Applying Model-Based Techniques to the Development of UIs for Mobile Computers
2021高考英语一轮优练题Unit2Robots(含解析)新人教版选修7
Unit 2 Robots李仕才(选修7Unit 2)【短文语法填空】按照短文内容,在空白处填入适当的内容(1个单词)或括号内单词的正确形式。
The classic advertisement,which is 1.likely(like) to be just the name of a company,gives information about finding certain products.This kind of advertising is unlikely to be suitable because of the 2petition(compete) in the market place now.What advertisements need to do is 3.to_attract(attract) the public’s attention.Some advertisements 4.are_made(make) up of pictures or the words of experts to show people how good the products are, 5.while others try to create advertisements people like looking at.So they spend much money 6.applying(apply) modern techniques to the advertisements.Modern advertisements combine the 7.highest(high) standards of design with ideas linked to the products.What’s more,these advertisers look 8.for other ways such as humour as well as unusual ideas to make people forget that someone 9.is_trying(try) to sell them something.There are also some public advertisements 10.which aim to help increase public knowledge and make our society a better place for everyone.Ⅰ.阅读理解AEach year,hikers and mountain bikers get lost or injured in the wilderness.Search and rescue efforts can involve 20 or more people.But a new “smart” drone(无人机) can follow hiking trails(小路) without a pilot’s assistance.This could allow rescuers to search more efficiently.Scientists outfitted a craft with a single camera.As the drone’s “eye”,the camera pointed forwards.But having an eye wasn’t enough.The drone also needed a “brain” to unders tand what it was seeing.And that brain would have to recognize what constitutes a trail.Camera images,however,can be very difficult for a computer to interpret,study leader Alessandro Giusti notes.So he and his team used photos of forest trails to train th eir drone’s neural network(神经网络).They attached three GoPro cameras to a single headband.One camera pointed straight forward.The other two were directed 30 degrees to the right and left of the centre.A hiker put the package on and then hit the trails in a forested part of Switzerland.Over several weeks,the cameras recorded a total of 8 hours of video covering 7 kilometres of trails.The researchers then divided the video into individual still images to train the neural network.The network learned to identify what a trail looked like.The team then tested the program with unused images from the video.The computer did a slightly better job than the people had in correctly classifying the images.This meant the drone was ready to navigate the real world on its own.Giusti and his team took their now “smart” device to a forest with trails that had not been used in the drone’s training.It flew along the path,constantly adjusting its direction based on the images coming in through its camera.The drone didn’t perform as well in real-life as it did in the lab,Giusti admits.That’s because the drone’s camera took lower-quality images than the cameras that had been used to train it.As a result,the images being taken by thedrone looked different,he explains.This confused its neural network.“It’s an exciting use for neural networks,” says Christopher Rasmussen,a computer-vision scientist who was not involved with the study.“However,the problems faced in the experiments show that there are still some important issues to be w orked out.”1.The “smart” drone has been created in order to help .A.find travelers who get lostB.ensure the safety of travelersC.deliver necessities to travelersD.show travelers the way to a place2.While being tested to classify the images in the lab,the computer .A.did as well as the peopleB.did a lot better than the peopleC.did much worse than the peopleD.did a little better than the people3.Why didn’t the drone perform well in the forest?A.The light in the forest was very poor.B.The trees or bushes covered the trails.C.The drone couldn’t fly very low there.D.The pictures taken were of poor quality.4.What is Christopher Rasmussen’s attitude towards the results of the experiments?A.Critical.B.Doubtful.C.Objective.D.Optimistic.B(2021·石家庄调研检测)Shopping centres,stadiums and universities may soon have a new tool to help fight crime.A California company called Knightscope says its robots can predict and prevent crime.Knightscope says the goal is to reduce crime by half in areas the robots guard.William Santana Li is the chief executive officer of Knightscope.He says,“These robot security guards will change the world.Our planet has seven billion people on it.It’s going to qui ckly get to nine billion people.The security equipment that we have globally is just not going to develop that fast.The company’s Autonomous Data Machines can become the eyes and ears of law enforcement (执行).”“You want it to be machines plus humans.Let th e machines do the heavy and sometimes dangerous work and let the humans do the strategic decision-making work,so it’s always working all together.”The machines are one and a half meters tall and weigh 136 kilograms.They do not carry weapons but they have day-and-night time video cameras which are able to turn 360 degrees and can also sense chemical and biological weapons.Some people may become concerned about their privacy,especially in connection with the video recordings.Some people may worry that such recordingswill appear on the Internet.Eugene Volokh,a law professor at the University of California,says the machines have to be used in the right way and it will be interesting to see how state laws deal with this kind of video.William Santana Li says there is a long waiting list for the robots in the US.Workers in the company are working overtime to meet the demands of the market.At least 25 other countries are also interested in these robotic security guards.5.What can this new tool do for humans?A.Make strategic decisions.B.Keep watching day and night.C.Carry heavy weapons.D.Stop crime autonomously.6.Why are people worried?A.Their privacy may be let out.B.The robots are very expensive.C.Robots will replace humans.D.They will be out of work soon.7.Which of the following can be the best title of the text?A.Robots Are Becoming More PopularB.Robots Contribute a Lot to the WorldC.Robots Are in Great Demand NowD.Security Robots Could Help Cut CrimeCFrom young kids to fitness lovers,to those looking for a laugh,or to families looking for a free movie night,Atlantic Station prepares some days for them to enjoy this year.Tot Spot—Each Tuesday morning.Atlantic Station's Central Park transforms into every child's dream playground! From 10:00 am to noon,kids can enjoy games,storytelling, toys,music and some very special things.This event begins on April 5 and lasts through September 27.Wellness Wednesday—Each Wednesday from 6:30 pm to 7:30 pm,Atlantic Station's Central Park becomes the perfect place to find quietness of the mind and body while instructors lead guests through exercises including yoga andmore.Wellness Wednesday welcomes all ages and skill levels.This event begins on April 6 and lasts through September 28.Improv in the Park—Whole World Theatre,Atlanta's premier improv group,has once again partnered with Atlantic Station to bring a familyfriendly night of comedy to the Central Park on the first Wednesday of each month until September.Bring a blanket,relax under the stars and prepare to laugh until your stomach hurts!The hourlong show begins at 8:00 pm.This event occurs on April 5,May 4,June 1,July 6 and August 3.Movies in the Central Park—Each Thursday night at dusk,guests are invited to bring chairs,blankets,togo snacks and picnics to Atlantic Station's Central Park.All outdoor screenings are available,weather permitting,so keep your fingers crossed for no The Wizard of Oztype storms!Be sure to arrive early to find a good seat.1.Mothers can take their kids who like listening to stories to ________.A.Tot SpotB.Improv in the ParkC.Wellness WednesdayD.Movies in the Central Park2.When can you do yoga with an instructor in Atlantic Station's Central Park?A.On each Tuesday from 6:30 pm to 7:30 pm in August.B.On each Tuesday morning from 10:00 am to noon in July.C.At 8:00 pm on April 5, May 4,June 1,July 6 and August 3.D.On each Wednesday at 7:00 pm in June and July.3.What can we learn from the text?A.Atlantic Station sets the days for guests to have fun.B.Tickets for Movies in Central Park are hard to get.C.Movies in the Central Park are shown only indoors.D.Only teenagers are welcome to join in Wellness Wednesday【解题导语】本文主要介绍了大西洋站几个可让人们放松自己、享受生活和取得乐趣的活动。
人教版高中英语选择性必修第二册精品课件 Unit 5 Section A
adj.与电有关的
→ electrically
adv.电力地;有关电地
4.swollen adj.(身体部位)肿起的;肿胀的→ swell
vi.膨胀;肿胀
5.nerve n.神经→ nervous adj.神经的;紧张不安的
6.loose adj.松的;未系紧的;宽松的→ loosely adv.宽松地;放荡地;轻率
Para.1
A.First aid treatment.
Para.2
B.Characteristics of burns.
Para.3
C.Causes of burns.
Para.4
D.Types of burns.
Para.5
E.The functions of the skin.
