Integrating Models of Human-Computer Visual Interaction

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仿真算法知识点总结

仿真算法知识点总结

仿真算法知识点总结一、简介仿真算法是一种通过生成模型和运行模拟来研究系统或过程的方法。

它是一种用计算机模拟真实世界事件的技术,可以用来解决各种问题,包括工程、商业和科学领域的问题。

仿真算法可以帮助研究人员更好地理解系统的行为,并预测系统未来的发展趋势。

本文将对仿真算法的基本原理、常用技术和应用领域进行总结,以期帮助读者更好地了解和应用仿真算法。

二、基本原理1. 离散事件仿真(DES)离散事件仿真是一种基于离散时间系统的仿真技术。

在离散事件仿真中,系统中的事件和状态都是离散的,而时间是连续变化的。

离散事件仿真通常用于建模和分析复杂系统,例如生产线、通信网络和交通系统等。

离散事件仿真模型可以用于分析系统的性能、验证系统的设计和决策支持等方面。

2. 连续仿真(CS)连续仿真是一种基于连续时间系统的仿真技术。

在连续仿真中,系统中的状态和事件都是连续的,而时间也是连续的。

连续仿真通常用于建模和分析动态系统,例如电力系统、控制系统和生态系统等。

连续仿真模型可以用于分析系统的稳定性、动态特性和系统参数的设计等方面。

3. 混合仿真(HS)混合仿真是一种同时兼具离散事件仿真和连续仿真特点的仿真技术。

混合仿真可以用于建模和分析同时包含离散和连续过程的系统,例如混合生产系统、供应链系统和环境系统等。

混合仿真模型可以用于分析系统的整体性能、协调离散和连续过程以及系统的优化设计等方面。

4. 随机仿真随机仿真是一种基于概率分布的仿真技术。

在随机仿真中,系统的状态和事件都是随机的,而时间也是随机的。

随机仿真通常用于建模和分析具有随机性质的系统,例如金融系统、天气系统和生物系统等。

随机仿真模型可以用于分析系统的风险、概率特性和对策选择等方面。

5. Agent-Based ModelingAgent-based modeling (ABM) is a simulation technique that focuses on simulating the actions and interactions of autonomous agents within a system. This approach is often used for modeling complex and decentralized systems, such as social networks, biologicalecosystems, and market economies. In ABM, individual agents are modeled with their own sets of rules, behaviors, and decision-making processes, and their interactions with other agents and the environment are simulated over time. ABM can be used to study the emergent behavior and dynamics of complex systems, and to explore the effects of different agent behaviors and interactions on system-level outcomes.三、常用技术1. Monte Carlo方法蒙特卡洛方法是一种基于随机模拟的数值计算技术。

