A State-based Approach to Integration Testing based on UML Models
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中医专业求职英语作文英文回答:As a graduate of Traditional Chinese Medicine (TCM), I am eager to join your esteemed organization and contribute my expertise to your esteemed practice. My comprehensive understanding of TCM principles, combined with my clinical experience, has equipped me to excel in this field.During my studies, I gained a profound knowledge of the fundamental concepts of TCM, including yin-yang theory, the five elements, and the meridian system. I also developed a strong foundation in herbal medicine, acupuncture, and other TCM modalities. My clinical rotations in various hospitals and clinics have provided me with hands-on experience in the diagnosis and treatment of a wide range of conditions.Throughout my academic and professional journey, I have demonstrated exceptional analytical, problem-solving, andcommunication skills. I am proficient in conductingthorough patient assessments, developing personalized treatment plans, and effectively communicating medical information to both patients and colleagues. My ability to blend traditional Eastern wisdom with modern scientific knowledge allows me to provide a holistic and evidence-based approach to healing.I am particularly interested in the integration of TCM with Western medicine to create a comprehensive andpatient-centered approach. I believe that TCM offers valuable insights into the interconnectedness of mind, body, and spirit, and that it can complement Western medical interventions to enhance patient outcomes.Furthermore, I am passionate about research and ameager to contribute to the advancement of TCM knowledge. I have actively participated in research projects exploring the efficacy of TCM therapies and am keen to continue this work in a collaborative and innovative environment.I am confident that my qualifications and dedicationwould make me a valuable asset to your organization. I am eager to learn from experienced practitioners, share my knowledge, and contribute to the pursuit of optimal patient care while upholding the principles of TCM.中文回答:作为一名中医药专业的毕业生,我热切地希望加入贵公司,并贡献我的专业知识。
智能机器会让人的大脑变懒吗英语作文全文共3篇示例,供读者参考篇1Will AI Make Our Brains Lazy?The rapid advancement of artificial intelligence (AI) technology has sparked concerns about its potential impact on the human brain. As AI systems become increasingly capable of performing tasks that once required human intelligence, some fear that our reliance on these technologies could lead to a decline in cognitive abilities, making our brains "lazy." In this essay, I will explore both sides of this argument, drawing upon research and examples to determine whether AI truly poses a threat to our mental faculties.On one hand, the integration of AI into our daily lives could indeed lead to a certain level of mental complacency. WithAI-powered digital assistants handling a wide range of tasks, from scheduling appointments to answering factual queries, we may become overly reliant on these technologies and less inclined to exercise our own cognitive skills. For instance, instead of mentally calculating a tip or memorizing a phone number, wemay instinctively turn to our AI-enabled devices for assistance. This habitual offloading of mental tasks to AI could, over time, lead to a diminished capacity for critical thinking,problem-solving, and memory retention.Moreover, the widespread use of AI in education could potentially foster a passive learning environment, where students become accustomed to having information readily provided by AI tutors or learning algorithms, rather than actively engaging in the process of knowledge acquisition and synthesis. This could hinder the development of important cognitive skills, such as analytical reasoning, creative thinking, and self-directed learning.Additionally, the increasing automation of various professions by AI systems could potentially lead to a decline in the cognitive demands placed on workers. As AI takes over routine tasks that once required human intelligence, there may be a reduced need for professionals to exercise their mental faculties to the same extent, potentially leading to cognitive stagnation or even regression.On the other hand, proponents of AI argue that these technologies can actually enhance and augment human cognitive abilities, rather than diminish them. By offloadingmundane or repetitive tasks to AI systems, humans can free up mental resources to focus on more complex, higher-order thinking and creative endeavors. For example, an AI writing assistant could handle the tedious aspects of drafting and editing, allowing the human writer to concentrate on developing ideas, structuring arguments, and crafting compelling narratives.Furthermore, AI can serve as a powerful tool for learning and knowledge acquisition. AI-powered educational platforms can adapt to individual learning styles, providing personalized instruction and feedback tailored to each student's needs and pace. This could foster a more engaging and effective learning experience, ultimately strengthening cognitive skills rather than diminishing them.Additionally, the integration of AI into various fields, such as healthcare, scientific research, and data analysis, could amplify human cognitive capabilities by providing powerful computational tools and insights that would be impossible for the human mind alone to achieve. For instance, AI systems can process vast amounts of data, identify patterns, and generate hypotheses, augmenting human researchers' ability to make groundbreaking discoveries and advance our understanding of complex phenomena.Ultimately, the impact of AI on the human brain will likely depend on how we choose to integrate and utilize these technologies. If we allow AI to replace or diminish cognitive activities altogether, there is a risk of mental complacency and a potential decline in certain cognitive abilities. However, if we approach AI as a complement to human intelligence, leveraging it as a tool to enhance our cognitive capacities and free up mental resources for more complex tasks, AI could actually serve to sharpen and augment our mental faculties.In my opinion, the key to mitigating the potential negative effects of AI on the human brain lies in striking a balance between offloading certain tasks to AI and actively engaging in cognitive activities that challenge and exercise our minds. We must remain vigilant in preserving and cultivating essential cognitive skills, such as critical thinking, problem-solving, and creativity, while simultaneously embracing AI as a powerful tool to augment and extend our intellectual capabilities.Furthermore, it is crucial to foster a culture of lifelong learning and intellectual curiosity, where individuals are encouraged to continuously expand their knowledge and exercise their cognitive faculties, rather than becoming complacent or overly reliant on AI. Educational institutions, inparticular, should prioritize the development of metacognitive skills and self-directed learning, equipping students with the tools and mindset necessary to navigate an AI-driven world while maintaining cognitive agility and resilience.In conclusion, while the rise of AI does present potential challenges to the preservation of human cognitive abilities, it also offers remarkable opportunities for cognitive enhancement and augmentation. By adopting a balanced and thoughtful approach to the integration of AI into our lives, and by prioritizing the cultivation of essential cognitive skills and lifelong learning, we can harness the power of AI to unlock new realms of human potential, rather than allowing it to make our brains lazy.篇2Will Intelligent Machines Make Our Brains Lazy?In today's rapidly advancing technological landscape, the development of intelligent machines has sparked intense debate and speculation about their potential impact on human cognition and intellectual capabilities. As students, we find ourselves grappling with the question: Will the increasing presence of artificial intelligence (AI) and sophisticatedalgorithms in our daily lives lead to a deterioration of our mental faculties, rendering our brains lazy and overly reliant on these technological aids?To begin exploring this complex issue, we must first understand the nature of intelligent machines and their current applications. AI systems, powered by intricate algorithms and vast amounts of data, are designed to mimic human intelligence and perform tasks that typically require human cognition, such as problem-solving, decision-making, and pattern recognition. From virtual assistants like Siri and Alexa to self-driving cars and advanced medical diagnostics, intelligent machines are already deeply embedded in our modern lives.Proponents of AI argue that these technologies will augment and enhance our cognitive abilities, freeing us from mundane and repetitive tasks, and allowing us to focus our mental energies on more complex and creative endeavors. They posit that by offloading routine cognitive processes to machines, we can conserve our mental resources and channel them towards higher-order thinking, innovation, and intellectual pursuits that truly challenge and stimulate our minds.On the other hand, critics warn that our increasing reliance on intelligent machines could lead to a gradual atrophy of ourcognitive skills. They argue that by outsourcing tasks to AI systems, we may become complacent and fail to exercise our own problem-solving abilities, leading to a decline in critical thinking, reasoning, and mental agility. Furthermore, the convenience and accessibility of these technologies could foster a culture of intellectual laziness, where we become overly dependent on them and neglect to develop and nurture our inherent cognitive capacities.As students, we stand at the intersection of this debate, and our experiences offer valuable insights into the potential impact of intelligent machines on our mental development. On one hand, the integration of AI-powered educational tools, such as adaptive learning platforms and intelligent tutoring systems, has undoubtedly enhanced our learning experiences. These technologies can tailor instruction to our individual needs, providing personalized feedback and adjusting the pace and content based on our strengths and weaknesses. This customized approach can foster more efficient learning and help us overcome specific cognitive barriers, ultimately strengthening our understanding and retention.Moreover, AI-driven research tools and information retrieval systems have revolutionized the way we access and processknowledge. With vast databases and powerful search algorithms at our fingertips, we can quickly locate and synthesize information from a multitude of sources, facilitating more comprehensive and well-informed research endeavors. This exposure to diverse perspectives and vast pools of knowledge could potentially stimulate our intellectual curiosity and encourage us to engage in more rigorous critical analysis and synthesis.However, we must also consider the potential pitfalls of relying too heavily on these technologies. As AI systems become increasingly sophisticated, there is a risk that we may become overly dependent on them for problem-solving anddecision-making, leading to a gradual erosion of our ability to think critically and independently. If we habitually defer to the solutions provided by intelligent machines without questioning or understanding the underlying reasoning, we may inadvertently stunt the development of our own analytical and reasoning skills.Furthermore, the abundance of information and instant gratification offered by AI-powered search engines and virtual assistants could cultivate a culture of intellectual passivity. Rather than deeply engaging with complex ideas and concepts, we maysuccumb to the temptation of seeking quick, ready-made answers, neglecting the mental effort required for genuine understanding and knowledge acquisition.As students navigating this rapidly evolving landscape, it is crucial for us to strike a balance between leveraging the power of intelligent machines and actively