Automating Software Design Exploring and Evaluating Design Alternatives
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Tegron, Osgood Industries Gain Competitive Advantage in Marketplace With Autodesk Manufacturing SoftwareSeptember 20, 2004Manufacturers Create, Manage and Share Electrical Design Data to Streamline Accurate Drawings of Control Systems With AutoCAD ElectricalSAN RAFAEL, Calif., Sep 20, 2004 /PRNewswire-FirstCall via COMTEX/ -- Autodesk Inc. (Nasdaq: ADSK), the world's leading design software and digital content company, continues to experience momentum in adoption and use of AutoCAD(R) Electrical by U.S. manufacturers to create, manage and share electrical design information. The software gives companies in the manufacturing industry the ability to create electrical controls designs faster and more accurately by automating many of the manual processes. AutoCAD Electrical customers such as Tegron and Osgood Industries Inc., have significantly improved the speed with which accurate designs are produced, for quality and efficiency that translate into competitive advantage. Serving vertical markets ranging from food and beverage to steel production, Tegron is a leading control systems integrator that assists manufacturers with plant automation, plant information and plant services. The company sought to improve its competitive advantage in terms of quality and speed in resolving customers' challenges. Using AutoCAD Electrical to automate their controls design process, Tegron has established a foundation for consistent quality and adherence to global design standards, as well as much faster response to customer change requests -- with far less labor involved. As a result, Tegron has achieved a permanent 80 to 90 percent reduction in design errors, and has trimmed typical drawing time from more than a day to just a few hours."Companies such as Tegron and Osgood recognize the value in automating the repetitive, detail-oriented aspects of controls design, so their engineers can focus on solving customer problems," said Robert Kross, vice president of the Manufacturing Solutions Division at Autodesk. "AutoCAD Electrical features and functions were developed to address many of the labor-intensive design tasks that electrical controls engineers often complete using AutoCAD."Leaders in U.S. Manufacturing Depend on AutoCAD ElectricalControls design is typically a labor-intensive process with many tedious and error prone design and documentation requirements. Tegron, a plant automation services provider, and Osgood, specializing in food packaging equipment, both depend on AutoCAD Electrical to automate complex and time-consuming manual tasks, from automatically generating PLC I/O drawings to updating schematics, creating panel layouts, automatically numbering components and tracking relay assignments. The potential for simple but costly errors in detail is minimized -- and that reduction yields benefits from greater productivity to reduced expense."The impact of AutoCAD Electrical on Tegron's performance is dramatic," said Steve Voelzke, CEO of Tegron. "The software paid for itself in just six months and has given Tegron a time-to-market advantage we estimate is roughly 20 percent faster than our competitors."For more than 30 years, Osgood has been making machines that fill, package, lid, and seal products in the food, dairy, drug, and cosmetic industries --where regulatory compliance and consumer safety are high priorities, and quality assurance can be a competitive differentiator. In an ongoing commitment to quality, Osgood chose to standardize their controls design process on AutoCAD Electrical, creating templates to ensure re-use of proven design elements; and automating cross-referencing of circuitry elements to reduce error. As a result, Osgood cut design costs by 25 percent, and reduced schematic and panel layout errors by 90 percent."Because the software automates a number of key processes and produces more detailed schematics, it's allowing us to do more for customers in less time," says Tim Hortaridis, a controls engineer with Osgood. "The time saved translates directly into lower expenses, and Osgood invests the time and money saved back into research and development, which helps us keep ahead of the market."Collaboration across TeamsHistorically, electrical engineers have relied on AutoCAD(R) and spreadsheet tools to devise control systems in parallel with product designers' work. As a result, teams must engage in a series of trial-and-error exchanges to arrive at controls that integrate properly with the product design. Based on the AutoCAD(R) platform, that electrical and product engineers share in common, AutoCAD Electrical can be integrated with business and engineering systems such as Autodesk Inventor Professional to facilitate rapid development of compatible electrical control and product designs. In conjunction with Autodesk Inventor Professional, AutoCAD Electrical can further streamline the development of accurate designs and pre-empt problems that otherwise might not show up until prototyping or production.A Comprehensive Portfolio of Manufacturing SolutionsDelivering on its strategy to help customers create, manage, and share their digital design data and solve critical business challenges, Autodesk offers the most comprehensive portfolio of integrated 2D and 3D design and data management solutions available -- helping customers design better quality products, accelerate time to market, and achieve maximum project visibility and collaboration. Unlike other offerings on the market today, these solutions are easy to deploy and use, and help companies easily transition from 2D to 3D design at their own pace. Autodesk's manufacturing solutions include Autodesk Inventor Series, the world's #1 selling 3D mechanical design software, Autodesk Inventor(R) Professional, AutoCAD(R) Mechanical and AutoCAD(R) Electrical software -- all with Autodesk(R) Vault data management capabilities built in; and the Autodesk Streamline(R) collaboration service. In addition, customers can take advantage of widely available third-party applications purpose-built for Autodesk software. Autodesk Consulting, including integrated consulting and training, helps customers worldwide maximize the value of their investment in Autodesk technology. For more information about Autodesk Consulting, see /consulting.Autodesk Subscription is the easiest way to keep design tools and learning up to date. For an annual fee, customers benefit from the latest versions of their licensed Autodesk software, web support direct from Autodesk, self-paced training options, and a broad range of other technology and business benefits. For more information, contact your Autodesk Authorized Reseller or visit /subscription.About AutodeskAutodesk is the world's leading design software and digital content company, offering customers progressive business solutions through powerful technology products and services. Autodesk helps customers in the building, manufacturing, infrastructure, digital media, and wireless data services fields increase the value of their digital design data and improve efficiencies across their entire project lifecycle management processes. For more information about the company, see .NOTE: Autodesk, AutoCAD, Autodesk MapGuide, and Discreet are either registered trademarks or trademarks of Autodesk, Inc., in the USA and/or other countries. All other brand names, product names, or trademarks belong to their respective holders.Contact: Tania Kempf415-547-2469EMAIL:************************SOURCE Autodesk, Inc.Tania Kempf of Autodesk, Inc., +1-415-547-2469, or************************。
AS500213Moving Toward the Future of Design with Generative Design in RevitLilli SmithAutodeskEsra AbumounsharStantecElisa AmbrassaENELSean FruinSigma AEC SolutionsDescriptionGenerative Design in Revit software was released last year for the first time in Revit 2021. This new suite of emerging tools enables generative design workflows that automate the creation and analysis of design options directly in the Revit context. This session will showcase the value that generative design brings to the design process, and demonstrate how analyzing more data-backed design options can lead to an enhanced design process. We will show how customers are using the tools to automate design exploration in their projects to optimize sustainability and efficiency and reduce construction waste. We’ll cover the product principles we use to prioritize new work and future directions. Finally, we’ll address the future of the product, where we intendto invest, and the road map for achieving our vision.Speaker(s)Lilli Smith, AIA, Sr. Product Manager at Autodesk, is an architect with apassion for re-envisioning the way that buildings are designed. Afterworking for several years as an architect, she joined Revit Technology asa fledgling start up and helped grow it to where it is today in almost everyarchitect’s tool box. She has gone on to work on many Autodesk toolsincluding Vasari, FormIt, Dynamo, Project Fractal and Project Refinerywhich recently graduated to a suite of tools for generative design studiesin Revit.Esra Abumounshar is the generative and computational design lead atStantec. She has been working on adopting computational and generativedesign tools and implementing them across her company. My workinclude Healthcare, High Ed, Mixed-use & Master Planning.Elisa Ambrassa is a Structural Engineer who is curious and passionateabout buildings, architecture and innovation. As a BIM Coordinator sheworks in the BIM Implementation unit of Enel, based in Rome, Italy,where she carries out coordination and automation of wind and solarplants desing and model checkings. She started her career in 2018 at anarchitecture and engineering office, where she designed structures,buildings and bridges. During my Master Degree she worked inSwitzerland applying BIM methodology in the context of seismicvulnerabily of masonry buildings.Sean Fruin is a Mechanical Engineer (EIT) who has an ardentfascination with automation and the exploration of computational designsolutions for the AEC industry. He has had the opportunity to learn manyaspects of the design industry, having worked in manufacturing, MEPdesigning, and General Contracting. Sean started Sigma AEC Solutions,a BIM consulting firm focusing on engineering and process improvementand is living his dream; having the opportunity to explore the latesttechnologies and acquire the knowledge to innovate, improve efficiencyand increase quality in the AEC industry.Safe HarborDuring the course of this presentation, we may make statements regarding future events and/or statements regarding planned or future development efforts for our existing or new products and services. We wish to caution you that such statements reflect our current expectations, estimates and assumptions based on factors currently known to us and that actual events or results could differ materially. Also, these statements are not intended to be a promise or guarantee of future delivery of products, services or features but merely reflect our current plans, which may change. Purchasing decisions should not be made based upon reliance on these statements. The statements made in this presentation are being made as of the time and date of its live presentation. We do not assume any obligation to update any statements we make to reflect events that occur or circumstances that exist after the date of this presentation. Autodesk, the Autodesk logo, 3ds Max, BIM 360, Forge, Revit, and other solutions mentioned by name are registered trademarks or trademarks of Autodesk, Inc., and/or its subsidiariesand/or affiliates in the USA and/or other countries. All other brand names, product names, or trademarks belong to their respective holders. Autodesk reserves the right to alter product and services offerings, and specifications and pricing at any time without notice, and is not responsible for typographical or graphical errors that may appear in this document.© 2021 Autodesk, Inc. All rights reserved.Why Generative Design?A stunning 40% of global energy is used by our built environment. Buildings alone consume 25% of our water, and building construction produces 30% of all global waste. Architects and engineers as designers of the built environment have a responsibility to take on these issues. Workflows like generative design have the potential to revolutionize the way we design by using goals and measurable outcomes to guide our designs.Architectural and engineering services have evolved from drawing by hand on paper and delivering it to others to build buildings. Autodesk digitized this process over 40 years ago with the advent of AutoCAD. We’ve evolved to Building Information Modeling and more efficient ways to deliver building instructions to the field. What we really want to do next is to pair human intelligence with machine intelligence so that we can use data-backed design decisions to create a better built environment.Over the past few years we’ve been exploring how generative design can help improve desig n and construction work. Autodesk Research experimented with generative design workflows to help us better optimize space during our Toronto office renovation a few years ago. We surveyed our employees about their preferences for collaboration, lighting, acoustics, and distance to the kitchen. Then used that data to guide the design. Different floor plan layouts are created and the design process keeps track of the scores for each of the preference metrics. These kind of automated design explorations are not new – generative designers have been using automated techniques for decades, but the have mostly been in the realm of research.Autodesk’s mission is to bring new technology to the market so that more people can use it an participate in the design process. You’re all are here today to hear about a new suite of generative design tools first added to Revit 2021 and updated in Revit 2022,and I imagine you want to understand more about what they are and who’s using them. You also may be wondering what new tools are under development and what is on our future roadmap. This talk will be split into 3 sections:1. What’s new?2. How are people using Generative Design?3. What’s next?1. What’s new?More resources on the generative design tools enhancements in Revit 2022.https://youtu.be/yv8Kcz1XGBgMore additions in Revit 2022.1https://youtu.be/LliPUgosPfYWhat’s new in Dynamo 2.10 (version in Revit 2022)https:///dynamo-core-2-10-release/What’s new in Dynamo 2.12 (version in Revit 2022.1)https:///dynamo-core-2-12-release-part-1-2/https:///dynamo-core-2-12-release-part-2-2/2. How are people using Generative Design?This section covers three customer use cases. Check out the presentations for more details.1. Building Mass GeneratorEsra Abumounshar, Generative Design Lead at Stantec, will show us a massingworkflow where she can evaluate different forms very quickly, keeping track of floorarea and pushing the designs back into Revit for further development. She willexplain how she enables many members of her team even those not skilled inDynamo to take advantage of these tools.2. RPC CoordinationSean Fruin, Director of Technology at Sigma AEC Solutions, will show us a workflow he developed to automate the design of reflected ceiling plans so that among other reasons he could free up his Friday evenings and maintain a healthier work life balance.3. Windfarm AccessFinally, Elisa Ambrassa, BIM Coordinator at Enel Green Power Corporation in Italy,will show us how she uses generative