Geometric Modeling

Geometric Modeling

Geometric ModelingGeometric modeling is a fundamental concept in computer graphics and design, playing a crucial role in various industries such as architecture, engineering, and entertainment. It involves creating digital representations of physical objects or environments using mathematical and computational techniques. Geometric modeling allows designers and engineers to visualize, analyze, and manipulate complex shapes and structures, leading to the development of innovative products and solutions. However, it also presents several challenges and limitations that need to be addressed to ensure its effectiveness and efficiency. One of the key challenges in geometric modeling is the accurate representation of real-world objects and environments. This requires the use of advanced mathematical algorithms and computational methods to capture the intricate details and complexities of physical entities. For example, creating a realistic 3D model of a human face or a natural landscape involves precise measurements, surface calculations, and texture mapping to achieve a lifelike appearance. This level of accuracy is essential in industries such as animation, virtual reality, and simulation, where visual realism is critical for creating immersive experiences. Another challenge in geometric modeling is the efficient manipulation and editing of geometric shapes. Designers and engineers often need to modify existing models or create new ones to meet specific requirements or constraints. This process can be time-consuming and labor-intensive, especially when dealing with large-scale or highly detailed models. As a result, there is a constant demand for more intuitive and user-friendly modeling tools that streamline the design process and enhance productivity. Additionally, the interoperability of geometric models across different software platforms and systems is a persistent issue that hinders seamless collaboration and data exchange. Moreover, geometric modeling also faces challenges in terms of computational resources and performance. Generating and rendering complex 3D models requires significant computing power and memory, which can limit the scalability and accessibility of geometric modeling applications. High-resolution models with intricate geometries may strain hardware capabilities and lead to slow processing times, making it difficult for designers and engineers to work efficiently. This is particularly relevant in industries such as gamingand virtual reality, where real-time rendering and interactive simulations are essential for delivering engaging and immersive experiences. Despite these challenges, geometric modeling continues to evolve and advance through technological innovations and research efforts. The development of advanced modeling techniques such as parametric modeling, procedural modeling, and non-uniform rational B-spline (NURBS) modeling has significantly improved the accuracy and flexibility of geometric representations. These techniques enable designersand engineers to create complex shapes and surfaces with greater precision and control, paving the way for more sophisticated and realistic virtual environments. Furthermore, the integration of geometric modeling with other disciplines such as physics-based simulation, material science, and machine learning has expanded its capabilities and applications. This interdisciplinary approach allows for the creation of interactive and dynamic models that accurately simulate physical behaviors and interactions, leading to more realistic and immersive experiences. For example, in the field of architecture and construction, geometric modeling combined with structural analysis and environmental simulation enables the design and evaluation of sustainable and resilient buildings and infrastructure. In conclusion, while geometric modeling presents several challenges and limitations, it remains an indispensable tool for innovation and creativity in various industries. The ongoing advancements in geometric modeling techniques and technologies continue to push the boundaries of what is possible, enabling designers and engineers to create increasingly realistic and complex digital representations of the physical world. As computational power and software capabilities continue to improve, the future of geometric modeling holds great promise for revolutionizing the way we design, visualize, and interact with the world around us.。

Advanced Mathematical Modeling Techniques

Advanced Mathematical Modeling Techniques

Advanced Mathematical ModelingTechniquesIn the realm of scientific inquiry and problem-solving, the application of advanced mathematical modeling techniques stands as a beacon of innovation and precision. From predicting the behavior of complex systems to optimizing processes in various fields, these techniques serve as invaluable tools for researchers, engineers, and decision-makers alike. In this discourse, we delve into the intricacies of advanced mathematical modeling techniques, exploring their principles, applications, and significance in modern society.At the core of advanced mathematical modeling lies the fusion of mathematical theory with computational algorithms, enabling the representation and analysis of intricate real-world phenomena. One of the fundamental techniques embraced in this domain is differential equations, serving as the mathematical language for describing change and dynamical