nurturing our own cognitive abilities. We must approach these technologies with a critical mindset, using them as tools to enhance our learning and understanding, but not as substitutes for our own mental efforts.One way to achieve this balance is by actively engaging with the processes and reasoning behind AI-driven solutions. Rather than blindly accepting the outputs of these systems, we should strive to understand the underlying algorithms, data models, and decision-making processes. By developing a deeper comprehension of how these technologies work, we can better evaluate their strengths and limitations, and apply our own critical thinking skills to assess and validate their outputs.Additionally, we must consciously prioritize activities and practices that challenge and exercise our cognitive abilities. This could involve actively participating in classroom discussions, engaging in collaborative problem-solving exercises, and pursuing extracurricular activities that require critical thinking,creativity, and intellectual rigor. By consistently pushing ourselves to think deeply, analyze information from multiple perspectives, and synthesize complex ideas, we can counteract the potential for intellectual laziness and maintain the vigor of our mental faculties.Furthermore, it is essential for educators and educational institutions to adapt their curricula and pedagogical approaches to this evolving landscape. While integrating AI-powered tools and resources can enhance the learning experience, it is equally important to emphasize the development of critical thinking, problem-solving, and independent reasoning skills. This can be achieved through project-based learning, inquiry-driven assignments, and opportunities for students to grapple with open-ended problems and formulate their own solutions.In conclusion, the advent of intelligent machines presents both opportunities and challenges for our cognitive development as students. While these technologies undoubtedly offer powerful tools for augmenting our learning and expanding our access to knowledge, we must be vigilant against the potential for intellectual complacency and over-reliance. By actively engaging with these technologies, prioritizing activities that challenge our cognitive abilities, and fostering a culture ofcritical thinking and intellectual curiosity, we can harness the power of intelligent machines while simultaneously nurturing and strengthening our own mental faculties. Only by striking this delicate balance can we truly unlock the full potential of our minds and ensure that our brains remain agile, inquisitive, and primed for lifelong learning and intellectual growth.篇3Will Intelligent Machines Make Our Brains Lazy?Ever since the dawn of new technologies like artificial intelligence (AI) and advanced robotics, there has been an ongoing debate about the potential impact these innovations could have on the human mind. As a student witnessing the rapid integration of intelligent machines into various aspects of our lives, I can't help but ponder this burning question: Will these remarkable advancements lead to a decline in our cognitive abilities, rendering our brains lethargic and complacent?To delve deeper into this inquiry, we must first understand the nature of intelligent machines and their evolving capabilities. AI systems, for instance, are designed to mimic and potentially surpass human intelligence by processing vast amounts of data, identifying patterns, and making decisions based on complexalgorithms. From digital assistants that can answer our queries to self-driving cars that navigate through intricate traffic conditions, the applications of AI are truly mind-boggling.At first glance, the advent of such advanced technologies might seem like a blessing, promising to alleviate the mental strain imposed by arduous tasks and intricate problem-solving. With machines taking over tedious computations, data analysis, and even creative endeavors, one could argue that our cognitive resources could be redirected towards more profound and intellectually stimulating pursuits.However, this rosy picture raises some valid concerns. Excessive reliance on intelligent machines could potentially lead to a phenomenon known as "cognitive offloading," where our brains become increasingly dependent on external tools and devices, gradually losing the ability to perform certain mental functions independently. This dependency could result in a gradual erosion of our critical thinking, problem-solving, and memory skills, much like how the advent of calculators has diminished our ability to perform mental arithmetic.Moreover, the constant exposure to AI-powered systems that provide instantaneous solutions and curated information might condition our minds to expect immediate gratification,hampering our capacity for patience, perseverance, and deep contemplation. The risk of intellectual laziness looms large, as we become accustomed to having machines do the "heavy lifting" for us, both figuratively and literally.On the flip side, proponents of intelligent machines argue that these technologies can serve as powerful cognitive enhancers, augmenting our mental capabilities rather than diminishing them. By offloading routine tasks to machines, we can free up our cognitive resources to focus on higher-order thinking, creativity, and intellectual pursuits that truly exemplify the uniqueness of the human mind.Additionally, the integration of AI into educational settings holds the potential to revolutionize the learning experience. Personalized learning algorithms could adapt to individual learning styles and pace, ensuring that students receive tailored instruction and support. Interactive simulations and immersive virtual environments could make abstract concepts more tangible and engaging, fostering a deeper understanding and retention of knowledge.Ultimately, the impact of intelligent machines on our cognitive abilities will largely depend on how we choose to embrace and integrate these technologies into our lives. Withthe right mindset and a balanced approach, we can harness the power of these innovations to augment our intellectual capacities while simultaneously nurturing and exercising our inherent cognitive abilities.One potential solution lies in cultivating a symbiotic relationship between human and machine intelligence, where we leverage the strengths of both to achieve remarkable feats. By recognizing the unique capabilities of each entity, we can strike a harmonious balance, utilizing machines for tasks they excel at while reserving the more abstract, creative, and emotionally intelligent endeavors for the human mind.Moreover, educational curricula and lifelong learning initiatives should emphasize the development of critical thinking, problem-solving, and adaptability skills. These cognitive competencies will not only empower us to effectively navigate the ever-changing technological landscape but also equip us with the mental resilience to resist the potential pitfalls ofover-reliance on intelligent machines.In essence, the relationship between intelligent machines and human cognition is a delicate dance, one that requires careful choreography and a deep understanding of the intricate interplay between technology and the human mind. Byembracing these advancements with a judicious and mindful approach, we can harness their potential to enhance our intellectual capabilities while safeguarding against the risks of cognitive complacency.As a student poised to navigate a world increasingly intertwined with intelligent machines, I remain cautiously optimistic about the future. While the concerns surrounding cognitive laziness are valid, I believe that with the right strategies and a commitment to nurturing our inherent mental faculties, we can leverage the power of these technologies to propel ourselves towards new heights of intellectual achievement.The onus lies on us, as individuals and as a society, to strike the delicate balance between embracing innovation and preserving the essence of human cognition. Only then can we truly unlock the synergistic potential of intelligent machines and the remarkable capabilities of the human mind, paving the way for a future where technology serves as a catalyst for intellectual growth rather than a catalyst for cognitive stagnation.。
英语作文-涉外旅游事务管理行业:推动文化旅游融合,提升旅游发展质量In the realm of international travel management, the integration of culture and tourism has emerged as a pivotal strategy for enhancing the quality of tourism development. This approach not only enriches the travel experience by immersing visitors in local traditions and customs but also fosters a deeper understanding and appreciation of cultural diversity.The fusion of culture and tourism can be seen as a symbiotic relationship where each element complements the other. Cultural attractions such as museums, historical sites, and traditional performances become more accessible and appealing when they are part of a well-organized travel itinerary. Conversely, tourism provides a platform for cultural preservation, allowing traditions that might otherwise fade into obscurity to thrive and be shared with a global audience.To effectively promote this integration, stakeholders in the travel industry must adopt a multifaceted approach. This includes creating comprehensive travel packages that highlight cultural experiences, training guides to convey cultural significance with accuracy and enthusiasm, and collaborating with local communities to ensure that tourism development benefits all parties involved.Moreover, the quality of tourism development hinges on sustainable practices. It is crucial to balance the economic benefits of increased tourism with the need to protect cultural heritage and the environment. This means implementing policies that minimize the impact of tourism on natural resources and ensuring that cultural representations are respectful and authentic.In conclusion, the integration of culture and tourism is a dynamic and enriching process that holds the potential to elevate the quality of travel experiences while contributing to cultural preservation and sustainable development. By embracing thisapproach, the international travel management industry can create meaningful and memorable journeys that resonate with travelers long after their return home.(Note: This is a brief excerpt from a larger document that would typically contain more detailed examples and strategies to illustrate the integration of culture and tourism in travel management.)。