design to lay out access roads in a windfarm.She will explain that because the demand for windfarms is growing so rapidly andtheir company has so many projects to do, they can no longer design things likethese access roads manually - they MUST use automation to design and documentthem.3. What’s Next?Here is a brief summary of some of the things are working on for future releases:1. Generative Design to Core Dynamo: We are working on bringing a lot of thefunctionality that we developed for generative design, like file descriptions and images into Dynamo core. We have always had a Generative Design menu available fromDynamo for Revit, but this move to core will also enable generative design tools to be natively available for all of our dynamo enabled products like Formit, Civil 3D, as well as Dynamo Sandbox.2. Dynamo Player Updates: In recent months, we’ve seen a big increase in the numberof Dynamo Player users as more and more people discover the power of automating parts of their BIM workflows. This warrants making some updates to Dynamo Player. We plan to start by bring a lot of the updates that we’ve made in the Generative Design in Revit tools into Dynamo Player.3. Dynamo UI Updates: While providing tools to run Generative Design studies directlyfrom Revit is appealing to many users, we find that most of the value of generativedesign is in customization and being able to run specialized studies for individual design needs. We continue to see an increase in Dynamo use for BIM Automatin andGenerative Design. More and more people are investing in learning how to useDynamo. Therefore, we are investing heavily in improving the tools and giving Dynamoa user interface update, making it easier to express custom logic while making theexperience more visually appealing. We’ve heard a lot of feedback that Dynamo error messages can b e annoying and confusing so we’re working on making these messages and warnings, more helpful and less in the way. Organizing and annotating Dynamo scripts for use by others is vital when handing off a script. We’re enhancing groups with more room for notes, enabling groups within groups, and providing ways to collapsegroups down to just show their inputs and outputs to reduce visual distraction andcomplexity.4. Dynamo Node Auto-Complete We’ve heard a lot of people complain that they often getstuck trying to figure out which nodes can feed into others. Node Autocompleteaddresses these concerns by providing an applicable list of choices and even presenting the mostly likely nodes first.5. More Output Types: Going back to generative design outcomes, we want to expand thetypes of outcomes that are available for automated generation. We currently can create numbers and design thumbnails, but it would be really great if we could create more views of a design, assets like excel files, and data in charts to name a few of thepossibilities we think would be useful.6. Faster Energy Analysis Autodesk has many analysis tools that we want people to beable to access through whichever design tools they may be using. We are working on ways to speed up energy analysis with machine learning so that energy use intensity metrics can be studied while designing with Generative Design, Dynamo, FormIt, and/or Spacemaker.7. Spacemaker Synergies Spacemaker is a company that we have recently acquired –that is thinking about early stage design problems in a similar way. When you start a design by choosing a site it can imply a whole design space and come up with databacked options that you can compare against eachother. We’ve already released tools that make generative methods available to communities of designers who have never been able to access these ways of solving problems, and with the Spacemakeracquisition we will continue in similar and even more powerful ways, makingcustomizable tools available for more and more people. Analysis needs to be a pre-emptive part of the design process, to create a close collaboration with our existingcustomers and our new colleagues in Spacemaker and together building a future of outcome based designResourcesAU2021 Courses on Generative Design•Optimize Road Design with Dynamo for Civil 3D and Generative Design (CES500103)•Generative Design Using Dynamo for Multifamily Residential (AS500109)•HVAC System Selection with Generative Design (AS500212)•Two Weeks to Four Hours: How Populous Built Efficiency with Generative Design (AS500272)AU2020 Courses on Generative Design•Generative Design in Revit for Workspace Layout - Tomasz Fudala•Non-Geeks Guide to Optimizing Daily Workflows with Generative Design - Raquel Bascones Recio•Using Generative Design and Machine Learning for Faster Analysis Feedback - Varvara Toulkeridou•Generative Design at Hogwarts: Using Tech Instead of Magic - Jacob Small •Generative Design für Revit in der Praxis - Lejla Secerbegovic•Diseño Generativo en Revit para todos los públicos - Raquel Bascones Recio •Generative Design—Daylighting and CFD: A Practical Application for a Nonprofit - Luc Wing•Generative Design of Landforms with Dynamo in Civil 3D - Andreas LukaPast Years Autodesk University Courses on Generative Design and Project Refinery•Geometry Systems for AEC Generative Design: Codify Design Intents into the Machine •MEP Explore: Generative Design for MEP Designers•Getting Started with Generative Design for AEC•Using Generative Design in Construction ApplicationsDynamo Resources•Getting Started with Dynamo:https:///https:///learn/•Dynamo Forum for questions, inspiration:https:///•Design Script:http://designscript.io/DesignScript_user_manual_0.1.pdfhttps:///wp-content/links/DesignScriptGuide.pdfhttps:///Amoursol/dynamoDesignScriptGenerative Design Resources•Generative Design Primerhttps:///•Generative Design in Revit Help •Generative Design general education:https:///generative-design。
auto-detect and installAuto-Detect and InstallIntroductionIn modern computing, automation plays a crucial role in simplifying various tasks. One such task is the process of detecting and installing software or drivers on a computer system. Auto-detect and install mechanisms have made this process easier and more efficient, saving time and effort for users. In this document, we will explore the concept of auto-detect and install, its benefits, and how it works.DefinitionAuto-detect and install refers to the ability of a computer system to automatically identify and install the necessary software or drivers required for a specific hardware component. Instead of manually searching for the appropriate software and performing the installation, the system uses various techniques to detect the hardware and automatically download and install the necessary software or drivers.BenefitsThe auto-detect and install feature offers several benefits to users and system administrators:1. Time-Saving: Manually searching for software or drivers can be time-consuming, especially when dealing with multiple hardware components. Auto-detect and install eliminate the need for manual intervention, resulting in significant time savings.2. Ease of Use: Auto-detect and install mechanisms are designed to be user-friendly. Users do not need to have in-depth technical knowledge to install a hardware component. The system takes care of the entire process, making it easier for anyone to install hardware.3. Accuracy: Auto-detect and install ensure that the correct software or drivers are installed for a specific hardware component. This reduces the risk of compatibility issues and ensures optimal performance.4. Regular Updates: With the auto-detect and install feature, the system can automatically check for any updated versions of the software or drivers and install them accordingly. This ensures that hardware components are always up to date with the latest features and security patches.Working MechanismThe auto-detect and install mechanism typically involve the following steps:1. Hardware Detection: The system uses various techniques, such as querying the hardware identifiers, to identify the connected hardware component. This information is then used to determine the appropriate software or drivers needed for the specific component.2. Software/Driver Search: Once the hardware is identified, the system initiates a search for the corresponding software or drivers. This can be done by querying a central software repository or by searching online.3. Download and Installation: Once the appropriate software or drivers are found, the system automatically downloadsthem. The files are then installed using predefined installation routines, ensuring a smooth and seamless process.4. Verification: After installation, the system verifies that the software or drivers are correctly installed and functioning as expected. This may involve checking the version numbers, performing tests, or comparing the installed files with known signatures.ConclusionAuto-detect and install mechanisms have revolutionized the process of software and driver installation. By automating the detection and installation process, users can save time and effort while ensuring accurate and up-to-date installations. This feature simplifies the installation of hardware components, making it more accessible to a wider range of users. As technology continues to advance, auto-detect and install mechanisms will become even more sophisticated, further enhancing the user experience in the world of computing.。
技术发明的英语作文英文回答:Technological Innovation: A Catalyst for Transformative Change.Technological innovation has emerged as a driving force behind transformative societal progress, revolutionizing the way we live, work, communicate, and interact with the world around us. Through its relentless pursuit of novel solutions, technology has empowered us to solve complex problems, enhance human capabilities, and unlock unprecedented possibilities.At the heart of technological innovation lies a spirit of curiosity, exploration, and a deep-seated belief in the potential of human ingenuity. Driven by this unyielding thirst for knowledge and progress, inventors, scientists, and engineers have dedicated themselves to pushing the boundaries of what is possible. From the invention of thewheel to the advent of the internet, technological breakthroughs have consistently reshaped human civilization, paving the way for advancements in industry, medicine, transportation, and communication.One of the most profound impacts of technological innovation has been its role in increasing productivity and efficiency. By automating tasks and streamlining processes, technology has enabled us to produce more goods andservices with fewer resources. This increased efficiencyhas led to economic growth, improved living standards, anda reduction in physical labor. For example, the mechanization of agriculture has revolutionized farming practices, allowing farmers to produce more food with less effort. Similarly, the development of computer-aided design (CAD) software has empowered engineers to design and test products more efficiently, reducing development time and costs.Another transformative aspect of technological innovation lies in its ability to enhance humancapabilities. Through the development of assistivetechnologies, prosthetics, and wearable devices, technology has empowered individuals with disabilities to overcome physical limitations and live more fulfilling lives. For instance, cochlear implants have provided hearing to the deaf, while wheelchairs have enabled individuals with mobility impairments to navigate their surroundings with greater ease. Furthermore, advancements in artificial intelligence (AI) are creating new possibilities for human-machine collaboration, promising to enhance our cognitive abilities and augment our creative potential.Beyond its practical applications, technological innovation has also played a pivotal role in shaping cultural and societal values. The advent of social media platforms has transformed the way we communicate and connect with others, fostering global interconnectedness and giving voice to marginalized communities. Likewise, the proliferation of digital content and technologies has expanded access to information, education, and entertainment, empowering individuals to engage in lifelong learning and pursue personal enrichment. By breaking down barriers of distance and accessibility, technology hasfostered greater understanding, empathy, and collaboration among individuals from diverse backgrounds.However, it is important to acknowledge that technological innovation is not without its challenges. Unforeseen consequences, ethical dilemmas, and potential risks must be carefully considered and addressed as we embrace the transformative power of technology. Responsible innovation requires ongoing dialogue and collaboration among policymakers, researchers, industry leaders, and the public to ensure that technological advancements align with societal values and promote inclusive and sustainable development.In conclusion, technological innovation is a powerful force that continues to shape our world in profound ways. Through its relentless pursuit of novel solutions and its ability to enhance human capabilities and foster societal transformation, technology holds immense potential to address complex challenges and create a more equitable, prosperous, and fulfilling future for all. As we navigate the complexities of the digital age, it is imperative thatwe embrace the opportunities offered by technological innovation while simultaneously mitigating potential risks and ensuring its responsible use.中文回答:技术发明,变革性变革的催化剂。
