ABSTRACT A MODEL-BASED APPROACH FOR COMPONENT SIMULATION DEVELOPMENT

规则类的英语短语相关英语短语这个世界充满了规则，没有规矩不成方圆。

那么规则类的英语短语都有哪些呢?下面就由店铺为大家带来关于规则类的英语短语相关英语短语的英语短语集锦，希望大家能有所收获。

关于规则类的英语短语相关英语短语的相关短语规则类rule class规则类吸引子 regular quasi-attractors规则类知识 knowledge in rule form细胞团是磁规则类细菌 Magnetotactic Bacteria规则聚类区域 regular cluster region规则聚类 rules clustering ;关于规则类的英语短语相关英语短语的相关单词规则类关于规则类的英语短语相关英语短语的相关例句规则类是十分简单的，典型情况下只包含一个方法。

The rule class is quite simple, typically containing only a single method.在您详细察看转换之前，我们先要修正规则类，使其能够调用刚刚产生的类。

Before you look in detail at the transform, amend the rule class to invoke this generated class.在规则类被完成之后，它需要通过在分析架构中的所提供的扩展点被描述出来，从而使得代码评审引擎能够将其发现。

After the rule class is completed, it needs to be described through the provided extension pointsin the analysis framework so that the code review engine can discover it.您可能会想，添加一条新规则，要比创建规则类和向插件添加一个扩展容易。

As you might expect, adding a new rule is a simple matter ofcreating a rule class and adding anextension to the plug-in.列表3是一个显示如何执行规则类的代码片段。

学术论文英文摘要模板AbstractSince Dewey developed the concept of “critical thinking”, many scholars abroadhave carried out a series of studies about improving students' critical thinking skills ineducation field. In the 1980s,critical thinking became the target of higher educationprograms in such foreign countries as the US and Canada. It has gained its widespreadattention in China only in recent years. But there are only few studies about it ineducation field. Our traditional English teaching method pays much attention to thetraining of students' linguistic knowledge and language skills but ignores thecultivation of students' critical thinking abilities. In the process of skill practice,teachers often stress the importance of memorizing vocabulary and imitating skillsrigidly,but neglect the students' abilities in analyzing problems and putting forwardinnovative solutions. Therefore, English writing teaching is affected by this andmerely attaches emphasis to train students' reading and writing skills. There are fewstudies which aim at systematically cultivating students' analysis, synthesis, summary,comparison and reasoning skills while they are writing. Therefore,this study aims atdesigning some writingstasks and teaching strategies which can be used to fostercollege students' critical thinking awareness and promote students' all-rounddevelopment.According to six critical thinking skills,this study was carried out by requiringstudents to hand in an argumentation. All participants in this study are non-Englishmajor college freshmen from a 211 key university. The revised version of Rubric forQualitative Critical Thinking Skills Instrument was used in this study. Withquantitative and qualitative analysis,writing experiment is conducted within a wholesemester to collect data concerning students' learning behavior. Reading-to-write isused in experimental class while traditional method is adopted in control class. Thewriting scores by the experimental and control class were statistically processed bysoftware SPSS 19.0. And also the interview was launched in some of students inexperimental class to assess students' critical thinking abilities reflected in theirwritings-The final analysis indicated that EGAP writing model exerted a significantlypositive influence in improving students' critical thinking skills, especially in arousingstudents' writing enthusiasm and critical thinking awareness. Compared with controlclass, students in experimental class made bigprogress in writing competence. Inaddition, this study put forward some reform proposals to the teaching of Englishwriting. The study is of great value to instruct students to employ critical thinkingskills in their writing.AbstractA large body of research has been conducted on the effects of technology-enhancedEnglish vocabulary learning since the 1960s (Marty, 1981)。

第43 卷第 5 期2024 年5 月Vol.43 No.5792~797分析测试学报FENXI CESHI XUEBAO（Journal of Instrumental Analysis）基于反向比例解析的近红外光谱定量模型快速构建方法张晓兵1，徐志强1，钟永健1，朱宏福1，李峥1，张军2，詹映2，彭云发2，刘建国1*（1．浙江中烟工业有限责任公司技术中心，浙江杭州310024；2．上海创和亿电子科技发展有限公司，上海200082）摘要：为解决光谱漂移问题，该研究设计了一种基于反向比例解析的近红外光谱定量模型方法。

以烟叶近红外光谱和烟碱含量为研究对象，将数据划分为训练集和测试集。

通过计算训练集光谱与测试集光谱的相关性并按照高低排序，选择前20%的光谱，运用约束规划的方法，计算测试集的拟合系数，得到测试集光谱的估计值。

结果显示，使用反向比例解析法建立的模型的平均绝对误差为0.346 6，预测标准偏差为0.425 2，相关系数为0.793 2，优于PLS模型。

反向光谱比例解析可以有效解决光谱漂移问题，实现烟草中烟碱含量的准确预测，为烟碱的有效测量提供参考。

关键词：反向比例；近红外光谱；相关性；拟合系数；加权中图分类号：O657.3；TS41文献标识码：A文章编号：1004-4957（2024）05-0792-06A Rapid Construction Method for Near Infrared Spectral Quantita⁃tive Model Based on Reverse Proportional AnalysisZHANG Xiao-bing1，XU Zhi-qiang1，ZHONG Yong-jian1，ZHU Hong-fu1，LI Zheng1，ZHANG Jun2，ZHAN Ying2，PENG Yun-fa2，LIU Jian-guo1*（1．Technology Center of China Tobacco Zhejiang Industrial Co.，Ltd.，Hangzhou　310024，China；2．Shanghai Micro Vision Technology LTD.，Shanghai　200082，China）Abstract：To address the issue of spectral drift，this study proposes a quantitative model approach for near infrared spectroscopy based on reverse proportional analytical method. The research focuses on tobacco leaf near infrared spectra and nicotine content，with the data being divided into training and test sets. By calculating the correlation between the spectra in these sets and sorting them accord⁃ingly，select the top 20% of spectra for constraint programming calculation to estimate the spectra in the test set. The results demonstrate that the reverse proportional analytical method yields an average absolute error of 0.346 6，a predicted standard deviation of 0.425 2，and a correlation coefficient of 0.793 2，indicating its strong performance compared to PLS models. This highlights how the reverse spectral proportional analytical method effectively addresses spectral drift while accurately predicting nicotine content in tobacco，providing valuable insights for nicotine measurement.Key words：inverse proportion；near infrared spectroscopy；correlation；fit coefficient；weighted近红外光谱分析技术作为一种绿色分析技术，融合了光谱技术、信息学、化学计量学和计算机技术［1］，具有简单、高效、快速等优势，受到行业内的广泛关注。