Using Sonnet in a Cadence Virtuoso Design FlowPurpose of this document:This document describes the Sonnet plug-in integration for the Cadence Virtuoso design flow,for silicon accurate EM modelling of passive structures.Using Sonnet in a Cadence Virtuoso Design Flow (1)Using Sonnet in a Cadence Virtuoso Design Flow (2)Sonnet Professional Key Benefits (3)Sonnet Professional Key Features (3)When to Use Sonnet EM Analysis (3)When to Use Sonnet EM Analysis (4)Sonnet EM Design Process (5)Example1 (12)Example2 (13)Example3 (14)Document revised:15.August2011Document revision:1.2Using Sonnet in a Cadence Virtuoso Design Flow The plug-in integration of the Sonnet Professional analysis program into the Cadence Virtuoso layout environment allows Cadence users to perform accurate EM modelling on selected Virtuoso cells,for physical verification of critical components and interconnections.This plug-in solution allows designers to extract a Sonnet EM analysis cell view directly from the layout view.Simulation results can be easily back annotated to the Cadence schematic.High precision electromagnetic(EM)analysis with Sonnet complements the traditional RC extraction tools.With Sonnet,simulation results include all physical effects like coupling, skin effect,proximity effect,surface waves and radiation.While traditional RC extraction tools like Cadence Assura are optimised to handle full chip extraction,Sonnet analysis is most suitable to rigorously analyze individual components,interconnects and smaller parts of a layout with very high confidence.With Sonnet,you can replace legacy3D finite element solvers,which are often not integrated into the Cadence design flow and require cumbersome and error prone manual modelling and data transfer.Sonnet Professional Key BenefitsSonnet Professional enables you to:∙Accurately model passive components (inductors,capacitors,resistors)to determine values like RLC and Q factor∙Accurately model multi layer interconnects and via structures∙Generate a technology accurate electrical model for arbitrary layout shapes ∙Quantify parasitic coupling between components,interconnects and vias ∙Include substrate induced effects like substrate loss∙Visualize the current flow in components,interconnects and viasSonnet Professional Key FeaturesThe key features of Sonnet Professional include:∙FFT based Method of Moments analysis for ultimate reliability and accuracy ∙Easy to learn,easy and efficient to use∙Only one high precision analysis engine –no need to switch between solvers ∙Conformal Meshing for very efficient high accuracy meshing of curved structures ∙Finite thickness modelling (including advanced n-sheet model)∙Dielectric bricks for truncated dielectric materials (e.g.MIM capacitor)∙Adaptive Band Synthesis for fast and reliable frequency sweeps with a minimum number of EM samples -more efficient than traditional approaches∙Easy to use data display for analysis results,including R,L,C,Q evaluation ∙Equation capability for pre-defined or customized calculation on simulated data ∙Seamless integration into the Cadence Virtuoso design environment∙All configuration and technology setup is menu /dialog based–no need to edit configuration text files∙Remote simulation capability∙Compatible with the LSF cluster and load balancing system ∙Sonnet Software Inc.is a Cadence Connectionspartner.Technology (Cadence library)Spectre SPICES/Y/Z-parametersBroad band SPICE model w/symbolsWhen to Use Sonnet EM AnalysisThe use of electromagnetic analysis with Sonnet Professional is especially valuable in the following design situations:When parasitic coupling is present.Parasitic coupling is not always easy to predict without using electromagnetic analysis.Even elements which are"sufficiently"far apart can suffer from parasitic coupling:inductive or capacitive coupling,resonance effects due to grounding and surface waves that might propagate at the substrate boundary under certain conditions.Sonnet Professional analysis is based on the physical properties of your technology and will account for such physical effects.When accurate circuit models are not available or circuit model parameters are out of range.Model based circuit simulators are based on models for a specific application, with limited parameter range.For example,only selected geometries,substrate types and substrate parameters are available.It is difficult to estimate the error induced by parameter extrapolation,so using models outside their designed parameter range is not suitable for critical applications.Whenever a layout feature cannot be described by a circuit model,due to its geometry or technology,the physics based analysis with Sonnet Professional will provide the answer. An example for this could be a special inductor,capacitor or transformer which is not included in the design kit.Sonnet can be used to analyze those components"on the fly",or generate a full library of components models with trust worth electrical results.Sonnet EM Design ProcessThe following steps describe a typical process for creating and simulating a design with Sonnet Professional for Cadence Virtuoso.Define the stack-up and material properties.A simulation model for Sonnet Professional contains a number of layered dielectrics,conductor levels at the interface between dielectric layers and vias to connect different conductor levels.To simulate a layout in Sonnet,these material properties and definitions("technology")are required.Typically,the EDA support group will define and qualify a technology file for a Cadence library and release that to the RFIC designers.This is an easy and straightforward process once the material properties are known,because that definition is fully menu and dialog driven.When a designer creates a Sonnet simulation view of a cell,that pre-defined Sonnet technology file will be automatically loaded from the Cadence library.Make Sonnet View.Based on the layout view of a cell,the designer can easily create the Sonnet analysis view for that cell.If the cell layout contains hierarchy,the hierarchy will be resolved to create a flattened Sonnet EM view.Define the analysis box.With Sonnet's FFT based approach to method of Moments,it is necessary to define a finite analysis area("box")and a uniform sampling resolution("cell size").This defines the granularity for the analysis,and usually requires a trade off between analysis time and accuracy.The user defined cell size is very useful to control the meshing density of very complex shapes,to avoid over-meshing the circuit without any need for manual clean-up.Assign port numbers and properties.In Sonnet,circuit ports connect the analysed structure withthe outer circuit.Different port types are available fordifferent purposes.Cadence pins can be converted to Sonnetports fully automatically,based on the defined mapping.Where needed,feed lines will be extended to the boundaryof the analysis area automatically,and de-embedded fromthe analysis results.Define analysis frequencies.Sonnet uses the Method of Moments where the circuit is analysed at different frequencies of interest.With the unique Adaptive Band Synthesis (ABS)in Sonnet,an accurate wide band response can be obtained from a minimum number of EM simulated data points within a given frequency range.Using ABS,the designer only needs to enter the start and stop frequency.Of course, composite frequency sweeps are also possible,as well as a"DC"point.Save state(optional).An optional step after setting up all these parameters is to store the current"state"of the analysis settings for later re-use.This way,all settings can be loaded into a similar project easily.Define desired output format(optional).The desired analysis results can be for example S/Y/Z parameters,a schematic symbol with ADS or Spectre frequency domain data or a schematic symbol for broad band SPICE extracted data.The designer can define the desired output data before starting the Sonnet EM simulation,or generate the data later as a post processing task after EM analysis has finished.View simulation model in Sonnet(optional).If desired,the designer can take the simulation model as a2D or3D view to Sonnet,and review it in the Sonnet model editor. This is especially useful for complex multi layer circuits.The Sonnet interface will keep track of any manual changes,to makes sure that the Virtuoso view and the Sonnet view stay in sync.Simulate the circuit.The simulation can be started from within Cadence Virtuoso.The Sonnet analysis monitor will show analysis progress and an estimate of the memory requirement and total simulation time.View simulation results.When the simulation is done,simulation results can be viewed with the Sonnet plotting tool.It is possible to plot already available results while the analysis engine is still analysing more frequencies.Parameters like inductor L and Q or capacitor C and Q can be plotted immediately by using pre-defined equations.When the current distribution is of interest,the simulation can be configured to store current density data.That data can be visualized in various ways as2D or3D graphs.For a better understanding of the circuit,the current density or charge visualization can also be animated over time or frequency.Current density results can be exported to a spread sheet for post processing.In the current density image shown here,note the smooth display of the current distribution,which shows high edge current(required to calculate the conductor losses properly)and current crowding.This is one indication of the high resolution and high precision of the Sonnet analysis result.Back annotate results to the Cadence schematic.When the Sonnet analysis is finished, results are available in different formats.This includes both S/Y/Z-parameters for frequency domain simulation,as well as a broad band SPICE extraction for time domain (SPICE)simulation.Cadence schematic symbols to hold those Sonnet results are created fully automatically, with all the required mapping files.A sub-circuit schematic for the analysed cell is also created fully automatically.Example1Octagon inductor in the IHP250nm technology(SGB25V)with thick metal effects modeled. The technology files for Sonnet EM analysis have been developed by Dr.Mühlhaus Consulting&Software GmbH and are available to IHP customers with the design kit. Design and Measurement courtesy of IHP MicroelectronicsMeasured vs.Calculatedpink=measuredblue=Sonnet resultExample2Octagon inductor in the IHP250nm technology(SGB25V)with thick metal effects modeled. The technology files for Sonnet EM analysis have been developed by Dr.Mühlhaus Consulting&Software GmbH and are available to IHP customers with the design kit. Design and Measurement courtesy of IHP MicroelectronicsMeasured vs.Calculatedpink=measuredblue=Sonnet resultExample39.25-turn Circular Spiral Inductor on100um Silicon(step-graded conductivity in substrate). 5insulating layers between1um and3um,thick metal effects modeledData and design courtesy of Motorola SPS/WISDMeasured vs.Calculatedred=measuredblue=Sonnet result。
有机融合英语表达Organic Integration of English ExpressionThe dynamic and ever-evolving nature of language is a testament to the adaptability and ingenuity of the human mind. As we navigate the complexities of communication, the seamless integration of various linguistic elements has become a crucial aspect of effective expression. In this essay, we will explore the concept of organic integration of English expression, delving into the nuances and benefits of this approach.At the core of organic integration lies the recognition that language is not a static entity but rather a living, breathing medium that evolves alongside the changing needs and dynamics of human interaction. In the context of English expression, this principle encourages a holistic and adaptive approach to language use, where the speaker or writer consciously incorporates diverse elements to enhance the richness and impact of their communication.One of the primary advantages of organic integration is its ability to bridge the gap between formal and informal language use. Traditional language instruction often emphasizes the importance ofadhering to rigid grammatical rules and prescribed norms. While this foundation is undoubtedly crucial, the reality of everyday communication often demands a more flexible and contextual approach. Organic integration empowers individuals to seamlessly transition between formal and informal registers, allowing them to adapt their language to the specific needs of the situation and their audience.This flexibility is particularly valuable in the modern era, where diverse modes of communication have become the norm. From professional email exchanges to casual social media interactions, the ability to navigate these varying contexts with ease can be a significant asset. By organically integrating elements of both formal and informal language, individuals can cultivate a more nuanced and effective communication style, enabling them to convey their message with clarity, authenticity, and impact.Furthermore, organic integration fosters the incorporation of cultural and linguistic diversity into English expression. As the world becomes increasingly interconnected, the influence of other languages and cultural frameworks on the evolution of English is undeniable. Organic integration encourages the embracing of these diverse linguistic elements, allowing individuals to infuse their English expression with unique perspectives, idioms, and modes of thought.This approach not only enriches the individual's communication but also contributes to the broader tapestry of English as a global language. By embracing the organic integration of diverse linguistic influences, speakers and writers can actively shape the trajectory of English, ensuring that it remains a vibrant and inclusive medium of