软件技术专业介绍英语作文Software Engineering: A Comprehensive Overview.Software engineering is a comprehensive and multifaceted discipline that encompasses the design, development, deployment, and maintenance of software systems. It involves the application of scientific and mathematical principles to the creation and improvement of software, ensuring its efficiency, reliability, and maintainability.Software engineering professionals, known as software engineers, are responsible for transforming user requirements into functional and robust software solutions. They utilize a structured and systematic approach to software development, adhering to well-defined processes and methodologies.Key Concepts in Software Engineering.1. Software Development Life Cycle (SDLC): The SDLC isa comprehensive framework that outlines the phases of software development, from planning and requirements gathering to testing and deployment. It ensures a systematic and organized approach to software creation.2. Software Requirements: Software requirements define the functionality, performance, and other attributes of the software system. They serve as the foundation for software design and development, ensuring that the final product meets the intended needs of the users.3. Software Design: Software design involves creating blueprints for the software system. It defines the architecture, data structures, and algorithms that form the backbone of the software.4. Software Implementation: The implementation phase involves writing the actual code that brings the software design to life. Software engineers select appropriate programming languages and development tools to translate the design into a functional system.5. Software Testing: Testing is a crucial phase that ensures the software meets the specified requirements and functions as expected. Software engineers employ various testing techniques to identify and rectify any errors or defects.6. Software Deployment: Deployment refers to the process of delivering the software to the end-users. It involves creating installation packages, configuring the software, and providing documentation and training.7. Software Maintenance: Software maintenance involves updating and improving the software over its lifespan to ensure it remains effective and meets changing user needs. It includes bug fixes, feature enhancements, and performance optimizations.Importance of Software Engineering.Software engineering plays a vital role in the modern world, underpinning the functionality of countless devices,systems, and applications that we rely on daily.1. Efficiency and Productivity: Software engineering practices promote efficiency and productivity by automating tasks, streamlining processes, and enhancing data management.2. Reliability and Security: Software systems are designed to be reliable and secure, ensuring data integrity and protection from vulnerabilities and malicious attacks.3. Innovation and Growth: Software engineering enables continuous innovation and growth by facilitating the creation of new products, services, and solutions that drive technological advancements.4. Economic Impact: The software industry is a major contributor to the global economy, creating jobs and stimulating growth in various sectors.Career Opportunities in Software Engineering.Software engineering offers a wide range of career opportunities for individuals with the necessary skills and qualifications.1. Software Developer: Responsible for designing, developing, and testing software solutions.2. Software Architect: Leads the design andarchitecture of complex software systems.3. Software Tester: Ensures the quality andreliability of software by performing various testing procedures.4. Software Project Manager: Manages the planning, execution, and delivery of software projects.5. Software Consultant: Provides expertise and adviceto organizations on software development and implementation.Education and Training in Software Engineering.Becoming a software engineer typically requires a formal education in computer science, software engineering, or a related field. Many universities offer undergraduate and graduate programs that provide a solid foundation in software development concepts and practices.In addition to formal education, software engineers must continuously update their skills and knowledge to keep pace with evolving technologies and best practices. Industry certifications and professional development courses can help engineers enhance their expertise and stay competitive.Conclusion.Software engineering is a rapidly evolving field that drives innovation and shapes the modern world. By applying scientific and mathematical principles to the design, development, and maintenance of software systems, software engineers create solutions that empower businesses, enhance our lives, and drive economic growth. The demand forskilled software engineers is expected to continue to riseas technology continues to permeate every aspect of our society.。
科学小制作扫地机英语作文A Robotic Vacuum Cleaner" with over 1,000 words, as requested:A Science Project: A Robotic Vacuum CleanerIn today's fast-paced world where time is a precious commodity, the need for efficient and time-saving household appliances has become increasingly important. One such appliance that has gained immense popularity in recent years is the robotic vacuum cleaner. As a science enthusiast, I was intrigued by the idea of creating my own robotic vacuum cleaner as a project. The prospect of combining my love for science and technology with the practical application of automating a mundane household chore was too compelling to resist.The journey of building a robotic vacuum cleaner began with extensive research and planning. I delved into the underlying principles of robotics, studying the various components and mechanisms that make these autonomous devices function. From understanding the role of sensors and microcontrollers to exploring the algorithms that govern the navigation and cleaning patterns, I immersed myself in the technical aspects of the project.One of the key challenges I faced was the selection of the appropriate hardware components. The heart of the robotic vacuum cleaner would be the microcontroller, which would serve as the "brain" of the system, responsible for processing sensor data, controlling the motor movements, and coordinating the cleaning process. After carefully evaluating the market, I opted for an Arduino Uno, a popular and versatile open-source microcontroller board that offered a wide range of features and a thriving community of developers.Alongside the microcontroller, I needed to incorporate various sensors to enable the robotic vacuum cleaner to navigate its surroundings and detect obstacles. I chose to use ultrasonic sensors, which use sound waves to measure distances, and infrared sensors, which can detect the presence of objects. These sensors would work in tandem to provide the robotic vacuum cleaner with a comprehensive understanding of its environment, allowing it to navigate efficiently and avoid collisions.The next step involved designing the mechanical structure of the robotic vacuum cleaner. I carefully considered the dimensions, weight distribution, and overall stability of the device. Using computer-aided design (CAD) software, I created a 3D model of the chassis, which would serve as the foundation for the entire assembly. This model allowed me to experiment with different design iterations,optimize the weight balance, and ensure that all the necessary components would fit seamlessly within the enclosure.With the hardware components and the mechanical design in place, I turned my attention to the software development. Programming the robotic vacuum cleaner's behavior was a crucial aspect of the project.I utilized the Arduino's programming environment to write the code that would control the sensors, motors, and cleaning mechanisms. This involved developing algorithms for navigation, obstacle avoidance, and efficient cleaning patterns.One of the key features I aimed to incorporate was the ability for the robotic vacuum cleaner to map its surroundings and navigate autonomously. By integrating the sensor data and implementing path-planning algorithms, I was able to create a system that could dynamically adjust its cleaning routes, avoiding obstacles and ensuring comprehensive coverage of the designated area.Another important consideration was the cleaning mechanism itself. I designed a rotating brush system that would effectively pick up dust, dirt, and debris from the floor. The brush would be powered by a dedicated motor, coordinated with the overall movement of the robotic vacuum cleaner. Additionally, I included a suction fan to enhance the cleaning performance and ensure that even the finest particles were captured and stored in an onboard dust container.As the project progressed, I faced various challenges that required creative problem-solving and a deep understanding of the underlying principles. For instance, I had to optimize the power consumption of the system to ensure extended battery life, balance the weight distribution to maintain stability, and fine-tune the sensor calibration to improve the navigation accuracy.Throughout the development process, I found immense satisfaction in the iterative nature of the project. Each challenge I encountered presented an opportunity to learn, experiment, and refine the design. The process of troubleshooting, testing, and fine-tuning the robotic vacuum cleaner became a captivating journey of discovery and growth.One of the most rewarding aspects of this project was the sense of accomplishment I felt when the robotic vacuum cleaner finally came to life, navigating seamlessly through the test environment and effectively cleaning the floor. Watching the device autonomously traverse the room, detecting obstacles, and meticulously cleaning every corner was a testament to the power of science and technology.Beyond the practical application of the robotic vacuum cleaner, this project has also had a profound impact on my personal development.It has honed my problem-solving skills, strengthened my analytical thinking, and fostered a deeper appreciation for the integration of hardware and software in the field of robotics. The experience has also inspired me to continue exploring the boundless possibilities of science and technology, constantly seeking new challenges and opportunities to push the boundaries of what is possible.In conclusion, the journey of building a robotic vacuum cleaner as a science project has been a truly enriching and transformative experience. It has not only resulted in a functional and efficient household appliance but has also instilled in me a deeper passion for the pursuit of knowledge and the application of scientific principles. As I look to the future, I am excited to continue exploring the realm of robotics and applying my newfound skills and insights to tackle even more ambitious projects that can positively impact the world around me.。
Autodesk®Factory Design SuiteThe flexibility to innovate and accelerate new business.Rendering of Packaging Automation layout.Autodesk® Inventor®, AutoCAD®, and Autodesk®3ds Max® Design software products, included inAutodesk® Factory Design Suite, were used in thedesign process. Packaging Automation layoutprovided by Barry-Wehmiller Design Group, Inc.Extend the Benefits of Digital Prototyping to the Factory FloorAutodesk ® Factory Design Suite enhances the power ofAutoCAD ®software with the benefits of Digital Prototyping—so you spend less time drafting and more time optimizing and visually communicating factory layouts.Autodesk ® Factory Design Suite is an interoperable 2D and 3D factory layout and optimization solution built specifically to help you design and communicate the most efficient layout by creating a digital model of your factory. It enhances AutoCAD ® and Autodesk ® Inventor ® software with exclusive access to interoperable layout workflows and factory-specific content to help improve your design efficiency, accuracy, and communication.Win More BusinessFactory Design Suite helps you quickly evaluate multiple what-if layout scenarios to determine the best solution before any equipment is installed. It provides factory-specific visualization tools to help impress potential clients with immersive layout proposals in 3D instead of multilayered 2D drawings that can be difficult to interpret.Meet Compressed Project SchedulesComplete layout projects on time and within budget with automated workflows and a factory-centric work environment in AutoCAD and Inventor. Move from 2D conceptual layout to manipulating a 3D factory model with a library of parametric factory content instead of sketching it all by hand. It supports the DWG™ file format, so you can build on top of existing data to boost your efficiency. Optimize Your Factory Layout ProcessThis factory-focused solution can help you create layout designs much faster than traditional layout workflows. Analyze existing 2D layouts for more efficient material flow, and transform layout liabilities into profit-generating assets. Incorporate point cloud scans to capture the as-built state of your factory, drastically reducing time spent on manual measurement.Collaborate More Effectively with Suppliers and PartnersBring the factory to life and improve communica-tion using immersive, high-quality 3D renderings and visualizations. Include models from suppliers in your layout regardless of CAD format, shrink-wrapping and stripping them of unwanted details. Reduce installation risks by analyzing the digital factory model for clashes and space constraints, before they become problems on-site.Take Advantage of Cloud-based 3D Asset Publishing, Sharing, and StorageWith Autodesk ® 360, Factory Design Suite users can manage their assets, collaborate, and share layout designs with various stakeholders online via the DWF™ file format. Both public and private sharing capabilities make it easy to collaborate internally or share with external stakeholders.Conceptual Factory Layout3D Visualization & Analysis3D Visual LayoutFactory Asset CreationAutodesk ® 3ds Max ® DesignDemonstrate the operation of layout designs in real-world settings for visual validation and improved communication.Autodesk ® Navisworks ®Integrate 3D models and multiformat data, coordinate designs, and resolve conflicts.AutoCAD ®Efficiently design, document, and share factory layout drawings in the DWG™ file format.Unique factory-specific functionality in AutoCAD:• Material flow analysis• Large library of factory content • I nteroperable 2D-3D layout workflows with bidirectional associativity • Parametric asset variantsAutodesk ® Showcase ®Transform your designs into immersive, interactive presentations.Autodesk ® VaultGain more control over your design data with software for managing design creation, simulation, and documentation processes.Autodesk ® Inventor ®Create accurate digital models of factory equipment with easy-to-use 3D mechanical design software.Autodesk ® Inventor ®Create accurate digital models of factory layouts to easily try different what-if scenarios.Unique factory-specific functionality in Inventor: • I nteroperable 2D-3D layout workflows with bidirectional associativity • A bility to create accurate factory models with a predefined floor • A bility to drag 3D models of factory assets onto your 2D floor plan • L arge library of 3D parametric factory content • A bility to add smart connection points and landing surface definitions on the assetAutodesk Factory Design Suite Standard • AutoCAD ®• AutoCAD ® Architecture • AutoCAD ® Mechanical • Autodesk ® Vault• Autodesk ® Showcase ®• Autodesk ® Factory Design Suite UtilitiesAutodesk Factory Design Suite Premium • AutoCAD ®• Autodesk ® Inventor ®• Autodesk ® Navisworks ® Simulate • AutoCAD ® Architecture • AutoCAD ® Mechanical • Autodesk ® Vault• Autodesk ® Showcase ®• Autodesk ® Factory Design Suite Utilities Autodesk Factory Design Suite Ultimate • AutoCAD ®• Autodesk ® Inventor ® Professional • Autodesk ® Navisworks ® Manage • AutoCAD ® Architecture • AutoCAD ® Mechanical • Autodesk ® Vault• Autodesk ® Showcase ®• Autodesk ® Factory Design Suite UtilitiesAutodesk Factory Design Suite offers:• 2D and 3D visual layout environment Easily try what-if scenarios by dragging models of machine and facilities content on top of your 2D floor plan. With bidirectional associativity, 2D drawings and the 3D factory layout model automatically update whenever the layout design changes.• Large library of factory assetsAccess out-of-the-box 2D and 3D parametric factory content such as conveyors, material handling equipment, and facility equipment that can be resized and reused.• Factory asset builderUse Autodesk Inventor software to create 3D models of factory equipment, or easily import factory assets from suppliers to include in your layout.• Factory cloud-based servicesPublish, share, and manage assets with both public and private sharing capabilities that make it easy to collaborate internally or share with external stakeholders. Collaborate and share layout designs with various stakeholders in the DWF file format on mobile devices or online. • Factory design efficiencyImprove your digital factory design efficiency by automating repetitive manual tasks such as creation of plan views and section views of the layout, and save time on tape measurements by using laser scanning in your layout workflows.