赏识教育的外文文献Title: Appreciative Education: A Holistic Approach to Fostering Scholarly DelightAbstract:Appreciative Education is a comprehensive pedagogical approach that emphasizes the recognition and enhancement of students' strengths and talents. It focuses on fostering an atmosphere of positivity, empathy, and mutual respect within the educational setting. By shifting the focus from adeficit-based approach to one that appreciates and builds upon students' capacities, Appreciative Education aims to promote learner engagement, motivation, and academic success. This paper explores the theoretical framework of Appreciative Education, its core principles, and its potentialimplications for transformative educational practices.Introduction:In traditional educational models, students' weaknesses and deficiencies receive more attention than their strengths and abilities. This deficit-based approach often results in demotivation, disengagement, and low self-esteem among students. In response to these challenges, Appreciative Education emerged as an alternative approach that seeks to cultivate an environment of flourishing and celebration of students' unique qualities. Grounded in positive psychology, this pedagogical philosophy acknowledges the power ofpositive reinforcement, authentic feedback, and collective appreciation.Theoretical Underpinnings of Appreciative Education:Appreciative Education draws from several theoretical perspectives such as positive psychology, positive organizational scholarship, and strength-based theories. It incorporates concepts such as positive emotions, character strengths, resilience, and well-being into the educational framework. By focusing on students' inherent strengths and abilities, educators can create a learning environment that fosters personal and academic growth, deep engagement, and a sense of accomplishment.Core Principles of Appreciative Education:1. Asset-Based Thinking: Appreciative Education encouragesboth educators and students to adopt an asset-based thinking approach. Rather than focusing on problems and deficits, the emphasis is placed on identifying and nurturing students' unique talents, strengths, and passions.2. Strengths-Based Feedback: Feedback in Appreciative Education revolves around acknowledging and building on students' strengths. Educators provide specific, genuine, and constructive feedback that aims to capitalize on students' existing skills while encouraging continuous improvement.3. Inclusive and Empathetic Community: Appreciative Education promotes the development of an inclusive and empathetic school or educational community. It involves fostering positive relationships, creating a sense of belonging, and valuing diversity among students and educators.Implications for Transformative Educational Practices: Appreciative Education has the potential to transform traditional educational practices by creating student-centered learning environments. It has been linked to increased student engagement, academic achievement, andoverall well-being. Additionally, it can foster positiveteacher-student relationships, enhance intrinsic motivation, and promote a culture of collaboration and support.Conclusion:Appreciative Education offers a paradigm shift in how education is conceptualized and implemented. By focusing on students' strengths and talents, this approach helps build resilient, self-confident, and successful learners. Further research and practical implementation of Appreciative Education principles can contribute to the creation of more joyful, inclusive, and effective educational settings globally.。

专利名称：System and method for a multiclassapproach for confidence modeling inautomatic speech recognition systems 发明人：SUNDARAM,Ramasubramanian,GANAPATHIRAJU,Aravind,TAN, Yingyi申请号：AU2019270168申请日：20190517公开号：AU2019270168A1公开日：20201203专利内容由知识产权出版社提供摘要：A system and method are presented for a multiclass approach for confidence modeling in automatic speech recognition systems. A confidence model may be trained offline using supervised learning. A decoding module is utilized within the system that generates features for audio files in audio data. The features are used to generate a hypothesized segment of speech which is compared to a known segment of speech using edit distances. Comparisons are labeled from one of a plurality of output classes. The labels correspond to the degree to which speech is converted to text correctly or not. The trained confidence models can be applied in a variety of systems, including interactive voice response systems, keyword spotters, and open-ended dialog systems.申请人：Greeneden U.S. Holdings II, LLC代理人：Spruson & Ferguson更多信息请下载全文后查看。