expression.Moreover, the practice of organic integration fosters creativity and innovation in language use. By breaking free from the constraints of rigid rules and traditional norms, individuals can experiment with novel combinations of language elements, unleashing their linguistic imagination. This creative exploration can lead to the emergence of new expressions, the evolution of existing idioms, and the development of unique rhetorical strategies.The benefits of organic integration in English expression extend beyond the individual level, as it can also have a profound impact on educational and professional spheres. In the realm of language education, for instance, this approach can challenge the traditional emphasis on rote learning and passive acquisition of linguistic knowledge. Instead, it encourages a more dynamic and engaged learning process, where students are empowered to explore the nuances of language, experiment with different modes of expression, and develop a deep understanding of the contextual and cultural factors that shape communication.In the professional world, the ability to organically integrate English expression can be a valuable asset in a variety of settings. From effective business communication to persuasive public speaking, the mastery of this skill can contribute to career advancement, collaboration, and the successful negotiation of complex situations. Employers increasingly seek individuals who can navigate the ever-changing landscape of language use with agility and adaptability.In conclusion, the organic integration of English expression is a multifaceted and powerful concept that holds immense potential for personal growth, cultural enrichment, and professional success. By embracing the dynamic nature of language and capitalizing on the diversity of linguistic elements, individuals can cultivate a more nuanced, versatile, and impactful communication style. As we continue to navigate the evolving landscape of language, the practice of organic integration will undoubtedly play a crucial role in shaping the future of English expression.。
uIntegration of Bosch and third party systems through deployment of OPCu All relevant information in one user interface u Fully embedded access controlu Full event log for forensic investigations uScalable system that grows with your needsThe Building Integration System (BIS)BIS is a flexible, scalable security and safetymanagement system that can be configured to handle an enormous spectrum of operational scenarios.It contains a huge range of applications and features which enable both the integration and coupling as well as the monitoring and control of all technical building systems.This new version builds on Bosch's many years of experience in management systems and was considerably influenced by the following market trends:•Increasing complexity of technical building equipment The increasing complexity of technical equipment inside buildings requires a powerful management system which combines the most varied functions (e.g. fire and intrusion alarm systems, access control,video systems and building automation... etc.) in the best possible way. The OPC standard enables BIS to process and share information efficiently with a huge variety of hardware devices and other sources.•Using new technologies and standardsWhile the strict regulations in the field of security technology ensure a high degree of reliability in security matters, they hinder the integrated use of new technologies from the IT world. BIS hassucceeded in harnessing the benefits of non-security-based technologies (e.g. OPC, CAD, web) and harmonizing them with the world of security technologies.•Need for complete solutionsFacility managers and integrators are demanding a single building-management solution that is nevertheless able to integrate all their security subsystems.System overviewThe Building Integration System is a versatile product made up of a basic package plus various optional components (also known as Engines) based on a common software platform. The engines can becombined to tailor building management systems to detailed requirements.These main components are:•Automation Engine •Access Engine •Video Engine •Security Engine* not available in all countriesThese engines are described in greater detail in separate datasheets.FunctionsSystem architectureThe BIS Engines provide fire and intrusion detection,access control, video surveillance plus the monitoring of HVAC and other vital systems.BIS is based on a performance-optimized multi-tier architecture especially designed for use in Intranet and Internet environments.Subsystems are connected via the well-established,world-wide OPC standard. This open standard makes it easy to insert BIS into existing OPC-compliant subsystems.Optionally, individual BIS systems can cooperate by providing data to, or consuming data from, other BISsystems. The result is a Multi-server BIS system.1. A BIS consumer server with workstations and router in a local area network (LAN)2.Wide area network (WAN)3.BIS provider servers with workstations and routers in local area networks (LAN)Organizational structure and configurationA number of automatic functions and easy-to-use tools make configuration installer-friendly, saving time and expense.Hierarchical location trees can be created by theimport of existing CAD data containing layers, named views and detector locations. Zooming and panning allow rapid navigation through the building.The user interface is web -based using dynamic HTML pages. Default pages for different screen resolutions and formats are included in the installation software,and the default pages can easily be customized using a standard HTML editor.BIS automatically detects the monitor resolution and provides the appropriate user interface.OperationThe system’s main task is to operate as the alarm-monitoring and control center for the various security systems within a site. Its graphical interface isdesigned to help the operator grasp the extent and urgency of an occurrence quickly, and to take promptand effective action.The heart of the system, the State Machine, monitors all incoming events and operator requests and, if desired, can take actions prescribed by user-defined rules or Associations, thus unburdening the operators.System securityAES encryption between BIS central server andworkstations provides additional security in addition to configurable user-access rights. If PCs within a corporate network are to be used as clientworkstations then enhanced security can be achieved by restricting operators to specific workstations or IP-addresses.Basic packageThe Building Integration System basic packageprovides many features used in common by the various Engines.•Customizable device condition counters to provide an overview of the condition of subsystems across the entire BIS system•Message processing and alarm display•Alarm queue with up to 5000 simultaneous alarmevents and detailed alarm information•Fixed assignment of operators to workstations for higher security•State machine for automated event and alarm handling.•Web-server-based platform allows client workstations to connect to BIS via just the Internet Explorer •Direct support for location maps in standardAutoCAD DWF vector format reduces configurationeffort.•Changes to architecture within a graphic (new walls,moving a door, etc.) can be implemented without changing the BIS configuration, simply import a new plot file.•Automated workflows between operators, with message broadcasting and customizable escalation paths•Huge library of standardized detector icons in standard vector format including color, event and control definitions•Direct control and monitoring of detectors via the context menus of their icons in the location maps •Direct control and monitoring of detectors via the logical tree-structure (e.g. building – floor – room) of a site, with hyperlinks to photos, manuals,instructions•Location tree generated automatically from the "named views" within the AutoCAD graphic•Action management for automatic and manual control into connected subsystems and their peripherals•Device overview for all connected subsystems, and their peripherals (detectors) and internal virtual devices (operator, server, ...) in the form of a tree structure with detailed information about address,status, type, location and notes. Control theperipherals via the context menus of their tree nodes.•Ability to compartmentalize the managed site into autonomous Divisions, and to restrict operators to the control of specific Divisions.•Ability to provide specific information to the operator in the form of free-form “miscellaneous” hypertext documents, including text, bitmaps, video images,etc.•Highly configurable operator access rights for monitoring and control of subsystems and their peripherals•Event log to ensure all events are completely documented (including messages received and actions taken)•Reporting services to quickly create reports from the event log•Linking and embedding of OPC servers from any computer in the network •Online HelpAction plans and location mapsBIS amplifies standard alarm-handling by its ability to display action plans and location maps, including graphical navigation and the alarm-dependentvisualization of layers inside those maps. This ensures optimal guidance to operators especially in stress situations, such as fire or intrusion alarms.Alarm-dependent action plans or workflows provide detailed event-dependent information such as standard operating procedures, live images, control buttons, etc. to the operator. Simply create and assign one action plan to each possible alarm type in your system, e.g. fire alarm, access denied, technical alarms, etc.With the deletion of an alarm message an unmodifiable snapshot of the displayed action plan is attached to the event log. This ensures accountability by providing a trace of all steps performed by the operator duringthe alarm response.•Location maps are a visualization of premises e.g.floors, areas or rooms, based on the popular AutoCAD vector-graphics format. Detectors and other devicesare represented by colored, animated icons thatprovide direct control via their context menus. In the case of an alarm the system zooms automatically tothe location in the map where it was triggered.• A location tree provides entry points to the locationmap and its graphical navigation functions (pan,zoom).