答案 Para.1—E;Para.2—C;Para.3—D;Para.4—B;Para.5—A
clean
Treatment cloth→burns on the face:make sure the victim can still 9._b_r_e_a_th_e_
→second or third-degree burns:there is an 10. urgent need to
take him/her to the hospital at once.
below the top
1. _m__il_li_m__et_r_e_s__of 2. ___la_y_e_r__of the skin skin,and sometimes the
the skin
3. __ti_ss_u_e_____under it
Details
First-degree Second-degree
abaqus fastener机理 -回复
abaqus fastener机理-回复Abaqus Fastener MechanismFasteners play a crucial role in various engineering applications, including static and dynamic load-bearing structures. They are widely used in industries such as aerospace, automotive, and construction. Abaqus is a powerful finite element analysis software that can simulate and analyze the behavior of fasteners under different mechanical loads. In this article, we will delve into the fastener mechanism in Abaqus, discussing its various components and their respective functions.1. Introduction to FastenersFasteners are mechanical devices used to join two or more components together. They are designed to resist the external loads acting on the joint, such as tension, compression, shear, or a combination of these forces. Fasteners come in various forms, such as bolts, screws, rivets, and nuts. In Abaqus, we can model different types of fasteners to simulate their behavior accurately.2. Modeling Fasteners in AbaqusTo simulate the behavior of a fastener accurately, we need to modelits geometry, material properties, and connection with other components. Abaqus provides several predefined modeling techniques to capture the fastener mechanics effectively.2.1 Bolt ModelingBolts are commonly used fasteners in structural engineering. In Abaqus, we can model a bolt using the continuum element technology. The bolt's geometry, including its threads, can be defined using analytical representations or finite element-based approaches. The material properties of the bolt, such as its Young's modulus, yield stress, and Poisson's ratio, are also crucial inputs for accurate simulation.2.2 Nut ModelingA nut is an essential component in a bolted joint, providing secure fastening. Modeling a nut in Abaqus involves defining its geometry, material properties, and its interaction with the bolt. Abaqus allows us to define contact surfaces between the nut and bolt, simulating the frictional behavior accurately. The contact algorithm in Abaqus calculates the distribution of forces between the contacting surfaces, enabling an accurate representation of the nut's tightening or loosening forces.2.3 Thread ModelingThreads are integral parts of bolts and nuts, providing the necessary interlocking mechanism. In Abaqus, we can model threads using various techniques, such as modeling them as solid geometries, as independent surface elements, or using coupling constraints. Accurately modeling threads is essential to capture their effect on the bolt torque and overall joint behavior.3. Loading and AnalysisAfter modeling the fastener and its components in Abaqus, we can subject them to various loading conditions to simulate their response. Common loading scenarios include tensile, compressive, shear, and combined loads. Abaqus provides precise boundary conditions to replicate the real-world loading conditions, ensuring accurate simulation results.3.1 Preload ApplicationIn many bolted joint applications, a preload is applied to the bolt to avoid unintentional loosening. Abaqus allows us to specify the desired preload through applied forces or torques. By defining the preload correctly, we can simulate the clamping force distributionin the joint accurately.3.2 Load-Displacement AnalysisFasteners are typically subjected to external loads that induce displacement in the joint. Abaqus enables load-displacement analysis by applying forces or displacements to simulate the joint's behavior under different load scenarios. The analysis results provide insights into the fastener's stress distribution, deformation, and tightening/loosening behavior.4. Post-Processing and Result InterpretationAbaqus offers powerful post-processing tools to analyze and visualize the simulation results. We can generate stress and deformation plots, displacement vectors, or contour plots to understand the fastener's behavior under different load conditions. The post-processing capabilities of Abaqus enhance result interpretation and aid in making design decisions for fastened joints.ConclusionIn conclusion, Abaqus is a versatile software package that enables accurate simulation and analysis of fastener mechanism behavior.By modeling fasteners, nuts, and threads accurately and applying appropriate loading conditions, we can evaluate the performance of fastened joints, optimize designs, and ensure the safety and reliability of engineering structures.。
科技英语—3-11章总复习题剖析
第3章总复习题1.Other factors affect the configuration of the total system.另一些因素则将影响整个系统的结构。
2.In normal flight the hatch doors fair into the fuselage.飞行正常时,舱门与机身平整贴合。
3.Energy can neither be created, nor destroyed by any means known to man.用人们已知的方法,既不能创造能量也不能消灭能量。
4.It is customary to refer to design levels as high or low on component complexity.习惯上根据部件的复杂程度把设计级称为高设计级和低设计级。
5.The main economy of the system stems from the ability to move cars in a continuous train without uncoupling.此系统的主要经济之处在于它能移动列车的车厢而不必将它们脱钩分开。
6.He is a stranger to the operation of the electronic computer.他对电子计算机的操作是陌生的。
7.A key element in system capacity planning is the financial cost of performance.系统能力计划中关键因素是性能的金融成本。
8.The assembler can expand the key words in the assembly code into their full instruction set.这种汇编程序能把汇编码中的关键字扩展成完整的指令集。
9.The flame does not touch the flask directly.火焰没有直接接触烧瓶。
编译原理英文缩写
The Acronyms of Compiler DesignIntroductionCompiler design is an essential field in computer science that deals with the creation of software programs called compilers. A compiler is responsible for translating high-level programming languages into machine-readable code. To better understand the concepts and discussions related to compiler design, it is crucial to become familiar with some of the frequently used acronyms in this domain.1.Overview1.1 CompilerA Compiler is a program that converts source code written in a high-level programming language into machine code or an intermediate representation (IR). It plays a vital role in software development by bridging the gap between human-readable code and the machine’s binary language.1.2 IR (Intermediate Representation)IR refers to the intermediate form of the source code generated by the compiler. It serves as an intermediary between the high-level language and the low-level machine language. An IR is typically lower level than the source code, making it easier for the compiler to optimize and translate into machine code.1.3 AST (Abstract Syntax Tree)AST represents the hierarchical structure of the source code and is created during the parsing phase of the compiler. It captures the syntax and semantics of the program in a tree-like data structure. The AST helps the compiler process and understand the source code during various compilation stages.2.Lexical Analysis2.1 DFA (Deterministic Finite Automaton)DFA is a mathematical model or an abstract machine that recognizes and processes regular languages. In compiler design, DFAs are used to perform lexical analysis by tokenizing the source code into individual tokens. DFAs help in identifying keywords, identifiers, constants, and other language constructs.2.2 LexerA lexer, often referred to as a scanner or tokenizer, is responsible for breaking the source code into meaningful tokens based on the predefined grammar rules. The lexer analyzes the input character by character and outputs a stream of tokens for further processing by the compiler.3.Syntax Analysis3.1 ParserA parser is a component of the compiler that analyzes the token stream generated by the lexer and checks if it conforms to the defined grammar rules of the programming language. It constructs the AST by recursively applying production rules defined in the grammar.3.2 LL Parsing (Left-to-Right, Leftmost derivation)LL parsing is a top-down parsing strategy where the production rules are applied from left to right and the leftmost non-terminal is expanded first. It is commonly used in LL(k) parsers, where ‘k’ denotes the number of lookahead tokens used to decide which production rule to apply.4.Semantic Analysis4.1 Symbol TableA symbol table is a data structure maintained by the compiler to store information about variables, functions, classes, and other program entities. It provides a mapping between the identifier names and their attributes, such as type, scope, and memory location. Symbol tables help in detecting semantic errors and resolving references during compilation.4.2 Type CheckingType checking is a crucial part of semantic analysis that ensures the compatibility and consistency of types in the source code. It verifies if the operations performed on variables and expressions are valid according to the language rules. Type-checking rules are defined based on the programming language’s type system.5.Code Generation5.1 IR Code GenerationIR code generation involves translating the high-level source code into an intermediate representation code. The IR code is closer to the machine language and allows for further optimization before generating the final machine code.5.2 OptimizationOptimization aims to improve the efficiency of the generated code by applying various techniques. Common optimization strategies include removing redundant code, optimizing loop structures, and reducing the number of memory accesses. Optimization helps in producing faster and more efficient programs.6.Code Optimization6.1 Liveness AnalysisLiveness analysis determines the live range of variables in the program, i.e., the portion of the program where a variable is being used or has a potential to be used. This analysis is crucial for register allocation and code elimination optimizations.6.2 Register AllocationRegister allocation is the process of assigning variables to registers of a processor, considering the limited number of available registers. Efficient register allocation reduces the usage of memory accesses, which leads to faster program execution.ConclusionUnderstanding the acronyms commonly used in compiler design is essential for grasping the intricacies of this field. The mentioned acronyms provide a foundation for discussing various concepts, techniques, and stages involved in the compilation process. By familiarizing ourselves with these acronyms, we can delve deeper into the study and development of compilers.。
模型训练与推理 英文