2008-01-0085Model-Based Design for Hybrid Electric Vehicle SystemsSaurabh Mahapatra, Tom Egel, Raahul Hassan, Rohit Shenoy, Michael Carone Copyright © 2008 The MathWorks, Inc.ABSTRACTIn this paper, we show how Model-Based Design can be applied in the development of a hybrid electric vehicle system. The paper explains how Model-Based Design begins with defining the design requirements that can be traced throughout the development process. This leads to the development of component models of the physical system, such as the power distribution system and mechanical driveline. We also show the development of an energy management strategy for several modes of operation including the full electric, hybrid, and combustion engine modes. Finally, we show how an integrated environment facilitates the combination of various subsystems and enables engineers to verify that overall performance meets the desired requirements. 1. INTRODUCTIONIn recent years, research in hybrid electric vehicle (HEV) development has focused on various aspects of design, such as component architecture, engine efficiency, reduced fuel emissions, materials for lighter components, power electronics, efficient motors, and high-power density batteries. Increasing fuel economy and minimizing the harmful effects of the automobile on the environment have been the primary motivations driving innovation in these areas.Governmental regulation around the world has become more stringent, requiring lower emissions for automobiles (particularly U.S. EPA Tier 2 Bin 5, followed by Euro 5). Engineers now must create designs that meet those requirements without incurring significant increases in cost. According to the 2007 SAE’s DuPont Engineering survey, automotive engineers feel that cost reduction and fuel efficiency pressures dominate their work life [1] and will continue to play an important role in their future development work.In this paper, we explore key aspects of hybrid electric vehicle design and outline how Model-Based Design can offer an efficient solution to some of the key issues. Due to the limited scope of the paper, we do not expect to solve the problem in totality or offer an optimal design solution. Instead, we offer examples that will illustrateThe MathWorks, Inc.the potential benefits of using Model-Based Design in the engineering workflow. Traditionally, Model-Based Design has been used primarily for controller development.One of the goals of this paper is to show how Model-Based Design can be used throughout the entire system design process.In section 2, we offer a short primer on HEVs and the various aspects of the design. Section 3 is devoted to Model-Based Design and the applicability of the approach to HEV development. Sections 4, 5, and 6 will focus on examples of using Model-Based Design in a typical HEV design.2. HYBRID ELECTRIC VEHICLE DESIGNCONCEPTA block diagram of one possible hybrid electric vehicle architecture is shown in Figure1. The arrows represent possible power flows. Designs can also include a generator that is placed between the power splitter and the battery allowing excess energy to flow back into thebattery.Figure 1: The main components of a hybrid electric vehicle.Conceptually, the hybrid electric vehicle has characteristics of both the electric vehicle and the ICE (Internal Combustion Engine) vehicle. At low speeds, it operates as an electric vehicle with the battery supplying the drive power. At higher speeds, the engine and the battery work together to meet the drive power demand. The sharing and the distribution of power between thesetwo sources are key determinants of fuel efficiency. Note that there are many other possible designs given the many ways that power sources can work together to meet total demand.DESIGN CONSIDERATIONSThe key issues in HEV design [2] are typical of classical engineering problems that involve multilayer, multidomain complexity with tradeoffs. Here, we discuss briefly the key aspects of the component design: very similar to those of a traditional ICE. Engines used in an HEV are typically smaller than that of a conventional vehicle of the same size and the size selected will depend on the total power needs of the vehicle.design are capacity, discharge characteristics and safety. Traditionally, a higher capacity is associated with increase in size and weight. Discharge characteristics determine the dynamic response of electrical components to extract or supply energy to the battery. motors, AC induction motors, or Permanent Magnet Synchronous Motors (PMSM). Each motor has advantages and disadvantages that determine its suitability for a particular application. In this list, the PMSM has the highest power density and the DC motor has the lowest. [3].splitter that allows power flows from the two power sources to the driveshaft. The engine is typically connected to the sun gear while the motor is connected to the ring gear.aerodynamic drag interactions with weight and gradability factors accounted for in the equations.process of the hybrid powertrain is to study the maximum torque demand of the vehicle as a function of the vehicle speed. A typical graph is shown in Figure 2. Ratings of the motor and the engine are determined iteratively to satisfy performance criteria and constraints. The acceleration capabilities are determined by the peak power output of the motor while the engine delivers the power for cruising at rated velocity, assuming that the battery energy is limited. Power sources are coupled to supply power by the power-splitter, and the gear ratio of the power-splitter is determined in tandem. The next steps include developing efficient management strategies for these power sources to optimize fuel economy and designing the controllers. The final steps focus on optimizing the performance of this system under a variety of operating conditions.Figure 2: Maximum torque demand as a function of vehicle tire speed.3. MODEL-BASED DESIGN OF AN HEVMOTIVATIONIn this section, we outline some of the challenges associated with HEV design and explain the motivation for using Model-Based Design as a viable approach for solving this problem.of an HEV design problem is reflected in the large number of variables involved and the complex nonlinear relationships between them. Analytical solutions to this problem require advanced modeling capabilities and robust computational methods.set of requirements to meet the vehicle performance and functionality goals. Requirements refinement proceeds iteratively and depends on implementation costs and equipment availability.conceptualize the operation of the system’s various components and understand the complex interactions between them. This often requires experimentation with various system topologies. For example, studies may include comparing a series configuration with a parallel configuration. Because the goal is a better understanding of the overallsystem behavior, the models must include the appropriate level of detail. system level to a more detailed implementation, engineers elaborate the subsystem models to realize the complete detailed system model. This can be accomplished by replacing each initial model of a component with the detailed model and observing the effects on performance. Completing this process andrealizing a detailed model of the system requires robust algorithms for solving complex mathematics in a timely fashion.and mechanical components. Typically these components are designed by domain specialists. To speed development, these engineers need to effectively communicate and exchange design ideas with a minimum of ambiguity.typical HEV design is to increase the fuel efficiency of the vehicle while maintaining performance demands. Intuitively, one can look at this problem as finding the optimal use of the power sources as a function of the vehicle internal states, inputs, and outputs satisfying various constraints. This translates to the requirement for switching between various operational “power modes” of the vehicle as a func tion of the states, inputs, and measured outputs [4]. In a true environment for Model-Based Design the power management algorithms co-exist with the physical system models.complexity of the various subsystems, HEV controller design is typically a complex task. A variety of control algorithms specific to each subsystem may be required. For example, the controller that manages the frequency of the input voltage to the synchronous motor will be different from the simple control used for torque control of the same motor. Typically, this will manifest itself as a multistage, multiloop control problem. Successful implementation of the controllers requires deployment of these algorithms on processors that are integrated while interfacing with the physical plant. testing ensures that it continues to meet requirements. Detection of errors early in the process helps reduce costs associated with faulty designs. As design errors trickle down the various workflow stages the costs associated with correcting them increase rapidly[5]. The ability to continually verify and validate that requirements are being satisfied isa key aspect of Model-Based Design.A software development environment for Model-Based Design must be able to address the aforementioned challenges. Additionally, a single integrated environment facilitates model sharing between team members. The ability to create models at various levels of abstraction is needed to optimize the simulation time. A mechanism for accelerating the simulation as the complexity increases will also be important. PROCESS OF MODEL-BASED DESIGNModel-Based Design can be thought of as a process of continually elaborating simulation models in order to verify the system performance. The overall goal is to ensure first pass success when building the physicalprototype. Figure 3 shows the key elements of Model-Based Design.The system model forms the “executable specification” that is used to communicate the desired system performance. This model is handed over to the various specialists who use simulation to design and further elaborate the subsystem models. These specialists refine the requirements further by adding details or modifying them. The detailed models are then integrated back into the system level realization piece by piece and verified through simulation. This goes on iteratively until a convergence to an optimal design that best meets the requirements results. During Model-Based Design, C-code generation becomes an essential tool for verifying the system model. The control algorithm model can be automatically converted to code and quickly deployed to the target processor for immediate testing. Code can also be generated for the physical system to accelerate the simulation and/or to test the controller with Hardwarein the Loop simulation.Figure 3: The key elements of Model-Based Design.4. SYSTEM LEVEL MODELING OF AN HEVIn the first stage of the HEV design, the system-level description of the system is realized. Experimentation enables the system designer to explore innovative solutions in the design space resulting in optimal architectures. Our approach has been inspired by an earlier SAE paper [6]. REQUIREMENTSIn the initial stages of the project, it is not uncommon for the specifications of subsystem components to shift. The requirements are in a preliminary form, and are based on previous designs, if available, or best engineering judgment. Requirements are refined when each of the component models is delivered to component designers for additional refinement. There are, however, certain requirements that the system architect understands fully, and can lock down. As the project moves from requirements gathering to specification, the concepts of the system architects can be included in the model. Collaboration between architects and designers leads to a much better and more complete specification. The system can be expressed as a series of separate models that are to be aggregated into an overall system model for testing. Breaking down the model into components facilitates component-based development and allows several teams to work on individual components in parallel. This kind of concurrent development was facilitated by the parallel configuration we chose for our example, in which the electrical and mechanical power sources supply power in parallel. The broad design goals were:Improve fuel efficiency to consume less than 6.5liters per 100 km (L/100 km) for the driver input profile shown in Figure 4.Cover a quarter mile in 25 seconds from rest. Attain a top speed of 193 kph.Figure 4: Driver input profile as outlined in the requirements document.These and other such requirements are typically captured in a requirements document that engineers can associate with the design models. This provides the ability to trace the requirements throughout the model, a key component of Model-Based Design. VEHICLE DYNAMICSModeling the vehicle dynamics can be a challenging task. When creating any simulation model it is important to consider only the effects that are needed to solve the problem at hand. Superfluous details in a model will only slow down the simulation while providing little or noadditional benefit. Because we are primarily interested in the drive cycle performance, we will limit our vehicle model to longitudinal dynamics only. For example, the vehicle was initially modeled as a simple inertial load on a rotating shaft connected to the drive train. ENGINEA complete engine model with a full combustion cycle is also too detailed for this application. Instead, we need a simpler model that provides the torque output for a given throttle command. Using Simulink® and SimDriveLine™, we modeled a 57kW engine with maximum power delivery at 523 radians per second, as shown in Figure5.Figure 5: Engine modeled using blocks from the SimDriveline™ library. SYNCHRONOUS MOTOR/GENERATORThe synchronous motor and generator present an interesting example of electromechanical system modeling. Standard techniques for modeling synchronous machines typically require complex analysis of equations involving electrical and mechanical domains. Because the input source to this machine drive is a DC battery and the output is AC, this would require the creation of complex machine drive and controller designs – often a significant challenge at this stage.An averaged model that mathematically relates the control voltage input with the output torque and resulting speed is a useful alternative. This simplification allows us to focus on the overall behavior of this subsystem without having to worry about the inner workings. Furthermore, we can eliminate the machine drive by simply feeding the DC voltage directly to this subsystem. With this averaged model, we only need a simple Proportional-Integral (PI) controller to ensure effective torque control. TheMotor/Generator subsystem design will be explored in more detail in the next section. POWER-SPLITTERThe power-splitter component is modeled as a simple planetary gear, as shown in Figure 6. With these building blocks, more complex gear topologies can easily be constructed and tested within the overall system model.Figure 6: Power-splitter modeled as a planetary gear with connections.POWER MANAGEMENTThe power management subsystem plays a critical role in fuel efficiency.The subsystem has three main components:• Mode logic that manages the various operatingmodes of the vehicle.