•Alarm-dependent layer control allows the display ofadditional graphical information for specificsituations, e.g. escape routes in case of fire alarms. BIS optional accessoriesThe optional features listed below can be added to the BIS system to meet specific customer requirements. They are usable with all the BIS Engines (Automation, Access, Video and Security Engine).Alarm management packageThis package extends the standard alarm-handling of your BIS system by some additional features: Message distribution allows the definition of escalation scenarios which are activated automatically when an operator or operator group fails to acknowledge an alarm message within a defined period. BIS will then forward the message automatically to the next authorized operator group. The timer feature allows the setup of time schedules which can be used to perform automatic control commands, such as closing a barrier at 8:00 pm, as well as for time-dependent redirection of alarm messages, e.g. within time period 1 show message tooperator group 1 else to operator group 2.The operator alarm feature allows an operator to trigger an alarm manually from the location tree, for example, if informed by telephone of a dangerous situation. Such manual alarms are processed in the same way as those triggered by a detector: that is, the associated documents are displayed and all steps taken are recorded in the event log.The application launcher allows the invocation of non-BIS applications by the system based upon predefined conditions, e.g. alarms or timers. A typical application of this would be for an automatic, scheduled system backup.Building Integration System in figuresParts includedWhen ordered as Installation Media in Box the box contains:ponents1BIS Installation medium with software and installation manuals as PDF1Quick installation guide (printed)When downloaded (Version 4.0 and later) the online documentation is contained in the download.The basic package includes the following licenses: ponents1Operator client license1Division licenseTechnical specificationsMinimum technical requirements for a login or connection serverMinimum technical requirements for a client computerOrdering informationBIS is available in the following languages:•DE = German•EN = English•ES = Spanish•FR = French•HU = Hungarian•NL = Dutch•PL = Polish•PT = Portuguese•RU = Russian•TR = Turkish•ZH-CN = Simplified Chinese•ZH-TW = Traditional ChineseA BIS basic license is required when setting up a new systemBIS 4.1 Basic LicenseLicense for the use of the software as downloadedfrom the website. No physical parts are delivered andthe user documentation is contained in the download.Order number BIS-BGEN-B41BIS 4.1 Installation Media in BoxBox contains the installation medium for all languagesand the Quick Installation Guide.Order number BIS-GEN-B41-BOXBIS 4.1 Alarm Management PackageLicense for the addition to BIS of the feature specifiedOrder number BIS-FGEN-AMPK41BIS 4.1 additional 1 Operator ClientLicense for the addition to BIS of the feature specifiedOrder number BIS-XGEN-1CLI41BIS 4.1 additional 1 DivisionLicense for the addition to BIS of the feature specifiedOrder number BIS-XGEN-1DIV41BIS 4.1 Multi-Server Connect per ServerLicense for the addition to BIS of the feature specifiedOrder number BIS-FGEN-MSRV41BIS Upgrade from 3.0 to 4.xLicense for an upgrade between the versionsspecified.Order number BIS-BUPG-30TO40BIS Upgrade from 2.x to 4.xLicense for an upgrade between the versionsspecified.Order number BIS-BUPG-2XTO40BIS 4.1 BVMS ConnectivityLicense for the connection between one BIS and oneBVMS installationOrder number BIS-FGEN-BVMS41Represented by:Americas:Europe, Middle East, Africa:Asia-Pacific:China:America Latina:Bosch Security Systems, Inc. 130 Perinton Parkway Fairport, New York, 14450, USA Phone: +1 800 289 0096 Fax: +1 585 223 9180***********************.com Bosch Security Systems B.V.P.O. Box 800025617 BA Eindhoven, The NetherlandsPhone: + 31 40 2577 284Fax: +31 40 2577 330******************************Robert Bosch (SEA) Pte Ltd, SecuritySystems11 Bishan Street 21Singapore 573943Phone: +65 6571 2808Fax: +65 6571 2699*****************************Bosch (Shanghai) Security Systems Ltd.203 Building, No. 333 Fuquan RoadNorth IBPChangning District, Shanghai200335 ChinaPhone +86 21 22181111Fax: +86 21 22182398Robert Bosch Ltda Security Systems DivisionVia Anhanguera, Km 98CEP 13065-900Campinas, Sao Paulo, BrazilPhone: +55 19 2103 2860Fax: +55 19 2103 2862*****************************© Bosch Security Systems 2015 | Data subject to change without notice 181****2875|en,V7,30.Nov2015。
第1篇IntroductionProject-Based Learning (PBL) is an instructional method that emphasizes active student engagement, collaboration, and real-world problem-solving skills. It has gained significant attention in the field of education due to its effectiveness in fostering critical thinking, creativity, and independence. In recent years, PBL has been increasingly adopted in English language teaching (ELT) to enhance students' languageproficiency and intercultural communication skills. This paper aims to explore the implementation of PBL in English language teaching in China, examining its effectiveness, challenges, and future prospects.BackgroundThe adoption of PBL in ELT is driven by several factors. Firstly, the traditional teacher-centered approach to language learning has been criticized for its focus on rote memorization and lack of real-world application. PBL, on the other hand, encourages students to engage in authentic language use and develop a deeper understanding of the language. Secondly, with the rapid globalization of the world, there is an increasing demand for English language skills in various fields. PBL helps students develop these skills by immersing them in real-life contexts.Implementation of PBL in Chinese ELT1. Integration of PBL into the curriculumIn China, PBL has been gradually integrated into the English language curriculum. Many schools have adopted a project-based approach to complement the traditional teaching methods. The integration of PBL into the curriculum involves several steps:a. Designing project-based units: Teachers design units that are relevant to students' lives and interests. These units are typically interdisciplinary, combining language learning with other subjects such as science, history, or art.b. Selecting project topics: Teachers and students collaborate to choose project topics that are meaningful and engaging. The topics should be challenging yet achievable and should promote critical thinking and problem-solving skills.c. Implementing project activities: Students work in groups to complete various tasks, such as research, writing, presenting, and creating multimedia products. Teachers facilitate the learning process by providing guidance and resources.2. Student engagement and collaborationPBL encourages active student engagement and collaboration. In Chinese ELT, students are often encouraged to work in pairs or small groups to complete project tasks. This promotes peer learning and allows students to learn from each other's strengths and weaknesses. Additionally, students are expected to take on different roles within the group, such as leader, researcher, or presenter, which helps develop their communication and teamwork skills.3. Assessment of PBLAssessment in PBL is often more holistic than in traditional teaching methods. Teachers evaluate students based on various criteria, including:a. Project completion: The extent to which the project goals are achieved and the quality of the final product.b. Group collaboration: The effectiveness of teamwork, communication, and division of labor within the group.c. Individual contributions: The level of participation and contribution of each student to the project.d. Language skills: The use of English in communication, writing, and other language-related tasks.Challenges and Solutions1. Teacher training and professional developmentOne of the main challenges in implementing PBL in Chinese ELT is the lack of teacher training and professional development. To address this, schools can offer workshops, seminars, and online courses to help teachers develop the necessary skills and knowledge to effectively implement PBL.2. Time constraintsPBL requires more time than traditional teaching methods, which can be challenging for schools with a packed curriculum. To overcome this, teachers can allocate specific time slots for project-based activities or integrate PBL into existing units to maximize the use of class time.3. Cultural differencesCultural differences can also pose challenges to PBL implementation. To address this, teachers should be aware of cultural nuances and adapt their teaching strategies accordingly. They can also encourage students to explore their own cultural backgrounds and share them with others in the classroom.ConclusionProject-Based Learning (PBL) has shown great potential in enhancing English language teaching in China. By promoting active student engagement, collaboration, and real-world problem-solving skills, PBL helps students develop a deeper understanding of the language and prepares them for future challenges. However, the successful implementation of PBL requires ongoing teacher training, flexibility in the curriculum, and an awareness of cultural differences. As PBL continues to gain popularity in Chinese ELT, it is essential for educators to address these challenges and capitalize on the benefits of this innovative teaching approach.ReferencesBarr, R. B., & Kozol, R. J. (2009). Project-based learning for the 21st century: Skills for the future. San Francisco: Jossey-Bass.Duffy, T. M., & Cunningham, D. G. (2003). Constructivism: Implicationsfor the design and delivery of instruction. Upper Saddle River, NJ: Pearson Education, Inc.Harmer, J. (2007). The practice of English language teaching (4th ed.). Essex: Pearson Education Limited.Little, D., &ourage, A. (2001). Theories of curriculum development. New York: RoutledgeFalmer.第2篇Project-based learning (PBL) has gained significant traction in the educational landscape worldwide, and China is no exception. This innovative teaching approach, which emphasizes hands-on, student-centered learning, has been increasingly adopted in Chinese schools and universities. This article delves into the practical implementation of PBL in China, exploring its benefits, challenges, and future prospects.The Rise of Project-Based Learning in ChinaThe integration of PBL into the Chinese educational system is a response to the country's evolving educational goals and the demands of a rapidly changing global economy. The traditional rote-learning model, which has long dominated Chinese classrooms, is being replaced by a more dynamic and interactive approach that fosters critical thinking, problem-solving, and creativity.Benefits of Project-Based Learning1. Enhanced Student Engagement: PBL encourages students to take anactive role in their learning process. By working on real-world problems and projects, students become more motivated and engaged in the subject matter.2. Development of 21st Century Skills: PBL promotes the development of critical 21st-century skills such as collaboration, communication, and creativity. These skills are essential for students to succeed intoday's interconnected world.3. Increased Retention of Knowledge: When students are actively involved in their learning, they are more likely to retain the knowledge andskills they acquire. PBL encourages students to apply their knowledge in practical situations, making the learning experience more memorable.4. Enhanced Teacher-Student Interaction: PBL creates a morecollaborative and interactive classroom environment, fostering better communication between teachers and students. This can lead to a more supportive and engaging learning experience.Challenges of Implementing PBL in ChinaDespite its many benefits, the implementation of PBL in China faces several challenges:1. Resource Allocation: PBL requires additional resources, including time, space, and materials. Many schools in China struggle with limited resources, making it difficult to fully implement PBL.2. Teacher Training: Teachers need to be trained in PBL methodologiesand techniques. However, many Chinese educators lack the necessary training and experience to effectively implement PBL in their classrooms.3. Assessment and Evaluation: The traditional assessment methods used in Chinese schools may not be suitable for evaluating PBL projects. Developing new assessment tools and criteria can be challenging.4. Cultural and Educational Barriers: The traditional educationalculture in China may resist the adoption of PBL. Some educators and parents may view PBL as a less rigorous or less effective teaching method compared to the traditional approach.Practical Approaches to Implementing PBL in ChinaTo overcome these challenges, Chinese educators and policymakers cantake the following steps to implement PBL effectively:1. Invest in Teacher Training: Provide comprehensive training programsfor teachers to develop their skills in PBL methodologies and techniques.This will enable them to create engaging and effective learning experiences for their students.2. Develop Curricula and Resources: Create PBL-friendly curricula and resources that align with the country's educational goals. These resources should be designed to support the development of 21st-century skills and promote student-centered learning.3. Collaborate with Industry and Community: Partner with local businesses, non-profit organizations, and community groups to provide real-world project opportunities for students. This will help students connect their learning to the outside world and develop practical skills.4. Foster a Culture of Innovation: Encourage schools and educators to adopt a more innovative and flexible approach to teaching and learning. This includes creating an environment that supports risk-taking, experimentation, and collaboration.Case Studies of Successful PBL Implementation in ChinaSeveral schools and universities in China have successfully implemented PBL. Here are a few examples:1. Tsinghua University: The university has integrated PBL into its engineering and business programs, encouraging students to work on real-world projects with industry partners.2. Beijing Normal University: The university offers a PBL-based curriculum in its education program, where students design and implement educational projects in local schools.3. Shanghai High School: The school has implemented PBL in its science and technology courses, allowing students to work on projects related to environmental sustainability and renewable energy.Future Prospects of PBL in ChinaThe future of PBL in China looks promising. As the country continues to modernize its educational system, PBL is expected to play anincreasingly important role in preparing students for the challenges ofthe 21st century. By addressing the challenges and leveraging the benefits of PBL, China can create a more dynamic and effective educational environment for its students.In conclusion, project-based learning is a valuable teaching approach that has the potential to transform education in China. By embracing PBL and addressing the challenges associated with its implementation, Chinese educators can help prepare a generation of students who arewell-equipped to thrive in the global economy and society.