模型训练与推理英文Model Training and Inference.Model training and inference are two crucial stages in the development and deployment of machine learning models. Model training involves the process of feeding the model with labeled data to enable it to learn and make predictions. During training, the model adjusts itsinternal parameters to minimize the difference between its predictions and the actual labels. This is typically done using optimization algorithms such as gradient descent.On the other hand, model inference refers to the stage where the trained model is used to make predictions on new, unseen data. This could involve feeding new input data into the model and obtaining the corresponding output or prediction. Inference is the phase where the model's performance is evaluated based on its ability to generalize to unseen data and make accurate predictions.It's important to note that model training and inference have different computational requirements. Training a complex model often requires substantial computational resources and time, as it involves processing large amounts of data and performing numerous iterations to optimize the model's parameters. In contrast, inference is typically less computationally intensive, as it mainly involves applying the trained model to new data for prediction.Furthermore, the deployment of machine learning models for real-world applications often requires efficient and scalable inference mechanisms to handle varying workloads and ensure low latency. This may involve optimizing the model for inference, utilizing hardware accelerators such as GPUs or TPUs, and implementing techniques like model quantization to reduce the computational cost of inference.In summary, model training and inference are essential components of the machine learning lifecycle. Training enables the model to learn from data, while inference allows the model to make predictions on new data. Bothstages have distinct considerations in terms of computational requirements, performance evaluation, and real-world deployment.。
利用点云构建bim模型的流程
利用点云构建bim模型的流程## Point Cloud to BIM Modeling Workflow.### Workflow Overview.The following steps provide a comprehensive workflow for utilizing point cloud data to construct a Building Information Model (BIM):1. Data Acquisition: Capture the existing structure using a laser scanner or other data acquisition method.2. Data Registration: Align and stitch multiple scans to create a complete and accurate representation of the building.3. Point Cloud Processing: Remove noise, outliers, and unneeded data from the point cloud.4. Feature Extraction: Identify and extract relevantbuilding features such as walls, floors, and ceilings from the processed point cloud.5. Geometric Modeling: Create 3D models of the extracted features using parametric or NURBS modeling techniques.6. Semantic Labeling: Assign appropriate materials, properties, and other semantic information to the geometric models.7. BIM Integration: Import the labeled models into a BIM platform to create a comprehensive and information-rich BIM representation of the structure.### Detailed Workflow.1. Data Acquisition.Utilize a laser scanner or other technology to capture a dense and accurate point cloud representation of the existing structure.Ensure proper calibration and setup of the data acquisition equipment to minimize errors.2. Data Registration.Align and register multiple scans using software tools to create a seamless and complete point cloud dataset.Utilize techniques such as ICP (Iterative Closest Point) or other registration algorithms.3. Point Cloud Processing.Remove noise and outliers from the point cloud using filtering algorithms.Segment the point cloud into different categories or clusters based on geometric properties.4. Feature Extraction.Identify and extract building features by applying geometric analysis techniques to the processed point cloud.Utilize edge detection, region growing, or pattern recognition algorithms to identify walls, floors, ceilings, and other structural elements.5. Geometric Modeling.Create 3D models of the extracted features using parametric or NURBS modeling techniques.Parametric modeling allows for automated feature creation based on defined parameters.NURBS modeling enables the generation of smooth and accurate surface representations.6. Semantic Labeling.Assign appropriate materials, properties, and other semantic information to the geometric models.Utilize a BIM classification system or industry standards to define material types, structural properties, and other relevant attributes.7. BIM Integration.Import the labeled models into a BIM platform such as Revit, ArchiCAD, or Bentley AECOsim.Create a comprehensive BIM representation of the structure that includes geometry, semantic data, and related documentation.## 中文回答:点云构建 BIM 模型流程。
特许工程师认证简介
IET提供一系的工具和服务帮助会员取得工程科技人才 资质认证
IET工程科技人才资质认证
经英国工程理事会授权,IET可授予如下工程科技人才资质证书:
特许工程师-CEng 具备创新能力,技术和商业领域的领军人才 技术工程师-IEng 熟练运用现有技术,技术和商业领域的管理人才 工程技师-EngTech 技术和商业主管,工段长 信息通信技术技师-ICTTech ICT系统维护员/工程师
步骤二
步骤三
CEng和 IEng的申请者 需要经过 同行专家的 面试
步骤四
审核委员会 决定 是否同意 授予资质
同行专家 审查 申请报告
如果全部 符合要求, 转步骤二
视申请 资质的不同 转步骤三 或者 步骤四
如果 全部合乎要求, 转步骤四
同意授予; 如果 未获同意, 可咨询 资质认证顾问
特许工程师-CEng
Chartered Engineers(CEng) are characterised by their ability to develop appropriate solutions to engineering problems, using new or existing technologies, through innovation, creativity and change. They might develop and apply new technologies, promote advanced designs and design methods, introduce new and more efficient production techniques, marketing and construction concepts, pioneer new engineering services and management methods. Chartered Engineers are variously engaged in technical and commercial leadership and possess effective interpersonal skills.
控制科学与工程英语面试问答
控制科学与工程英语面试问答一、介绍控制科学与工程控制科学与工程是一门综合性的学科,涵盖了自动控制、信息理论、系统工程、人工智能等多个领域。
它致力于研究如何设计、分析和实现能够自动控制各种系统的方法和技术。
在现代工程领域中,控制科学与工程起到了至关重要的作用,它可以应用于各个领域,如制造业、交通运输、航天航空、能源等。
二、控制科学与工程英语面试常见问题及回答1. What is control engineering?Control engineering is a multidisciplinary field that deals with the design, analysis, and implementation of systems that can automatically control various processes to achieve desired outputs. It involves applying mathematical models and control algorithms to manipulate inputs and outputs ofa system.2. How is control engineering different from other engineering fields?Control engineering focuses on the development of systems that can regulate and manipulate processes to achieve specific objectives. It differs from other engineeringfields in that it deals with the dynamic behavior of systems and the design of controllers to achieve desired performance.3. What are the key components of a control system?A control system typically consists of a plant or process, sensors, actuators, and a controller. The plant refers to the system being controlled, while sensors and actuators are used to measure and manipulate the variables of interest. The controller processes the sensor data and generates control signals to adjust the actuators.4. What are the different types of control systems?Control systems can be classified into open-loop and closed-loop systems. Open-loop systems do not have feedback, and the control action is based solely on the input. Closed-loop systems, also known as feedback control systems, use feedback from the output to adjust the control action. This allows for better regulation and compensation for disturbances.5. What are the main challenges in control engineering?One of the main challenges in control engineering is dealing with system uncertainty and variability. Real-worldsystems often have unknown or time-varying parameters, which can affect the performance of control systems. Another challenge is ensuring stability and robustness in the face of disturbances and noise.6. What are some popular control techniques?There are various control techniques used in control engineering, such as PID (Proportional-Integral-Derivative) control, optimal control, adaptive control, and robust control. Each technique has its own advantages and is suitable for different types of systems and applications.7. How is control engineering applied in real-world systems? Control engineering is widely applied in various industries, such as manufacturing, transportation, aerospace, and energy. It is used to control processes in factories, regulate traffic flow, stabilize aircraft, and optimize energy consumption. It plays a crucial role in improving efficiency, safety, and reliability in these systems.8. What are the future trends in control engineering?With the advancement of technology, control engineering is evolving to incorporate new concepts and techniques. Some future trends include the integration of control andartificial intelligence, the development of autonomous systems, and the application of control in emerging fields such as renewable energy and healthcare.三、总结控制科学与工程是一门重要的学科,其在现代工程领域中发挥着关键作用。
实景三维建模的流程和方法英语
实景三维建模的流程和方法英语Three-dimensional modeling of real scenes is a complex and detailed process that involves capturing the environment in three dimensions and converting it into a digital model. 实景三维建模是一个复杂且详细的过程,涉及捕捉环境的三维信息,并将其转化为数字模型。
This process requires a combination of various methods and techniques to ensure accuracy and realism in the final model. 这个过程需要结合各种方法和技术,以确保最终模型的准确性和逼真度。
One of the first steps in real scene three-dimensional modeling is data acquisition. 数据采集是实景三维建模的第一步之一。
This involves using specialized equipment such as laser scanners, photogrammetry, or LiDAR to capture the physical environment in three dimensions. 这包括使用激光扫描仪、摄影测量术或激光雷达等专业设备来捕捉环境的三维信息。
Each method has its own set of advantages and limitations, and the choice of which to use depends on the specific requirements of the project. 每种方法都有其自身的优势和局限性,选择使用哪种方法取决于项目的具体要求。
瓷器的工艺介绍英文作文
瓷器的工艺介绍英文作文英文:As a lover of ceramics, I am always fascinated by the intricate techniques used in creating these beautiful pieces of art. The process of creating ceramics involves several steps, each requiring precision and skill. 。
Firstly, the clay is prepared by mixing it with water and other materials to give it the desired consistency. The clay is then shaped into the desired form using various techniques such as throwing, coiling, or slab building. 。
Once the clay has been shaped, it is left to dry completely before being fired in a kiln at a high temperature. This process is called bisque firing and it hardens the clay, making it ready for glazing. 。
Glazing is the process of applying a liquid coating to the ceramic piece, which is then fired again in the kiln.The glaze melts and forms a glass-like surface on the ceramic, giving it a smooth and glossy finish. 。
large language model data augmentation