• An energy computation block that computes theenergy required to be delivered by the engine, the motor, or both in response to gas pedal input at any given speed.• An engine controller that ensures the engine is theprimary source of power and provides most of the torque. The motor and generator controllers provide torque and speed control.MODE LOGICFor efficient power management, an understanding of the economics of managing the power flow in the system is required. For example, during deceleration, the kinetic energy of the wheels can be partially converted to electrical energy and stored in the batteries. This implies that the system must be able to operate in different modes to allow the most efficient use of the power sources.We used the conceptual framework shown in Figure 7 to visualize the various power management modes.Algorithm design starts with a broad understanding of the various possible operating modes of the system. In our example, we identified four modes—low speed/start, acceleration, cruising, and braking modes. For each of these modes, we determined which of the power sources should be on and which should be off.The conceptual framework of the mode logic is easily implemented as statechart. Statecharts enable the algorithm designer to communicate the logic in an intuitive, readable form.Figure 7: Mode logic conceptualized for the hybrid vehicle.The Stateflow® chart shown in Figure 8 is a realization of the conceptual framework shown in Figure 7. While very similar to the conceptual framework, the Stateflow chart has two notable differences. The “acceleration” and “cruise” states have been grouped to form the “normal” superstate, and the “low speed/start” and “normal” states have been grouped together to form the “motion” superstate. This grou ping helps organize the mode logic into a hierarchical structure that is simpler to visualize and debug.Figure 8: Mode logic modeled with Stateflow®. SYSTEM REALIZATIONAfter the HEV components have been designed, they can be assembled to form the parallel hybrid system shown in Figure9.Figure 9: System-level model of the parallel HEV.This system model can then be simulated to determine if the vehicle meets the desired performance criteria over different drive cycles. As an example, for the input to the system shown in Figure 4, the corresponding speed and the liters per 100 km (L/100 km) outputs are shown in Figure 10. Once the baseline system performance has been evaluated using the system model, we begin the process of model elaboration. In this process, we add more details to the subsystems models to make them more closely represent the actual implementation. During this process, design alternatives can be explored and decisions made based on the analysis results. This is a highly iterative process that is accelerated using Model-Based Design.5. MODEL ELABORATIONIn the model elaboration stage, the subsystem components undergo elaboration in parallel with requirements refinement.A subsystem block is an executable specification because it can be used to verify that the detailed model meets the original set of requirements.As an example, we show how the generator machine drive undergoes requirements refinement and model elaboration. We assume that the engineer responsible for themachine drive design will carry out the model elaboration of the plant and the associated controller.REQUIREMENTS REFINEMENTThe machine drive is an aggregated model of the machine and the power electronics drive. In the system level modeling phase, the key specification is the torque-speed relationship and the power loss. This information was sufficient to define an abstract model to meet the high-level conceptual requirements.Figure 10: Output speed and L/100 km metric for the averaged model.As additional design details are specified, the model must become more detailed to satisfy the subsystem requirements. For example, the generator model will need parameters such as the machine circuit equivalent values for resistance and inductance. Engineers can use this specification as the starting point towards the construction of an electric machine customized for this HEV application.In the case of the generator drive, as the machine model is elaborated from an averaged model to a full three phase synchronous machine implementation, the controller must also be elaborated. PLANT ELABORATIONThe machine model for the synchronous generator is elaborated using SimPowerSystems™ blocks that represent detailed models of power system components and drives. For this model, the electrical and mechanical parts of the machine are each represented by a second-order state-space model. Additionally, the internal flux distribution can be either sinusoidal or trapezoidal. This level of modeling detail is needed to make design decisions as the elaboration process progresses.Figure 11: Detailed PMSM model parameters.The details of this model are captured in the model parameters shown in Figure 11, which specify the effects of internal electrical and magnetic structures.CONTROL ELABORATIONThe controller used in the averaged model of the AC machine drive is a simple PI controller. In model elaboration of the synchronous machine plant, a DC battery source supplies energy to the AC synchronous machine via an inverter circuit that converts DC to AC. These changes in plant model structure and detail require appropriate changes to the controller model to handle different control inputs and implement a new strategy. For example, the power flow to the synchronous machine is controlled by the switching control of the three phase inverter circuit. This added complexity was not present in the initial model of the machine drive because we focused on its behavior rather than its structure. We implemented a sophisticated control strategy, shown in Figure 12, that included cascaded speed and vector controllers [7]. The controllers were developed using Simulink® Control Design™ to satisfy stability and performance requirements.VERIFICATION AND VALIDATIONAt every step of the model elaboration process, the model is verified and validated. Figure 13 shows the averaged and detailed models as they are tested in parallel.Figure 12: Controller elaboration as we move from averaged (top) to detailed (below) model.The test case is a 110 radians per second step input to the machine. The response, shown in Figure 14, reveals comparable performance of both models. This serves as a visual validation that the detailed model is performing as desired. More elaborate testing schemes and formal methods can be devised with test case generation and error detection using assertion blocks from Simulink® Verification and Validation™ [8].Figure 13: Testing of the averaged and the detailed models for speed control with a 1000 rpm step input.SYSTEM INTEGRATIONAfter the component model elaboration and testing is complete, the subsystem containing the averaged model is replaced with the detailed model and the overall system is simulated again.Figure 14: Comparison between the averaged andthe detailed models of the machine drive. This integration will proceed, one component at a time, until the overall system level model contains all the detailed models for each component. This ensures each component is tested and verified in the system model. A single modeling environment for multidomain modeling facilitates the integration. In our example, we used Simulink for this purpose. In Figure 15, we compare the results of the averaged and the detailed models for the driver input profile shown in Figure 4. The detailed model shows deterioration in the speed and L/100 km performance metrics, which can be attributed to the additional detail incorporated into the model.4. CONTROLLER DEPLOYMENTThe electronic control unit (ECU) layout, deployment, and implementation are challenging problems that require innovative thinking. Typically, this requires exploration of the design space to optimize various criteria.Once the design of the system controllers is complete, ECU layout strategy must be considered. In a typical vehicle, we would likely keep some of the controllers inside a centralized ECU, while distributing the others throughout the car.One potential layout would implement the controller for the synchronous motor on a dedicated floating point microcontroller situated closer to the machine, instead of incorporating the controller as part of the centralized ECU. Such a strategy would allow for faster response times from the motor controller for efficient control. If a mix of centralized and distributed controller architecture is under consideration, then the extra layer of complexity introduced by the communication networkshould be accounted for in the modeling.Figure 15: Speed and L/100 km metric comparisons for averaged and detailed models for the HEV. Cost and performance considerations will drive design decisions regarding the selection of floating point or fixed point implementation of each controller. For example, one may consider implementing the controller for the synchronous generator on a fixed-point processor to lower the cost of the overall architecture.6. SIMULATION PERFORMANCEThe final system-level model of the HEV will contain detailed lower-level models of the various components. As model complexity increases, it will take longer to simulate the model in the software environment. This behavior is expected because the model contains more variables, equations, and added components which incur an additional computational cost. Intuitively, this can be visualized as an inverse relationship between simulation performance and complexity of the model as shown in Figure 16.Running the simulations in a high-performance computing environment can offset the increase in simulation times that comes with increased complexity. . With the advent of faster, multicore processors, it is possible to run large simulations without having to investin supercomputer technology.Figure 16: Simulation performance deteriorates with increasing model complexity. We used Simulink simulation modes that employ code generation technology [9] to accelerate the simulation of our model. The improvements in the simulation performance are shown in Figure 17.Figure 17: Comparison of Simulink® simulation modes for the detailed HEV model.CONCLUSIONIn this paper, we first described a typical HEV design and gave an overview of the key challenges. We discussed how the multidomain complications arise from the complex interaction between various mechanical and electrical components—engine, battery, electric machines, controllers, and vehicle mechanics. This complexity, combined with the large number of subsystem parameters, makes HEV design a formidable engineering problem.We chose Model-Based Design as a viable approach for solving the problem because of its numerous advantages, including the use of a single environment for managing multidomain complexity, the facilitation of iterative modeling, and design elaboration. Continuous validation and verification of requirements throughout the design process reduced errors and development time.Our first step in the development process was the realization of a system-level model of the entire HEV. The subsystem components were averaged models, which underwent model elaboration with requirements refinement and modifications in parallel. We showed how statecharts can be used to visualize the operating modes of the vehicle. After each component model was elaborated, we integrated it into the system-level model, compared simulation results of the averaged and detailed models, and noted the effect of model elaboration on the outputs. When simulation times grew long as we moved towards a fully detailed model, we introduced techniques to alleviate this issue. ACKNOWLEDGMENTSThe authors would like to acknowledge the following fellow MathWorks staff who contributed towards the development of the HEV models used in this paper and the writing of this paper. In alphabetical order—Bill Chou, Craig Buhr, Jason Ghidella, Jeff Wendlandt, Jon Friedman, Rebecca Porter, Rick Hyde, and Steve Miller. REFERENCES1. L. Brooke, “Cost remains the boss”, AutomotiveEngineering International, April 2007, SAE International.2. Iqbal Husain, “Electric and Hybrid Vehicles—DesignFundamentals”, 1st E dition, © 2003 CRC Press.3. S J. Chapman, “Electric Machinery Fundamentals”,4th Edition, © 2004 McGraw-Hill Inc.4. Han, Zhang, Yuan, Zhu, Guangyu, Tian andQuanshi, Chen, “Optimal energy management strategy for hybrid electric vehicles”, SAE Paper 2004-01-0576. 5. P. F. Smith, S. Prabhu, and J. Friedman, “Best。

