of solid fundamentals in their quest for excellence and success.。
双语试题--管理信息系统
Management Information System 课程号:课序号:开课系:信息工程学院20 Questions 1Select the best answer for each of the following unrelated items。
Answer each of these items in your examination booklet by circling the number of your choice. If more than one answer is given for an item, that item will not be marked. Incorrect answers will be marked as zero。
Marks will not be awarded for explanations。
Note:2 marks eacha.Which of the following is a method for considering a collection of IS projects in termsof their potential risks and benefits as a means of selecting which projects to undertake?1) Scoring models2) Strategic IS planning3) Scenario planning4) Portfolio analysisb。
Which of the following is a key challenge in managing data?1) Determining appropriate field widths2) Choosing a DBMS3) Managing data security4) Distinguishing between data and informationc.Which of the following is a tangible benefit?1) More timely information2) Higher client satisfaction3) Reduced facility costs4) Increased organizational learningd。
access创建数据库的方法和流程
access创建数据库的方法和流程1.首先打开Access数据库管理软件。
First, open the Access database management software.2.在“文件”菜单中选择“新建”选项。
Select the "New" option in the "File" menu.3.在新建数据库对话框中选择新建数据库的保存位置,并填写数据库名称。
In the new database dialog, choose the location to save the new database and enter the database name.4.点击“创建”按钮,开始创建新数据库。
Click the "Create" button to start creating a new database.5.在数据库中添加数据表和字段。
Add data tables and fields in the database.6.选择“创建”选项卡,然后点击“表格设计”按钮。
Select the "Create" tab, and then click the "Design View" button.7.在表格设计视图中添加字段的名称和数据类型。
Add field names and data types in the design view of the table.8.设定字段的属性,如主键、唯一值等。
Set the properties of the fields, such as primary key, unique value, etc.9.点击“保存”按钮保存数据表设计。
Click the "Save" button to save the table design.10.添加完所有需要的数据表后,点击“保存”按钮保存数据库。
Collaborative Innovation A Viable Alternative to Market
Jean Hartley is professor of public leadership in the Department of Public Leadership and Social Enterprise at the Open University Business School. Her research interests are in public leadership (political, managerial, professional, and community) and innovation in govern-ance and public services, including both institutional perspectives and employee experiences of innovation and other forms of organizational change.E-mail: jean.hartley@ Eva Sørensen is professor of public administration in the Department of Society and Globalization at Roskilde University. She is currently director of a large research project on public innovation and vice direc-tor of the Centre of Democratic Network Governance. Her main research interests are the impact of new forms of governance on the provision of effective, democratic, and innovative public governance. A special research interest is the study of how new forms of governance challenge traditional role perceptions among citizens, public employees, and politicians.E-mail: eva@ruc.dkJacob Torfi ng is professor of politics and institutions in the Department of Society and Globalization, Roskilde University. He is director of the Centre for Democratic Network Governance and vice director of a strategic research project on collaborative innovation in the public sector. His research interests include public governance reforms, governance networks, democracy, and public innovativon. He recently published Interactive Governance: Advancing the Paradigm (Oxford University Press), coauthored with Jon Pierre, Guy Peters, and Eva Sørensen.E-mail: jtor@ruc.dkCollaborative Innovation: A Viable Alternative to Market Competition and Organizational Entrepreneurship 821Public Administration Review , Vol. 73, Iss. 6, pp. 821–830. © 2013 by The American Society for Public Administration. DOI: 10.1111/puar.12136.Jean HartleyOpen University Business School, United KingdomEva Sørensen Jacob Torfi ngRoskilde University, DenmarkTh ere are growing pressures for the public sector to be more innovative but considerable disagreement about how to achieve it. Th is article uses institutional and organizational analysis to compare three major public innovation strategies. Th e article confronts the myth that the market-driven private sector is more innovative than the public sector by showing that both sectors have a number of drivers of as well as barriers to innovation, some of which are similar, while others are sector specifi c. Th e article then systematically analyzes three strategies for innovation: New Public Management, which empha-sizes market competition; the neo-Weberian state, which emphasizes organizational entrepreneurship; and collabo-rative governance, which emphasizes multiactor engage-ment across organizations in the private, public, and nonprofi t sectors. Th e authors conclude that the choice of strategies for enhancing public innovation is contingent rather than absolute. Some contingencies for each strategy are outlined.There is growing demand and pressure for thepublic sector to become more innovative(Borins 2008; Osborne and Brown 2011)in response to rising citizen expectations, dire fi scalconstraints, and a number of “wicked problems”that, because of their complexity, cannot be solvedby standard solutions or by increasing the fundingof existing mechanisms. While the eff ects of publicinnovation are sometimes evaluated diff erently bypublic and private stakeholders and may involve sig-nifi cant trade-off s (Abrahamson 1991; Hartley 2005; Tidd and Bessant 2009), there is a growing percep-tion that innovation can contribute to increased pro-ductivity, service improvement, and problem-solving capacity in the public sector, though not all innova-tions are eff ective or involve improvement. However, there seems to be considerable disagreement about how to spur and sustain public innovation. Th erefore, in order to better understand the drivers of as well as the barriers to public innovation, this article endeav-ors to compare three diff erent public innovation strat-egies in order to show that although market-drivenand bureaucratic innovation strategies have important qualities, a collaborative approach to public innova-tion seems to have some comparative advantages in certain contexts.In the last two decades, proponents of New Public Management (NPM) reforms have claimed that the public sector should imitate or learn from the private sector. Th e public sector should become more inno-vative, fl exible, and effi cient by introducing market-based competition and private sector management techniques (Osborne and Gaebler 1992). Critics claim that the marketization of the public sector has not helped make the public sector more innovative. Th ey suggest instead that public innovation should be enhanced by means of strengthening organiza-tional entrepreneurship in neo-Weberian bureauc-racies through a combination of transformational leadership (Bass and Riggio 2006), institutional and organizational integration (Christensen and Lægreid 2010), trust-based management (Nyhan 2000), and increased responsiveness toward the demands from citizens and users of specifi c public services (Pollitt and Bouckaert 2004). Although these strategic rec-ommendations, under the right conditions, may help spur public innovation, we argue that the dichoto-mous opposition between market-based competition and bureaucratic reform is an unfortunate and false choice. Unfortunate because both strategies tend to favor “in-house” innovation (i.e., by managers and staff ) and thus fail to reap the fruits of inter-organizational, intersectoral, and open innovation. False because a collaborative approach to innova-tion highlights the role of multiactor engagement in informing the understanding of the problem to be addressed, as well as in creating and implement-ing innovation and garnering support and owner-ship of the problem and the innovation. However, although collaborative innovation seems to besupported by new trends associated with New PublicGovernance (Osborne 2010), there are both merits and limitations of this particular strategy, and it may require the development of new kinds of innovation management.Collaborative Innovation: A Viable Alternative to MarketCompetition and Organizational Entrepreneurship822 Public Administration Review • November | December 2013Th e article focuses on innovation in the public sector, but we do not defi ne the public sector in legal terms as a public realm separated from civil society and the economy. Th e public sector is defi ned here in terms of a collective eff ort to produce and deliver public value that is authorized or sponsored by federal, state, provincial, or local government. Innovation in the public sector is still undertheorized and under-researched and is only just emerging from a period of being dominated by studies from the private sector (Hartley 2013; Moore 2005). Th is explains why we need to focus on the specifi c conditions and strategies for public sector innovation.The Myth of Private Sector Superiority in Innovation Th e myth that the private sector is much more innovative than the public sector is widespread. It stems from the fact that much of the generic innovation literature is “context blind,” assuming