large language model dataaugmentationLarge language model data augmentation refers to the process of increasing the amount and diversity of data used to train large language models (LLMs). This is an important technique as it can help improve the performance and generalization ability of the model.One common approach to data augmentation is to use existing data to generate new data. This can be done by applying various transformations and modifications to the existing data, such as text generation, paraphrase, and language translation. For example, existing text can be used to generate new text by applying language models or rule-based generation techniques.Another approach is to use external data sources to augment the data. This can include using web pages, books, newspapers, and other text sources. These data sources can provide a large amount of diverse data that can help the model learn different language expressions and semantic understanding.In addition, data augmentation can also be achieved by mixing different datasets. This can help the model learn different language styles and semantic understanding, thereby improving its generalization ability.In general, large language model data augmentation is an important technique that can help improve the performance and generalization ability of the model. By generating new data, using external data sources, and mixing different datasets, we can increase the amount and diversity of data used to train the model, thereby improving its performance and accuracy.。
分析方法的开发流程
分析方法的开发流程Analyzing method development is a complex process that requires careful planning and execution. The first step in this process is to clearly define the objectives of the analysis. This involves identifying the key questions that need to be answered and the specific goals that the analysis is intended to achieve. By setting clear objectives, analysts can better focus their efforts and ensure that their work is relevant and meaningful. 完善的目标定义是开发分析方法过程中的首要步骤。
这涉及确定需要回答的关键问题和分析旨在实现的具体目标。
通过设定明确的目标,分析师们可以更好地集中精力,确保他们的工作是相关和有意义的。
Once the objectives have been established, the next step is to design the analysis methodology. This involves determining the data sources that will be used, the analytical techniques that will be applied, and the overall approach that will be taken. The methodology is critical to the success of the analysis, as it provides a framework for how the data will be collected, processed, and interpreted. 一旦确定了目标,下一步是设计分析方法论。
竞争市场中产品组合管理博弈模型(英文)
2. Literature review
A PPM is defined as a decision making that optimizes some criteria, such as market share. The main contribution of the most researches in PPM is summarized in following issues: 1) Generating design alternatives via multi-objective optimization(通过多目标优化生成设计方案). 2) Accounting for uncertainty and competition when estimating the achievement of business goals. 3) Applying meta-heuristic algorithms(元启发式算法)
PPM is developed to direct a product and its diversity
including not only attributes(属性), levels, and price’s, but also analysis results,environmental requirements(环保需求), manufacturing procedures (生产流程), product performance information(产品 性能信息), and etc.Therefore PPM has been classified as a combinatorial optimization problem. Each company strives for the optimality of its product offerings through various combinations of products .
运用所学解决实际问题的一次经历英语作文
An Insightful Experience of Applying Learned Knowledge to Solve a Real-World Problem In the realm of academic pursuits, the most rewarding moments often arise when the theoretical knowledge we acquire is successfully applied to address practical challenges. Such an experience occurred recently when I had the opportunity to utilize my understanding of statistics and data analysis to solve a real-world problem in my workplace.My role as a data analyst in a marketing firm necessitated a deep understanding of various statistical techniques and their application in market research. One day, our team faced a significant challenge: our latest advertising campaign had yielded disappointing results, and we needed to identify the underlying reasons. It was evident that a thorough analysis of the campaign's data was required to uncover insights and formulate an effective strategy for improvement.Armed with my knowledge of descriptive statistics, I embarked on the task of collecting and organizing the campaign's data. This involved compiling information onvarious metrics such as click-through rates, conversion rates, audience demographics, and more. The next step was to apply inferential statistics to identify patterns and correlations within the data. Through techniques like hypothesis testing and regression analysis, I was able to detect significant relationships between certain variables and the campaign's performance.One key finding was that the campaign's messaging did not resonate well with a specific segment of our target audience. This revelation was crucial in understanding why the campaign had failed to achieve its desired impact. Based on this analysis, I proposed a revised strategy that focused on realigning the messaging to better appeal tothis audience segment.The implementation of this revised strategy was a collaborative effort that involved members from various departments. However, my role in providing data-driven insights was crucial in guiding the direction of the revised campaign. In the end, the efforts paid off, and the revised campaign yielded significantly improved results.Reflecting on this experience, I realize that the application of learned knowledge is not just about regurgitating theories but about understanding their relevance in real-world contexts. This experience has not only reinforced my belief in the power of data-driven decision-making but has also instilled a sense of accomplishment and pride in being able to contribute to solving a practical problem.Moreover, this experience has highlighted the importance of continuous learning and adaptability in the workplace. As the world continues to evolve and new challenges arise, it is essential to stay updated with the latest knowledge and techniques to ensure that we are equipped to handle them effectively.In conclusion, the experience of applying my learned knowledge to solve a real-world problem has been an enriching and rewarding one. It has not only validated my academic pursuits but has also provided me with a valuable lesson in the practical application of knowledge. I am confident that this experience will serve as a foundationfor future endeavors and inspire me to continue exploring and applying my knowledge to solve real-world challenges. **运用所学解决实际问题的一次深刻经历**在学术追求的领域里,最令人欣慰的时刻往往出现在我们将所学的理论知识成功应用于解决实际问题时。
典范英语8博莎的秘密招数读后感
典范英语8博莎的秘密招数读后感After reading "The Secret Techniques of Model English 8: The Bosha Method", I was truly inspired by the innovative and effective strategies presented in the book. The author, Bosha, has truly unlocked the secrets to mastering the English language, and I am excited to share my thoughts and reflections on this insightful read.One of the key takeaways from the book is the emphasis on immersion and practice. Bosha highlights the importanceof surrounding oneself with English language input, whether it be through reading books, watching movies, or listeningto music. By immersing oneself in the language, one can develop a natural feel for its nuances and expressions. Additionally, Bosha stresses the need for consistentpractice in order to solidify language skills. This resonated with me, as I have always believed that practiceis the key to improvement in any skill.Another aspect of Bosha's method that stood out to meis the focus on building vocabulary through context. Rather than rote memorization of words, Bosha advocates forlearning vocabulary in the context of sentences and phrases. This approach not only helps in retaining the meaning of words but also aids in understanding how they are used in everyday communication. I found this to be a refreshing perspective on vocabulary acquisition, as it makes the learning process more engaging and practical.Furthermore, Bosha's emphasis on speaking and writing practice as essential components of language learningstruck a chord with me. It is one thing to understand the language passively, but actively using it in conversations and written communication is where true proficiency is developed. Bosha provides practical tips and exercises for improving speaking and writing skills, which I found to be invaluable in my own language learning journey.The book also delves into the importance of cultural awareness in language learning. Bosha emphasizes theinterconnectedness of language and culture, and how understanding cultural nuances can enhance one's language skills. By learning about the customs, traditions, and values of English-speaking countries, learners can gain a deeper appreciation for the language and connect with native speakers on a more meaningful level. This insight opened my eyes to the richness of language and culture intertwining, and I am eager to explore this aspect further in my own studies.In conclusion, "The Secret Techniques of Model English 8: The Bosha Method" has been a transformative read for me. Bosha's innovative approach to language learning has inspired me to rethink my own study habits and techniques. By immersing myself in the language, practicing consistently, building vocabulary in context, honing speaking and writing skills, and embracing cultural awareness, I am confident that I can take my English proficiency to new heights. I am grateful for the valuable insights shared in this book, and I look forward to applying them in my language learning journey. Bosha's secrets are indeed powerful tools for mastering English,and I am excited to see where they will take me in the future.。
如何提升学习的作文英文