• 3D factory visualization and analysis Collaborate better with immersive, high-quality renderings and visualizations, and reduce installation risks by exploring digital factory models with interactive 3D virtual walk-throughs and fly-throughs.Learn how Autodesk Factory Design Suite can accelerate your factory layout process at /factorydesignsuite .Build Your Digital FactoryOnly Autodesk Factory Design Suite adds factory-specific functionality to AutoCAD, AutodeskInventor, and Autodesk ® Navisworks ® software and combines them with powerful visualization tools such as Autodesk ® 3ds Max ® Design and Autodesk ® Showcase ® software to help manufacturers improve innovation, collaboration, and flexibility when responding to changing business requirements.Autodesk Factory Design Suite adds the following factory-specific functionality in AutoCAD:• Material flow analysis• Large library of factory content• Interoperable 2D-3D layout workflows with bidirectional associativity • Parametric asset variantsAutodesk Factory Design Suite adds the following factory-specific functionality in Inventor:• Interoperable 2D-3D layout workflows with bidirectional associativity• Ability to create accurate factory models with a predefined floor• Ability to drag 3D models of factory assets onto your 2D floor plan• Large library of 3D parametric factory content • Ability to add smart connection points and landing surface definitions on the asset• Automatic conversion of 2D drawings into 3D layouts Autodesk Factory Design Suite adds the following factory-specific functionality in Navisworks:• Floor plane for layout workflows• Repositioning commands specifically built for quickly laying out machines and other equipment • Switchback with InventorAutoCAD ArchitectureAutoCAD ® Architecture is AutoCAD software for architects, combining architectural drafting tools with a familiar AutoCAD software−based working environment to increase design productivity and improve collaboration.Autodesk InventorCreate accurate digital models of factory layouts and equipment with a factory-specific parametric work environment that helps you to make better layout decisions before any equipment is installed.Autodesk Inventor ProfessionalDesign, visualize, and simulate factory equipment under real-world conditions with advanced 3D mechanical design, product simulation, routed systems design, and tooling creation software.AutoCAD MechanicalCreate and revise mechanical drawings quickly using all the functionality of world-class AutoCAD software, plus a complete set of features designed to boost mechanical design productivity.Autodesk 3ds Max DesignCreate photorealistic renderings and cinema-quality 3D animations with award-winning software. Demonstrate the operation of layout designs in real-world settings to improve communication and accelerate your path to new business.Autodesk ShowcaseTransform CAD data into compelling imagery, movies, and interactive presentations to improve the design review process, secure internal buy-in, and win competitive bids. Realistic environments, lighting, and materials let stakeholders and prospects experience your designs before any equipment is installed.Autodesk NavisworksWith Autodesk ® Navisworks ® software you can integrate 3D models and multiformat data, reduce construction risks, and validate design accuracy by detecting space constraints and equipment collisions early in the design process with project review software.Autodesk VaultGain more control over your design data with software for managing the factory layout designcreation, optimization, and documentation processes.。
人工智能带来的就业机遇英语作文全文共6篇示例,供读者参考篇1The Exciting Future of Jobs with AIHi there! My name is Timmy and I'm 10 years old. Today, I want to tell you all about the amazing job opportunities that artificial intelligence (AI) is creating for the future. AI is really cool technology that allows computers to think and learn like humans. While some people worry that AI might take away jobs, I thinkit's actually going to lead to tons of new and exciting jobs that we can't even imagine yet!First, let me explain what AI is. Basically, it's computer software that can process information, learn from data, and make decisions or take actions based on that learning, just like how you and I learn new things every day. We're using AI all the time without even realizing it - like when we talk to digital assistants like Siri or Alexa, or when we get movie recommendations from streaming services. AI is getting smarter and smarter at understanding human language, recognizing images and patterns, and solving complex problems.So how is AI going to create new jobs? Well, as this technology keeps advancing, we'll need lots of people to design, develop, and maintain these AI systems across pretty much every industry you can think of - healthcare, education, business, entertainment, you name it. We'll need software engineers to build the AI algorithms and model architectures. We'll need data scientists and analysts to collect, process, and feed data into the AI models to train them. And we'll need AI researchers constantly working to push the boundaries and come up with even more capable AI.For example, imagine AI assistants that can understand everything we say and help us with any task - scheduling appointments, answering questions, offering advice and recommendations. To create those assistants, you'd need engineers to develop the speech recognition and natural language processing capabilities. You'd need data labelers to annotate huge datasets of conversations to train the AI on how to communicate naturally. You might even need creative writers to craft unique personalities and dialogue for the AI assistants. So many cool job opportunities!Or think about AI that can detect diseases from medical scans faster and more accurately than human experts. We'd needAI engineers to develop those diagnostic models using latest techniques like deep learning and neural networks. Robotics experts would be needed to build surgical robots that can use that AI for better, minimally invasive procedures. And doctors would team up with AI to get second opinions and explore treatment plans. The healthcare field is going to be transformed by AI.AI will create tons of opportunities in creative fields too. Can you imagine an AI that can automatically generate amazing music, art, videos, games or stories? We'll need artists, musicians, designers and creators of all kinds to work with AI and push what's possible. They might use AI tools to enhance their creativity or maybe even collaborate directly with AI systems to produce new creative works. That's going to open up so many avenues for entertaining and inspiring people in wildly new ways.But that's not all - AI will also give rise to entirely new job categories that we can't predict yet because the technology will make new things possible that we can't even imagine today. It's like how nobody could have foreseen jobs like social media managers, app developers, or drone operators existing back in the 1990s before those technologies emerged and transformed our lives. The evolution of AI will be just as revolutionary, if notmore! Who knows what awesome new AI-powered jobs will exist in 10 or 20 years?I'm really excited to see how AI will reshape the workforce and create so many opportunities in my lifetime. Some of today's jobs might change or go away, but I think even more jobs will emerge that let people work with AI in creative, productive, and enriching ways.I can't wait to see what sorts of amazing AI breakthroughs and AI-inspired jobs will exist by the time I'm an adult out in the workforce. Maybe I'll become an AI developer, creating the next generation of intelligent systems. Maybe I'll be an AI-human partnership manager, overseeing teams where AI and people collaborate. Or maybe I'll have a job that doesn't exist yet - something we can't even conceive of today!No matter what, I'm confident AI will open up paths to tons of rewarding career opportunities as long as I work hard, keep learning, and nurture both my technical abilities and my uniquely human traits. The future world of work with AI is going to be awesome. I can't wait to be a part of it!篇2The Exciting World of AI and New JobsHi there! My name is Timmy, and I'm a fourth-grader at Sunny Hills Elementary School. Today, I want to talk to you about something really cool and futuristic – artificial intelligence (AI)! I know it might sound like a complicated term, but don't worry, I'll explain it in a way that's easy to understand.You see, AI is all about creating really smart computers and machines that can think and learn like humans do. These machines can process huge amounts of information, recognize patterns, and even make decisions on their own. Pretty amazing, right?Now, you might be wondering, "But Timmy, what does AI have to do with jobs and employment?" Well, let me tell you – AI is opening up a whole new world of exciting job opportunities that didn't even exist before!One of the coolest things about AI is that it can help us automate tasks that are repetitive or boring for humans. This means that machines can take care of those tasks, freeing up people to focus on more creative and innovative work. Imagine having a robot that can do all your chores for you – how awesome would that be?But AI isn't just about automating tasks; it's also creating entirely new types of jobs that we've never seen before. Forexample, there are now people whose job is to train and develop AI systems. These are called AI engineers or AI researchers. They work on making AI systems smarter and more capable, so that they can tackle even more complex problems.Another cool job that AI has created is that of a data scientist. Data scientists are like modern-day explorers, but instead of exploring new lands, they explore vast oceans of data. They use AI and advanced analytics to find patterns and insights in huge datasets, which can help businesses make better decisions or even lead to new discoveries in fields like medicine or environmental science.And do you know what else? AI is also creating new opportunities in creative fields like art, music, and even writing! There are now AI systems that can create original artworks, compose music, and even write stories or poems. Of course, these AI systems still need human guidance and supervision, which means there's a need for artists, musicians, and writers who can work alongside AI to create truly amazing and innovative pieces.But that's not all! AI is also making its way into fields like healthcare, transportation, and manufacturing. For example, there are AI systems that can assist doctors in diagnosingdiseases or predicting patient outcomes. In the transportation industry, AI is being used to develop self-driving cars and optimize traffic flow. And in manufacturing, AI can help robots and machines work more efficiently and accurately.Now, I know what you might be thinking – "But Timmy, won't AI take away jobs from humans?" That's a valid concern, but here's the thing: while AI might replace some jobs, it's also creating new ones that we can't even imagine yet. Just like how the industrial revolution created new jobs that didn't exist before, like factory workers and engineers, AI is doing the same thing for our modern age.The key is to embrace change and be willing to learn new skills. If we stay curious and keep learning, we can adapt to the changing job market and take advantage of the exciting opportunities that AI is bringing.So, what kind of AI-related job would you like to have when you grow up? Maybe you'd like to be an AI engineer, developing the next generation of intelligent systems. Or perhaps you'd like to be a data scientist, uncovering hidden insights in vast amounts of data. Or maybe you'd like to be a creative artist or writer, collaborating with AI to create amazing works of art or literature.Whatever your dream job is, just remember – the future is bright, and AI is opening up a world of possibilities. So, let's embrace this exciting technology and see where it takes us!Well, that's all I have to say about AI and employment opportunities for now. I hope you found it interesting and informative. And who knows, maybe someday you'll be the one creating the next big AI breakthrough that changes the world!篇3Title: Robots and Computers: Our New Friends at WorkHave you ever wondered what it would be like to work with robots and computers that are almost as smart as humans? Well, that's exactly what's happening with artificial intelligence (AI)! AI is a type of technology that allows machines to think and learn like people. It's pretty cool stuff!You might be thinking, "But won't AI take away our jobs?" That's a valid concern, but the truth is, AI will create lots of new jobs too! Let me tell you how.First of all, AI is already being used in many industries, like healthcare, transportation, and manufacturing. In hospitals, AI can help doctors diagnose diseases more accurately by analyzingX-rays and other medical data. Pretty neat, right? And in factories, AI-powered robots can assemble products faster and more precisely than humans.But AI doesn't just replace human workers; it also creates new job opportunities. For example, someone has to design and program those AI systems, right? That's where AI engineers and developers come in. They're the ones who teach the machines how to think and learn.Another cool job that AI has created is that of a data analyst. You see, AI systems need lots and lots of data to learn from. That's where data analysts come in – they collect, organize, and analyze huge amounts of data so that the AI systems can learn from it.And let's not forget about AI trainers! These are the people who teach AI systems how to do specific tasks, like recognizing objects in images or understanding human speech. It's kind of like how you train your pet dog to do tricks, but with robots and computers instead!But that's not all! AI is also creating new opportunities in fields like customer service, education, and even creative industries like art and music.Imagine having a virtual assistant that can answer your questions or help you with your homework whenever you need it. That's what AI chatbots and tutoring systems can do! And in the future, AI might even be able to create its own artwork or compose music. How awesome is that?For example, instead of spending hours doing paperwork or data entry, office workers might be able to use AI to automate those tasks and focus on more important and creative aspects of their jobs.And let's not forget about jobs that require human skills that AI can't replicate, like teaching, nursing, and counseling. These jobs will always need human touch and empathy.So, while AI might change the way we work, it doesn't mean that we'll all be out of a job. In fact, it might even create more opportunities for us to do the things that we're really good at and enjoy.Just think about it: you'll get to work with cool robots andsmart computers every day. How awesome is that?And who knows, maybe one day you'll even get to design your own AI system or train a robot to do something really cool. The possibilities are endless!So, instead of worrying about AI taking away our jobs, let's embrace the opportunities it brings. With the right skills and mindset, we can all be part of this amazing technological revolution and work alongside our new robot and computer friends.After all, the future of work is already here, and it's full of exciting possibilities. All we have to do is be ready for it!