systems. Whether in physics, engineering, biology, or economics, differential equations offer a powerful framework for understanding the evolution of variables over time. From classical ordinary differential equations (ODEs) to their more complex counterparts, such as partial differential equations (PDEs), researchers leverage these tools to unravel the dynamics of phenomena ranging from population growth to fluid flow.Beyond differential equations, advanced mathematical modeling encompasses a plethora of techniques tailored to specific applications. Among these, optimization theory emerges as a cornerstone, providing methodologies to identify optimal solutions amidst a multitude of possible choices. Whether in logistics, finance, or engineering design, optimization techniques enable the efficient allocation of resources, the maximization of profits, or the minimization of costs. From linear programming to nonlinear optimization and evolutionary algorithms, these methods empower decision-makers to navigate complex decision landscapes and achieve desired outcomes.Furthermore, stochastic processes constitute another vital aspect of advanced mathematical modeling, accounting for randomness and uncertainty in real-world systems. From Markov chains to stochastic differential equations, these techniques capture the probabilistic nature of phenomena, offering insights into risk assessment, financial modeling, and dynamic systems subjected to random fluctuations. By integrating probabilistic elements into mathematical models, researchers gain a deeper understanding of uncertainty's impact on outcomes, facilitating informed decision-making and risk management strategies.The advent of computational power has revolutionized the landscape of advanced mathematical modeling, enabling the simulation and analysis of increasingly complex systems. Numerical methods play a pivotal role in this paradigm, providing algorithms for approximating solutions to mathematical problems that defy analytical treatment. Finite element methods, finite difference methods, and Monte Carlo simulations are but a few examples of numerical techniques employed to tackle problems spanning from structural analysis to option pricing. Through iterative computation and algorithmic refinement, these methods empower researchers to explore phenomena with unprecedented depth and accuracy.Moreover, the interdisciplinary nature of advanced mathematical modeling fosters synergies across diverse fields, catalyzing innovation and breakthroughs. Machine learning and data-driven modeling, for instance, have emerged as formidable allies in deciphering complex patterns and extracting insights from vast datasets. Whether in predictive modeling, pattern recognition, or decision support systems, machine learning algorithms leverage statistical techniques to uncover hidden structures and relationships, driving advancements in fields as diverse as healthcare, finance, and autonomous systems.The application domains of advanced mathematical modeling techniques are as diverse as they are far-reaching. In the realm of healthcare, mathematical models underpin epidemiological studies, aiding in the understanding and mitigation of infectious diseases. From compartmental models like the SIR model to agent-based simulations, these tools inform public health policies and intervention strategies, guiding efforts to combat pandemics and safeguard populations.In the domain of climate science, mathematical models serve as indispensable tools for understanding Earth's complex climate system and projecting future trends. Coupling atmospheric, oceanic, and cryospheric models, researchers simulate the dynamics of climate variables, offering insights into phenomena such as global warming, sea-level rise, and extreme weather events. By integrating observational data and physical principles, these models enhance our understanding of climate dynamics, informing mitigation and adaptation strategies to address the challenges of climate change.Furthermore, in the realm of finance, mathematical modeling techniques underpin the pricing of financial instruments, the management of investment portfolios, and the assessment of risk. From option pricing models rooted in stochastic calculus to portfolio optimization techniques grounded in optimization theory, these tools empower financial institutions to make informed decisions in a volatile and uncertain market environment. By quantifying risk and return profiles, mathematical models facilitate the allocation of capital, the hedging of riskexposures, and the management of investment strategies, thereby contributing to financial stability and resilience.In conclusion, advanced mathematical modeling techniques represent a cornerstone of modern science and engineering, providing powerful tools for understanding, predicting, and optimizing complex systems. From differential equations to optimization theory, from stochastic processes to machine learning, these techniques enable researchers and practitioners to tackle a myriad of challenges across diverse domains. As computational capabilities continue to advance and interdisciplinary collaborations flourish, the potential for innovation and discovery in the realm of mathematical modeling knows no bounds. By harnessing the power of mathematics, computation, and data, we embark on a journey of exploration and insight, unraveling the mysteries of the universe and shaping the world of tomorrow.。