the existence of fi rms, markets, and competition as a precondition of innovation (Hartley 2013; Lynn 1997). Th e centrality of markets in theories of private sector innovation has created a particular, though inaccurate, form of reasoning. Innovation enables fi rms to survive in competitive markets (Johnson 2008; Schumpeter 1950); public organizations do not operate in markets; ergo, the public sector lacks the ability to produce innovation. Th e further apparent logical consequence is to try to make the public sector more like the private sector in structure, culture, and management.It is futile to try to assess whether there is “more” innovation in one sector or another. Measures are indirect, approximate, and incom-mensurate across diff erent innovation dimensions and organizations. Cross-sector comparison may also hide important subsector varia-tion, including variation across types of services, diff erent organiza-tions, and across levels of government (the last, most notably, in countries such as the United States). However, a comparison of the institutional conditions for innovation in the public and private sectors is illuminating and tends to undermine the myth of private sector superiority in innovation.Th e institutional conditions for private sector innovation bearexamination. Markets are institutional orders based on rules, norms, and regulations that aim to encourage free competition among buy-ers and sellers. Competition creates a clear and undeniable incentive for fi rms to innovate because failure to do so will tend to eliminate them from the market. However, while market-based competition can drive innovation, it also can act as a barrier. Teece (1992) shows that market competition tends to generate both too little and tooTh e argument proceeds in the following way: First, we confront the myth that the market-driven private sector is more innovative than the public sector by showing that both sectors are characterized by a number of drivers of as well as barriers to innovation, some of which are the same, while others are sector specifi c. Th ese insights are used to critically scrutinize the extent to which NPM can enhance public innovation. After identifying the drivers and limitations of the market competition approach of NPM, we briefl y explore the drivers and limitations of the second innovation strategy, which is based on reforming public bureaucracies in order to enhance organizational entrepreneurship. Finally, we analyze the comparative merits of the collaborative approach to public innovation and discuss how the drivers and barriers here might be harnessed by developing new kinds of innovation leadership and management. In the conclusion, we emphasize that this consideration of the drivers and barriers of these three institutional modes indicates that the choice between diff erent strategies for enhancing public innovation is contingent rather than absolute, and we outline some of the contingencies for each strategy. Before proceeding with the argument, we provide a brief outline of our theoretical starting point and defi ne some of the key concepts.An Institutional Approach to Public Innovation Th is article draws on institutional and organizational theories in public administration and governance in order to answer the increasingly important question of how to understand, analyze, and enhance public innovation. Institutional theory asserts that situated actors act within an institutional framework of rules, norms, knowl-edge, and sedimented discourses (March and Olsen 1989; Peters 2011). Th e institutional conditions are reproduced in the course of action, but they may also be modifi ed or transformed by inten-tional or nonintentional actions that involve collaboration based on resource interdependency as well as confl icts rooted in diff erent interests, interpretations, and worldviews. Th e institutional perspec-tive on innovation is important because it draws attention to the organizational and cultural conditions that might hamper or drive social and political actors aiming to produce innovative solutions.Th ere is no agreement in the literature about how to defi ne the con-cept of innovation, but in order to avoid confl ating innovation with creativity, we insist that innovation not only involves the generation but also the practical realization of new, creative ideas (Damanpour 1991; Van de Ven 1986). Hence, innovation can be defi ned as a complex and iterative process through which problems are defi ned; new ideas are developed and combined; prototypes and pilots are designed, tested, and redesigned; and new solutions are imple-mented, diff used, and problematized. Figure 1 depicts the diff erent analytical phases of the innovation cycle.Innovation involves change, but not all kinds of change qualify as innovation. Hence, we reserve the notion of innovation for those forms of change that break with the established practices and mind-sets of an organization or organizational fi eld to create something new (Damanpour 1991), so that innovation is a step change or a disruptive change (Lynn 1997; Osborne and Brown 2011). Innovation can be either radical or incremental, and it can be based on either the genera-tion of an original invention or the adoption and adaptation of others’ innovations (Damanpour and Schneider 2008). Hence, it is not the source of innovation but the local site of implementation that deter-mines whether something is an innovation (Roberts and King 1996).Figure 1The Cycle of InnovationTestingDiffusionProblem definitionIdea generationImplementationCollaborative Innovation: A Viable Alternative to Market Competition and Organizational Entrepreneurship 823diff erent publics, on the one hand, and actual service provision, on the other, as important drivers (e.g., Albury 2005). In some cases, the drive to innovate comes from public employees with profes-sional training who seek to advance their professional values and aspirations, for example, by inventing new methods for treating patients or teaching children to read and write. Nevertheless, the presence of strong professions in the public sector may also act as a barrier to innovation (Ferlie et al. 2005). Th e motivation for innovation in the public sector comes not only from managers and staff within the organization (Borins 1998) but also from elected and appointed politicians, who wish to change society (Hartley 2005; Polsby 1984). Citizens and civic groups, as well as users of public services cast in the role of “customers,” can also trigger public innovation by exiting or giving voice to their views and demands (Hirschman 1970; Osborne, Chew, and McLaughlin 2008) and/or by engaging in the co-creation and coproduction of public services (Alford 2009; Pestoff 2012).When it comes to the crucial issue of size, the public sector has a clear advantage. Research shows that large organizations, contrary to common opinion, tend to be better at innovation through all stages to implementation and diff usion (Damanpour 1992; Hage and Aiken 1967). Large organizations have more resources to invest in innovation and are capable of absorbing the costs of innovation failure. Th is is true across sectors, and there are many more large organizations in the public sector than in the private sector. In addition, the institutional, political, and normative pres-sures to diffuse innovations in order to try to improve services (Bate and Robert 2003; Rashman and Hartley 2002) and public value(Benington and Moore 2011) is another driver that can be promi-nent in the public sector.Overall, the comparison of the drivers and barriers in each sector shows that the two sectors are facing both some of the same, as well as some sector-specifi c drivers and barriers (Halvorsen et al. 2005). In both sectors, innovation can be driven by competition, although competition in the public sector in most cases is based on the desire for growth and reputation rather than market pressures. If public innovation is less motivated by market-based competition, thereappear to be other sector-specifi c drivers, some of which tend to be more prevalent in the public sector than in the private sector. As for the barriers, both sectors confront a number of innovation barriers deriving from bureaucratic organizational form. Market competi-tion, however, may act as a sector-specifi c barrier in private mar-kets, whereas other sector-specifi c barriers, such as the presence of risk-aversive political decision makers, tend to hamper innovation inthe public sector. In sum, the myth of private sector superiority in innovation—which is based on the apparent syllogism that becausethe public sector is not subject to market competition, it is not innovative—appears to be completely unsustained.The Contributions and Limits of NPM as a Viable Innovation StrategyTh e recognition that both the public and private sectors have particular drivers and barriers in innovation helps reveal why NPM reforms that introduce private sector governance and management much innovation. Th ere can be too little innovation because fi rms are unable to eff ectively exclude other fi rms from exploiting the innovations that they have developed (the “free-riding” problem). However, competition also tends to produce too much innova-tion because fi rms overinvest in the early stages of innovation to be fi rst at the patent offi ce but consequently deplete their exploitation opportunities and fail at the point when the serious development work begins (the “overbidding” problem).Despite its limitations, competition clearly motivates organizations in market environments to innovate their products, production methods, and marketing techniques. However, we should not forget that many private fi rms operating in competitive markets are organ-ized as bureaucracies, which is an organizational form that acts as a barrier to innovation (Burns and Stalker 1961; Halvorsen et al. 2005). Th erefore, organizational entrepreneurs in private business will tend to be hampered by hierarchical decision making, risk-aversive leaders, departmentalization, infl exible rules and routines,professional boundaries, and institutional seclusion. In this sense,there are similarities with many public organizations. Rainey andChun (2005) conclude that there is mixed evidence as to whetherpublic or private organizations are morebureaucratic, and where diff erences are found,they are not large. So, competition may createpressures for fi rms to innovate, but it does notprovide a specifi c method for developing and implementing innovation.T urning to the institutional conditions forpublic sector innovation, it appears that themyth of an inertial public sector can be problematized by examining some of the drivers of and barriers to public innovation. Th e barriers to innovation in the public sector have been well rehearsed, evenover-rehearsed (Halvorsen et al. 2005). Public organizations have no clear fi nancial bottom line to use in measuring the value of innova-tion, and the public value of innovations is hard to assess. Publicorganizations and partnerships often lack fi nancial incentives toinnovate and are rarely allowed to keep the cost savings from inno-vations. Public organizations develop innovations in the presump-tion of openness and transparency and often with contested goalsand outcomes, magnifi ed by media interest, which has enhancedthe view that public organizations are risk averse in their innovation decisions (Brown and Osborne 2013). Finally, public organizationsare governed by politicians who have to take account of multiplestakeholders in innovation while knowing that innovation failuremay be exploited by the political opposition.Arguably, however, the barriers to public sector innovation havebeen overplayed, mainly from a private sector perspective, while the drivers are underacknowledged. Despite recent attempts to createpublic quasi markets, market-based competition still carries limited weight as a motivating factor, and there are other drivers of inno-vation. Some lie in the organization and some in its institutionalcontext. Koch and Hauknes (2005) note that people in both publicand private sectors may be motivated by a range of reasons beyondprofi t, including problem solving; the propagation of a policy, idea, or rationality; the desire for growth; and reputation (both per-sonal and organizational). Others perceive the attempt to improveperformance and address gaps between needs and aspirations ofCompetition may create pres-sures for fi rms to innovate, but it does not provide a specifi cmethod for developing andimplementing innovation.824 Public Administration Review • November | December 2013systematic monitoring of results enables local managers to identify ineffi ciencies, performance gaps, and new opportunities that are sometimes addressed through innovation (Walker, Damanpour, and Devece 2011), although frequently, public managers are content with pursuing rationalization through Lean techniques that neither produce innovation nor user value (Radnor and Osborne 2013). Hence, few commentators on performance management have linked it empirically to the generation, implementation, and diff usion of innovation despite the salience of innovation in NPM discourse.Although NPM has spurred some public innovation, the gains have been accompanied by some clear drawbacks, as NPM unin-tentionally has introduced some serious barriers to innovation. Competition, which in the public sector has taken the form of government-controlled quasi markets, is a double-edged sword. While it may drive innovation, it can also discourage service provid-ers from sharing knowledge and engaging in interorganizational learning, both of which, along with trust, are central to developing innovative solutions to joint problems (Rashman, Withers, and Hartley 2009; Teece 1992).Moreover, NPM has introduced a number of barriers to innovation that are similar to those found in traditional public administration. First, the unrelenting focus on performance often accelerates the production of the kind of detailed bureaucratic rules that NPM was meant to eliminate. Th e creation of new rules is often the standard response of elected politicians and executive administrative leaders to cases of severe underperformance of public services publicized in the mass media. Th e concern with risk in public service produc-tion also encourages middle managers to extend and develop rules in order to maintain standards and avoid risk (Brown and Osborne 2013). Th e incessant proliferation of rules keeps public employees in a straitjacket, which inhibits innovation.Second, accountability through managerial control is a key character-istic of NPM and is increasingly obtained through a self-accelerating system of performance measurement that aims to eliminate oppor-tunistic behavior (Power 1997). Th e measure-ment of particular processes and output targetstends to hamper innovation because innova-tive solutions may produce diff erent kinds of outputs through entirely new processes that may not initially have measurement data. In addition, new ways of working will oftencause an initial performance dip, for both psychological and operational reasons (Hartley2011). Th e use of evidence-based solutions is an integral part of the new performance man-agement system. It tends to favor the adoption of “best practices” but creates the risk that the “best practice” trumpsthe development of the “next practice” (Albury 2005). Third, the structural divisions of labor in public organizations (a signifi cant barrier to innovation) have been strengthened by NPM’s recom-mendations of arm’s-length governance that separates “steering” from“rowing” (Osborne and Gaebler 1992) and creates special-purpose agencies (Koppenjan and Klijn 2004).Finally, the fundamental problem of NPM is its inherent tendency to give priority to the enhancement of effi ciency in the production practices into the public sector may not result in noticeable growth in public innovation (Hartley 2005; Hess and Adams 2007;Newman, Raine, and Skelcher 2001). To assume that public innova-tion will fl ourish because of the creation of quasi markets and the adoption of new forms of strategic leadership and performance management overlooks the fact that the private sector is also prey to innovation barriers. However, this argument does not mean that enhanced competition in quasi markets and the adoption of new management practices have not contributed at all to public innovation. NPM has helped spur public innovation in some areas (Lubienski 2009; Parker, Ryan, and Brown 2000), but there has been insuffi cient refl ection on the innovation barriers associated with competition and managerialism. In order to develop a more nuanced view of the impact of NPM on public innovation, we fi rst look at the positive eff ects of NPM and then discuss some of the barriers.NPM reforms have contributed to enhancing public sector innova-tion in at least two ways. First, NPM has enhanced the competition for public service contracts among public, private, and nonprofi t providers. While sometimes spurring a “race to the bottom,” this marketization strategy has forced both public and private service providers to “do more with less” and even sometimes to innovate the form, content, and delivery of public services in order to win con-tracts and ensure contract renewal (Sørensen 2012). Because service providers are competing not only for contracts but also for citizens now cast in the role as consumers (e.g., users of public services with exit options), public service organizations have become more demand driven in some service areas, and this has spurred user-driven innovation (Jæger 2013). Service providers aim to attract as many users of public services as possible where they are fi nanced by direct payments from service users, by government vouchers, or payment by results.Second, NPM has enhanced public innovation by infl uencing themanagement culture in the public sector. Th e traditional bureau-cratic emphasis on legal regulation through lawmaking and rulefollowing has been supplemented by a newemphasis on strategic management thatfocuses on performance and results (Bryson,Berry, and Yang 2010). Here, the role ofsenior managers is to support elected politi-cians in formulating the overall goals andtargets and in defi ning the legal, economic, and discursive framework for public regula-tion