篇4Title: Awesome Artificial Intelligence and the Cool Jobs It Creates!Hi there! My name is Emma, and I'm a 10-year-old student who loves learning about science and technology. Today, I want to share my thoughts on a really cool topic – Artificial Intelligence (AI) and the awesome job opportunities it's creating!You might have heard about AI from movies or TV shows. It's like having really smart computers that can think and learn just like humans. But instead of using a brain like us, AI uses complex algorithms and lots of data to understand patterns and make decisions.AI is already being used in many ways that make our lives easier. Smart assistants like Siri, Alexa, and Google Assistant can answer our questions, set reminders, and even control our smart home devices. Cool, right? AI is also used in self-driving cars, which can sense their surroundings and navigate without a human driver. Isn't that mind-blowing?But AI isn't just about making our lives more convenient; it's also creating some really awesome job opportunities! Here are a few exciting careers that involve working with AI:AI Engineer: These are the people who design, build, and maintain the AI systems we use. They write complex computer code and algorithms that allow AI to learn and make decisions. AI engineers need to be really good at math, programming, and problem-solving. Imagine creating the next smart assistant or self-driving car – how cool would that be?Data Scientist: AI relies on huge amounts of data to learn and make predictions. Data scientists are the ones who collect, analyze, and interpret this data. They use statistical techniques and machine learning algorithms to find patterns and insights that can be used to train AI systems. Data scientists need to be experts in math, statistics, and programming languages like Python and R.AI Ethicist: As AI becomes more advanced, it's important to make sure it's being used in a safe and ethical way. AI ethicists study the potential impacts of AI on society and help ensure that AI systems are designed and deployed responsibly. They need to understand the technical aspects of AI as well as its social and ethical implications.AI Researcher: These are the people who push the boundaries of what's possible with AI. They conduct research to develop new AI algorithms, techniques, and applications. AI researchers often work in universities, research labs, or tech companies, and they need to have a strong background in computer science, mathematics, and other scientific fields.AI Product Manager: Once AI systems are developed, someone needs to figure out how to turn them into useful products and services. AI product managers work with engineers, designers, and marketers to bring AI-powered solutions to the market. They need to understand both the technical aspects of AI and the needs of customers and businesses.Isn't it amazing how many cool jobs are being created because of AI? And these are just a few examples – there are many other exciting careers in fields like healthcare, finance, and entertainment that are being transformed by AI.That's why it's so important for us to keep learning and developing new skills. Even though I'm just a kid, I'm already trying to learn as much as I can about coding, math, and science – the skills that will be valuable in the AI-powered future.Who knows, maybe one day I'll become an AI engineer or a data scientist and help create the next big AI breakthrough! Or maybe I'll pursue a different career that doesn't exist yet but will be made possible by AI.The possibilities are endless, and that's what makes AI so exciting. It's a technology that has the potential to change the world and create amazing new opportunities for all of us.So, what do you think? Are you as pumped about AI and the cool jobs it's creating as I am? Let me know your thoughts and dreams for the future – I'd love to hear them!篇5The Rise of the Robots: Job Chances with AIHi there! My name is Alex, and I'm 10 years old. Today, I want to tell you all about artificial intelligence (AI) and the awesome job opportunities it could create for us when we grow up. AI isreally cool computer software that can think and learn almost like humans.You've probably heard some adults worry that AI will take all the jobs and leave none for people. But I think the opposite is true - AI will actually create way more jobs than it replaces! Let me explain why.First off, AI is already helping humans do their jobs better in all kinds of fields. In healthcare, AI systems can study X-ray and MRI images much faster than human doctors. They help spot diseases earlier so patients can get treated sooner. But we still need human doctors and nurses to actually treat the patients. The AI just gives them a big head start.Same goes for other fields like finance, weather forecasting, scientific research and more. AI crunches through tons of data at lightning speeds. But it needs human experts to make sense of the AI's findings and put them to good use. So AI and humans end up working as a team, with the AI handling the boring data grunt work to free up humans for more interesting, creative work.That's the way it'll be with most existing jobs - AI will pitch in on the tedious parts to make humans' jobs easier and more fun,not replace humans entirely. We'll all have cool AI assistants working beside us!But that's just the start. What really excites me are all the brand new jobs that AI will spawn which never existed before. There'll be tons of opportunities for us kids once we grow up!Think about all the sci-fi tech from movies that seemed impossible, but now AI is actually making it real. Like self-driving cars! We're going to need huge numbers of people to design and operate those smart transportation systems.Or realistic virtual reality worlds for gaming, training, you name it. Somebody has to create and oversee those amazingly immersive digital environments.How about ultra-advanced robotics to build stuff in harsh environments like underwater or in space? More robots means more human experts to build and boss them around. Same with smart homes, smart cities, and any other whiz-bang AI application you can dream up. The future is going to be so unbelievably high-tech that we'll always need humanproblem-solvers, designers, engineers and visionaries.But wait, there's more! We haven't even talked about the brand new fields that AI itself will create from scratch.See, once an AI gets really advanced "artificial general intelligence" like a super-smart human, it can then help design the next generation of even smarter AI systems. And those hyper-intelligent AIs can in turn help build AI that's even more mindblowingly smart. It'll be a feedback loop of intelligence building more intelligence!At that point, scientific and technological progress will be happening at an absolutely insane speed. We'll be discovering new fields of research and invention so rapidly that I can't even imagine what some of them will be yet. But you can bet they'll need human experts, human problem-solvers, and human creativity more than ever before to keep everything moving ahead safely.So many job opportunities, so little time! Maybe I'll become a smart robot inventor. Or design immersive virtual worlds. Or come up with incredible new AI applications we can't yet picture. Or some totally new type of job that doesn't exist yet but will be vital in the AI-powered future.I can't wait! The age of artificial intelligence is going to be the most amazing, opportunity-filled era for kids like me. Instead of robots taking all the jobs, AI is creating a mind-bending number of new human jobs and career paths. The possibilitiesare endless for us humans to work side-by-side with brilliant AI systems on building an incredible future.We just have to stay curious, keep our minds open, and be ready to wholeheartedly embrace the mind-boggling transformations heading our way. Easy peasy for a kid, right? AI is going to make our future job prospects buzzingly exciting. I'm stoked to grow up alongside superintelligent AI and see where we can go together. Buckle up, grown-ups, the robots are our friends!篇6The Exciting World of AI and New Job OpportunitiesHi there, friends! Today, I want to talk to you about something really cool – artificial intelligence, or AI for short. AI is like having a super-smart robot friend that can help us with all sorts of tasks. And you know what's even more exciting? AI is creating brand new job opportunities that we've never seen before!Have you ever dreamed of working with robots or teaching them how to do things? Well, with AI, that dream could become a reality! As AI gets smarter and smarter, we'll need people totrain these intelligent machines, teach them new skills, and make sure they're working properly.One job that could be really fun is an AI trainer. Imagine getting to teach a robot how to recognize different objects, understand human language, or even play games! You'd be like a teacher, but instead of teaching human students, you'd be teaching super-smart robots and computers.Another cool job is being an AI engineer. These are the people who design and build the AI systems that power things like virtual assistants, self-driving cars, and even video games! If you love solving puzzles and coming up with creative solutions, this could be the perfect job for you.But AI isn't just about robots and machines – it's also changing the way we work in lots of other fields. For example, doctors might use AI to help diagnose diseases or develop new treatments. Writers and artists could use AI to generate ideas or create amazing visuals. And scientists could use AI to analyze huge amounts of data and make exciting new discoveries!One job that I find really interesting is an AI ethicist. As AI gets more and more advanced, we need to make sure it's being used in responsible and ethical ways. AI ethicists help to createguidelines and rules for how AI should be developed and used, so that it benefits people and doesn't cause any harm.And you know what's really cool? You might even get to invent completely new jobs that we can't even imagine yet! As AI keeps growing and changing, there will be all sorts of opportunities for creative and innovative people to come up with new ways to use this amazing technology.But as exciting as all of this sounds, it's important to remember that AI is a tool, and it's up to us humans to use it wisely and responsibly. We need to make sure that AI is developed in a way that benefits everyone and doesn't cause any harm or unfairness.That's why it's so important for kids like you to learn about AI and get involved in this amazing field. You'll not only get to work with cutting-edge technology, but you'll also help shape the future of AI and make sure it's used in a way that makes the world a better place.So, what do you think? Are you excited about the possibilities of AI and all the new job opportunities it's creating? Maybe you'll be the one to invent the next big AI breakthrough or come up with an entirely new way to use this incredible technology!No matter what path you choose, just remember to dream big, work hard, and always keep learning. The future of AI is in your hands, and I can't wait to see what amazing things you'll create!。
计算机软件优点英语作文The Advantages of Computer Software.Computer software, an essential component of modern technology, has revolutionized the way we live, work, and interact with the world. It encompasses a vast array of applications, tools, and platforms that facilitate various tasks, enhance productivity, and promote innovation. The advantages of computer software are numerous and diverse, affecting almost every aspect of our daily lives.Improved Efficiency and Productivity.One of the most significant advantages of computer software is its ability to improve efficiency and productivity. Whether it's a word processing tool that helps us draft documents quickly or a spreadsheet application that enables us to analyze and manage data effortlessly, software simplifies complex tasks and saves us valuable time. Additionally, automated softwaresolutions, such as those used in manufacturing and logistics, eliminate the need for manual labor, further boosting productivity.Enhanced Communication and Collaboration.Computer software has also revolutionized the way we communicate and collaborate. Email and messaging applications allow us to stay connected with people across the globe, sharing ideas, information, and documents instantly. Collaborative tools, such as version control systems and project management software, facilitate teamwork and ensure that multiple users can work on the same project simultaneously, without any conflicts or duplications of effort.Facilitated Decision-Making.Another crucial advantage of computer software is its ability to facilitate decision-making. Analytical tools and software applications that process vast amounts of data, such as business intelligence tools and data miningsoftware, provide insights and predictions that help businesses make informed decisions. Similarly, simulation software allows engineers and designers to test their ideas and prototypes before investing in actual production, thus minimizing risks and maximizing efficiency.Enhanced Creativity and Expression.Computer software has also opened up new avenues for creativity and expression. Graphic design software allows artists and designers to create stunning visuals and graphics, while music and video editing tools enable musicians and filmmakers to produce professional-quality audio and video content. Even writing and publishing software provide authors with the means to craft and share their stories with a wider audience.Improved Accessibility and Convenience.The widespread availability of computer software has made technology more accessible and convenient for everyone. Software can be downloaded and installed on personalcomputers, laptops, smartphones, and tablets, allowing users to access their tools and applications anytime, anywhere. This flexibility and portability have transformed the way we work, learn, and entertain ourselves, making it easier to fit technology into our daily lives.Cost Efficiency.Finally, computer software often offers cost-effective solutions for businesses and individuals. By automating tasks and streamlining processes, software can help organizations reduce their operational costs. Additionally, with the advent of cloud computing and subscription-based models, software is becoming more affordable and accessible to small businesses and individuals, enabling them to compete and innovate on a global scale.In conclusion, computer software offers a wide range of advantages that have transformed the way we live and work. Its ability to improve efficiency, enhance communication, facilitate decision-making, and promote creativity has made it an indispensable tool for businesses and individualsalike. As technology continues to evolve, we can expect computer software to bring even more remarkable advancements and benefits in the future.。