Unit 8 Writing AbstractObjectives- Learn the purpose of writing an academic abstract- Get to understand different types of abstracts and the abstract elements- Understand features of academic English in writing an abstract- Learn how to write an academic abstract- Learn how to write key wordsContents- Teacher’s introduction- Reading and discussion:What is an academic abstract?What are the elements of an abstract?- Language focus: commonly used verbs and tenses; sentence patterns- Rewriting practice: understand different styles of academic abstracts- Rewriting practice: understand the elements of an academic abstract- Writing practice: write an abstract and key words based on the given material1.Reading Activity1.1 Pre-reading TaskAbstract is an important part of academic assignments, most often, reports and research papers. The abstract is the last item that you write, but the first thing people read when they want to have a quick overview of the whole paper. We suggest that you leave abstract writing to the end, because you will have a clearer picture of all your findings and conclusions.Before you learn the detailed steps to write an abstract, please discuss the following questions:What is the purpose of writing an abstract?What are the basic elements for an academic abstract?What language problems may you have in abstract writing? (For example: the wording problem, the tense problem and the voice problem, etc.)1.2Reading PassageSample Abstract 1This dissertation examines the impacts of social movements through a multi-layered study of the Mississippi Civil Rights Movement from its peak in the early 1960s through the early 1980s. By examining this historically important case, the writer clarifies the process by which movements transform social structures and the constraints when they try to do so. The time period studied includes the expansion of voting rights and gains in black political power, the desegregation of public schools and the emergence of white-flight academies, and the rise and fall of federal anti-poverty programs. Two major research strategies were used: (1) a quantitative analysis of county-level data and (2) three case studies. Data have been collected from archives, interviews, newspapers, and published reports. This dissertation challenges the argument that movements are inconsequential. Some view federal agencies, courts, political parties, or economic elites as the agents driving institutional change, but typically these groups acted in response to the leverage brought to bear by the civil rights movement. The Mississippi movement attempted to forge independent structures for sustaining challenges to local inequities and injustices. By propelling change in an array of local institutions, movement infrastructures had an enduring legacy in Mississippi.(Kenneth Tait Andrews, “‘Freedom is a constant struggle’: The dynamics and consequences of the Mississippi Civil Rights Movement, 1960-1984″ Ph.D. State University of New York at Stony Brook, 1997 DAI-A 59/02, p. 620, Aug 1998)1.3 Reading Comprehension1.3.1 What does the abstract talk about?1.3.2Decide how many elements this sample includes and how they function.2Language Focus2.1 Commonly used verbs and tenses in abstractsRead the following sample abstract and pay attention to the verbs used in it. Sample abstract 2Cybercrime –crime on the Internet –is of growing concern in the business community. Despite UK Government initiatives (such as BS7799) and growing sales in software solutions (e.g. anti-virus software), cyber attacks are on the increase. This dissertation focuses on ways to assess the effectiveness of current preventative measures to cybercrime and to understand why organizations continue to be vulnerable to cybercrime. This dissertation met these twin research aims through an extensive study of relevant literature and the implementation of practical research. The latter was carried out through a Case Study with Company XXX using semi-structured interviews with key I.T. security personnel. This research produced a number of key findings: recent surveys confirm a significant increase in the incidences of cybercrime and their impact on the business community but also the types of cybercrime (viruses, hacking, spam, identity theft, fraud, privacy issues, web vandalism, etc.); organizations lacked the security expertise to deal with cybercrime and so depended too much on readily available technical ways to combat cybercrime (and failing); organizations were not aware of Government recommendations on how to address Internet-based security issues; and Governments and law enforcement agencies tended to localize cybercrime, allocating scant resources to contributing to a global solution. The main conclusions drawn from this research were that current approaches to fighting cybercrime are deficient because they fail to embrace a holistic approach, instead opting for a narrow local software-based focus, and that a lack of communication between major stakeholders at local, national and international level has hindered security development. This research argues for a multi-pronged model to reduce incidences of cybercrime. It takes into account Risk-Assessment models, local management of company policies, implementation issues (including proper resourcing and review policies), the need for global support infrastructures, and a means of fostering communication networks.(/Dissertation_Abstract.htm)2.2 More verbs and sentences patterns2.2 Verb tenses in abstractsRead the abstract above again and check the tenses in the abstract.3Writing Practice3.1 Abstract writing practice3.1.1 Why do we care about the problem and the results? If the problem is not obviously "interesting", it might be better to put motivation first; but if your work is incremental progress on a problem that is widely recognized as important, then it is probably better to put the problem statement first to indicate which piece of the larger problem you are breaking off to work on. This section should include the importance of your work, the difficulty of the area, and the impact it might have if successful. Read the following paragraph and write down the Motivation in the blank.A review of groundwater remediation in use today shows that new techniques are required to solve the problems of pump and treat, containment and in-situ treatment. One such technique is the method that involves the use of permeable treatment walls. These methods use a reactive medium such as iron to remediate contaminated groundwater.3.1.2 What problem are you trying to solve? What is the scope of your work (a generalized approach, or for a specific situation)? Be careful not to use too much jargon. In some cases it is appropriate to put the problem statement before the motivation, but usually this only works if most readers already understand why the problem is important. Read the following paragraph and write the problem (aim) in the blank.Several methods of implementing this remediation strategy have been described. These methods include injection and trenching. The use of a funnel and gate system via a trench has been examined in detail using a groundwater modeling option of the FLAC program.3.1.3 How did you go about solving or making progress on the problem? Did you use simulation, analytic models, prototype construction, or analysis of field data for an actual product? What was the extent of your work (did you look at one application program or a hundred programs in twenty different programming languages?) What important variables did you control, ignore, or measure? Read the following paragraph and write the approach in the blank.The use of a funnel and gate system via a trench has been examined in detail using a groundwater modeling option of the FLAC program. The modeling involved an analysis of the effect of changing the lengths of the walls and gate, varying the permeability, and varying the number of gates.3.1.4 What is the answer? Specifically, most good computer architecture papers conclude that something is so many percent faster, cheaper, smaller, or otherwise better than something else. Put the result there, in numbers. Avoid vague, hand-waving results such as "very", "small", or "significant." If you must be vague, you are only given license to do so when you can talk about orders-of-magnitude improvement. There is a tension here in that you should not provide numbers that can be easily misinterpreted, but on the other hand, you do not have room for all the caveats. Read the following paragraph and write the result in the blank.The results showed that increasing the wall length, gate length and permeability increases the size of the plume captured. An important factor in designing the walls is the residence time of the water in the gate or the contact time of the contaminant with the reactive media.3.1.5 What are the implications of your answer? Is it going to change the world (unlikely), be a significant "win", be a nice hack, or simply serve as a road sign indicating that this path is a waste of time (all of the previous results are useful). Are your results general, potentially generalizable, or specific to a particular case? Read the following and write the conclusion in the blank:A sensitivity analysis has been conducted that shows that increasing the size of the capture zone decreases the residence time which will limit the design. The results of the modeling and sensitivity analysis are presented so that they can be used as an aid to the design of permeable treatment walls.3.2 The following is a structured abstract from a report examining the network legitimacy in China telecommunication market (Low, Johnston, and Wang 97). Read it and transfer it into an informative abstract.Abstract structurePurpose – The purpose of this paper is to establish the importance and approaches in securing an organization’s legitimacy from the network community of customers, suppliers and manufacturers, including private investors and state-owned institutions when marketing their products.Design/methodology/approach –The paper presents an inductive interpretative approach complemented by action-based research founded on inquiry and testing.Findings –The paper finds that the key to legitimacy success involves using legitimacy orientations to demonstrate commitment to the interests of constituents, acquiring legitimacy from them, but concurrently considering the central government’s influence on a firm’s legitimacy performance.Research limitations/implications –The multiple interactions proposed in this paper remain untested and might have to be modified pending further empirical testing and analysis.Practical implications –In China’s telecommunication market, a company’s legitimacy emanates first and foremost from the development and commercialization of innovative and creative technological solutions. This requires good, creative management of technological resource and activity links, connecting the company’s technology to network constituents which include local manufacturers, carriers, software developers, investors.Originality/value – This is the first published paper that examines the proposed interactions among legitimacy orientations, alignments, and performances from a “market-as-network” perspective in a dynamic, transitional Chinese telecommunication market.3.3Writing keywordsKeywords often stand alone after the Abstract. In choosing the key words, a wide choice of keywords increases the probability that a paper will be retrieved and read, thereby potentially improving citation counts and journal impacts. To ensure that your paper can be found and cited by as many readers as possible, as suggested by James Hartley, it might be worth considering selecting keywords from a series of categories such as Discipline (e.g. economic, chemistry, biomedical), Methods (e.g. experiment, case study, questionnaire, grounded theory), Data source (e.g. primary, secondary, tertiary students, senior citizens), Location (e.g. country, city, town, institution), Topic (e.g. air pollution, super-virus, earthquake). Such a selection of keywords allows the search engine, such as Google Advanced Scholar, to list your paper in the results no matter which of the above keywords the reader types in.The researchers sometimes have to trade-off between the keywords, particularly when they write for the journals that bound the number of keywords in the limit of 3~5. In this situation, choose the keywords from recent or often-cited titles close to your contribution. If you pick your keywords in this way, the searches that retrieve these articles will also