第3篇IntroductionProject-based learning (PBL) has gained popularity in recent years as an effective teaching method that emphasizes students' active engagement and collaborative learning. In China, PBL has been increasingly adopted in various educational contexts, including primary, secondary, and higher education. This paper aims to explore the practices of PBL in China, focusing on its implementation, challenges, and benefits. Through a literature review and case studies, this paper aims to provideinsights into the integration of PBL in the Chinese educational system and its potential for enhancing students' learning outcomes.1. Theoretical Framework of Project-Based LearningPBL is an instructional approach that involves students in an inquiry process in which they investigate and respond to a complex question, problem, or challenge (Krauss, 2011). This method encourages students to work collaboratively, integrate knowledge and skills from different disciplines, and apply their learning to real-world contexts. The theoretical framework of PBL is based on constructivist learning theory, which posits that learning is an active process of constructing knowledge and understanding through social interaction and problem-solving (Vygotsky, 1978).2. Practices of Project-Based Learning in China2.1 Implementation of PBL in SchoolsIn China, PBL has been implemented in various educational settings, such as primary schools, secondary schools, and higher education institutions. Here are some examples of PBL practices in China:2.1.1 Primary SchoolsIn primary schools, PBL is often integrated into language arts, science, and social studies curricula. Teachers design projects that encourage students to explore themes and topics across different subjects. For instance, a project on "My Community" may involve students inresearching local history, geography, and culture, and presenting their findings through different forms of media, such as videos, podcasts, or presentations.2.1.2 Secondary SchoolsIn secondary schools, PBL is more likely to be used in specialized subjects such as science, technology, engineering, and mathematics (STEM). Teachers design projects that require students to apply their knowledge and skills to solve real-world problems. For example, aproject on "Designing a Sustainable Home" may involve students in researching energy-efficient materials and constructing a model homethat minimizes energy consumption.2.1.3 Higher EducationIn higher education, PBL is commonly used in interdisciplinary courses and research projects. Students are encouraged to work in teams to investigate complex issues and propose innovative solutions. For instance, a project on "Global Warming" may involve students inanalyzing data, conducting experiments, and developing policy recommendations.2.2 Challenges of Implementing PBL in ChinaDespite the growing popularity of PBL in China, there are several challenges associated with its implementation:2.2.1 Teacher TrainingMany teachers in China are not adequately trained to implement PBL effectively. They may lack the necessary skills in project design, assessment, and facilitation. This can hinder the successful implementation of PBL in the classroom.2.2.2 Curriculum RestrictionThe traditional Chinese curriculum is often structured around teacher-centered instruction and standardized testing. This may limit the flexibility required for PBL, which emphasizes student-centered,inquiry-based learning.2.2.3 AssessmentAssessment in China is often based on standardized tests and paper-based exams. This may make it challenging to assess students' project-based learning outcomes effectively.3. Benefits of Project-Based Learning in ChinaDespite the challenges, PBL has several benefits for students and educators in China:3.1 Enhanced Learning OutcomesPBL has been shown to improve students' learning outcomes in various domains, including critical thinking, problem-solving, and collaboration (Hannafin, Land, & Oliver, 1999). In China, PBL can help students develop a deeper understanding of complex concepts and apply their knowledge to real-world contexts.3.2 Increased Student EngagementPBL can increase student engagement by providing a more dynamic and interactive learning experience. Students are more likely to be motivated and interested in learning when they are actively involved in project work.3.3 Teacher Professional DevelopmentPBL can also promote teacher professional development by encouraging teachers to reflect on their teaching practices and collaborate with their colleagues. This can lead to improved teaching and learning outcomes in the classroom.ConclusionProject-based learning has gained significant traction in China as an effective teaching method that encourages students' active engagement and collaborative learning. While there are challenges associated with its implementation, PBL has the potential to enhance students' learning outcomes and promote teacher professional development. Further research and collaboration are needed to explore the best practices for implementing PBL in the Chinese educational system and to address the challenges faced by educators and students.。
巡网一体化出租车经营方案范文(中英文实用版)English:The integration of patrol and network-based taxi operation schemes is a innovative approach to enhance the efficiency and convenience of taxi services.This sample business plan outlines the key components and strategies for a successful integration of these two models.Firstly, the integration of patrol and network-based taxi services allows for a more flexible and responsive transportation solution.With a combination of traditional street-hailing and digital app-based bookings, passengers can easily hail a cab either on the street or through a mobile app.This dual approach ensures that no potential customer is left unserved.中文:巡网一体化出租车经营方案是一种创新模式,旨在提高出租车服务的效率和便利性。
本范例商业计划概述了这两种模式成功整合的关键组成部分和策略。
首先,巡网一体化出租车服务的整合为乘客提供了一个更加灵活和响应迅速的交通解决方案。
结合传统的街头招手和数字应用程序预约,乘客可以轻松地在街头或通过移动应用程序召唤出租车。
四链融入创新案例In the realm of innovation, the integration of four key chains—the technology chain, the industry chain, the capital chain, and the talent chain—has proven to be a pivotal strategy for driving sustainable growth and competitiveness. This approach not only enhances the efficiency of innovation processes but also facilitates the commercialization of novel ideas and technologies.在创新领域中,技术链、产业链、资金链和人才链这四大链条的整合,已成为推动可持续发展和竞争力的关键策略。
这种方法不仅提高了创新过程的效率,还促进了新颖想法和技术的商业化。
Let's delve into a specific case study where this integration has been successfully implemented. A leading technology company, seeking to expand its market share in a rapidly evolving industry, embarked on a journey to integrate these four chains. The company recognized that a siloed approach to innovation, where each chain operated independently, was hindering its ability to bring new products to market quickly and effectively.现在,我们深入剖析一个具体案例,该案例成功实施了这一整合策略。
A State-based Approach to Integration Testing based on UML Models Shaukat Ali1, Lionel C. Briand2, Muhammad Jaffar-ur Rehman1, Hajra Asghar1, Muhammad Zohaib Z. Iqbal1, AamerNadeem11Center for Software Dependability, Mohammad Ali Jinnah UniversityIslamabad, Pakistan{shaukat, hajra, zouhaib, anadeem}@.pk2Software Quality Engineering Laboratory, Department of Systems and Computer Engineering, CarletonUniversity, Canadabriand@sce.carleton.caAbstract:Correct functioning of object-oriented software depends upon the successful integration ofclasses. While individual classes may function correctly, several new faults can arise when theseclasses are integrated together. In this paper, we present a technique to enhance testing of interactionsamong modal classes. The technique combines UML collaboration diagrams and statecharts toautomatically generate an intermediate test model, called SCOTEM (State COllaboration TEst Model).The SCOTEM is then used to generate valid test paths. We also define various coverage criteria togenerate test paths from the SCOTEM model. In order to assess our technique, we have developed atool and applied it to a case study to investigate its fault detection capability. The results show that theproposed technique effectively detects all the seeded integration faults when complying with the mostdemanding adequacy criterion and still achieves reasonably good results for less expensive adequacycriteria.Key Words: UML based testing, automated testing, object-oriented systems1 IntroductionThe Object-oriented (OO) paradigm offers several benefits, such as encapsulation, abstraction, and reusability to improve the quality of software. However, at the same time, OO features also introduce new challenges for testers: interactions between objects may give rise to subtle errors that could be hard to detect.The Unified Modeling Language (UML) has emerged as the de-facto standard for analysis and design of OO systems. UML provides a variety of diagramming notations for capturing design information from different perspectives. In recent years, researchers have realized the potential of UML models as a source of information in software testing [17, 53, 7, 23, 26, 29, 30, 11, 35, 39, 56, 47, 14, 48]. Many UML design artifacts have been used in different ways to perform different kinds of testing. For instance, UML statecharts have been used to perform unit testing, and interaction diagrams (collaboration and sequence diagrams) have been used to test class interactions.Modularity aims at encapsulating related functionalities in classes. However, complete system-level functionality (use case) is usually implemented through the interaction of objects. Typically, the complexity of an OO system lies in its object interactions, not within class methods which tend to be small and simple. As a result, complex behaviours are observed when related classes are integrated and several kinds of faults can arise during integration: interface faults, conflicting functions, missing functions [1]. Thus testing each class independently does not eliminate the need for integration testing. A large number of possible interactions between collaborating classes may need to be tested to ensure the correct functionality of the system.In this paper, we present a technique that enhances the integration testing1 of classes by accounting for all possible states of collaborating classes in an interaction. This is important as interactions may trigger correct behavior for certain states and not for others. In order to achieve such an objective the proposed technique builds an intermediate test model called SCOTEM (State COllaboration TEst Model) from a UML collaboration diagram and statechart diagrams of the objects involved in the object interactions. The SCOTEM models all