and service production. Ideally, opera-tional managers in devolved agencies deployrules, resources, and employees fl exibly andeffi ciently in order to achieve predefi ned goalsand targets and provide high-quality services in an effi cient manner. Th is system of “regulated self-regulation” (Sørensen and T riantafi llou 2009) tends, at least in theory, to create more room for localexperimentation and service development than traditional forms ofbureaucratic service production. However, in practice, the room for local self-regulation is limited by the development of an elaborateand rather bureaucratic system of performance management basedon large numbers of measures, targets, indicators, and benchmarks,which creates gaming behaviors, distorting superordinate goals(e.g., Andrews et al. 2008; Hood 2006). On the other hand, theTh e measurement of particular processes and output targets tends to hamper innovation because innovative solutions may produce diff erent kinds of outputs through entirely newprocesses that may not initially have measurement data.Collaborative Innovation: A Viable Alternative to Market Competition and Organizational Entrepreneurship 825simplifi es formal rules and performance measures and encourages trust and engagement with staff so that they apply their professional knowledge and skills to innovations that create public value (Nyhan 2000). A fourth set of reforms aims to make the public sector more responsive to users’ and citizens’ demands and aspirations (Pollitt and Bouckaert 2004). Organizational entrepreneurs can use diff er-ent techniques, including digital ones, to discover the acknowledged and unacknowledged needs of citizens. Th e list could be contin-ued, but the argument is clear: a neo-Weberian public sector can support and sustain organizational entrepreneurship that enhances innovation.Th e strategy of innovation in a neo-Weberian state provides a promising alternative to NPM that addresses some of the weak-nesses of the latter. However, while it is more outwardly focused, with its interest in citizens, than NPM, both view innovation as predominantly an “in-house” activity. Whereas NPM celebrates public and private contractors operating within quasi markets as the true innovation heroes, the neo-Weberian state praises the organiza-tional entrepreneurship of public leaders, managers, and employees operating within public organizations as the primary source of innovation. Both of these innovation strategies fail to realize and mobilize the huge innovation potential that lies in extraorganiza-tional innovation.Toward a Viable Collaborative Approach to Public Innovation Th ere is growing evidence that collaboration can spur public inno-vation (Bommert 2010; Eggers and Singh 2009; Roberts and King 1996). Th eories of collaborative innovation in the public sector derive both from theories of network governance, which emphasize the role of collaborative networks in fi nding innovative solutions to complex problems (Koppenjan and Klijn 2004; Powell, Koput, and Smith-Doerr 1996), and from theories of learning that conceptual-ize step change as occurring through interorganizational interaction and collaborative processes (Engeström 2008; Lave and Wenger 1991). Th eories of collaborative innovation also echo insights from management theories about private sector innovation, where it focuses on “social innovation” (Phills, Diegelmeier, and Miller 2008), “co-creation” (Prahalad and Ramaswamy 2004), and “open innovation” (Chesbrough 2003).Innovation is most often a result of interaction between actors from diff erent levels and organizations. A meta-analysis of scien-tifi c studies of public and private innovation reveals that internal and external communication and collaboration have positive eff ects on innovation (Damanpour 1991). Analysis of the U.S. public innovations submitted to a national award program showed that 60 percent were created through interorganizational collabo-ration (Borins 2001). Finally, national surveys and case studies from the United Kingdom demonstrate that local authorities with greater collaboration within and across organizations and in peer networks are more innovative than those without (Downe, Hartley, and Rashman 2004; Newman, Raine, and Skelcher 2001).Th e empirical evidence is supported by arguments about how col-laboration can strengthen all stages of innovation (Eggers and Singh 2009; Sørensen and Torfi ng 2011). Th e defi nition and framing ofof standardized services over the enhancement of eff ectiveness of public policies and service systems. “Lean” is an example of an incremental methodology to achieve effi ciencies in public service delivery. Although Lean methodology is not entirely suited to public services, in part because it does not suffi ciently take account of the integrated service systems that can span several organizations along with service users (Osborne, Radnor, and Nasi 2013; Radnor and Osborne 2013), it is widely used in the public sector. Th e problem, at least from an innovation perspective, is that Lean is primarily a tool for rationalizing work processes in relation to pre-defi ned service and does not attempt to produce innovative services or create entirely new service systems by reframing problems or goals.Overall, this institutional and organizational analysis shows that NPM has a number of features that can spur public innovation, but also that the positive impact of NPM on innovation is undermined by some unintended consequences of competition, performance management, the focus on effi ciency more than eff ectiveness, and the focus on single services and organizations rather than service systems.Public Innovation in Neo-Weberian BureaucraciesNPM has many supporters among public choice theorists, but there is also a growing number of critics (Christensen and Lægreid 2007; Ferlie et al. 1996). Th e main critique is NPM’s focus on the mar-ketization of the public sector, which tends to overlook fundamental diff erences between public and private sectors. So, it is tempting to opt for a return to traditional forms of public bureaucracy (Du Gay 2000) or perhaps to develop a modifi ed version of public adminis-tration that unifi es traditional virtues of Weberian bureaucracy with certain elements of NPM while also adding new elements. To this end, a group of public administration scholars has started to talk about the “neo-Weberian state” (Pollitt and Bouckaert 2004). Th ere is no coherent or comprehensive doctrine delineating the precise content of the neo-Weberian state (Lynn 2008), but some central features of this institutional form have been sketched. It is a form claimed to be more capable of enhancing innovation than either traditional public administration or NPM (Drechsler and Kattell 2008–09).A key to understanding the innovation potential of the neo-Weberian state is the implicit emphasis on the organizational entrepreneurship of public leaders, managers, and professionals. Entrepreneurship is promoted by a variety of public sector reforms, such as further strengthening transformational, post-transfor-mational, and distributive leadership. Whereas transformational leadership strengthens strategic responsibility for creating substan-tial organizational change (including innovation) (Bass and Riggio 2006), post-transformational and distributive leadership strategies encourage senior leaders to share the responsibility for leading and driving change with frontline managers and employees (Parry and Bryman 2006; Spillane 2005). Another set of reforms aims to strengthen the coordination between public agencies enhanc-ing intraorganizational and interorganizational integration, both vertically and horizontally, thus countering the problems gener-ated by arm’s-length governance (Christensen and Lægreid 2010). A third set of reforms seeks to replace the control-based systems of performance management with a more trust-based system that。
比较两个公司的不同英语作文