retrieve yours. Consequently, the chances of your paper being read will increase. Read the above sample abstracts and write down the key words:4. Writing project4.1 Get prepared for writing an abstractBefore you write the Abstract section of your research paper, you need to make everything ready for your writing. The following steps may be helpful for your preparation.1) Identify the major objectives and conclusions.2) Identify phrases with keywords in the methods section.3) Identify the major results from the discussion or results section.4) Assemble the above information into a single paragraph.5) State your hypothesis or method used in the first sentence.6) Omit background information, literature review, and detailed description ofmethods.7) Remove extra words and phrases.8) Revise the paragraph so that the abstract conveys only the essential information.9) Check to see if it meets the guidelines of the targeted journal.10) Give the abstract to a colleague (preferably one who is not familiar with yourwork) and ask him/her whether it makes sense.Work in groups and discuss what other preparations you can make for writing an abstract section of your research paper.4.2 Outline an abstractWhen we outline an abstract, there are usually five major aliments to follow. The following sample paper is finished without the abstract and key words. Read the paper, find the statements concerned and fill in the blank after it.Sample paperGLOBAL MEGACITIES AND LOW CARBON: FROM CONCEPT PLANNING TO INTEGRATED MODELLINGPhil Jones, Simon Lannon, Robbert van Nouhuys, Hendrik RosenthalMega citiesIn 1950, 30% of the world’s population lived in cities. In 2000, it was 47%. By 2010 more than half of the world’s population will be living in cities. The total may even reach 60% by 2030 and possibly 85% by the middle of this century. Such rapidly increasing urbanization, particularly in developing countries, creates many opportunities and challenges.We are living in a globalized and changing world whereby increasingly we require wise use of human and natural resources. At the same time, we need to reduce the risk urbanization poses and enhance the quality of life for all those who live in, or are impacted by Megacities. Megacities are more than just large cities with populations of 10 million inhabitants or more. They are critical to national economies. Their scalecreates new dynamics, new complexity and new simultaneity of events and processes –physical, social and economic. They host highly efficient economic activities utilizing intense and complex interactions between different demographic, social, political, economic and ecological processes.Nations undergoing economic progress often generate rapid urbanization linked with considerable opportunities, as well as strong pressures for change accompanied by environmental degradation. In current times in the developing world, Megacities grow faster than ever before and much faster than their infrastructure can support. Traditionally this results in uncontrolled urban sprawl, high traffic volumes and congested transport systems, high concentrations of industrial production, ecological overload, unregulated and disparate land and property markets, insufficient housing development, excessive waste generation, loss of productivity, general economic constipation, degradation and decline.Over the past decades traditional Megacities have been suffering from inadequate representative governance, inhibiting spatial planning, building control, delivery of services (such as water supply, sewage disposal and energy distribution), and the establishment of general order (including security and disaster prevention). Existing administrations and their organizational structures may have been outgrown by the rapidly expanding city and may simply be unable to cope with the huge scale of their new responsibilities. On the other hand, megacities contain a rich mix of coexisting people and support systems when properly planned and managed. Groups with their own distinctive ethnic, community, cultural roots, lifestyles and social surroundings have opportunity to thrive and develop. Differences in economic development, social polarization, quality of infrastructure and governance are recognized and taken into account. The scale and dynamism of Megacities, coupled with complex interacting processes and the sheer concentration of human capital make them incubators of huge growth and innovation. Megacities are the focal points of globalization as well as the driving forces for development; they harbor a wide spectrum of human skill and potential, creativity, social interaction and cultural diversity.For Hanoi to develop within a rapid urbanization scenario it must look far ahead –not 20 years, not 50 years but 100 years –into the 22nd Century. The use of conventional planning and economic development guidelines have proven to be outdated, resulting in the risk of harboring pronounced poverty, social inequality, and aggravating rapid environmental degradation. Population density, if not managed, increases vulnerability to natural and man-made hazards. Thus, Megacities are both victims and producers of risk, if unmanaged and exposed to the global environmental, socio-economic and political changes to which they contribute.Megacities will be essential and efficient drivers of a nation’s gross domestic product, processes and activities. Megacities will be ideal places to drive activities and innovation to solve social, environmental, medical, socio-economic and political issues. For these reasons, Megacities are necessary and have potential to substantially contribute towards global justice and peace – and thereby prosperity.Low Carbon and Energy ModelingAspects of sustainable master planning that impact carbon and energy implications need to be understood to help inform concepts at the earliest stage of the design process. For example, the full benefits of reducing operating energy demand of buildings can only be realized if the energy supply can respond to the reduced demand, which includes the additional benefits of reducing the energy supply infrastructure, which in turn reduces its embodied energy. Likewise, if a low (or zero) carbon energy supply is to be used, for example, renewable energy, this is easier to achieve if first the energy demand is reduced. Also, as the operating energy performance of buildings is improved the carbon dioxide emissions associated with the operation of the building, for heating, cooling, lighting, etc., becomes of the same order as the embodied energy used in construction and fit-out of the building and its infra-structure. So a balanced approach across energy demand and supply infrastructure, operating energy and embodied energy, is needed to achieve optimum performance.This paper describes how the aspects of low carbon planning and design (i.e. operating energy use, embodied energy associated with buildings, energy supply infrastructures, and other infrastructures such as transport, waste, water, sewage, etc.) can be assessed using urban scale modeling, namely EEP-Urban, at a whole city and building plot level. In particular, it explores how the reduction in energy supply infrastructure together with reduced energy demand can lead to reductions in carbon dioxide emissions associated with both operating and embodied energy. The concept of the Megacity in the context of Hanoi in 2110 is used to illustrate the model.The Concept of Metabolic Super ClustersHanoi in 2110 will feature super tall skyscrapers, elevated connectors and railways, nodal communication networks, as well as electrical and energy corridors. Vertical neighborhoods, where people live, shop, relax and work, are built on and above this surface. Built structures are not just individual towers standing independent from another but instead are interlinked and inter-dependent to form an urban spatial organization that allows for vertical connectivity.The urban model proposes 1 million people on a 1 square kilometer floor plate, hence called a Super Cluster. Under current suburban density standards a similar population would require in the order of 100 square kilometers. Thus, this vision for Hanoi in 2110 saves 99% of land for other uses, most notably conservation of ecological functions and provides food, leisure, material and energy support systems for the city thereby localizing the ecological footprint of the city.Another distinct aspect of Hanoi in 2110 is that it does not have static building functions. Instead, land use layers, building envelopes and orientations change over time – hourly, daily, weekly, monthly, yearly – to optimize performance efficiencies, therefore becoming a Metabolic Super Cluster. It is envisaged that Hanoi by the end of this century will consist of 30 metabolic super clusters in addition to its traditional urban city centre.Concentrated compact development will enhance the quality of life for urban dwellers because all infrastructures, environmentally damaging and other undesirablesurface activities are located underground or integrated into the vertical structure, thereby significantly improving the quality of living space at the ground, open-air level. Underground space may also provide a safer environment for some public and commercial activities as well as providing shelter from inclement weather conditions. This may prove to be essential for infrastructure in particular, given the predicted impacts associated with climate change. Elevated multi-level connectors between building clusters are converted into common corridors with public amenities, farms and open space.Quality of life depends on individual perceptions, attitudes, aspirations and value systems. These differ with age, ethnicity, culture and religion, as well as lifestyles, education and cultural background. An individual’s priorities and attitudes to life depend heavily upon socio-economic background and cultural environment. Historic places, cultural sites or public spaces may give Megacities a certain unique identity, heritage, and authenticity. As a result, such spatial capital contributes to social cohesion and makes people feel at home.Nevertheless, the general opinion may be that the quality of life for many residents in Megacities would be low – for rich and poor alike. Air, water and soil pollution, water and energy supply shortages, traffic congestion, environmental health problems, limited green spaces, poverty and malnutrition, social security and public safety problems place many burdens and restrictions on people.The Megacity of the future has adapted to greater diversity in socio-cultural circumstances by including and enhancing the often widespread and dynamic informal activities that enrich such communities. Further development of new visions and innovative management tools are now urgently needed in order to enhance quality of life and create cohesive communities.Urban governance and management is one of the key success factors of any global Megacity. As society and aspirations evolve over time, the city has to be designed to adapt to change. Utopian cities built around fixed ideologies have never worked. Megacities need to be versatile in order to adapt.The main challenges for a Megacity in terms of urban governance are: dealing with the speed of change with intelligent urban infrastructure systems; eradicating social exclusion; and introducing proper forms of urban governance.Way ForwardWhether or not 1 million people are appropriate for a 1 km2 super cluster remains to be seen. The optimum density for sustainability, land use and quality of life may be less and will vary with global location. The above approach is essential to inform the design of high rise high density Megacities if they are to realize their full potential for providing sustainable healthy zero carbon cities of the future that can co-exist in a sustainable way with their neighboring rural areas.4.3 According to the above table, draft an abstract and keywords for the sample paper. Abstract:Key words:5.Final Checklistbackground, purpose, findings, conclusions, recommendations and follow strictly the chronology of the report/papers.∙Avoid excessive use of jargon, and exaggerative language∙Keep within the specified word limit. Most institutions will have their own "house rules" as to the length of the abstract. The abstract should stand alone and be able to be understood without reference to citations,∙Ensure the abstract contains all your key words (for the searchable databases). ∙Add no new information but simply summarize the report/papers. Be intelligible to a wide audience。