possible paths for object state transitions that a message sequence may trigger. The test generator uses SCOTEM to generate test paths whose corresponding test cases aim at detecting the faults that may arise due to invalid object states during object interactions. This paper also reports a case study in order to assess the cost-effectiveness of various test adequacy criteria based on the SCOTEM test model.The rest of this paper is organized as follows: Section 2 presents a brief survey of the related works in the areas of state-based testing and UML-based test path generation; Section 3 presents the proposed approach to integration testing, including a discussion of coverage criteria for test path generation; Section 4 describes the prototype tool that we have developed to automate the proposed technique; Section 5 presents a case study to investigate the cost-effectiveness of the proposed technique; and finally Section 6 concludes the paper.Work2 RelatedTraditional testing strategies for procedural programs, such as data flow analysis and control flow analysis cannot be directly applied to OO programs [35]. Extensions of these techniques for OO programs have been proposed by Buy et al. [26] and Martena et al. [41]. A structural test case generation strategy by Buy et al. [26] generates test cases through symbolic execution and automates deduction for the data flow analysis of a class. Kung et al. [36] proposed an idea to extract state models from the source code, whereas others suggest test generations from pre-existing state-models [58, 29, 48, 11, 47, 56, 40]. In the sections below, we will discuss more specific UML-based testing techniques.2.1 UML based Test GenerationIn the section below, we will discuss techniques that support different levels of testing using UML diagrams.2.1.1 Unit Level TestingUnit level testing refers to the tests performed to check the correct functionality of individual execution units. In case of procedural languages, functions or procedures are the smallest possible execution units, while for OO programs a class is considered the smallest unit. Unit testing forms the basis for the subsequent higher level testing activities as it establishes the minimal operability of units that will be integrated to produce the actual functionality.Tse and Xu [57] have proposed an approach to derive test cases from Object Test Models (OTM). State space partitions of the attributes of a class are used with the OTM to generate a test tree. The actual test cases are derived from the test tree. Nori and Sreenivas [55] have proposed a specification-based testing technique that splits the specifications of a class into structural and behavioral components. Structural aspects define the attributes and method specifications of a class, whereas the behavioral component is a state machine describing the valid method invocation sequences. Another specification-based testing technique is presented by Vieira et al. [51] that utilizes UML statecharts to generate test cases automatically. A tool, DAS-BOOT, has also been built that partially automates the procedure. An idea of converting test generation into an AI planning problem has also been proposed [29, 48]. UML statecharts are used for testing information and producing AI planning specifications, which are then processed by planning tools to produce test cases. Kim et al. [11] propose a test case generation strategy from UML statecharts. These statecharts are converted to Extended Finite State Machines (EFSMs) and traditional control and data flow analysis is then performed on the EFSMs to generate test cases.1 In the paper, the term integration testing denotes the testing of interactions between classesA unique approach for state-based class testing is proposed by Sokenou and Herrmann [56]. This approach uses UML statecharts and the Object Teams approach [59] to test classes. Another state-based approach is presented by Li et al. [38] that can be used to test specific properties of reactive systems. Kim et al. [34] used statecharts to generate test sequences for Java-Based concurrent systems. Kansomkeat and Rivepiboon [33] have converted UML statecharts into an intermediate model known as Testing Flow Graph (TFG). This graph reduces complexities of statecharts and produces a simple flow graph. Test cases are finally generated by traversing the TFG using state and transition coverage criteria. The proposed methodology was evaluated using mutation testing. A systematic way of defining test cases from statistical usage models is defined by Riebisch et al. [47]. A statechart is derived from the use cases and is used to generate a usage model. Another approach for statistical test case generation from UML statecharts is proposed by Chevalley and Thevenod-Fosse [27]. This approach applies functional distribution to generate input values and transition coverage to generate test paths. Offut et al. [42] present a formal technique to derive tests at different coverage levels from UML statecharts. These levels include All-Transition, Transition Pair Coverage,Full Predicate Coverage, and Complete Sequence Coverage. A tool has also been developed to support the strategy. An extension of this work to support system level test generation from state-based specification has been made [14]. Results of an experiment carried out to validate the application of Round Trip Test Strategy [1] on UML statecharts are presented in Briand et al. [7]. Authors also propose improvements on the strategy based on the analysis of these results. In [25], a method to derive test data based on UML statecharts is defined to generate test cases given in the form of transition sequences on an object.2.1.2 Integration Level TestingThe integration testing of OO software is concerned with testing the interactions between units. This essentially attempts to validate that classes, implemented and tested individually, provide the intended functionality when made to interact with each other. The focus at this level is on testing interactions between classes through method calls or asynchronous signals, as well as interactions with databases or hardware. Adequate unit-level testing of individual classes supports but does not produce a reliable integrated cluster (group of interacting classes). This is because some of the bugs remain dormant during unit testing and pop-up only after integration for a specific state of the cluster. Hence the need of integration testing is inevitable. In the section below, we will discuss various approaches relating to integration testing of object-oriented software.Abdurazik et al. have used collaboration diagrams for static checking of source code and measuring adequacy of a test suite [17]. The approach applies traditional control and data flow analysis on collaboration diagrams to generate integration tests. TEst Sequence generaTOR (TESTOR) [44] is an approach used to generate integration tests using UML statecharts and collaboration diagrams for component based systems. The behavior of each component is specified in the form of UML statecharts, while the test directives are specified in the form of UML collaboration diagrams. Basanieri and Bertolino [20] used a User Interaction Testing (UIT) model to perform integration testing. A UIT is generated from use cases and UML sequence diagrams. An enhancement to this approach is proposed in [21]. Pilskalns et al. [46] have proposed a methodology to generate test cases from use case diagram and sequence diagrams. These diagrams are converted into an intermediate form Object Method Directed Acyclic Graph (OMDAG), which is used to generate integration tests. The SeDiTec [28] approach is used for testing interactions between the classes involved in a sequence diagram. Badri et al. [50] have used use cases and collaboration diagrams to generate integration test cases. Another approach for UML based integration testing is proposed by Le Traon et al. [12] and Jeron et al. [12]. This approach uses UML class diagram and generates an intermediate model known as TD Graph (TDG). This graph has three types of dependencies: Class to Class, Class to Method, and Method to Method dependency. This information was further used to determine the ordering of classes. Le Hanh et al. [37] have compared different integration test ordering strategies based on TDG. Another approach for determining class test orders for integration testing is discussed by Briand et al. [6]. This approach uses UML class diagrams and finds a class test order which minimizes the number of stubs required for integration testing.2.1.3 System Level TestingA few approaches in the literature also discuss testing at the system level. Briand and Labiche [23] have proposed an approach to generate system level test cases. This approach uses use case diagrams, activity diagrams, and sequence diagrams to generate system level test cases. Various techniques are reported that target different types of systems such as embedded and web based systems [49, 8, 22, 54, 5].2.1.4 Conformance Level TestingTesting software in order to establish the fulfillment of the specified requirements is known as conformance testing. A conformance relation defines the correctness criterion of the implementation with respect to the formal specification. General interpretation of conformance testing makes it resemble system level testing where high-level requirements are verified against the observed behavior. In the section below, we will discuss various approaches relating to conformance testing of object-oriented software.Hartmann [30] has proposed an approach for the conformance testing of distributed component based systems. UML statecharts are used for this purpose. UML statecharts are converted into extended statecharts and properties of Communicating Sequential Processes (CSP) are added. This extended model represents system wide behavior of the system. This model is given as an input to the Test Development Environment (TDE), which generates unit, integration, and system level conformance tests for the system. Another approach for conformance testing of component based systems using UML models has been proposed by Pickin et al. [45]. UML models have also been used to support regression testing [58, 24, 15, 32].2.2 Other Related State based Testing TechniquesA few state-based testing techniques have been proposed in other contexts than UML and are nonetheless related to our approach.Burton [53] presents an automated approach to test case generation from statechart specifications. The statecharts are represented in Z notation for the input to the test generation mechanism. Tests are generated using the Category Partition Strategy [43]. The generated test cases are also specified in Z. The paper also presents theorems to validate the existence of some desirable properties in the statecharts that can also help in removing faults before they are propagated to the implementation.Bogdanov [52] describes an automated testing method based on X-machines (a powerful variation of a Finite State Machine) that attempts to check the compliance of an implementation against its design. Each feature of a statechart is considered independently. The approach also describes ways to reduce the size of generated test suites. The work also includes various case studies that validate the proposed testing technique and a tool (TestGen) to automate the proposed approach.Gallagher et al. [10] have proposed a methodology to ensure that messages are exchanged between classes in an appropriate order and states of corresponding classes are changed properly. Classes are modeled as finite state machines, which are in turn converted into data flow graphs. Data flow analysis is performed on data flow graphs to automatically generate tests. The approach is applied to component based systems and focuses on testing one component at a time. The approach is also applicable in the context of concurrent applications.2.3 Comparison with Existing WorkFrom the above survey, we note that different kinds of UML diagrams have been used for software testing from different perspectives. UML statecharts have been widely used for testing the state-based