SD3231113ds Max Design Automation—Locally and in the Cloud Kevin Vandecar – Developer AdvocateAutodeskLanh Hong – Developer AdvocateAutodeskDescriptionThis class will discuss the various techniques for automating 3ds Max software. We’ll first cover techniques to build automated routines to drive complex tasks within 3ds Max. 3ds Max includes a local tool called 3dsmaxbatch that enables local automation of complex tasks. This functionality is also available in the cloud under the Forge Design Automation API. We’ll discuss MAXScript, Python, C++, and .NET approaches to automation, and how to connect your routines to the web to drive configurable automation.Speaker(s)Kevin Vandecar is a Forge developer advocate and also the manager for the Media & Entertainment and Manufacturing Autodesk Developer Network Workgroups. His specialty is3ds Max software customization and programming areas, including the new Forge Design Automation for 3ds Max service.Lanh Hong joined Autodesk as an intern in the summer of 2017 and knew she wanted to come back after graduation. Upon finishin g her bachelor’s in Computer Science at the University of California, Davis in 2018, she was given the opportunity to join Autodesk as a Developer Advocate working closely with the Autodesk Maya API.Build automation routines for 3ds Max3ds Max has always been a powerhouse of customization, so if you are currently using 3ds Max, it’s likely you have used at least MAXScript to d rive some custom behavior. There are so many resources out there for MAXScript and plugins, even if you are not a coder, it’s easy to find custom routines.What is Automation?Any routine that can run unattended to do batch processing. Examples include:Batch process files sets•Export MAX scenes to other formats. For example to the FBX format•Import other formats into 3ds Max scene format. For example, import FBX.•Modify MAX scenes requiring common automated changesTools to build, modify, or analyze content•Configurator for content•for example: based on user input, build a specialized assetModify content•for example: LOD or Mesh manipulationAnalysis tool•for example: given model is analyzed for defect or problem criteriaUse 3dsmaxbatch tool to automate tasksThe 3dsmaxbatch.exe tool has been provided with 3ds Max since 2018 release. Note that there were a few adjustments after 2018 updates 2 and 3 , but from there on it has been consistent and ready for use locally. This is also the default Forge Design Automation engine for 3ds Max. The complete and latest docs are provided here:/view/3DSMAX/2020/ENU/?guid=GUID-48A78515-C24B-4E46-AC5F-884FBCF40D59Remember that Design Automation for 3ds Max will support back to the 2018 version, and is using the latest Update, so you should not have to worry about the “legacy” behavior.The best approach for automation is to test and work through all your kinks locally in a known environment. Once you are confident in the automation, you can deploy to a local pipeline, or then extend it to Forge Design Automation.Because 3dsmaxbatch is accepting scripts (MAXScript or Python) to initiate the automation, you will need at least some scripting code to get things started. There are essentially two ways to handle this:1. Build a script that executes functionality directly. When passed into the 3dsmaxbatch, itwill be executed immediately and launch any automation in that job execution.2. Using the Application Plug-in Package system. This was originally created to handle appstore plugins, but it is also a very powerful loader that allows multiple versions to besupported in the same bundle, plus other configuration options. It also resides outside of the 3ds Max installation folder structure, so provides a nice way to stay independent ofthe 3ds Max installation. The specification file “PackageContents.xml” has a tag called“post-start-up scripts parts” that will load and evaluate a script after 3ds Max is fullyrunning. This is another way to directly kick-off automation. See here for completedocumentation:/view/3DSMAX/2020/ENU/?guid=__developer_writing_plug_ins _packaging_plugins_packagexml_format_htmlExpose functionality from C++, .NET, Python, and MAXScript to enable configurable automation3ds Max has a very rich customization system and provides several environments for programming behavior. This includes:•MAXScript – a powerful and mature scripting system specific to 3ds Max. The syntax and API are unique to 3ds Max,•Python – The python environment is basically a wrapper around the MAXScript APIs.You can use Python syntax to call the MAXScript APIs directly.•C++ SDK – the 3ds Max SDK in primarily C++ based. In order to use the SDK, you will need to install it separately. After 3ds Max itself is installed, you can restart the installer and select tools->SDK. Or even easier is to use the MSI file directly from the distribution file set. Typically, this is located here: <distribution folder>\x64\Tools\MAXSDK. Although there ways you can code “start-up” execution from a C++ plugin, it is better to exposethe functionality to MAXScript so it can be called directly there. You can use Parameter Blocks or Function Publishing for this:/view/3DSMAX/2020/ENU/?guid=__developer_3ds_max_sdk_f eatures_function_publishing_html•.NET API – The .NET API is a wrapper for the C++ SDK. Even though it is not required to install the SDK to use .NET 3ds Max API assemblies, you should consider installing it.Because the .NET API is wrapper, the samples and other support from the SDK can be very helpful when working in .NET API. The easiest way to expose functionality here is to use a static class and static methods. There is helper MAXScript functions that willallow you to access the class and methods, that you can then call directly. The onlydrawback here is that you can only support standard data types and it is not easy tohandle 3ds Max types.Tips:When developing, keep logic separate from UI•Allows you to call the logic without needing UI interaction•Define clean and clear parameters for maintainabilityPlugins using Parameter Blocks•Get/Set for parameters•Even if Auto-UI, you can still set the parameters from codeBe a ware that most C++ plugins are using parameter blocks. Even if there is no “exposed” API, you can usually configure a plugins data by get/set on the parameters stored in the parameter block. There are two versions of the Parameter block system:1. ParamBlock1 is the older system. Most plugins within 3ds Max and the SDK sampleshave been moved to ParamBlock2. But be aware that there is a chance you can still run across an older parameter block. If you have plugins using the older system, there is aporting guide here:/view/3DSMAX/2020/ENU/?guid=__developer_3ds_max_sdk_f eatures_working_with_plug_ins_parameter_blocks_pb1_to_pb2_conversion_html2. ParamBlock2 is the current system. See here for complete details:/view/3DSMAX/2020/ENU/?guid=__developer_3ds_max_sdk_f eatures_working_with_plug_ins_parameter_blocks_htmlIf your plugin is simple and is driven mainly by parameter blocks, you really do not needto use function publishing unless you want to provide a more robust way to drive theplugin.Using the parameter block from the ProOptimzer plugin is how the .NET plugin for the 3ds Max Design Automation sample is working. The automation plugin is located in the design automation repo. See here: https:///kevinvandecar/design.automation.3dsmax-csharp-meshoptimizer/Using MAXScript (or Python) is certainly an easy way to build up routines. These can still be installed as an Application Plug-in Package bundle. Again this allows you to keep your routines separate from the actual 3ds Max installation folder structure. Plus you can also support multiple versions and differences easily in the same bundle.Let’s take a look at how a C++ Plugin can be automated. Again, the direct and easiest ways is to use the parameter blocks. In this example, we look at the C++ source code from the bend modifier:bend_angle, _T("BendAngle"),TYPE_FLOAT, P_RESET_DEFAULT|P_ANIMATABLE,IDS_ANGLE,p_default, 0.0f,p_range, -BIGFLOAT, BIGFLOAT,p_ui, TYPE_SPINNER,EDITTYPE_FLOAT, IDC_ANGLE, IDC_ANGLESPINNER,0.5f,p_end,Then from MAXScript you can add the modifier to every object in a scene and set the values like this:for obj in Geometry do (bendModADN = Bend_OSM_ADN()addModifier obj bendModADNbendModADN.BendAngle = 45bendModADN.BendDir = 70)Now let’s take a look at a more complex example using the .NET API:First, using .NET API we are configuring the C++ plugin that comes with 3ds Max called ProOptimizer. This plugin is a modifier that does mesh reduction by setting a percentage value. Add the modifier:IObject obj = node.ObjectRef;IIDerivedObject dobj = global.CreateDerivedObject(obj);object objMod = ip.CreateInstance(SClass_ID.Osm, cid as IClass_ID);IModifier mod = (IModifier)objMod;dobj.AddModifier(mod, null, 0); // top of stacknode.ObjectRef = dobj;Insure the ProOptimizer modifier exists on an object, and then configure it.IModifier mod = GetModifier(node, cidOsmProoptimizer);if (mod != null){// In order to get the "Calculate" parameter to trigger// the modifier to execute, we have to enable some UI elements.ip.CmdPanelOpen = true; // ensures the command panel in general is openip.SelectNode(node, true); // Select the node to make it activemandPanelTaskMode = 2; //TASK_MODE_MODIFY. This makes the modifier panel active // Now we can set the parameters on the modifier, and at end "calculate" the results. IIParamBlock2 pb = mod.GetParamBlock(0);pb.SetValue((int)ProOptimizerPBValues.optimizer_main_ratio, t, VertexPercent, 0);pb.SetValue((int)ProOptimizerPBValues.optimizer_options_keep_uv, t, 1, 0);pb.SetValue((int)ProOptimizerPBValues.optimizer_options_keep_normals, t, 0, 0);// There is no true way to know if this was valid/invalid for the mesh,// so we check the outer level routine on triobject for changes. **pb.SetValue((int)ProOptimizerPBValues.optimizer_main_calculate, t, 1, 0);ip.ClearNodeSelection(false);}These routines are wrapped inside a static class and methods. For example:namespace Autodesk.Forge.Sample.DesignAutomation.Max{static public class RuntimeExecute{static public int ProOptimizeMesh(){...}}From MAXS cript we can call it like this…da = dotNetClass("Autodesk.Forge.Sample.DesignAutomation.Max.RuntimeExecute") da.ProOptimizeMesh()The MAXscript function “dotNetClass” gains access to the .NET class and methods exposed there. See here for details: /view/3DSMAX/2020/ENU/?guid=GUID-779FD7AC-953D-4567-B2A8-60B1D8695B95Use Forge Design Automation for 3ds Max to automate your tasks in the cloud Forge Design Automation V3 has been recently released after being in beta for nearly a year. During this time Autodesk collected much feedback and have now delivered a stable set of traditional desktop engines in the Forge cloud. The Design Automation APIs support 3ds Max, Revit, Inventor, and AutoCAD.The Design Automation API itself is identical for all engines. This allows you to build reusable frameworks and tools that can automate any of the four engines with simple code changes. It also allows you to easily work with more than one engine at the same time.Let’s start with a look at how the Forge Design Automation API fits into the overall Forge technology stack. Currently the APIs include:•Data Management•Reality Capture•BIM 360•Webhooks API•Model Derivative API and Viewer JavaScript library•Design Automation APIBecause Design Automation is just another set of end points in the Forge technology stack, this allows you to easily connect multiple aspects of your automation and workflow together in a singles web app. For example, after processing something in 3ds Max Design automation, maybe you would like to preview the geometry. Here you can combine Design Automation for 3ds Max with the Viewer and Model Derivative functionality. Or perhaps you want to use reality Capture to generate a 3d Asset, and then further process it within 3ds Max automation.The benefits to using Forge Design Automation, instead of local automation include: •No local resources needed•No licenses consumed•No 3ds Max “compatible” hardware•No branding requirements•Build custom experiencesFor example, with an inhouse automation, you might use Forge Design Automation to run regular jobs at any time, and free up a 3ds Max license for creative work. Or you might build a commercial online tool that provides assets to your customer in 3ds Max format, or any of the other formats that 3ds Max can export.How does it work? Basically, it is very similar to running locally, except you will need to use the Forge Design Automation APIs to manage the jobs. The fundamental idea is like this:Here you can see there is input data, processing, and output/modified data.The key idea is to be sure you understand that the data is yours and can be stored anywhere. For example, another cloud storage service (ie. Amazon, Dropbox) or Autodesk hub storage (a360 or BIM 360), or can even be locally uploaded. In that case even in-house centralized network storage can be used. Once the data is downloaded from your storage to the Design Automation instance, it is then processed as you request. Once the job is finished, the output is then uploaded back to your desired location. After the Design Automation job is finished, the instance is shutdown and no data is maintained.The Design Automation API is built our as industry standard REST API endpoints. The key concepts are listed in the chart below:For details of each of these concepts, please refer to the online documentation here: https:///en/docs/design-automation/v3/developers_guide/basics/ and https:///en/docs/design-automation/v3/developers_guide/field-guide/In the 3ds Max context, see below for how each concept relates to the others and are used in conjunction to setup an automation job.The Activity is the major aspect that defines the automation itself. It describes the AppBundle to use, how many and what are the input files, optionally can use zip files (data sets), types of parameter, and how many and what are the outputs. You can also indicate whether they are shared or not, and by Forge ID or with everyone. You can specify an alias to help you identify each activity and its state. For example, production, beta or alpha. And finally, you can also versions the activities.Here is an example JSON data structure for a 3ds Max activity that exports the input scene to FBX and provides it back as the output. There is no bundle in this example, and the execution script is provided directly here in the activity:{"id": "ExportToFBX","commandLine": "$(engine.path)/3dsmaxbatch.exe -sceneFile\"$(args[InputFile].path)\" \"$(settings[script].path)\"","description": "Export a single max file to FBX","appbundles": [],"engine" : "Autodesk.3dsMax+2020","parameters": {"InputFile" : {"zip": false,"description": "Input 3ds Max file","ondemand": false,"required": true,"verb": "get","localName": "input.max"},"OutputFile": {"zip": false,"ondemand": false,"verb": "put","description": "Output FBX file","required": true,"localName": "output.fbx"}},"settings": {"script": "exportFile (sysInfo.currentdir + \"/output.fbx\") #noPrompt using:FBXEXP"}}There are also callbacks that are an important aspect to Design Automation interaction.•OnDemand callbacko Allows you to provide additional input data to the WorkItem during execution, on as needed basis•OnProgress callbacko Allows you to check for the status of WorkItem execution on a periodic basis •OnComplete callbacko Lets you know when the WorkItem execution has ended without the need to actively check the statusThe OnComplete callback is one that you would likely always use.Forge Design Automation for 3ds Max ExampleThis example is taking an input 3ds Max scene and reducing the mesh level of detail using the ProOptimizer feature. Once the optimization is finished, then the plug-in saves a new 3ds Max scene file, exports an FBX file, and also directly produces a SVF export. SVF is the format that the Forge Viewer is using, and so this allows us to also preview the design.A few final things to consider…•You have access to multiple versions of 3ds Max (currently 2018, 2019, 2020)•The jobs are run in parallel, so you can break things down as you want to optimize performance and speed.•Full MAXScript support (as automation). MAXScript/Python can drive functionality in C++ and .NET•Custom plug-ins (C++ and .NET)•No license needed, just pay for use•Rendering with Arnold for now will have a watermark•The job r uns in a “sandbox” that is protected. This means:o One job per worker, nothing shared with anyone elseo Protects your code, protects the Autodesk infrastructureo No access outside of working directoryo No Internet accesso What the user is executing should be able to run in low integrityo The execution should be self-contained to the low integrity folders •Be aware of the quotas and limits. Especially:o Input and Output file sizeo Job durationThe currently defined quotas for all Design Automation engines are listed here:https:///en/docs/design-automation/v3/developers_guide/quotas/SupportForge Portal - Design Automation API v3 Documentationhttps:///en/docs/design-automation/v3/developers_guide/overview/https:///en/docs/design-automation/v3/tutorials/3dsmaxAsk your questions on StackOverflow and use the tag autodesk-designautomation. This helps us to find your questions and ensure it is answered. We feel the community is already becoming quite mature and so there are great experiences that everyone is willing to share there. https:///questions/tagged/autodesk-designautomationYou can also ask directly if desired. See complete details here:https:///en/support/get-helpSamples are provided via github. The main organization is: Autodesk-Forge and you will find many repos there with code samples in a variety of languages and options.Tutorialshttps:///developer/getting-startedhttps:///en/docs/design-automation/v3/tutorials/3dsmax/https://learnforge.autodesk.io/#/tutorials/modifymodels (design automation)Sampleshttps:///code-sampleshttps:///kevinvandecar/design.automation.3dsmax-csharp-meshoptimizerhttps:///lanhhong/design.automation.3dsmax-nodejs-meshoptimizer。