专业英语文献翻译Quantifying the Cluster of Differentiation 4 Receptor Density on Human T Lymphocytes Using Multiple Reaction Monitoring Mass Spectrometry。

ABSTRACT： Cluster of differentiation 4 （CD4） is an important glycoprotein containingfour extracellular domains, a transmembrane portion and a short intracellular tail. It locates on the surface of various types of immune cells and performs a critical role in multiple cellular functions such as signal amplification and activation of T cells。

It is well-known as a clinical cell surface protein marker for study of HIV progression and for defining the T helper cell population in immunological applications。

Moreover，CD4 protein has been used as a biological calibrator for quantification of other surface and intracellular proteins. However，flow cytometry, the conventional method of quantification of the CD4 density on the T cell surface depends on antibodies and has suffered from variables such as antibody clones, the ommatophore and conjugation chemistries, the fixation conditions， and the flow cytometric quantification methods used. In this study, we report the development of a highly reproducible na no liquid chromatography−multiple reaction monitoring mass spectrometry-based quantitative method to quantify the CD4 receptor density in units of copy number per cell on human CD4+ T cells. The method utilizes stable isotope—labeled full—length standard CD4 as an internal standard to measureendogenous CD4 directly, without the use of antibodies. The development of the mass spectrometry-based approach of CD4 protein quantification is important as a complementary strategy to validate the analysis from the cytometry-based conventional method。