In the pursuit of academic excellence, it is crucial to develop and refine strategies that foster effective learning. The process of enhancing one's learning experience transcends mere rote memorization and involves a multi-dimensional approach that encompasses cognitive, emotional, and environmental aspects. This essay delves into various key elements that contribute to optimizing learning, offering a comprehensive and high-quality roadmap for students seeking to elevate their academic performance.1. **Establishing a Strong Foundation of Motivation**A compelling drive to learn is the cornerstone of academic success. To cultivate this motivation, it is essential to identify personal goals and aspirations, linking them explicitly to the learning process. This can be achieved by setting specific, measurable, achievable, relevant, and time-bound (SMART) objectives, which provide clear direction and a sense of purpose. Moreover, understanding the intrinsic value of knowledge acquisition, such as its potential to broaden perspectives, foster critical thinking, and enhance career prospects, can further fuel motivation.Additionally, extrinsic motivators, such as praise, rewards, or the prospect of higher grades, can also play a role in maintaining momentum. However, it is crucial to strike a balance between intrinsic and extrinsic motivation, as overreliance on external factors may undermine long-term interest and engagement.2. **Adopting Effective Study Techniques**The methods we employ to process and retain information significantly impact our learning outcomes. Here are some evidence-based study techniques: **Active Learning:** Engaging in activities like summarizing, discussing, teaching, or applying concepts promotes deeper understanding and retention compared to passive reading or listening. Techniques like the Feynman Technique, where one explains a concept to an imaginary audience in simple terms, can be particularly effective.**Spaced Repetition:** Revisiting material at increasingly longer intervals helps consolidate memories in long-term storage. Tools like flashcards or digital apps like Anki can facilitate this process.**Interleaving:** Alternating between different subjects or types of problems during a study session enhances retention and problem-solving skills by forcing the brain to discriminate and adapt to varying contexts.**Deep Processing:** Encouraging elaboration, organization, and critical thinking about the material, rather than superficial processing, leads to better retention and transfer of knowledge. Techniques like mind mapping or the PQ4R (Preview, Question, Read, Reflect, Recite, Review) method can promote deep processing.3. **Cultivating a Growth Mindset**A growth mindset, as opposed to a fixed mindset, embraces challenges, views effort as a path to mastery, and learns from setbacks. Cultivating this mindset involves:**Embracing Challenges:** Seeing difficult tasks as opportunities for growth rather than threats to competence.**Valuing Effort:** Recognizing that intelligence and talent are malleable and can be developed through persistent effort.**Learning from Failure:** Perceiving failures as informative feedback rather than a reflection of inherent abilities, and using them to adjust strategies and persist in learning.4. **Managing Time Effectively**Efficient time management is vital for balancing academic responsibilities, personal life, and self-care. Strategies include:**Creating a Study Schedule:** Designing a structured yet flexible plan that allocates time for coursework, revision, breaks, and leisure activities.**Prioritizing Tasks:** Using tools like the Eisenhower Matrix to categorize tasks based on urgency and importance, ensuring focus on high-value activities.**Minimizing Distractions:** Identifying and eliminating or mitigating distractions, such as social media or multitasking, to enhance concentration during study sessions.**Practicing Self-Discipline:** Establishing routines, setting boundaries, and holding oneself accountable to maintain consistency and productivity.5. **Promoting Physical and Mental Well-being**Optimal learning is contingent upon good physical and mental health. Steps to nurture well-being include:**Maintaining a Balanced Diet:** Consuming a diet rich in nutrients, vitamins, and minerals to support brain function and energy levels.**Regular Exercise:** Engaging in physical activity to improve mood, reduce stress, and enhance cognitive function.**Quality Sleep:** Ensuring adequate sleep to facilitate memory consolidation, attention, and emotional regulation.**Mental Health Support:** Seeking help when needed, practicing stress-reduction techniques like mindfulness or meditation, and cultivating positive relationships for emotional support.6. **Leveraging Technology and Resources**In today's digital age, technology offers numerous tools and resources to augment learning:**Online Learning Platforms:** Utilizing platforms like Coursera, Khan Academy, or edX for supplementary learning materials, interactive exercises, and expert insights.**Educational Apps:** Exploiting apps like Duolingo, Quizlet, or Evernote to facilitate language learning, memorization, or organization.**Collaborative Tools:** Employing tools like Google Docs, Zoom, or Slack to facilitate group work, discussions, and peer learning.7. **Engaging in Continuous Feedback and Reflection**Continuous assessment and reflection are instrumental in identifying strengths, weaknesses, and areas for improvement. Strategies include: **Self-Assessment:** Regularly evaluating one's understanding, progress, and study habits using quizzes, self-tests, or reflection journals.**Peer Feedback:** Seeking constructive criticism and suggestions from classmates, study groups, or online forums.**Teacher Feedback:** Actively engaging with instructors, asking questions, attending office hours, and incorporating their feedback into learning strategies.**Formal Assessments:** Analyzing exam results, assignment feedback, and course evaluations to inform future learning approaches.In conclusion, enhancing learning is a holistic endeavor that requires a blend of motivation, effective study techniques, mindset cultivation, time management, well-being promotion, technology utilization, and continuous feedback. By integrating these multifaceted strategies, students can embark on a transformative journey towards academic excellence, fostering not only improved grades but also a lifelong love for learning and a robust set of skills applicable beyond the classroom.。
英语完型技巧及方法
英语完型技巧及方法1When it comes to dealing with English cloze tests, there are several practical skills and effective methods that can greatly enhance your performance. Firstly, always read the entire passage thoroughly to grasp the main idea. This gives you a broad context and helps you make more informed choices when filling in the blanks. For example, in a story about a person's travel experience, you can predict the possible words based on the overall tone and the sequence of events.Secondly, pay close attention to the context and grammar knowledge. The words and phrases around the blanks often provide crucial hints. If the sentence requires a verb in a certain tense, you need to choose the appropriate form. Also, be familiar with common collocations and phrases. For instance, "make a decision" or "take part in" are fixed expressions that you should recognize instantly.Another useful tip is to eliminate obviously incorrect options. Sometimes, you can quickly rule out some choices based on the logic of the sentence or your prior knowledge. This narrows down your choices and increases the chances of getting the correct answer.In conclusion, by consistently applying these techniques and practicing regularly, you will find that your ability to handle English clozetests improves significantly over time.2When it comes to improving the ability in English cloze tests, several crucial techniques and methods can make a significant difference. Firstly, vocabulary accumulation is of paramount importance. By expanding your vocabulary through diligent word memorization, you enhance your comprehension of the options presented in the cloze test. For instance, when you encounter a word gap, having a rich vocabulary enables you to quickly narrow down the possible choices and make a more informed decision.Secondly, practicing regularly with a wide variety of cloze exercises is essential. This not only familiarizes you with different types of questions but also helps you identify patterns and tricks. For example, you might notice that certain verb tenses or prepositions are frequently tested. By summarizing these patterns from your mistakes, you can avoid similar errors in the future.In addition, reading English materials extensively can also contribute to your proficiency in cloze tests. Through reading, you develop a better sense of the language's flow and context, which is invaluable when filling in the blanks.In conclusion, by combining these methods - expanding vocabulary, practicing regularly, and extensive reading - you can significantly enhanceyour skills in English cloze tests and achieve better results.3When it comes to mastering English cloze tests, there are several effective techniques and methods that can greatly enhance your performance. Firstly, developing a sense of language is crucial. You can achieve this by reading a wide range of English articles on a regular basis. This helps improve your sensitivity to the language and enables you to make more accurate judgments in the cloze test. For instance, when you encounter a blank, your intuitive understanding of the language can guide you towards the most appropriate word.Secondly, analyzing the sentence structure is of great significance. By carefully observing the grammar and logic of the sentences, you can identify key words and phrases that provide hints for filling in the blanks. Pay attention to verb tenses, subject-verb agreement, and the relationship between different parts of the sentence.In addition, it is beneficial to build a rich vocabulary. Memorizing words and their usage in various contexts will expand your options when choosing the correct words for the blanks. Moreover, practicing regularly with mock cloze tests is essential. Through repeated practice, you can familiarize yourself with different types of questions and improve your speed and accuracy.In conclusion, by combining these techniques and methods, andmaintaining a consistent effort and practice, you will undoubtedly make significant progress in English cloze tests and enhance your overall language proficiency.4When it comes to dealing with English cloze tests, having the right techniques and methods can make a significant difference. One of the most effective strategies is to make full use of the elimination method. By carefully analyzing each option and eliminating those that are clearly incorrect based on grammar, vocabulary or context, we can narrow down the choices and increase the chances of picking the correct one. For instance, if a verb tense doesn't match the overall tense of the passage, it can be safely crossed out.Another useful approach is to understand the context of the article based on real-life experiences. Imagine yourself in the situation described and think about how things would typically unfold. This helps us make more logical and intuitive choices. Say, if the story is about a shopping trip, we can draw from our own shopping experiences to understand the characters' feelings and actions.Also, paying close attention to the fixed phrases and collocations is crucial. Some words always go together in a particular way in the English language. Recognizing these patterns can give us a clue as to which option is the right fit.In conclusion, with the combination of these techniques and continuous practice, we can improve our performance in English cloze tests and enhance our language proficiency.5When it comes to the challenging task of dealing with English cloze tests, there are several remarkable techniques and methods that can significantly enhance our performance. Firstly, it is of great essence to study the regular patterns of the test questions. By analyzing a considerable number of past papers, we can identify the common types of blanks and the logic behind them. For instance, we might notice that certain words or phrases tend to be frequently tested in a particular context.Another effective approach is to train ourselves in a targeted manner. We can focus on specific grammar points or vocabulary that are often involved in cloze tests and practice with relevant exercises. This helps us to consolidate our knowledge and improve our accuracy in answering such questions.Furthermore, adopting the thinking mode of native English speakers can also be extremely beneficial. Trying to think like them enables us to better understand the language's natural flow and make more intuitive choices. We can achieve this by reading extensive English materials, such as novels, newspapers, and magazines, to immerse ourselves in the language environment.In conclusion, by mastering these techniques and methods, and through continuous practice and reflection, we can undoubtedly make great progress in English cloze tests and improve our overall language proficiency.。