比较两个公司的不同英语作文全文共3篇示例,供读者参考篇1Comparing Two Companies: Apple Inc. and Samsung Electronics Co.IntroductionIn today's rapidly evolving business world, it is important for companies to stay competitive and innovative in order to succeed. Two companies that have been at the forefront of the technology industry for many years are Apple Inc. and Samsung Electronics Co. Both companies are known for their cutting-edge products and services, but there are also significant differences between the two. This essay will compare and contrast Apple Inc. and Samsung Electronics Co. in terms of their history, products, marketing strategies, and corporate culture.HistoryApple Inc. was founded in 1976 by Steve Jobs, Steve Wozniak, and Ronald Wayne. The company started out as a computer manufacturer, but has since expanded to include a wide range of products such as smartphones, tablets, andsmartwatches. Apple is known for its iconic designs anduser-friendly interfaces, and has a strong brand reputation around the world.On the other hand, Samsung Electronics Co. was founded in 1969 by Lee Byung-chul. The company originally started as a trading company before venturing into electronics manufacturing in the 1970s. Samsung is now one of the largest electronics companies in the world, producing a wide range of products including smartphones, TVs, and home appliances. Samsung is known for its innovative technology and high-quality products.ProductsWhen it comes to products, both Apple and Samsung offer a wide range of devices to consumers. Apple's flagship products include the iPhone, iPad, and Macbook, which are known for their sleek design and user-friendly interface. Apple also offers a range of services such as Apple Music and iCloud, which are integrated into its devices. In recent years, Apple has also focused on expanding its services business through initiatives such as Apple Pay and Apple TV+.On the other hand, Samsung's flagship products include the Galaxy smartphone series, Galaxy Tab tablets, and Galaxy Watchsmartwatches. Samsung is known for its innovative technology, such as its Infinity Display and S Pen stylus. Samsung also offers a range of services such as Samsung Pay and Samsung Health, which are integrated into its devices. In recent years, Samsung has also focused on expanding its artificial intelligence capabilities through initiatives such as Bixby.Marketing StrategiesBoth Apple and Samsung are known for their strong marketing strategies that have helped them become global leaders in the technology industry. Apple is known for its minimalist and sleek advertising campaigns that focus on the design and functionality of its products. Apple also has a strong retail presence with its Apple Stores, which offer a unique shopping experience for customers.Samsung, on the other hand, is known for its aggressive marketing campaigns that focus on the features and technology of its products. Samsung has also invested heavily in sponsorships and endorsements, such as its partnership with the Olympic Games. Samsung also has a strong retail presence with its Samsung Experience Stores, which showcase its latest products and innovations.Corporate CultureApple and Samsung have different corporate cultures that reflect their respective histories and values. Apple is known for its focus on design and innovation, with a strong emphasis on creativity and collaboration among its employees. Apple's founder, Steve Jobs, was known for his attention to detail and perfectionism, which continues to influence the company's culture today.Samsung, on the other hand, is known for its focus on engineering and manufacturing, with a strong emphasis on efficiency and scale. Samsung's founder, Lee Byung-chul, was known for his entrepreneurial spirit and risk-taking, which continues to influence the company's culture today. Samsung is also known for its hierarchical organizational structure, which reflects its Korean roots.ConclusionIn conclusion, Apple Inc. and Samsung Electronics Co. are two of the most successful companies in the technology industry, but they have different histories, products, marketing strategies, and corporate cultures. Apple is known for its design and innovation, while Samsung is known for its technology and scale. Despite these differences, both companies have been able to succeed and thrive in a highly competitive market.Overall, Apple and Samsung both have their own strengths and weaknesses, but they have both been able to capitalize on them in order to create successful products and services that resonate with consumers around the world.篇2Comparison of Two Companies: Apple Inc. and Microsoft CorporationIntroductionIn the fast-paced technology industry, two companies stand out as leaders: Apple Inc. and Microsoft Corporation. Both companies have a long history of innovation and have a strong influence on the global market. This essay aims to compare and contrast the two companies by examining various aspects such as their history, products, business strategies, and corporate culture.HistoryApple Inc. was founded in 1976 by Steve Jobs, Steve Wozniak, and Ronald Wayne. The company initially focused on developing personal computers, such as the Apple I and Apple II. In 1984, Apple launched the Macintosh, which revolutionized the computer industry with its graphical user interface. However,Apple faced financial difficulties in the 1990s and was on the brink of bankruptcy before Steve Jobs returned as CEO in 1997. Under Jobs' leadership, Apple introduced game-changing products like the iPod, iPhone, and iPad, which propelled the company to unprecedented success.On the other hand, Microsoft Corporation was founded in 1975 by Bill Gates and Paul Allen. The company's first major success came in 1980 when it signed a contract with IBM to provide an operating system for their personal computers. Microsoft's MS-DOS became the dominant operating system for PCs, paving the way for the company's future success. In 1985, Microsoft launched Windows, which eventually became the most widely used operating system in the world. Over the years, Microsoft expanded its product portfolio to include software applications like Microsoft Office and cloud services like Azure.ProductsApple is known for its innovative and aesthetically pleasing products that offer a seamless user experience. The company's flagship products include the iPhone, iPad, Mac, and Apple Watch. Apple's devices are known for their premium build quality, sleek design, and user-friendly interfaces. In addition tohardware, Apple also offers a range of software services like iCloud, Apple Music, and the App Store.On the other hand, Microsoft is best known for its software products, particularly its Windows operating system and Microsoft Office suite. Windows remains the dominant operating system for PCs, and Microsoft Office is the most widely used productivity software in the world. In recent years, Microsoft has expanded its product offerings to include Surface tablets, Xbox gaming consoles, and cloud services like Office 365 and Azure.Business StrategiesApple's business strategy is focused on constant innovation and differentiation. The company invests heavily in research and development to create new and groundbreaking products. Apple also places a strong emphasis on marketing and branding, cultivating a loyal customer base that is willing to pay a premium for its products. Additionally, Apple has a vertically integrated business model, controlling both hardware and software development to ensure a seamless user experience.In contrast, Microsoft's business strategy revolves around collaboration and partnerships. The company has a vast ecosystem of hardware manufacturers, software developers, and service providers that contribute to its products and services.Microsoft also has a strong focus on cloud computing, with its Azure platform competing with industry leaders like Amazon Web Services and Google Cloud. Moreover, Microsoft has been investing in artificial intelligence and machine learning to drive innovation across its product portfolio.Corporate CultureApple has a reputation for its secretive and highly driven corporate culture. The company is known for its strict adherence to design excellence and product quality. Apple employees are expected to work long hours and maintain a strong commitment to the company's vision and values. Despite its demanding work environment, Apple has been ranked as one of the best places to work in the technology industry.On the other hand, Microsoft has a more open and collaborative corporate culture. The company encourages employees to share ideas and work together to solve problems. Microsoft also has a strong emphasis on diversity and inclusion, with initiatives to promote equality and create a supportive work environment for all employees. As a result, Microsoft has been recognized for its inclusive workplace culture and commitment to social responsibility.ConclusionIn conclusion, Apple Inc. and Microsoft Corporation are two of the most influential companies in the technology industry. Despite their differences in history, products, business strategies, and corporate culture, both companies have achieved remarkable success and continue to shape the future of technology. Whether it's Apple's innovative devices or Microsoft's powerful software solutions, both companies have a lasting impact on the world of technology and have set high standards for innovation and excellence.