behavior of software (see 2.1.1). Similarly, UML interaction diagrams have been used for integration testing (see 2.1.2). However, existing approaches do not focus on exercizing the state-based behavior of interacting classes. Techniques in Section 2.1.1 focuses only on testing state-based behavior (internal behavior of aclass), whereas techniques in Section 2.2 focus only on testing interactions among classes. More specifically, none of the above works discuss testing by integrating UML interaction and statechart diagrams to uncover state-dependent, class interaction faultsWe propose a novel testing approach based on UML collaboration diagrams and statecharts that can be used to uncover state-dependent interaction faults, e.g., inconsistent states of classes involved in a collaboration diagram, wrong calling state of a class in a collaboration diagram, and wrong initial state of a class in a collaboration diagram. A similar methodology was recently proposed by Gallagher et al. [10]. Both approaches perform state dependent interaction testing. Their approach uses finite state machines and converts them to data flow graphs. Traditional data flow analysis criteria are then applied to generate possible test paths. Our proposed approach uses UML statecharts and collaboration diagrams to generate an intermediate model, SCOTEM, and applies different coverage criteria based on the SCOTEM graph representation. We use collaboration diagrams to determine the order of messages between classes and this is different from Gallagher’s approach, which uses data flow analysis to determine such orderings. Their approach focuses on testing the possible interactions of a component under test with other components. Relevant states and guards associated with these interactions are collected in a database and are used to construct a Component Flow Graph. Data flow testing criteria are then applied to the graph with respect to define/use of state variables to generate test paths. In contrast, our approach tests class interactions involved in a particular collaboration, modeling object interactions for a specific use case, in all possible object states.3 The Proposed ApproachThe run-time behavior of an object-oriented system is modeled by well-defined sequences of messages passed among collaborating objects. In the context of UML, this is usually modeled as interaction diagrams (collaboration or sequence). In many cases, the states of the objects sending and receiving a message at the time of message passing strongly influence their behavior:· An object receiving a message can provide different functionalities in different states.· Certain functionalities may even be unavailable if the receiving object is not in the right state,e.g., a stack cannot be popped if it is in the empty state.· The functionality provided by an object may also depend on the states of other objects including the sending object of a message.We propose an integration testing technique that is based on the idea that the interactions between objects should ideally be exercised for all possible states of the objects involved. This is of particular importance in the context of OO software as many classes exhibit a state-dependent behavior. Such testing objective is implemented by generating a graph-based test model (SCOTEM) and by covering all paths in the model. The proposed technique can be applied during the integration test phase, right after the completion of class testing. It consists of the following four steps:1. SCOTEM Generation: An intermediate test model, called SCOTEM (State COllaboration TEstModel) is constructed from a UML collaboration diagram, and the corresponding statecharts.2. Test Paths Generation: Test paths are generated from the SCOTEM based on several possiblealternative coverage criteria.3. Test Execution: All selected test paths are executed by using manually-generated test data and anexecution log is created, which records object states before and after execution of each message in a test path. The object states are determined using state invariant assertions.4. Result Evaluation: The object states in the execution log are compared with the expected object statesin the test paths generated from SCOTEM. This means that these test paths also contain oracle information in the form of expected states of the objects. If any state of any object after execution of atest path is not in the required resultant state, then the corresponding test case is considered to have failed.Figure 1 presents a flowchart for the proposed technique, which shows the above four phases, and their relationships with various artifacts. In the following sub-sections, we describe the proposed testing technique in greater detail with the help of a simple example.3.1 Defining the SCOTEM Test ModelThe SCOTEM is an intermediate test model used to automatically generate test specifications for class integration testing. In this sub-section, we describe how this test model is constructed from a given UML collaboration diagram, and its corresponding statecharts. We have, however, made some assumptions about these UML models:· Collaboration diagrams may contain synchronous call messages or asynchronous signal messages, and statecharts their corresponding call events. Though we have not experimented with them in our case study, asynchronous signals are handled in a similar fashion to synchronous call messages and have no effect on the SCOTEM construction and test path generation algorithm.· Statecharts are in a flattened form [1]. Note that the flattening process can be automated.· State invariants of modal classes that are relevant to the selected collaboration diagram must be specified. It is, however, common practice to write state invariants during the definition of statecharts.Though it requires extra effort, the specification of state invariants is important to give a precise meaning to each possible state of a class. Moreover, these state invariants can be implemented as source code assertions that are to be checked during test execution. This is expected to help fault detection (oracle) and debugging.· The algorithm to generate the SCOTEM test model depends, to some extent, on the version of UML used as a design notation. In the examples of this paper, collaboration diagrams and statecharts are assumed to conform to UML 1.5 (the latest standard when this research started).· All guards, path, and loop conditions are assumed to be specified using the OCL 1.5.In order to provide more precise rules for well-formedness and provide some degree of semantics, Figure 2 presents a meta-model for the SCOTEM using the UML class diagram notation. The SCOTEM is a specific graph structure: A vertex corresponds to an instance of a class (in a particular state) participating in the collaboration.A Modal Class can receive a message in more than one state and exhibit distinct behavior for the same message in different states. To capture this characteristic, for modal classes, the SCOTEM contains multiple vertices, where each vertex corresponds to an instance of the class in a distinct abstract state (corresponding to states defined in statecharts). On the other hand, a non-modal class only requires a single vertex in the SCOTEM graph.The edges in the SCOTEM test model are of two types: message and transition edges. A message edge represents a call action between two objects, and a transition edge represents a state-transition of an object on receiving a message. Each message edge may also contain a condition or iteration. Each message may cause a state transition to occur. A transition edge connects two vertices of the same class. Statecharts may have multiple transitions to distinct states for the same operation. Hence, there may be multiple transition edges (representing a conditional state transition) for the same message edge in SCOTEM. Each of these transitions is generally controlled by mutually exclusive conditions (to prevent non-determinism). The internal representation of a vertex holds the class name and state of the instance it corresponds to. Message edges are modeled in the SCOTEM by attributes of a message including message sequence number, associated operation, receiver object, and the sender object. The transition edges are modeled by the attributes of a transition including sequence number, associated operation, accepting state and sending state.Figure 1. Flowchart for the proposed testing techniqueFigure 2. A Metamodel for the SCOTEM Test Model3.2 Constructing the SCOTEMIn this section, we present an example of SCOTEM construction based on an algorithm presented in Section 4. In subsequent sections, we will discuss the process of test path generation (Section 3.3) and how to handle a potentially large number of test paths (Section 3.4).The example used consists of an implementation of an Arithmetic Tutor (AT). In its comprehensive form, an arithmetic tutor can be a very complex and large application handling a variety of arithmetic operations, but for the sake of simplicity and clarity, we consider only a limited view of it.A comprehensive version of an AT program generally runs in two modes: training and assessment modes. In the training mode, the AT provides a step-wise gradual explanation about a particular operation. On the other hand, in the assessment mode, the program evaluates a student’s arithmetic skills by presenting randomly generated problems. A detailed performance log is maintained for each session and the history record of a student is updated accordingly at the end. Different levels, regarding complexity and type of problems of training and assessment are available to suit the age and mental aptitude of a student. During the assessment, the level of complexity of the presented problems is adjusted dynamically according to the performance in the current session, while in the training mode students can directly request explanations for problems of any type and complexity.The implementation of AT that we consider in our example is a restricted form of the assessment mode that deals with the addition operation only. Currently, the application presents randomly generated problems, one after the other, to the students. Students are given unlimited time to solve each problem, but a stop-watch is provided so that they can keep track of the time they take to solve a problem. AT assists the students in solving the problems by laying out the problem in a format easy to understand and solve. AT manages the complexity of the generated problems based on the student’s performance in the current session (time taken to solve a problem is not considered in this). If the error count increases beyond a defined value, AT lowers the complexity level for subsequent problems. Similarly, good performance on the part of students increases the complexity level. The class diagram of the AT system is provided in Appendix B.Figure 3 shows a collaboration diagram for the newProblem()system-level operation that instructs AT to generate a new problem according to the current complexity level. An object of the Coordinator class receives the operation call message with an argument specifying the type of problem to be generated, which in this case is only addition. Several other classes also interact to generate the problem, which is then passed to the DisplayManager that handles its visual presentation. Several other operations, including evaluateProblem()and adjustComplexity(),are present in the AT. But for the purpose of explaining the technique, we only consider the newProblem() operation in the remainder of the section.In the given collaboration diagram (Figure 3), classes Coordinator, ProblemGenerator, Problem, and OperandGenerator are non-modal, while StopWatch, ComplexityRegulator, DisplayManager, Log, and PerformanceRegulator are modal. Figures 4, 5, 6, 7, and 8 show flattened versions of the statecharts for these modal classes, respectively. The statecharts for the ComplexityRegulator class and the DisplayManager class had concurrency in the form of sub-states, and thus needed to be flattened before use. The “|” sign in these diagrams denotes a separator for the original concurrent states.。