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Applying Model-Based Techniques to the Development of UIs for Mobile ComputersJacob Eisenstein, Jean Vanderdonckt, and Angel PuertaRedWhale Software CorporationTown and Country Village Suite 273-277, Palo Alto, CA 94301{jacob, jeanvdd, puerta}@ABSTRACTMobile computing poses a series of unique challenges for user interface design and development: user interfaces must now accommodate the capabilities of various access devices and be suitable for different contexts of use, while preserving consistency and usability. We propose a set of techniques that will aid UI designers who are working in the domain of mobile computing. These techniques will allow designers to build UIs across several platforms, while respecting the unique constraints posed by each platform. In addition, these techniques will help designers to recognize and accommodate the unique contexts in which mobile computing occurs. Central to our approach is the development of a user-interface model that serves to isolate those features that are common to the various contexts of use, and to specify how the user-interface should adjust when the context changes. We claim that without some abstract description of the UI, it is likely that the design and the development of user-interfaces for mobile computing will be very time consuming, error-prone or even doomed to failure.KeywordsUser-interface modeling, mobile computing, task model, platform constraints, plastic user-interface, adaptive user-interfaceINTRODUCTIONMobile computing poses a series of unique challenges for user interface (UI) design and development [20]. UIs must run on many different computing platforms [21], ranging from the powerful workstation to the tiny cellular phone. Each computing platform has its own constraints: some devices are immobile (e.g., a home-based Internet Screen Phone) while others are mobile (e.g., a Personal Digital Assistant – PDA); some support extensive graphical capabilities (e.g., a large monitor), while others only provide limited interaction capabilities (e.g., a cellular phone); some are equipped with enhanced input/output devices (e.g., a trackball), while others are constrained by limited input [7, 12]. In addition, mobile computing increases the probability of environmental change while the user is carrying out the task: e.g., the train may go into a dark tunnel, forcing the screen of the PDA to dim; the surrounding noise level may rise, forcing the volume of audio feedback to increase so it can still be heard.To meet these challenges, the most frequently adopted practice consists in developing unique UIs for each case. This poses further problems. Foremost is the unnecessary repetition involved in implementing a UI again and again, for each platform and usage case. In addition, a consistent UI design must be implemented across several platforms, even though that design will likely be implemented by many different designers, each with unique skills, experiences, and preferences. Revisions to the proposed design must be implemented multiple times, and the introduction of a new device requires a re-implementation of the UI.Clearly, current practices for UI design for mobile computers are in need of significant improvement. We believe that user interface modeling will be an essential component of any effective long term approach to developing UIs for mobile computing. User-interface modeling[22] involves the creation of knowledge bases that describe various components of the user-interface, such as the presentation, the dialog, the platform, the task structure, and the context. These knowledge bases can be further exploited to automatically produce a usable UI matching the requirements of each context of use.MANNA: THE MAP ANNOTATION ASSISTANTIn this section we describe MANNA, a hypothetical software application that reveals many of the challenges posed by user-interface development for mobile computing. MANNA is a multimedia application that must run on several platforms and can be utilized collaboratively over the internet. It is intended to be used by geologists, engineers, and military personnel to create annotated maps of geographical areas. Annotations can include text, audio, video, or even virtual reality walk-through.In our scenario, a geologist from the United States Geological Survey has been dispatched to a remote location in northern California to examine the effects of a recent earthquake. Using a desktop workstation, our geologist downloadsPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.IUI’01, January 14-17, 2001, Santa Fe, New Mexico, USA.Copyright 2001 ACM 1-58113-325-1/01/0001…$5.00.existing maps and reports on the area to prepare for her visit (fig. 1). The desktop workstation poses few limiting constraints to UI development, but unfortunately, it is totally immobile. The documents are downloaded to a laptop, and the geologist boards a plane for the site.On the plane, the laptop is not networked, so commands that rely on a network connection are disabled. When the geologist examines video of the site, the UI switches to a black-and-white display, and reduces the rate of frames per second. This helps to conserve battery power. In addition, because many users find laptop touch pads inconvenient, interactors that are keyboard-friendly are preferred, e.g., drop-lists are replaced by list boxes.After arriving at the airport, the geologist rents a car and drives to site. She receives a message through the MANNA system to her cellular phone, alerting her to examine a particular location. Because a cellular phone offers extremely limited screen-space, the map of the region is not displayed. Instead, the cell phone shows the geographical location, driving directions, and the geologist's current GPS position. A facility for responding to the message is also provided. Finally arriving at the site, our geologist uses a palmtop computer to make notes on the region (fig. 6). Since the palmtop relies on a touch pen for interaction, interactors that require double-clicks and right-clicks are not permitted. Screen size is a concern here, so a more conservative layout is employed. Having completed the investigation, our geologist prepares a presentation in two formats. First, an annotated walk-through is presented on a heads-up display (HUD). Because of the HUD's limited capabilities for handling textual input, speech-based interactors are used instead. A more conventionalpresentation is prepared for a high-resolution large-screen display.Since this is a final presentation, theusers will not wish to addinformation, and interactors that areintended for that purpose areremoved. The layout adapts toaccommodate the larger screenspace, and important information isplaced near the center and top,where everyone in the audience cansee it.THE USER-INTERFACE MODELThe highly adaptive, multi-platformuser-interface described in thisscenario would be extremelydifficult to realize usingconventional UI-design techniques.We will describe a set of model-based techniques that can greatlyfacilitate the design of such UIs. All such techniques depend on the development of a user-interface model, which we define as a formal, declarative, implementation-neutral description of the UI. A UI model is expressed by a modeling language; that language should be declarative, so that it can be edited by hand, but it should be formal so that it can be understood and analyzed by a software system. The MIMIC modeling language meets these criteria, and it is the language we have chosen to use for UI modeling [16].MIMIC is a comprehensive UI modeling language; ideally, all relevant aspects of the UI are included in a MIMIC UI model. However, we will focus on the three model components that are relevant to our design techniques for mobile computing: platform model, presentation model, and task model.A platform model describes the various computer systems that may run a UI [19]. This model includes information regarding the constraints placed on the UI by the platform. The platform model contains an element for each platform that is supported, and each element contains attributes describing features and constraints. The platform model may be exploited at design time and be used as a static entity. In this case, a set of user-interface can be generated: one for each platform that is desired. However, we prefer the dynamic exploitation of the platform model at run-time, so that it can be sensitive to changing conditions of use. For example, the platform model should recognize a sudden reduction in bandwidth, and the UI should respond appropriately.A presentation model describes the visual appearance of the user interface. The presentation model includes informationFigure 1. The desktop UI design for MANNA. Hyperlinks are indicated by color, and are underlined only when the mouse rolls over them.describing the hierarchy of windows and their widgets (e.g., sliders, list boxes), stylistic choices, and the selection and placement of these widgets. Widgets are described in accordance with the traditional distinction between AIOs and CIOs [25]. Each widget is modeled abstractly as an AIO: an abstract interaction object, which is platform-neutral. Then each AIO is associated with several CIOs: concrete interaction objects, which are executable on a specific platform. CIOs inherit some of their behavior from AIOs, and may supply some additional parameters. The CIO/AIO distinction allows our UI models to run on any computing platform, as long as the appropriate CIOs are present. Figure 2 