非遗与现代科技结合英语作文

非遗与现代科技结合英语作文

非遗与现代科技结合英语作文The Fusion of Intangible Cultural Heritage and Modern TechnologyIn today's rapidly evolving world, the preservation and promotion of intangible cultural heritage (ICH) have become increasingly crucial. As globalization continues to shape our societies, the unique traditions, practices, and knowledge passed down through generations face the risk of being overshadowed by the relentless march of modernity. However, a remarkable synergy has emerged, wherein the integration of modern technology and ICH has created a powerful platform for safeguarding and revitalizing these precious cultural assets.One of the most remarkable examples of this fusion can be seen in the realm of digital preservation. Through the use of cutting-edge technologies, ICH elements that were once confined to oral traditions or physical artifacts can now be meticulously documented, archived, and shared with global audiences. High-resolution scanning, 3D modeling, and virtual reality (VR) technologies have enabled the creation of immersive digital experiences that transport viewers into the heart of these cultural practices, allowing them to engage with the artistry, rituals, and narratives that define acommunity's identity.The digitization of ICH not only preserves its essence but also opens up new avenues for accessibility and dissemination. Online platforms and interactive digital archives have democratized the access to these cultural treasures, empowering individuals and communities worldwide to learn about, appreciate, and even participate in the traditions that were once restricted to specific geographic regions or social groups. This digital transformation has played a crucial role in bridging the gap between the past and the present, ensuring that the rich tapestry of human cultural diversity remains vibrant and accessible to future generations.Moreover, the integration of modern technology has also transformed the ways in which ICH is experienced and shared. Augmented reality (AR) applications have enabled the seamless overlay of digital elements onto physical environments, allowing users to virtually interact with cultural artifacts, participate in rituals, or witness the creation of traditional crafts. This immersive approach not only enhances the educational and experiential value of ICH but also fosters a deeper understanding and appreciation among both local and global audiences.Beyond mere preservation and dissemination, the fusion of ICH and technology has also unlocked new opportunities for culturalrevitalization and innovation. By incorporating digital tools and platforms, traditional artisans and practitioners have been able to expand the reach of their crafts, connecting with wider markets and collaborating with designers, technologists, and entrepreneurs to create novel products and experiences. This cross-pollination of ideas and techniques has led to the emergence of hybrid forms that blend the timeless essence of ICH with the dynamism of contemporary design and technology.One compelling example is the integration of traditional textile weaving techniques with digital fabrication methods, such as 3D printing and laser cutting. By merging the intricate manual skills of weavers with the precision and versatility of digital tools, artisans have been able to create innovative textiles and garments that retain the cultural significance of their crafts while adapting to modern aesthetic preferences and functional requirements. This symbiotic relationship between the traditional and the technological has not only preserved the artisanal legacy but also inspired new avenues for creative expression and commercial viability.Similarly, the application of interactive technologies, such as touchscreen displays and motion-sensing interfaces, has transformed the way in which visitors engage with cultural heritage sites and artifacts. By seamlessly integrating digital elements into physical spaces, these hybrid experiences have the power to captivate andeducate audiences, fostering a deeper understanding and appreciation of the rich narratives that underpin these cultural treasures.The fusion of ICH and modern technology also holds immense potential for community empowerment and sustainable development. By leveraging digital platforms and tools, local communities can actively participate in the documentation, preservation, and dissemination of their cultural heritage, ensuring that their voices and perspectives are central to the process. This collaborative approach not only safeguards the authenticity and integrity of ICH but also empowers marginalized communities to assert their cultural identity and gain economic opportunities through the commercialization of their traditional skills and products.Furthermore, the integration of technology in ICH-based enterprises and initiatives has the potential to drive sustainable development by fostering innovative business models, creating new job opportunities, and promoting environmentally responsible practices. For instance, the digital promotion and online distribution of artisanal products can reduce the carbon footprint associated with physical transportation, while the use of renewable materials and energy-efficient technologies in production processes can contribute to a more sustainable future.In conclusion, the convergence of intangible cultural heritage and modern technology has ushered in a transformative era, one that holds immense promise for the preservation, revitalization, and celebration of our shared cultural tapestry. By seamlessly integrating digital tools and platforms into the realm of ICH, we can not only safeguard the rich traditions and knowledge of the past but also empower communities, inspire innovation, and foster a more inclusive, sustainable, and culturally vibrant world. As we navigate the complexities of the 21st century, this synergy between the traditional and the technological stands as a testament to the resilience and adaptability of human cultural expression.。