篇3Comparison of Two Companies: A Case StudyIntroductionIn today's highly competitive business world, companies are constantly striving to differentiate themselves from their competitors in order to attract more customers and achieve long-term success. In this case study, we will compare and analyze two companies from different industries - Company A, a tech startup specializing in AI technology, and Company B, a traditional manufacturing company with a focus on sustainability. By examining the key differences between these two companies in terms of their business models, strategies, corporate cultures,and customer relationships, we will gain a deeper understanding of what sets them apart and how they are able to succeed in their respective markets.Company A: Tech StartupCompany A is a tech startup that was founded five years ago with the goal of revolutionizing the AI technology industry. The company's business model is based on developing innovative AI solutions for a variety of industries, including healthcare, finance, and retail. Company A differentiates itself from its competitors by focusing on cutting-edge research and development, which allows it to stay ahead of the curve and adapt to changing market trends quickly. In addition, the company has a strong emphasis on creating a collaborative and inclusive work environment that fosters creativity and innovation among its employees.One of the key strategies that Company A employs is a customer-centric approach, where it prioritizes the needs and preferences of its clients in order to deliver personalized and value-added solutions. This has helped the company buildlong-lasting relationships with its customers and establish a strong reputation for reliability and quality. Company A also invests heavily in marketing and branding efforts to raiseawareness of its products and services and effectively communicate its unique value proposition to potential clients.Company B: Traditional Manufacturing CompanyCompany B is a traditional manufacturing company that has been in business for over 50 years and has a strong focus on sustainability and environmental responsibility. The company's primary business model is centered around producingeco-friendly products using recycled materials andenergy-efficient processes. Unlike Company A, Company B does not rely on cutting-edge technology or research and instead focuses on traditional manufacturing methods that have been proven to be effective over time.One of Company B's key strategies is its commitment to environmental sustainability, which sets it apart from its competitors in the industry. By prioritizing ethical and environmentally-friendly practices, the company has been able to attract a loyal customer base that shares its values and beliefs. Company B also emphasizes transparency and accountability in its operations, by openly communicating with stakeholders about its sustainability initiatives and progress towards achieving its goals.Comparison and AnalysisWhen comparing Company A and Company B, it is clear that there are several key differences between the two companies that shape their respective business models and strategies. Company A stands out for its focus on innovation and technology, while Company B differentiates itself through its commitment to sustainability and ethical practices. While both companies have been successful in their own right, they have followed different paths to achieve their goals and have leveraged their unique strengths to gain a competitive advantage in the market.In terms of corporate culture, Company A places a strong emphasis on collaboration and teamwork, which is evident in the way its employees work together to develop and implement new ideas. On the other hand, Company B values individual responsibility and self-reliance, which is reflected in its decentralized decision-making process and employee autonomy. These cultural differences influence the way each company operates and interacts with its employees, customers, and partners.In terms of customer relationships, Company A adopts a customer-centric approach that prioritizes the needs and preferences of its clients in order to deliver personalized andvalue-added solutions. This has helped the company build a strong reputation for reliability and quality, as well as establish long-lasting relationships with its customers. On the other hand, Company B focuses on building trust and loyalty with its customers by being transparent and accountable in its operations and by prioritizing ethical andenvironmentally-friendly practices.ConclusionIn conclusion, the comparison of Company A and Company B highlights the key differences between the two companies in terms of their business models, strategies, corporate cultures, and customer relationships. While both companies have been successful in their own right, they have followed different paths to achieve their goals and have leveraged their unique strengths to gain a competitive advantage in the market. By understanding how these differences shape the way each company operates and interacts with its stakeholders, we can gain valuable insights into what sets them apart and how they are able to succeed in their respective industries.。
基地英文介绍作文
基地英文介绍作文Welcome to our base! This is a place where innovation and collaboration thrive. We are a diverse group of individuals with one common goal: to push the boundaries of what is possible.Here at the base, creativity knows no bounds. We are constantly experimenting, tinkering, and brainstorming new ideas. Failure is not seen as a setback, but as an opportunity to learn and grow. We believe that the best ideas often come from taking risks and thinking outside the box.Our base is a hub of activity. From early morning meetings to late-night brainstorming sessions, there is always something happening here. We thrive on the energyand excitement of working together towards a common purpose.The atmosphere at the base is one of constantexcitement and anticipation. We are always on the lookoutfor the next big breakthrough, the next game-changing idea. The sense of possibility and potential is palpable in the air.Collaboration is at the heart of everything we do. We believe that by working together, we can achieve far more than we ever could alone. Whether it's bouncing ideas off one another, or working together on a project, we know that the power of teamwork is unparalleled.Innovation is our driving force. We are constantly seeking new ways to do things, challenging the status quo, and pushing the boundaries of what is possible. We believe that the key to success lies in never becoming complacent, and always striving for something better.So, welcome to our base! Get ready to be inspired, to think differently, and to be part of something truly extraordinary. Here, the possibilities are endless, and the future is ours to create.。
英语作文-建筑设计服务行业竞争格局分析
英语作文-建筑设计服务行业竞争格局分析In the competitive landscape of the architectural design services industry, several key factors contribute to shaping the dynamics and success of firms within this sector. Understanding these elements is essential for navigating the challenges and opportunities present in this field.Firstly, one of the primary determinants of competitiveness in the architectural design services industry is the level of expertise and creativity offered by firms. Clients seek out firms that demonstrate a strong track record of innovative design solutions and the ability to translate their vision into reality. Therefore, firms must invest in cultivating a team of skilled professionals who possess not only technical proficiency but also a keen eye for design and aesthetics.Moreover, the reputation and brand image of a firm play a pivotal role in its competitiveness. A positive reputation built on past successes, client satisfaction, and adherence to deadlines and budgets can significantly enhance a firm's ability to attract new clients and secure lucrative projects. Conversely, firms that suffer from a tarnished reputation due to poor performance or ethical lapses may struggle to compete effectively in the market.In addition to expertise and reputation, another critical factor in the competitive landscape of the architectural design services industry is the ability to leverage technology effectively. The advent of advanced software tools and digital design technologies has revolutionized the way architects conceptualize, design, and present their projects. Firms that embrace these technological advancements can gain a competitive edge by offering clients enhanced visualization, efficient project management, and streamlined collaboration processes.Furthermore, geographical reach and market presence play a significant role in determining the competitive position of architectural design firms. While some firms may focus on serving local markets, others may seek to expand their footprint regionally oreven globally. The ability to establish a strong presence in key markets and leverage local networks and resources can provide firms with a competitive advantage over their rivals.Moreover, the ability to adapt to changing market trends and client preferences is crucial for staying competitive in the architectural design services industry. Firms must stay abreast of emerging design trends, sustainability initiatives, and regulatory requirements to meet the evolving needs of their clients and maintain relevance in the market.Lastly, effective marketing and business development strategies are essential for firms looking to thrive in a competitive market environment. By employing targeted marketing campaigns, cultivating strategic partnerships, and actively pursuing new business opportunities, firms can expand their client base and increase their market share.In conclusion, the architectural design services industry is characterized by intense competition, driven by factors such as expertise, reputation, technology, geographical reach, adaptability, and marketing strategies. Firms that excel in these areas are well-positioned to succeed in this dynamic and ever-evolving sector. By continuously innovating and delivering high-quality design solutions, firms can differentiate themselves and thrive in the competitive landscape of the architectural design services industry.。