describes the relationship between an AIO (the Push Button), several related CIOs, and the platforms on which they are instantiated.A task model is a structured representation of the tasks that the user of the software may want to perform. The task model is hierarchically decomposed into subtasks, and informationregarding goals, preconditions, and postconditions may be supplied [23]. In addition, we model features such as whether a task is optional, whether it may be repeated, and whether it enables another sub-task.By no means are these the only models that we consider relevant to mobile computing. For many applications, it is essential to model the users themselves, especially when there are multiple users with different preferences, abilities, and privileges. It is also often appropriate to model the domain characteristics of the tasks supported by the UI. Such information often guides the selection of widgets [9,13,25]. However, the techniques that we have developed for UI design for mobile computing depend only on the three models already described.Although the internal structure of each model component plays a significant role in the overall design of the UI, our approach places special emphasis on the connections between the various model components. We feel that it is these mappings that determine the interactive behavior of a UI. For mobile UIs, we are most concerned with the connections between the platform model and the presentation model. These connections describe how the constraints posed by the various platforms will influence the visual UI appearance. We are also interested in the task model, and how it relates to the other two models. The next section will describe how some platforms naturally lend themselves to specific tasks, and how this information can be used to tailor the presentation accordingly.TECHNIQUES FOR SUPPORTING MOBILE UIsIn this section, we describe a spectrum of model-based techniques that can be used to support mobile computing. Each technique involves creating mappings between the various model components that we have discussed. These mappings are interpreted to produce a UI that is specially customized for the relevant device and context of use. Handling Platform ConstraintsOne obvious constraint that is often posed by mobile computing platforms is the display resolution, which can range from a wall-size flat screen to a cellular phone to a head-mounted immersive environment. We will use this screen resolution constraint as an example case, and describe some methods for dealing with it, while showing how these methods might also be applied to other constraints. The screen resolution constraint was chosen because we feel that in many ways it is the most difficult constraint to deal with; whereas other constraints, such as limited interaction capabilities, can be handled through interactor selection, the screen space constraint often requires a more global solution. The screen resolution is typically expressed in pixels (e.g., 1024x768). It should not be confused with the screen surface area; two displays having different sized surfaces can share the same resolution. Because of screen resolution differences, an optimal layout for one display may be simply impossible to render on another device. This problem is particularly salient for mobile computing, because so many mobile platforms possess small-size, low-resolution displays. There are three parameters that contribute to the amount of display size required by a user-interface design: size of the individual interactors, layout of interactors within a window, and the allocation of interactors among several windows.Interactor Size.There are two possible methods for accommodating screen resolution constraints by adjusting the size of the interactors. The first possibility is simply to shrink the interactors, while observing usability constraints related to the AIO type. For example, the length of an edit box can be reduced to a minimum (e.g., 6 characters visible at the same time with horizontal scrolling) while its height cannot be decreasedbelow the limit of the smallest font size legible (e.g., 8 Figure 2. Concrete Interaction Objects are subclassed from an Abstract Interaction Object, and are then mapped on to specific platforms.pixels); usability experiments have determined that the minimum size for an icon is roughly 8 by 6 pixels.Of course, many interactors simply cannot be shrunk to any significant extent. An alternative to reducing the size dimensions of an interactor is to replace that interactor with a smaller alternative. For example, a Boolean checkbox typically requires less screen space than a pair of radio buttons. The technique of automatically selecting an appropriate interactor while considering screen resolution constraints has already been investigated and shown to be feasible [9,13,26].These techniques can easily be applied to constraints other than screen resolution. Interactors can be parameterized to reduce bandwidth usage or battery consumption–for example, a video player can reduce the frame rate or the number of colors. This parameterization is similar to reducing the display size of interactors. Likewise, interactor selection can be performed to accommodate reduced interaction capabilities. For example, a handwriting-based interactor from a PDA could be replaced with a voice-based interactor on a cellular phone. When there are several criteria that need to be optimized – e.g., screen size, usability, and power consumption – interactor selection can become a multidimensional optimization problem. An algorithm for solving this problem would be beyond the scope of this paper, but we hope to explore it in the future.Returning to the matter of screen resolution, we see that both techniques for adjusting the size of the interactors in a UI can help us to find an appropriately-sized presentation. However, we believe that in many cases, a more global solution isnecessary. A WAP-enabled cellular phone can display only one or two interactors at a time, no matter how small they are. To achieve the amount of flexibility necessary to support all mobile devices, we will have to examine window layout and the allocation of interactors among windows.Selecting the Appropriate Presentation StructureThe remaining two parameters—layout of interactors within a window, and allocation of interactors between windows—can be grouped together under the mantle of presentation structure. We want to select the appropriate presentation structure, given the constraint of the amount of screen-resolution afforded by a platform. To solve this problem, we need a set of alternative presentation structures, which can be generated by the designer or with the help of the system. The simplest solution would then involve creating mappings between each platform and an appropriate presentation structure.However, in this case a more dynamic solution is possible. Recall that the screen resolution of each device is represented declaratively in the platform model. Similarly, it is possible to represent the amount of screen space required by each presentation structure in the presentation model. We can exploit this knowledge by constructing an intelligentmediator agent [1,2]. This mediator should determine the maximum usable screen resolution for the relevant device, and evaluate the amount of screen resolution required by each presentation structure alternative. It can then select the presentation structure that consumes an amount of screen resolution that falls just under the maximum (fig. 3).This more dynamic solution is preferable because it accounts for the fact that the screen resolution of a device may change while it is in use. Moreover, it eases the integration of new devices into the platform model. Rather than forcing the user to explicitly specify the appropriate presentation structure for a new device, the user needs only to specify the amount of available screen space, and the mediator will find the correct mapping.Generating the Appropriate Presentation StructureUnder our proposed architecture, it is still left to the interface designer to specify a set of alternative presentation structures. However, it would be better if the correct presentation structure could be generated by the system, given a set of user-defined constraints [1,13,14,26]. For this purpose, we need to consider additional elements in our presentation Figure 3: A mediating agent dynamically selects theappropriate presentation model for each device.model besides AIOs and CIOs. Two new abstractions need to be defined:1. Logical Window (LW): this can be any grouping ofAIOs—a physical window, a subwindow area, a dialog box or a panel. Every LW is itself a composite AIO as itis composed of other simple or composite AIOs. All LWs should be physically constrained by the user's screen.2. Presentation Unit (PU): a PU is defined as a completepresentation environment required for carrying out a particular interactive task. Each PU can be decomposed into one or many LWs, which may be displayed on the screen simultaneously, alternatively, or in some combination thereof. Each PU is composed of at least one window called the main window, from which navigation to other windows is allowed. For example, a tabbed dialog box can be described as a PU, and it should be decomposed into LWs corresponding to each tab page.The abstractions can be structured into a hierarchy (fig. 4) that serves to expand modeling capabilities of a presentation model. We can use this hierarchy to construct an automated design tool that generates several platform-optimized presentation models from a starting presentation model that is platform independent. This tool could function by employing one of the redesign strategies described below.1. Re-modeling LWs within a PU: the contents of initialLWs are redistributed into new LWs within a single PU.Basic operations involve: ungrouping an LW into severalsmaller LWs; grouping the contents of several LWs intoa single, comprehensive LW; and moving AIOs fromone LW to another. For example, if ample space is available, then the LWs representing several tab sheets can be grouped into a single LW. Alternatively, if spaceis at a premium, the contents of a single window can bebroken into pages of a tab sheet. Some existing toolsapply some of these operations. S EGUIA suggests configurations based on the semantics [26]: minimal (as many logical windows as possible), maximal (one logicalwindow for a PU), input/output (one logical window gathering input while another gathers output for a same function), functional (LWs depending on the functional analysis), and free (as many LWs as the designer wants to). T IMM [18] enables designers to graphically specify how many LWs they want by sliding a cursor on a scroll bar. At one end of the