多模态数据融合英语

多模态数据融合英语

多模态数据融合英语Multimodal Data Fusion: Bridging the Gap between Diverse Information Sources.In the era of big data, the amount of information available to us is growing exponentially. This information often comes in various forms, such as text, audio, video, and images, each carrying its unique set of features and contextual information. To effectively extract meaningful insights from this diverse range of data, multimodal data fusion has become a crucial technique.Multimodal data fusion, simply put, is the process of combining and integrating information from multiple modalities or sources to create a comprehensive representation. It allows us to leverage the complementary nature of different data types, enhancing our understanding and analysis capabilities.Importance of Multimodal Data Fusion.The importance of multimodal data fusion lies in its ability to overcome the limitations of single-modality data. For instance, text data may provide detailed descriptive information, but it lacks visual cues or emotional context. On the other hand, audio and video data can capture non-verbal cues and emotional expressions that are often lostin textual representations. By combining these modalities, we can gain a deeper understanding of the underlying phenomena.Multimodal data fusion is also crucial in scenarios where data from different sources is incomplete or noisy.By combining multiple modalities, we can often compensatefor the missing or unreliable information in one modality with the help of another. This fusion of information notonly improves the quality of data but also enhances the reliability of the derived insights.Techniques of Multimodal Data Fusion.There are several techniques used for multimodal datafusion, each with its own strengths and applications. Someof the commonly used techniques include:1. Feature-level Fusion: This approach involves combining the features extracted from different modalitiesat an early stage. It allows for the integration of complementary information from various sources, but it can be challenging to handle the different types of featuresand their associated semantic gaps.2. Decision-level Fusion: In this technique, decisionsor predictions made by individual modalities are combinedto form a final decision. This approach is often used in scenarios where the modalities are highly diverse or whenit's desirable to maintain the independence of individual modalities.3. Model-level Fusion: Here, multiple models trained on different modalities are combined to create a unified model. This approach leverages the strengths of each model, enabling it to capture a broader range of information. However, it can be computationally expensive and requirescareful consideration of model complexity andgeneralization capabilities.Applications of Multimodal Data Fusion.Multimodal data fusion finds applications in various domains, including:1. Human-Computer Interaction (HCI): In HCI, multimodal data fusion enables computers to understand and respond to a wide range of user inputs, including voice, gesture, and facial expressions. This integration of multiple input modalities improves the naturalness and efficiency of human-computer interactions.2. Multimedia Processing: In the field of multimedia processing, multimodal data fusion is used to analyze and understand complex multimedia content, such as movies, TV shows, and advertisements. By combining audio, video, and textual information, we can gain insights into the emotional content, narrative structure, and semantic meaning of these multimedia pieces.3. Sentiment Analysis: Sentiment analysis aims to determine the emotional sentiment behind textual or spoken content. By combining textual data with audio and video modalities, such as facial expressions and tone of voice, we can more accurately capture the emotional context and sentiment behind the communication.Challenges and Future Directions.Despite its promise and widespread applications, multimodal data fusion faces several challenges. One of the key challenges is dealing with the semantic gap, which arises due to the inherent differences in the representations and interpretations of information across different modalities. Addressing this gap requires sophisticated fusion techniques that can effectively bridge the semantic differences.Another challenge lies in handling the complexity and diversity of real-world data. In many scenarios, the available data may be noisy, incomplete, or inconsistent,making it difficult to extract meaningful insights. Future research needs to focus on developing robust fusion methods that can handle such challenges and extract reliable information from diverse data sources.Moreover, with the increasing volume and velocity of data, efficient and scalable fusion techniques are needed. Current fusion methods may not be able to handle the large-scale data efficiently, necessitating the development of new algorithms and frameworks that can handle the computational demands of multimodal data fusion.In conclusion, multimodal data fusion represents a powerful tool for整合不同来源的信息,提升我们对复杂现象的理解和分析能力。