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A New Collaboration Design Method Based onDependency in Electrical DomainXinyin WangDepartment of Economics and Management, Shanghai University of Electrical Power,Shanghai, P.R. China shwangxy@Quansheng ShiDepartment of Economics and Management, Shanghai University of Electrical Power,Shanghai, P.R. China shiqs@Huaiyu WangDepartment of Information Technologies,Baoding University, Hebei, P.R. China why9866@Shaohua ZhangShanghai Development Center of Computer SoftwareTechnologies, Shanghai, P.R. China zsh@Abstract —Th i s paper proposes a new collaborat i ve des i gn method, wh i ch i s developed from the study of dependenc i es between the parameters of each part of apparatus, and can be devoted to solve the problems of collaborative product design of mult i ple doma i ns between several commun i t i es based on computer networks, and be applied to the design process such as electri cal appli cati on and mechani cal product etc. Thi s paper covers the emerg ng ssues and the pers stent requ rement of collaborat i ve product des i gn i n electr i cal i ndustry, and then elaborates the foundation ideas and formal definition systems of dependency, and the corresponding architecture.Keywords-Collaboration Design; Dependency; Electrical DomainsI. I NTRODUCTIONIn the fields of engineering design and engineering management, the utilization of a computer has become one of the symbols for measuring the quality of engineering design. Generally speaking, the boilers and the grid structures are always complicated in electrical power system, and the cross-checking exists among different specialty as well. And therefore, it is easy to find that the traditional design method is less efficient, ex parte, and potentially dangerous so that a minor error in design might lead to a severe disaster. Nevertheless, a sophisticated design can result in economic and social benefits through utilizing the modern design equipment, which is to be illustrated in detail as follows.The two- and three-dimensional design drafts of one boiler are shown respectively in figure 1. As a matter of fact, the actual parameters and data information are much more complex than those in this figure. Especially to meet the demand of energy-saving and environment-friendly and efficiency-improving, the power plant and grid techniques should be upgraded more rapidly. Thus there are some more rigid requirements for electrical power engineering design as follows:1. High reliability. With the enhancement of power and voltage grade the project reliability is urgently required. A single-point design will probably lead to a severe consequence.2. Electrical power design is a process that needs the efforts of a team through repeated decisions, conflicts and sedimentation. As it is technical-intensive, a perfect cooperation among specialists in different disciplines is a wise choice.Figure 1. 2D and 3D Boiler design3. In general, modern electrical power projects are usually conducted by more than one design institution; and with the increasingly intense competition, the time limit for a project is usually rigidly restricted.In conclusion, there are more rigid requirements for the design of modern electrical power projects in terms of exhibition, management and collaboration, thus the design decision of geometry, physics and working process should beThis work in this paper is supported by Leading Academic Discipline Project of Shanghai Municipal Education Commission under Grant No.J51302.978-1-4244-6763-1/10/$26.00 ©2010 IEEEProceedings of the 2010 14th International Conference on Computer Supported Cooperative Work in Designexhibited, communicated and decided through visual means. In this situation, it is more significant and urgent to join our efforts to plan electrical power projects.The following section gives way to review major achievements in C SC W fields ever before. The models and methods of dependencies will be discussed in the third part. The fourth section will cover the architectural system. And the last part will contribute to a summary of this applicable method and its prospect.II.RELATED RESEARCHInternationally, it has been a long time to start the research concerning collaboration application, which can be categorized as the collision resolving in terms of work space, time, task and role: the sources [1], [2], [3] lay emphasis on the mediation of work space with multiple user by the lock system; while the sources [4] and [5] attach importance to the synchronism in operation; and [6], [7], [8] focus on the collaboration work from the view of roles and processes.Most collaboration patterns are mostly dedicated to eliminating conflicts in terms of time, space, and task, which, to a large extent, have facilitated the development of this field. But generally speaking, the theories of the past and relevant system used to focus on the operating results instead of the intentions of the designers. Why there is such a problem is that the experts concerned used to focus on the formation of a mediating system that could be applied in various fields, but one will find it difficult to trace the specific intentions of the designers via this kind of method, from which a contradiction is solicited.So far as the collaborative design based on mutual constraints is concerned, one can follow the steps as [9], [10], [11]. The relevant expertise has to be used in the process of design and thus to help the designers consider the key rules from different domains and subsystems. This paper aims to study collaboration from the elements and their dependency instead of constraint itself, and stress the design objectives based on the constraints and the calculation sequence of its parameters.The above-mentioned traditional core methods, which can be universally practiced in various applications such as office, C AD, etc., are to be suggested. The users themselves are encouraged to illustrate the business constraints through their dependency in the factual design process. Only in this way can the system not only trace the intention of the user, but adapt to all kinds of the applicable design devices. The subtle difference lies in the definition of the conflictions from the purpose of design strategies instead of the operating results of terminal users. From this standpoint of collaboration theory, the system can better remove the conflict and maintain the consistency and dynamic qualities.A hypothesis is elaborated that so long as users follow the dependency principles, the design from users will be reasonable and feasible. So, the design conflict from process is not substantial. The following parts will be based on this hypothesis.III.DEPENDENCY MODELDef i n i t i on 1 (Elements, Attr i bute, Package) An Element can be defined as e::=<I,A>, where I: the identifier; A: the Attribute set of Element, which can be quoted as e.A1, e.A2, …, e.A n . Package can be regarded as the subset of E, which is the corpora of Element, can be quoted as P1, P2,… , P n . If e i contains P j , it can be denoted as e i ęP j .Def i n i t i on 2 (Constra i nts, Elementary Dependency,Self Dependency, Package Dependency, Predecessor, Successor) C onstraints, which can be denoted as S, is thenumerical relation should be satisfied between the attributes ofelements according to design rules. If S x is the C onstraintbetween e i.A m and e j.A n, furthermore, the value of e i.A m isdetermined by that of e j.A n, then the relation is called Elementary Dependency, denoted as e i.A mĝe j.A n, where e j.A nis the Predecessor of e i.A m, and e i.A m is the Successor of e j.A n. If i=j and m n, then it is called Self Dependency, if e ięP s and e ięP r, there is Package Dependency between P s and P r.Rule 1: Dependency satisfies transmission rules.Def i n i t i on 3 (Dependency Graph, Dependency Closure) Dependency Graph can be defined as G::=(E,D), where E:the corpora of Element, D: the corpora of Dependency. The closure of all elements who depend on e i directly or indirectly is called the dependency Closure of e i .Rule 2: The corpora of Element of E compose directiongraph.Definition 4 (Package consistency, Global consistency) If all the elements met dependency Graph G, then it satisfies Global C onsistency; suppose all the dependency Graph included by P-P i is G x , and all the elements in P i accords with G-G x , it is said that P i satisfies Package Consistency.Rule 3: If E is the final product met the designrequirement, the E can meet the Global Consistency.Definition 5 ( Event, User) The Event can be defined as o (e i, R x, T l), in which R x refers to the User, the corpora of User can be denoted as R, T l refers to abstract operation, includes creating ,deleting, modifying and browsing.Defi ni ti on 6 (Package Colli si on, Global Colli si on) IfEvent o t on Package P i deviates the dependency d x on P i , it’ssaid o t cause Package C ollision; if o t deviates S-S x , it’s saidthat o t cause Global Collision.Rule 4: If event o t does not cause Package Collision, thenit meet the requirement of Package C ollision, if o t does notcause Global Collision, then it meet the