软件工程专业毕业设计外文文献翻译1000字本文将就软件工程专业毕业设计的外文文献进行翻译，能够为相关考生提供一定的参考。

外文文献1: Software Engineering Practices in Industry: A Case StudyAbstractThis paper reports a case study of software engineering practices in industry. The study was conducted with a large US software development company that produces software for aerospace and medical applications. The study investigated the company’s software development process, practices, and techniques that lead to the production of quality software. The software engineering practices were identified through a survey questionnaire and a series of interviews with the company’s software development managers, software engineers, and testers. The research found that the company has a well-defined software development process, which is based on the Capability Maturity Model Integration (CMMI). The company follows a set of software engineering practices that ensure quality, reliability, and maintainability of the software products. The findings of this study provide a valuable insight into the software engineering practices used in industry and can be used to guide software engineering education and practice in academia.IntroductionSoftware engineering is the discipline of designing, developing, testing, and maintaining software products. There are a number of software engineering practices that are used in industry to ensure that software products are of high quality, reliable, and maintainable. These practices include software development processes, software configuration management, software testing, requirements engineering, and project management. Software engineeringpractices have evolved over the years as a result of the growth of the software industry and the increasing demands for high-quality software products. The software industry has developed a number of software development models, such as the Capability Maturity Model Integration (CMMI), which provides a framework for software development organizations to improve their software development processes and practices.This paper reports a case study of software engineering practices in industry. The study was conducted with a large US software development company that produces software for aerospace and medical applications. The objective of the study was to identify the software engineering practices used by the company and to investigate how these practices contribute to the production of quality software.Research MethodologyThe case study was conducted with a large US software development company that produces software for aerospace and medical applications. The study was conducted over a period of six months, during which a survey questionnaire was administered to the company’s software development managers, software engineers, and testers. In addition, a series of interviews were conducted with the company’s software development managers, software engineers, and testers to gain a deeper understanding of the software engineering practices used by the company. The survey questionnaire and the interview questions were designed to investigate the software engineering practices used by the company in relation to software development processes, software configuration management, software testing, requirements engineering, and project management.FindingsThe research found that the company has a well-defined software development process, which is based on the Capability Maturity Model Integration (CMMI). The company’s software development process consists of five levels of maturity, starting with an ad hoc process (Level 1) and progressing to a fully defined and optimized process (Level 5). The company has achieved Level 3 maturity in its software development process. The company follows a set of software engineering practices that ensure quality, reliability, and maintainability of the software products. The software engineering practices used by the company include:Software Configuration Management (SCM): The company uses SCM tools to manage software code, documentation, and other artifacts. The company follows a branching and merging strategy to manage changes to the software code.Software Testing: The company has adopted a formal testing approach that includes unit testing, integration testing, system testing, and acceptance testing. The testing process is automated where possible, and the company uses a range of testing tools.Requirements Engineering: The company has a well-defined requirements engineering process, which includes requirements capture, analysis, specification, and validation. The company uses a range of tools, including use case modeling, to capture and analyze requirements.Project Management: The company has a well-defined project management process that includes project planning, scheduling, monitoring, and control. The company uses a range of tools to support project management, including project management software, which is used to track project progress.ConclusionThis paper has reported a case study of software engineering practices in industry. The study was conducted with a large US software development company that produces software for aerospace and medical applications. The study investigated the company’s software development process,practices, and techniques that lead to the production of quality software. The research found that the company has a well-defined software development process, which is based on the Capability Maturity Model Integration (CMMI). The company uses a set of software engineering practices that ensure quality, reliability, and maintainability of the software products. The findings of this study provide a valuable insight into the software engineering practices used in industry and can be used to guide software engineering education and practice in academia.外文文献2: Agile Software Development: Principles, Patterns, and PracticesAbstractAgile software development is a set of values, principles, and practices for developing software. The Agile Manifesto represents the values and principles of the agile approach. The manifesto emphasizes the importance of individuals and interactions, working software, customer collaboration, and responding to change. Agile software development practices include iterative development, test-driven development, continuous integration, and frequent releases. This paper presents an overview of agile software development, including its principles, patterns, and practices. The paper also discusses the benefits and challenges of agile software development.IntroductionAgile software development is a set of values, principles, and practices for developing software. Agile software development is based on the Agile Manifesto, which represents the values and principles of the agile approach. The manifesto emphasizes the importance of individuals and interactions, working software, customer collaboration, and responding to change. Agile software development practices include iterative development, test-driven development, continuous integration, and frequent releases.Agile Software Development PrinciplesAgile software development is based on a set of principles. These principles are:Customer satisfaction through early and continuous delivery of useful software.Welcome changing requirements, even late in development. Agile processes harness change for the customer's competitive advantage.Deliver working software frequently, with a preference for the shorter timescale.Collaboration between the business stakeholders and developers throughout the project.Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.Working software is the primary measure of progress.Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely.Continuous attention to technical excellence and good design enhances agility.Simplicity – the art of maximizing the amount of work not done – is essential.The best architectures, requirements, and designs emerge from self-organizing teams.Agile Software Development PatternsAgile software development patterns are reusable solutions to common software development problems. The following are some typical agile software development patterns:The Single Responsibility Principle (SRP)The Open/Closed Principle (OCP)The Liskov Substitution Principle (LSP)The Dependency Inversion Principle (DIP)The Interface Segregation Principle (ISP)The Model-View-Controller (MVC) PatternThe Observer PatternThe Strategy PatternThe Factory Method PatternAgile Software Development PracticesAgile software development practices are a set ofactivities and techniques used in agile software development. The following are some typical agile software development practices:Iterative DevelopmentTest-Driven Development (TDD)Continuous IntegrationRefactoringPair ProgrammingAgile Software Development Benefits and ChallengesAgile software development has many benefits, including:Increased customer satisfactionIncreased qualityIncreased productivityIncreased flexibilityIncreased visibilityReduced riskAgile software development also has some challenges, including:Requires discipline and trainingRequires an experienced teamRequires good communicationRequires a supportive management cultureConclusionAgile software development is a set of values, principles, and practices for developing software. Agile software development is based on the Agile Manifesto, which represents the values and principles of the agile approach. Agile software development practices include iterative development, test-driven development, continuous integration, and frequent releases. Agile software development has many benefits, including increased customer satisfaction, increased quality, increased productivity, increased flexibility, increased visibility, and reduced risk. Agile software development also has some challenges, including the requirement for discipline and training, the requirement for an experienced team, the requirement for good communication, and the requirement for a supportive management culture.。

第21卷第4期2023年12月交通运输工程与信息学报Journal of Transportation Engineering and InformationVol.21No.4Dec.2023文章编号：1672-4747（2023）04-0103-12融合多源数据与元胞传输模型的高速公路交通状态估计方法易术*，黄丹阳（四川智能交通系统管理有限责任公司，成都610200）摘要：针对高速公路管控和决策应对交通状态进行准确、可靠和精细化估计的需求，本文提出了一种基于多源数据+元胞传输模型（Multi-Source Data Cell Transmission Model，MD-CTM）的交通状态估计方法。

该方法针对传统CTM模型要求元胞长度必须一致的局限性，提出了一种元胞长度划分的优化方法，能够灵活调整元胞长度和数量。

同时，应用卡尔曼滤波技术，将ETC门架流量、稀疏视频检测器流量和样本车辆平均速度数据融合，并与CTM模型相结合，实现高速公路元胞级交通状态估计。

为了验证本文提出方法的有效性和准确性，我们利用VISSIM软件构建了长度5km的高速公路仿真场景。

仿真案例结果表明，本文提出的MD-CTM模型能够较为准确地反映不同流量需求下交通流状态的时空演化特征，且相较于CTM模型，其元胞密度估计精度提高12.59%~36.26%。

此外，本文选取了成都市绕城高速路段实际场景，对模型的运行效果进行了展示。

关键词：智能交通；交通状态估计；卡尔曼滤波；元胞传输模型；多源数据融合中图分类号：U495文献标志码：A DOI:10.19961/ki.1672-4747.2023.08.001Freeway traffic state estimation based on multi-source data andcell transmission modelYI Shu*,HUANG Dan-yang（Sichuan Intelligent Transport System Management Co.,Ltd.,Chengdu610200,China）Abstract：Accurate,reliable,and efficient traffic state estimation is essential for effective freeway management and decision-making.This study presents a traffic state estimation method called MD-CTM,which combines multi-source data and the cell transmission model(CTM).As the traditional CTM has limitations owing to fixed cell lengths,we propose a cell division approach that allows for flexible lengths and numbers.To enhance the accuracy of traffic state estimation,we utilize the Kal-man filtering technique to fuse different types of traffic data,including traffic flow from the electron-ic toll collection system and sparse video detectors,and an average link speed with the CTM to achieve cell-level traffic state estimation on freeways.To evaluate the performance of the proposed approach,we conducted simulations using VISSIM on a freeway section of5km.The simulation re-sults show that the proposed MD-CTM model improves the accuracy of cell density estimation by12.59%~36.26%compared with the CTM model.Furthermore,our model effectively captures thespatio-temporal evolution characteristics of traffic flow states under different traffic demand condi-收稿日期：2023-08-07录用日期：2023-08-25网络首发：2023-09-12审稿日期：2023-08-07~2023-08-09；2023-08-17~2023-08-25基金项目：国家重点研发计划项目（2021YFB1600100）作者简介：黄丹阳（1988—），男，硕士，高级工程师，研究方向为交通智能控制、内模与预测控制，E-mail:****************通信作者：易术（1970—），男，硕士，高级工程师，研究方向为交通工程、智慧交通，E-mail:****************引文格式：易术，黄丹阳.融合多源数据与元胞传输模型的高速公路交通状态估计方法[J].交通运输工程与信息学报，2023，21(4)：103-114.YI Shu,HUANG Dan-yang.Freeway traffic state estimation based on multi-source data and cell transmission model[J].Journal of Transportation Engineering and Information，2023，21(4)：103-114.104交通运输工程与信息学报第21卷tions.Moreover,a real-world scenario of Chengdu city is used to further demonstrate the effective-ness of our proposed approach.Key words：intelligent transportation;traffic state estimation;Kalman filter;cell transmission model;multi-source data fusion0引言高速公路交通状态估计是交通领域中的一个重要研究方向。