2000 英语2 阅读text3

2000 英语2 阅读text3

2000 英语2 阅读text3全文共3篇示例,供读者参考篇1Title: The Influence of Technology on SocietyIn today's modern world, technology has become an integral part of our everyday lives. From smartphones to social media to artificial intelligence, technology has revolutionized the way we communicate, work, and live. However, as our reliance on technology continues to grow, it is important to consider the impact that it has on society as a whole.One of the most significant ways in which technology has influenced society is through communication. With the advent of smartphones and social media platforms, we are now able to connect with people from all around the world instantly. This has made communication more efficient and convenient, but it has also raised concerns about privacy and security. Our personal information is now more vulnerable to hacking and misuse, leading to potential risks for individuals and organizations.Furthermore, the rise of automation and artificial intelligence has transformed the way we work. Many routine tasks that wereonce performed by humans are now being automated, leading to increased efficiency and productivity. However, this has also resulted in job displacement and a growing digital divide between those who have the skills to adapt to new technologies and those who do not. It is important for society to address these issues and find ways to ensure that technology benefits everyone, not just a select few.Moreover, technology has also had a profound impact on our daily lives. From shopping online to streaming movies to using virtual reality, technology has made our lives more convenient and enjoyable. However, this constant connection to technology has also led to concerns about addiction and mental health. Many people now spend hours each day staring at screens, which can have negative effects on their physical and mental well-being. It is crucial for society to find a balance between using technology for our benefit and knowing when to disconnect and engage in real-world interactions.In conclusion, technology has had a profound influence on society in both positive and negative ways. While it has improved communication, efficiency, and convenience, it has also raised concerns about privacy, job displacement, addiction, and mental health. It is important for society to address these issues and findways to use technology responsibly and ethically. By doing so, we can ensure that technology continues to benefit society and improve our lives for the better.篇2The article titled "Text3: The Benefits of Traveling Abroad" explores the advantages of traveling to different countries, learning about new cultures, and experiencing new ways of life. The author discusses how traveling can broaden our horizons, improve our communication skills, and enhance our understanding of the world.One of the main benefits of traveling abroad is the opportunity to immerse ourselves in a different culture. By experiencing firsthand the customs, traditions, and lifestyles of other countries, we can gain a deeper appreciation for diversity and become more open-minded individuals. Traveling allows us to break out of our comfort zones and challenge our preconceived notions about the world.Additionally, traveling abroad can greatly improve our communication skills. When we visit a foreign country, we are forced to interact with people who may not speak the same language as us. This can help us develop patience, adaptability,and the ability to communicate effectively even in challenging situations. Furthermore, learning a new language or improving our language skills through immersion can greatly enhance our personal and professional opportunities.Another benefit of traveling abroad is the opportunity to expand our knowledge and understanding of the world. By visiting historical sites, museums, and cultural landmarks, we can learn about the rich history and heritage of different countries. This can help us gain a better understanding of global issues, build empathy for people from different backgrounds, and develop a more nuanced perspective on international affairs.Moreover, traveling abroad can have a positive impact on our personal growth and development. It can help us become more independent, self-reliant, and resilient individuals. By navigating unfamiliar environments, overcoming language barriers, and adapting to new situations, we can build our confidence and expand our comfort zones. Traveling can also provide us with valuable life experiences, memories, and connections that can enrich our lives in lasting ways.In conclusion, traveling abroad offers numerous benefits for personal, social, and professional growth. It can help us become more open-minded, improve our communication skills, expandour knowledge of the world, and facilitate our personal development. As we explore new countries, cultures, and experiences, we have the opportunity to gain valuable insights, broaden our perspectives, and become more well-rounded individuals. So pack your bags, book your tickets, and embark on a journey of discovery and self-discovery through traveling abroad.篇3Text 3 presents a comparison between two types of weather forecasting methods: numerical models and human forecasters. The text explores the advantages and limitations of each method, as well as the potential benefits of combining the two approaches.Numerical weather models are computer-generated simulations that use mathematical equations to predict future weather conditions based on current observations. These models are able to analyze vast amounts of data and provide detailed forecasts for specific locations. They are also able to predict weather patterns that human forecasters may not be able to detect.On the other hand, human forecasters rely on their expertise and experience to interpret weather patterns and make predictions. They are able to take into account factors that numerical models may not consider, such as local terrain and atmospheric conditions. Human forecasters are also able to communicate their forecasts in a more understandable and accessible way for the general public.Despite their strengths, both numerical models and human forecasters have limitations. Numerical models may be limited by inaccuracies in the data they rely on, as well as by the inherent complexity of weather systems. Human forecasters are subject to biases and errors in judgment, which can affect the accuracy of their predictions.However, there is potential for synergy between the two methods. By integrating numerical models with human expertise, forecasters can combine the strengths of both approaches to improve the accuracy and reliability of weather forecasts. For example, human forecasters can use their knowledge to evaluate and interpret the output of numerical models, identifying potential errors or inconsistencies.Overall, the text suggests that a combination of numerical models and human forecasters may be the most effectiveapproach to weather forecasting. By leveraging the strengths of both methods, forecasters can provide more accurate and reliable forecasts to the public, helping to mitigate the impact of severe weather events and improve overall preparedness.。

人工智能英语介绍ppt课件

人工智能英语介绍ppt课件
• Unsupervised Learning: Unsupervised learning algorithms are used to discover patterns or structures in unlabeled data Common unsupervised learning techniques include clustering, dimensionality reduction, and association rule learning
The field of AI has continued to grow quickly, with advantages in deep learning and other machine learning techniques leading to significant breakthroughs in areas such as image recognition, speech recognition, and natural language processing AI systems are now capable of performing complex tasks that were once thought to be the exclusive domain of humans
• Supervised Learning: Supervised learning algorithms are trained using labeled examples, such as input output pairs, and the goal is to generalize to new, unseen data Common supervised learning algorithms include linear regression, logistic regression, decision trees, and support vector machines