requirement of Globalcollision.Rule 5: Once E meets the requirement of Globalconsistency, if new event o t will not cause Package Collision,then o t will not cause Global collision.Def i n i t i on 7 (Collaborat i on Des i gn) CollaborationDesign is the evolutionary process of E influenced by Eventset U by user set R.Rule 6: During the process of collaboration design,efficient design can be maintained by detecting the collisioncaused by new event o t, and reducing collision constantly.Based on the model concept and principle mentionedabove, this article tries to describe a new collaboration designbased on deducing dependency, including conflict testing,conflict reducing and developing design strategies.First of all, in the process of design, by tracing back to thevery initial design via the dependency link, we can test thevalidity of the operation and monitor conflicts. When a conflictis identified, there are two methods to relieve this conflict: oneis to remove or weaken minor dependency and the other to revise the initial design along with the dependency. During themodern system, dependency within same packages should be strengthened, while those between PAC KAGES should be weakened, which requires dependency simplifying process. A feasible method is to define the dependency between PAC KAGES. A well-designed interface can reduce thedependency link between different PACKAGES. In the process of design, we always have to select different patterns, which require a reasonable decision. To make it specific, we need to assess the importance of attributes, elements and packages by separately calculating the number of dependency links of each item.Restriction of some elements can be defined automatically with definition methods, that is, it is automatically triggered when a users performs normal operations, hence it generates only moderate extra work flow during the design process.This method brings several advantages to the design process. Firstly for assignment planning, it can arrange time priority sequence according to dependency links, also decide at what timing and to what extent for different roles to get involved according to the dependency between the attributes of elements. Secondly, dependencies are advantageous in accumulating knowledge of decision-making in the design process, in inspiring innovations, in strengthening designers’ memories regarding restriction items, even directly forming a design KBS. Last but not the least, a dynamic and comprehensive adjustment of decision-making in the design process can be conducted through compelling adaptation of the very frontier of the dependency link.Figure 2. Dependency DiagramIn the following part, a case will be presented to illustrate the dependency in the collaborative design, where a boiler with the cycle contact of four corner burner is supposed to be developed. The objectives include the main part of the boiler: the body of hearth, the top of hearth, the furnace, furnace arch, burner, and relative elements such as fuel, cycle contact of the burner, etc. The relative parameter of these elements is listed as follows:Fuel (mc): fuel calorific value Q y dw, fuel kind (M), energy consumption (B);Hearth (bs): center (c), width h lt, depth (R), hearth dimensions (V l), cross section area (A l), dimensions calorific intensity (q v);Hearth top (tb): depth (l), depth (h);Furnace arch (ca): height (l), top oblique angle (ha), bottom oblique angle (la);Furnace hopper (lb): oblique angle (a), top entrance (hl), bottom entrance (ll);Hypothetical circle of contact (ic): diameter (d j), origin (c);Real circle of contact (rc): diameter (d s), origin (c);Sipping nozzle of burner (bm): mount (n), altitude (h), width (l);Figure 3. Boiler BodyFigure 4. Top ViewThere are strong design constraints between the parameters such as:V l =B Q ar,net /q v; h lt=[V l-(V ld+V hd)]/A l ; the angle of furnace hopper is below 50° and its bottom entrance is dependent on V l , with a value between 0.6~1.4m; the height of furnace arch is one third of the depth of hearth; the diameter of hypothetic circle of contact d j = (0.05~0.12)A l; the total altitude of sipping nozzle of burner h r is 4 or 6 times of the width of b r, the size from the center of burner to the hypothetic circle of contact l j = 9.438(h r/b r)0.583 * b r /2.In the process of design, we should lay out the most critical design decision according to some constraints and the requirements of engineering such as the power of a boiler, and then we can decide the priorities of parameters according to the counting sequence as well as the related expressions and formula discussed previously. For example, firstly we can determine the volume of a boiler by its power and main fuel, then the width and depth according to the rate between them and the supposed figure, then the size of furnace arch andfurnace hopper, etc. We mainly take turns from exterior to inner, from critical parameters to minor ones.Figure 5. Dependency Diagram in Boiler DesignIn figure 5, a dependency diagram between parameters, reflected as a directed one, can be developed according to theircounting sequence. The diagram includes elements and parameters, of which the elements represent the part, and the parameters hold the qualities of geometry and energy. Due to the stabilization of counting sequence of parameters, the dependency diagram is relatively stable, that’s why the knowledge of domain can usually be deposited. In thecollaborative design, the dependencies can be developed eitherby the user according to common domain rules or by the nearneighbors automatically. If it should be modified, the user can trace the influence to other user according to the dependencylinks.In conclusion, the dependency can effectively promote the collaboration design. It can notify and restrict the modification of user, can provide automatic mechanisms and tools to detect the collisions, can determine the importance of design by analyzing the dependencies, and can help gain experience for the subsequent design.IV. ARCHITECTURAL SYSTEMMVC model, adopted in most modern program designs, has been proven to be a very effectively systematic mode. In most cases, this model can redefine and reduce a big problem into minor segments, each separately focusing on different issues. As a result, it clarifies the systematic functions, and enforces the reuse of components. In order to apply a general resolution to in a collaboration design based on the MVC model, we should further reduce ‘C ontrol’ to divided parts, that is, application control, abstraction control and collaboration control, which should be independent to any specific application. ‘Peer’ is intended to handle most collaboration work, while ‘C lient’ works on the task to display application design. The interface in between is abstract data operations (such as add, delete, revise and check). Routing traffics are handled solely by ‘C ommunication’ layer. For the sake of better consistence, ‘Model’ is not stored in ‘C lient’ but replicated among all distribute ‘Peers’ to secure an acceptable responding rate.Figure 6. Layered ArchitectureIn order to provide better support to multi-collaboration and interaction in remote distance with lower communication traffic, this article optimizes the architecture of the systems that give supports to collaboration design. As shown in the graphic below, the bold lines represent communication routes based on intranet or internet, the thin lines represent the communication routes of high speed LAN, and icons of hexagon and circle respectively represent ‘Client’ and ‘Peer’ – computer nodes in the collaboration design network. This architectural system is to concern the responsibilities of collaboration work on Peer nodes. Due to the high speed of communication in LAN, the collisions between operations can be easily discovered and resolved, so the mode of Client-Servercomputing is adopted. On the other hand, with the highpossibilities of delay on the WAN, the mode of P2P distribution is adopted to collaborate with each other and resolve collisions. In this way, the system can enforce the consistence and reduce the communication traffic. Figure 7. System ArchitectureV. CONCLUSIONSThe essential theory elaborated in this paper is, to encourage the users themselves to elaborate the business design constraints by examining the dependency under concrete circumstance. On the basis of these strategies, the algorithms can easily be found out the reason why the users always conflict with one another by means of design intentions. It will be favorable to accumulating experience and precipitating knowledge for engineers through the design process; it will be outstanding and illustrating seriously for the most crucial design decision; it will be benefit for the mission-executing and role-planning.The further work concerning this topic will cover a full examination of the model for conflict solution, utilities-automatic method of design constraints, formal method of dependency reduced, etc.R EFERENCES[1]Liyin Xue, Kang Zhang, Chengzheng Sun: Conflict Control Locking inDistributed Cooperative Graphics Editors. WISE, pp. 401-408, 2000 [2]Richard E. 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