scroll bar, only one LW will be used in a PU; at the other end, one LW is used for each AIO for each LW.2. Re-modeling AIOs within a LW: according to existingconstraints, the contents of an initial LW are redistributed into new AIOs, composite or simple. For example, AIOs contained in a group box are split into smaller group boxes or individual AIOs. A group box can also be replaced by a push button that displays the AIO contained in this box on demand. This technique remains unexplored today. Moreover, we are aware of nounambiguously successful algorithm for the automatic generation of a presentation structure based on these abstractions that has yet been documented. Obviously, both of these techniques leave out the difficult question of dialog layout. M OBILE is a model-based layout tool which designers could use for this purpose [17].As we have said, screen resolution is not the only constraint that must be negotiated. Other constraints include bandwidth usage, battery power consumption, number of display colors, and interaction capabilities. However, unlike the screen-space constraint, these problems do not appear to require a global strategy; they can usually be accommodated through AIO selection. Previous research has addressed the problem of dynamic interactor selection at length, and the issue of platform-specific input constraints has been considered [9,13,25]. We realize that additional constraints may present themselves in the future. While the techniques described in this paper cannot be expected to handle any and all platform-based constraints arising from mobile computing, we feel that this work can serve as a starting point for the development of further model-based solutions.Focusing on Contexts of UseSo far we have assumed that on each device, the user will want to accomplish the same set of tasks. Often this is not the case. A device may be especially suited for a specific subset of the overall task model. For example, in the scenario in Section 2, we know that the cellular phone is especially suited for finding driving directions, because we can assume that if the user were not driving, she would use the PDA. The desktop workstation cannot be brought out into the field, so it is unlikely that it will be used to enter new annotations about a geographical area; rather, it will be used for viewingannotations. Conversely, the highly mobile PDA is the idealdevice for entering new annotations.Through the application of a task model, we can take advantage of this knowledge and optimize the UI for each device. The designer should create mappings between platforms (or classes of platforms) and tasks (or sets of tasks). Additional mappings are then created between task elements and presentation structures that are optimized for a given set of tasks. We can assume these mappings are transitive; as a result, the appropriate presentation model is associated with each platform, based on mappings through the task model. The procedure is depicted in fig. 5. In this figure, the task model is shown to be a mere collection of tasks. This is for simplicity's sake; in reality, the task model is likely to be a highly structured graph where tasks are decomposed into subtasks at a much finer level than shown here.There are several ways in which a presentation model can be optimized for the performance of a specific subset of tasks. Tasks that are thought to be particularly important should be represented by AIOs that are easily accessible. For example, on a PDA, clicking on a spot on the map of our MANNA application should allow the user to enter a new note immediately (fig. 6). However, on the desktop workstation, clicking on a spot on the map brings up a rich set of geographical and meteorological information describing the selected region, while showing previously entered notes. On the cellular phone, driving directions are immediately presented when any location is selected (fig. 7). On the other devices, an additional click is required to get the driving directions. The “bottom arrow” button of the cellular phone enables the user to select other options by scrolling between them. In this way, our treatment of optimizations for the task structure of each device is similar to our treatment of the screen-space constraint: global, structural modifications to the presentation model are often necessary, and adaptive interactor selection alone will not suffice. Here, we propose to solve this problem through the use of several alternative user-generated presentation structures. In many cases, automated generation of these alternative presentation structures would be preferable. We hope to explore the automated generation of task-optimized presentation structures in the future.FUTURE WORKIn the introduction, we mentioned a lack of support for the observation of usability guidelines in the design of user-interfaces for mobile computing. We have experience in implementing model-based UI development environments that incorporate usability guidelines [25,26]. However, the lack of a substantial existing literature on usability guidelines for mobile computing [3,5] prevents us for implementing such a strategy here. As the research literature grows, we hope to provide support for applying these guidelines to mobile UI development.Much of the information found in the platform and task models can be expressed as UI constraints: e.g., screen size, resolution, colors, available interaction devices, task structure, and task parameters (e.g., frequency, motivation). It is therefore tempting to address the problem of generating alternative presentation structures as a constraint-satisfaction problem. In this case, there are two types of constraints: first, features that are common to the user-interface across platforms and contexts of use; second, platform-specific constraints such as screen resolution and available bandwidth. In our future research, we hope to build a constraint-Figure 5. Platform elements are mapped onto high-level taskelements that are especially likely to be performed. In turn, thetask elements are mapped onto presentation models that areoptimized for the performance of a specific task.Figure 6. Final presentation for the PDA.satisfaction system that automatically generates presentation structures.Another possible solution to the problem of generating presentation structures for mobile devices is search. This strategy is motivated by the observation that user-interface guidelines are not always best represented as constraints; sometimes a usability heuristic is a more useful measure. In this case, we can assign a certain penalty to layout decisions, AIO selections, and presentation structures. As there are several usability guidelines, there will be several types of penalties; for example, an AIO may be optimal in regard to usability (and thus incur very little penalty), but may consume too much space (thus incurring a substantial penalty). We hope to design a system that searches for the best possible UI design by minimizing this penalty heuristic. We could then compare the performance of constraint-satisfaction and search as techniques for generating optimal presentation structures.RELATED WORKUser-interface modeling for traditional, non-mobile GUIs has been explored in depth [1,13,14,16,22,26]. Several papers describe graphical model editing tools that relieve the user of the burden of learning a modeling language [10,14,15,16,17,23,25].On an implementation level, the well-understood model-based distinction between AIOs and CIOs figures to play a key role in cross-platform development of all kinds, including mobile computers. Of particular interest is [13], which allows AIOs to be mapped to CIOs depending on user parameters, with the aim of accommodating users with special needs (e.g., user with disabilities). Galaxy [10] and Open Interface render a UI definition on different platforms with their native look and feel, while SUIT [15] provides an additional GUI layer for each supported environment on top of which the UI definition is rendered. The rendering is consequently identical on all supported computing platforms. Although these tools contain some presentation abstractions that are expressed in a platform-neutral format, these abstractions do not accommodate platform constraints.CT-UIMS was the first tool to add a platform component to a user-interface model; it supported some AIO [14] redistribution for OSF/Motif large screens and small Macintosh screens. It had the capability of dynamically deciding which part of a PU can be displayed, by filling the screen up to its maximum. Some LWs can then be omitted if screen constraints are too tight to allow further display.Cicero [1] includes a mediator that tries to allocate resources depending on constraints known at run-time. It also uses a model-based approach, but is more intended to support multimedia presentations rather than GUIs. In [26], Vanderdonckt et al. show how PUs and LWs can be used for database-oriented applications. Thevenin and Coutaz [24] are reusing these concepts for analyzing plastic UIs when a presentation and/or a dialog change according to any non-user variation such as the platform, the context, and the interaction capabilities. For example, a UI can change at run-time to accommodate a reduction of screen real estate.TIMM, a system for automatic selection of interactors, is described in [9,18]; it outputs a set of alternative interactors, and uses a decision tree that takes into account constraints such as screen space. In addition, it includes an adaptive component that learns the designer's preferences.In general, the research efforts described in this section were not directed at the problems posed by mobile computing.CONCLUSIONTechnological push and user pull in the domain of mobile computing are increasing the demand for consistent user-interfaces on a variety of platforms and in a variety of contexts. In this paper, we have described a spectrum of techniques for developing a single, consistent user-interface design for several mobile devices and contexts of use. These techniques range from relatively low-level implementation solutions, such as the use of abstract and concrete interactor objects, to high-level task-based optimization of the interface's presentation structure. Each technique requires that the user-interface be described from a position of abstraction. Our central claim is that the use of abstract, platform-neutral models to describe the user-interface greatly facilitates the development of consistent, usable multi-platform user-interfaces for mobile devices.REFERENCES1. Y. Arens and E.H. Hovy, “The Design of a Model-BasedMultimedia Interaction Manager”, Artificial Intelligence Review, Vol. 9, Nos. 2-3 (1995), pp. 167-188.Figure 7. Final presentation for the cellular phone.。