Automating Software Design:Exploring and Evaluating DesignAlternativesAbstract.Development of complex socio-technical IT systems is a very important and a relativelynew problem for Software Engineering.Traditional software development methodologies should berevised and improved to capture properties of both human and artificial agents and interactionsbetween them.This thesis proposal aims at building a framework for the automatic selection andevaluation of design alternatives.This is supposed to be done by(i)applying existing planning toolsto automate the generation of design alternatives,and(ii)developing methods and algorithms forthe evaluation and analysis of design alternatives based on game theory.Supporting tools will bedeveloped to guide their users through the software design process.Keywords:software design,socio-technical systems,planning,game theory1IntroductionMotivation.Development of complex socio-technical IT systems is nowadays a very important issue in Software Engineering[21].Modern IT systems involve human agents,thus,considering just system functionality is not enough–the interaction between system components and organizational/social envi-ronment should be taken into account.Because of this”human aspect”the design of socio-technical IT systems is a relatively new problem for Software Engineering.In addition,such systems are usually large-scale ones,while even for traditional large-scale systems existing software development methodologies are not very successful.Despite of the efforts put into establishing the software development methodologies during the last decades,big projects often run out of time and budget,and are not robust and secure enough to meet continuously increasing user requirements1.To face the problem the methodologies that guide the development process since its early stages should be revised,enriched,and further developed. Moreover,the complexity of present socio-technical systems is such that to be effective all methodologies have to be equipped with mechanisms for automation support.Problem.What kind of automation a designer needs?One of the proposals is to facilitate the designer’s work by automating the specification refinement process.The approach is reflected in Model Driven Architecture(MDA)[16]which focuses on(possibly automatic)transformation from one formal system model to another.Tools supporting MDA exist and are used in the Rational Unified Process for software development in UML.Yet the state-of-the-art is still not satisfactory[20].Another approach to the problem are design patterns[11]which propose to match standard documented solutions with the design problems arisen in the certain context.Such approaches only cover part of the designer’s work,while there is another activity where the support of automation could be beneficial as well[15]:”Exploring alternative options is at the heart of the requirements and design processes”.Indeed,in most current software engineering methodologies the designer has tools to report and verify thefinal choices(e.g.Goal-models in KAOS[4],UML Classes or Java code),but there is no,actually,the possibility of automatically exploring the alternatives andfinding a satisfactory one.This thesis proposal aims at exploring the problem and building the framework for the automatic selection and evaluation of design alternatives.The automated selection of alternatives at the early software development stages can 1See Standish Group reports at /sample research/.2Automating Software Design:Exploring and Evaluating Design Alternativesbe the most beneficial and effective.The reason is that at the early stages the design space is larger,it is at these stages when most alternatives are examined(and discarded)and thus a good choice might have significant economic impact.Supporting the selection of alternatives would lead to more alternatives being considered,more thorough analysis of considered alternatives and an overall more complete and trusted design.Approach.It can be noticed that requirements–at least within the frameworks such as i*[26], Tropos[2]and the like–are conceived as networks of delegations among actors(which are organi-zational/human/software agents,positions and roles).Every delegation involves two actors,where one actor delegates to the other the delivery of a resource,the fulfillment of a goal,or the execution of a task.The delegatee can deliver/fulfill/execute the delegated service(i.e resource,goal or task),or further delegate it,thus creating another delegation relation in the network.Intuitively,these can be seen as actions that the designer ascribes to the members of the organization and the system-to-be.Further,the task of designing such networks can be framed as a planning problem for multi-agent systems:selecting a suitable possible design corresponds to selecting a plan that satisfies the goals of the human or software agents.Many off-the-shelves planners are available that,given the problem domain description,generate a sequence of actions(or a plan)that satisfy a set of predefined goals.One of the aims of this proposal is to embed existing planning tools into the framework to automate the generation of design alternatives.Of course,the designer remains in the loop:designs generated by the planner are suggestions to be evaluated,amended and approved by the designer.The tricky point here is the solution evaluation which can be complex enough even for very experienced designers with considerable domain expertise.Indeed, a challenging characteristic of the design of socio-technical IT system is that human agents should be taken into account.They can be seen as players in a game theoretic sense as they are self-interested and rational.This means they want to minimize the load imposed personally on them,i.e.they want to reduce the number and the complexity of actions they are involved in.In a certain sense non-human agents,i.e.system components,are players as well as it is undesirable to overload them.Each player has a set of strategies he could choose from,e.g.he could decide whether to satisfy a goal himself or to pass it further to another system actor.Strategies are based on the player’s capabilities and his relations(e.g. subordination,friendship,or trust)with other human and artificial agents in the system.If we assume that each player ascribes a numerical weight to each possible action,then it is possible to calculate the cost of a given design alternative for the player by summing up the weights of actions in the solution he is involved in.Obviously,each rational player wants to minimize this cost,or at least he”searches for justice”,i.e.he wants the load to be more or less equally divided among all the involved actors.How to choose the”right”design alternative that will at the same time satisfy the overall system goal and be ”accepted”by all actors?A part of this research is to develop methods and algorithms for the evaluation and comparative analysis of design alternatives based on game theoretic ideas.The aim is to support the designer with the tool that will evaluate and try to optimize the solution to the design-as-planning problem.The rest of the proposal is structured as follows:Section2overviews briefly the areas related to the topic of the proposal;in Section3the selected approach to the problem is detailed;finally,in Section4 already obtained results are listed and work plan for the next two years is presented.2State-of-the-ArtRequirements Engineering and Software Design.Requirements engineering is considered to be a crucial part of software development process[23].Careful elicitation and analysis of requirements help to develop a system that meets user’s expectations,is trustful and robust.According to[23]requirements engineering involves such activities as domain analysis,elicitation,specification,assessment,negotiation, documentation,and evolution.Modeling requirements to software systems and organizations in terms of goals and their interdependences has been a topic of considerable research interest during the last decades[23].A number of goal-oriented approaches for requirements representation and reasoning wereAutomating Software Design:Exploring and Evaluating Design Alternatives3 introduced.For example,KAOS approach[4]supports modeling goals of different types,allows to define goal attributes,links between goals(e.g.to model the situation when a goal negatively or positively supports other goals),AND/OR goal refinement links,links between goals and agents,etc.The i*model [26]offers primitive concepts of actors,goals and actor dependencies,which allow to model both software systems and organizations.With i*framework one can capture why the software is being developed,while the earlier approaches(e.g.Object Oriented Analysis)reflect only what’s and how’s.Software design is an intermediate phase between the user requirements elicitation and analysis and the system implementation.The design process results in software specifications which are formulated in a vocabulary understandable by programmers,while requirements are formulated in terms of objects of the real world and their interconnections,and are understandable by stakeholders.The problem of designing software that meets user requirements is addressed,for example,in[24]where a goal-oriented approach to architectural design based on the KAOS framework is proposed.The authors describe the process of deriving software specifications from requirements,and then building an architectural draft from functional specifications.The obtained architecture is then recursively refined to meet non-functional requirements analyzed during requirements analysis phase.This research proposal is inspired by and was originated in Tropos project2.Tropos is an agent-oriented methodology which covers all software development phases from early and late requirements analysis through architectural and detailed design to implementation[2].It is based on i*framework with actors,goals,dependencies,plans,resources,and capabilities as basic modeling constructs.The key point in Tropos is in using the same notation through the whole software development process.During the early requirements analysis stakeholders and their intentions are identified,i.e.the organizational environment of the system under development is te requirements analysis puts the system-to-be into its operating environment and models its dependencies with the other actors of the organization. The design phase is subdivided into architectural and detailed design and is structured as follows.First, the overall architectural organization is defined,and the capabilities needed by the actors to fulfill their goals and plans are identified.Then,a set of agent types is defined together with assigning each of them one or more different capabilities.Next,agents’micro level is specified during the detailed design phase.Tropos framework includes not only modeling but also reasoning tools which help in requirements analysis,validation and verification(e.g.goal reasoning tools,automatic verification of security and trust requirements in Secure Tropos–see project homepage for the details).Designing Social Structures.Another perspective of information systems development,inspired by the organizational theory,is reflected in the literature.In[10]ontology for information systems is proposed which adopts i*organizational modeling framework with its actor,goal and social dependency primitives.The paper describes a number of organizational styles(e.g.joint venture,hierarchical con-tracting,etc.)and social patterns(e.g.broker,mediator,wrapper,etc.).The former describe the overall structure of the organizational context of the system or its architecture,while the latter focus on the social structures necessary to achieve one particular goal.Both organizational styles and social patterns guide the development of the organizational model for an information system.In[6]a methodology for the design of agent societies based on the type of co-ordination structure is described.Following the organizational theory,co-ordination in agent societies is divided into three types:markets,networks and hierarchies.Design steps include selecting a coordination model from ones available in the library;de-scribing interaction between the society and its environment,and behavior of the society in terms of agent roles and interaction patterns;finally,the internal structure of agents is defined.Automated Software Design.Almostfifty years ago the idea of actually deriving the code directly from the specification(such as that advocated by Manna and Waldinger landmark paper)started a large program of funding for deductive program synthesis that has not gained significant results in the past. The key idea of the approach is the following.A system goal together with the set of axioms are specified, and then a theorem,i.e.goal of the system described in a formal specification language,is proved with 2See project homepage at for the details.4Automating Software Design:Exploring and Evaluating Design Alternativesthe help of axioms.A program for solving the problem is extracted from the proof of the theorem.The field is still fairly active and several program synthesis systems were proposed(see,e.g.[8,19]),but they are mainly domain-specific,require considerable expertise,and in some cases do not actually guarantee that the synthesized program will meet all requirements stated by designer[8].Conceptually,the automatic selection of alternatives is done in deductive program synthesis:the theorem prover selects among the appropriate axioms to prove the theorem.Instead,in this proposal it is argued that the automatic selection of alternatives should and indeed can be done at earlier stages. Requirements models are by construction simpler and more abstract than software models.Therefore, techniques for automated reasoning about alternatives at the early stages of the development process may succeed where automated software synthesis has not been able to deliver.Another approach is to facilitate the work of the designer by supporting the tedious aspects of software development by automating the specification refinement process.Such approach underlies Model Driven Architecture(MDA)[16],which focuses on(possibly automatic)transformation from one formal system model to another.MDA approach,proposed by Object Management Group,is a framework for defining software design methodologies.The central focus of MDA is on the model transformation,for instance from the platform-independent model of the system(PIM)to platform-specific models(PSMs)used for implementation purposes.Models are usually described in some formal language(e.g.UML),and the transformation is performed in accordance with the set of rules,also called mapping.Transformation could be manual,or automatic,or mixed.However,the state-of-the-art is far from being satisfactory[20].Among the proposals on automating a software design process the one of Gamma et al.on design patterns[11]has been widely accepted.A design pattern is a solution(commonly observed from practice) to the certain problem in the certain context,so it may be thought as a problem-context-solution triple. Several design patterns can be combined to form a solution.Note that it is still the designer who makes the key decision–on what pattern to apply to the given situation.An interesting work of Gross and Yu[14]should be mentioned here which relates the representation and analysis of non-functional requirements with software design patterns.The proposed approach or-ganizes,analyzes and refines non-functional requirements to provide guidance and reasoning support in applying patterns during a software system design.AI Planning.Thefield of AI planning has been intensively developing during the last decades, and has found a number of applications(robotics,process planning,autonomous agents,etc.).Planning approach recently has proved to be applicable in thefield of automatic Web service composition[18]. There are two basic approaches to the solution of planning problems[25].One is graph-based planning algorithms in which a compact structure,called Planning Graph,is constructed and analyzed.In the other approach the planning problem is transformed into a SAT problem and a SAT solver is used.There exist several ways to represent the elements of a classical planning problem,i.e.the initial state of the world,the system goal,or the desired state of the world,and the possible actions system actors can perform.The widely used,and to the certain extend standard representation is PDDL(Planning Domain Definition Language),the problem specification language proposed in[13].Current PDDL version,PDDL 2.2[7]used during the last International Planning Competition3,supports many useful features,e.g. derived predicates and timed initial literals.Design as Planning.A few works can be found which relate planning techniques with software requirements analysis and design.In[1]a program called ASAP(Automated Specifier And Planner)is described,which automates a part of the domain-specific software specification process.ASAP assists the designer in selecting methods for achieving user goals,discovering plans that result in undesirable outcomes,andfinding methods for preventing such outcomes.The authors describe the planner they have implemented,which combines adaptive and hierarchical planning techniques(see[1,18]for references). The problem of their approach is that the designer still performs a lot of work manually determining the 3See http://ls5-www.cs.uni-dortmund.de/∼edelkamp/ipc-4/for the details.Automating Software Design:Exploring and Evaluating Design Alternatives5 combination of goals and prohibited situations appropriate for the given application,defining possible start-up conditions and providing many other domain-specific expert knowledge.Castillo et al.[3]present an AI planning application to assist an expert in designing control programs in thefield of Automated Manufacturing.The system they have built integrates POCL,hierarchical and conditional planning techniques(see[3,18]for references).The authors consider standard planning approaches to be not appropriate with no ready-to-use tools for the real world,while in this research proposal the opposite point of view is advocated.Another recent application of the planning approach to requirements engineering is proposed by Gans et al.[12].Essentially,the authors map trust,confidence and distrust described in terms of i*models[26]to delegation patterns in a workflow model.Their approach is inspired by and implemented in ConGolog(see[18]for description and references),a logic-based planning language.However,they focus more on representing/modeling trust in social networks, than on the design automation.The authors do not go far in explaining how they exploit the planning formalism in the design process and,moreover,do not give any examples of modeling.Game Theory.Game theory is an established discipline which deals with conflicts and cooperation among rational independent decision-makers,or players.A strategic game is defined by a set of players, and,for each player,a set of actions(called strategies)and a payofffunction that assigns a numeric value to each of the player’s action profile.The theory studies various types of games:non-cooperative and cooperative games,dynamic games in which the order of players’decisions is important,games with incomplete information,etc.The key concept in classical game theory is the notion of equilibrium[17] which defines the strategies of each player in such a way that all players are satisfied to a certain extent. In other words,this set of strategies is a stable state which none of the independent rational players wants to deviate from.However,this does not mean that each player maximizes his utility by choosing the equilibrium strategy;rather,we can say that by playing an equilibrium each player maximizes his utility locally,given some constraints(on the other players’actions).For example,playing the Nash equilibrium means that no player can benefit when deviating from his equilibrium strategy given that all other players play the equilibrium.Nash equilibrium is proved to exist in mixed strategies(i.e.when a player is randomizing over several strategies),while in pure strategies it might not exist.Game theory is applied in various areas,especially in economics(modeling markets,auctions,etc.), corporate decision making,defense strategy,telecommunications networks and many others.Among the examples are the applications of game theory to so called network games(e.g.routing,bandwidth allo-cation,etc.),see[22]for references.Recently the idea of applying mechanism design in the area of multi-agent systems has emerged [5].Mechanism design can be viewed as a branch of game theory which intends to design systems/game environments so that certain properties are satisfied when the equilibrium state is reached.Another name for this discipline is implementation theory[17]as it implements a particular objective despite the self-interests of individual players.However,a number of fundamental research problems should be solved[5] in order mechanism design to be actually applied to the design of complex distributed systems composed of multiple interacting agents.3Research Contribution3.1ProblemAs it was already introduced in Section1,this thesis proposal aims at building a framework for automatic selection and evaluation of design alternatives.This is supposed to be done in two phases.Thefirst is to apply existing planning tools to automate the generation of design alternatives.The second phase is to develop methods and algorithms for the alternatives evaluation and analysis based on game theoretic ideas,and,as a result,to support the designer with the tool to evaluate and optimize a solution to the design-as-planning problem.6Automating Software Design:Exploring and Evaluating Design AlternativesRequirements engineer/designer will be supported in the selection of the best alternative by changing the software development process as follows:–Requirements analysis phase•Identify system actors,goals and their properties.•Define dependency relationships among actors.–Design phase•Automatically explore the space of design alternatives to identify delegation links and assignments of goals to actors.If no alternatives can be generated,return to the requirements analysis phase and revise the initial structure.•With the help of supporting tools evaluate the obtained solutions.If necessary,ask for another, optimized solution.3.2Objectives and ApproachFormalizing the design-as-planning problem.We have chosen AI planning approach to support the designer in the process of selecting the best alternative.The motivation of such choice,as it was stated in Section1,is that the problem of generating design alternatives can be naturally represented as a planning problem.The basic idea behind planning approach is to automatically determine the course of actions (i.e.a plan)needed to achieve a certain goal where an action is a transition rule from one state of the system to another[25,18].Actions are described in terms of preconditions and effects:if the precondition is true in the current state of the system,then the action is performed.As a consequence of an action, the system will be in a new state where the effect of the action is true.Thus,once we have described the initial state of the system,the goal that should be achieved(i.e.the desiredfinal state of the system), and the set of possible actions that actors can perform,then the solution to the planning problem is the (not necessarily optimal)sequence of actions that allows the system to reach the desired state from the initial state.While casting the design process as a planning problem,the following question must be addressed: which are the“actions”in software design?In Tropos approach[2]when drawing the model of a system, the designer assigns goals to actors,defines delegations of goals from one actor to another,and identifies appropriate goal refinements among the predefined alternative refinements.Such actions will be used by a planner tofind a way to fulfill the goals of the system actors.Planning approach requires a specification language to represent the planning domain and the states of the system and its environment.Different types of logic could be applied for this purpose,e.g.first order logic is often used to describe the planning domain with conjunctions of literals specifying the states of the system.The language for planning domain description should provide support for specifying:–the initial state of the system;–the goal of the planning problem;–the description of actions;–the axioms of background theory.To describe the initial state of the system,actors’and goal properties,and social relations among actors should be specified.We propose to represent initial state in terms of predicates that correspond to –the possible ways of goal decomposition;–actors’capabilities and desires to achieve a goal;–possible delegation relations among actors.Automating Software Design:Exploring and Evaluating Design Alternatives7 The desired state of the system(or goal of the planning problem)is described through the conjunction of predicates derived from the description of actors’desires in the initial state.Essentially,for each desired goal a predicate is added to the goal of the planning problem.An action represents a temporal activity to accomplish an objective.The behavior of an actor can be formalized by the following actions he can perform.Goal satisfaction.An actor can satisfy a goal only if achieving this goal is among his desires and he can actually satisfy it.The effect of this action is the fulfillment of the goal.Goal delegation.An actor may have not enough capabilities to achieve his goals by himself,and so he has to delegate their satisfaction to other actors.This passage of responsibilities is performed only if the delegator wants a goal to be achieved and can depend on the delegatee to achieve it.The effect of this action is that the delegator does not worry any more about the satisfaction of the goal,while the delegatee takes the responsibility for the fulfillment of the goal and so it becomes his own desire to achieve it.The delegator does not care how the delegatee satisfies the goal(e.g.by his own capabilities or by further delegation),it is up to the delegatee to decide it.AND/OR goal decomposition.As in different goal-oriented modeling frameworks(e.g.as in Tropos and KAOS)two types of goal refinement are supported:OR-decomposition,which suggests the list of alternative ways to satisfy the goal,and AND-decomposition,which refines the goals into subgoals which all are to be satisfied in order to satisfy the initial goal.An actor can decompose a goal only if he wants it to be satisfied,and only in the way which is predefined in the initial state of the system.The effect of decomposition is that the actor who refines the goal focuses on the fulfillment of subgoals instead of the initial goal.It is assumed that different actors can decompose the same goal in different ways.In addition to actions,axioms of the planning domain can be defined.These are rules that hold in every state of the system and are used to complete the description of the current state.For example,to propagate goals properties along goal refinement the following axiom is used:a goal is satisfied if all its AND-subgoals or at least one of the OR-subgoals are satisfied.The proposed formalization of the design-as-planning-problem should be viewed as a starting point of our research.We foresee that the evaluation of the proposed approach on the basis of real case studies may cause the refinement and further development of the formalization.Applying planning.The next step,after the design problem is formalized,is to choose the”right planner”among off-the-shelves tools available.In the last years many planners have been proposed[18]. In order to choose one of them the following requirements are considered:–The planner should not produce redundant plans.Under non-redundant plan we mean that,by deleting an arbitrary action of the plan,the resulting plan is no more a“valid”plan(i.e.it does not allow to reach the desired state from the initial state).–The planner should use PDDL(Planning Domain Definition Language)since it is becoming a”stan-dard”planning language and many research groups work on its implementation.–The language should support a number of”advanced”features(e.g.derived predicates)that are essential for implementing our planning domain,i.e.it should be at least PDDL2.2.Thefirst requirement is concerned with the optimality of the generated design decisions.We argue that it is not necessary to focus on the optimal design:human designers do not prove that their design is optimal,why should a system do it?Instead,in our framework the plan is required to be non-redundant, which guarantees at least the absence of alternative delegation paths since a plan does not contain any redundant actions.The situation in which no solution can be found by the planner might be caused either by an error in the requirements,or by the lack of capabilities the human and software system actors were ascribed. At this point the designer needs tofind the way to relax the initial constraints,i.e.to revise actors’desires and capabilities,and possible social dependencies.The problem with our approach is that the planner does not usually provide the point where failure occurred.Thus,our goal is to interfere into the。