AEM 6.3 Forms Workbench 用户指南说明书

AEM 6.3 Forms Workbench 用户指南说明书

Workbench HelpAEM 6.3 FormsLegal noticesFor legal notices, see /en_US/legalnotices/index.html.Last updated 1/3/17ContentsAbout AEM Forms Workbench . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 About the user interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Views . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Editors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Preferences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Related software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Adobe Community Help Client (CHC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 What’s new in Workbench . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 New for Workbench . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Process designer enhancements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Looping in processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5Grouping in processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5 Automating legacy solutions upgrade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Archive Migration tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5Upgrade legacy processes and artifacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6 Dependency detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Visualizing dependencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6Asset renaming support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6 Timer enhancements to Event Behavior Configuration . . . . . . . . . . . . . . . . . . . 6 Workbench offline notifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Performance enhancements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Common variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Persisting XML form data with Data Models . . . . . . . . . . . . . . . . . . . . . . . . . 7 Integrating Data Models with Web Services . . . . . . . . . . . . . . . . . . . . . . . . . 7 Integrating Data Models with Data Services . . . . . . . . . . . . . . . . . . . . . . . . . 7 Building expressions with referred XSDs . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 iLeveraging legacy solutions in AEM forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 About the upgraded environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Review the AEM Forms run-time environment: . . . . . . . . . . . . . . . . . . . . . . . 9 Strategies for leveraging legacy solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Continued execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Maintenance of legacy items . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 To maintain legacy items: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 Progressive development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 To create AEM Forms assets from legacy items: . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 Importing resources, processes, and events to applications . . . . . . . . . . . . . . . . . . . .11 Importing multiple versions of a process . . . . . . . . . . . . . . . . . . . . . . . . . . .12 Importing from the run-time environment . . . . . . . . . . . . . . . . . . . . . . . . . .12 Import legacy items from the run-time environment: . . . . . . . . . . . . . . . . . . . . . . .12 Importing from the file system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13 Import from the file system: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13 Exporting files referenced by literal values . . . . . . . . . . . . . . . . . . . . . . . . . .14 Importing from AEM Forms 8.x archive files . . . . . . . . . . . . . . . . . . . . . . . . .14 Legacy LCA files that include service configurations . . . . . . . . . . . . . . . . . . . . . . . .14Import legacy items from AEM Forms archive files: . . . . . . . . . . . . . . . . . . . . . . . .15 Maintaining legacy run-time instances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15 Changing existing run-time instances . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15 Change legacy processes, events, and resources: . . . . . . . . . . . . . . . . . . . . . . . . . . . .16 Updating legacy solutions in other environments . . . . . . . . . . . . . . . . . . . . . .16 Selecting contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16Create an archive file: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17Update an archive file: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18 Upgrading legacy solutions to AEM forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19 Upgrading legacy artifacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19 Breaking the link to existing run-time instances . . . . . . . . . . . . . . . . . . . . . . .20 Remove the value of Deployment ID: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20 Creating endpoints for processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21 To add a start point: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21 Replacing legacy subprocesses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22 Replace legacy subprocesses: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22 Configuring security settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22 Using deprecated operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22 Exporting embedded documents from operation properties . . . . . . . . . . . . . . . .22 Export embedded documents: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 Changing the reliance on null value results from XPath expressions . . . . . . . . . . . .23 Upgrading human-centric processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 Replacing form-specific variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24Using legacy render and submit processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25Configuring Workspace start points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26Using the User 2.0 service . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28 Migrating LCAs to AEM Forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31 Updating references to assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32iiProcess services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32Using Workbench . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Before you begin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33 Process and form planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33 Assembling a development team . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33 Development process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34 Logging In to a AEM Forms Server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34 Logging in . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34 To log in to a server: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35 Increasing the memory allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35 Increase the allocated memory: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36 Configuring server connections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36 To configure a server: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36 Logging out . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37 To log out of a server: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37 User permissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38 Mutual authentication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38 Working with Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .39 About the Applications view . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .40 Developing applications in a multi-developer environment . . . . . . . . . . . . . . . .41 Synchronize the local version with the version in the repository . . . . . . . . . . . . . .41Checking in applications or assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41Checking out applications or assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42Discarding the changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43Viewing asset history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43Managing user access to applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43 Adding and removing applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44 Creating an application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44Adding applications from the server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45Removing applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45 Working with assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46 Adding and removing assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46Organizing assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49Editing and viewing assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .51Managing asset dependencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52 Applications and assets versioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53 Asset versions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53 Deploying applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54 Deploy an application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55Redeploy an application: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55Undeploy an application: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55 Moving applications into another environment . . . . . . . . . . . . . . . . . . . . . . .56 About archive files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .56Creating archive files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57 iiiAvoiding socket time-outs when creating archives . . . . . . . . . . . . . . . . . . . . . .60 Create archives asynchronously . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60 Creating Forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61 Create a form design using Workbench: . . . . . . . . . . . . . . . . . . . . . . . . . . . .62 Opening the Form Design perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62 Open the Form Design perspective: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62 Organizing your forms and assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63 Creating the form design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63 Create a form design: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64New Form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64Specify Form Data Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64Form Usage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65Opening Designer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67 Opening form designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67 Open a form design: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67Close a form design: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67 Saving the form design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .68 Where to find more information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .68 Creating XML Schemas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69 Create an XML schema . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69Edit an XML schema . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69 Managing Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70 Filtering resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70 Filter the resources in the Resources view: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70Ensuring that the PDF icon is displayed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71 Viewing resource relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71 View the resource relationships: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72Sort the list: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72 Working with file versions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72 Viewing the version history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72Using older versions of files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73 Setting access permissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73 About access permissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73Viewing and changing access permissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .74Adding access permissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75Adding different permissions to different subfolders . . . . . . . . . . . . . . . . . . . . . . . .76Removing access permissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77 Managing Components and Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77 Opening the Components view . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77 Installing components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78 To install a component: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78 Patching components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78 To patch a component: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78 Starting components and services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78 To start a component: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .79To start a service: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .79ivTo activate a service: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .79 Editing service configurations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .79 To edit a service configuration: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .79 Removing service configurations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80 To remove a service configuration: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80 Stopping components and services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80 To stop a component or service: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80 Deactivating services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80 To deactivate a service: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81 Uninstalling components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81 To uninstall a component: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81 Customizing Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81 Moving views . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81 Saving perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82 Restoring perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82 Getting started with process design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 About Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83 Opening the Process Design perspective . . . . . . . . . . . . . . . . . . . . . . . . . . .83 To open the Process Design perspective: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83 Process Design perspective views . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83 To open a view: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .84 Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .84 Process diagrams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .85 Process data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .86 Process input and output data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87 Process data model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87 Access to process data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .88 Process design guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .88 Order of implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .88 Process designs for reuse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .89 Reuse of variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .89 Process execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .90 Process instances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .90 Process modifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .90New processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .91 Process life cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .91 Short-lived processes and long-lived processes . . . . . . . . . . . . . . . . . . . . . . . .91 Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .91Client invocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .92Data persistence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .92Branch types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .93 Transaction Propagation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .93 Process diagram modeling examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .94 Sequential routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .94 vSynchronization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .95 Conditional routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .96 Simple merge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .96 Multi-choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .97 Gateway implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .97Event implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .98 Synchronizing merge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Implementation for a gateway multi-choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .100Implementation for an event multi-choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .100 Multi-merge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Loop counters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .103 Process completion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Multiple independent instances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Gateway implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .104Event implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .104 Multiple instances synchronization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Gateway implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .105Event implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .106Process Quick Starts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Recommended skills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Assigning tasks based on roles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Using form data with multiple forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Configuration when forms are similar . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Configuration when forms are not similar . . . . . . . . . . . . . . . . . . . . . . . . . 112 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 Assembling multiple documents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 Retrieving the DDX File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .115Assembling the document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .115 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Certifying policy-protected documents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 Throwing events to initiate processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121viUsing Barcode Data in Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Sending output to a printer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .128Batch Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .128Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .128Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .129 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Creating pre-filled and interactive PDF forms . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .131PDF Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .131Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .131Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .131 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Handling data submitted from a form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 Route Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .134Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .134Form Submission Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .134Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .135Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .135Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .135 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Applying usage rights to PDF documents using a watched folder . . . . . . . . . . . . . . . 136 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .137Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .138General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .138Server Configurations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .138Inputs/Outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .138 Other considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138Creating and managing processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 Creating processes using the New Process wizard . . . . . . . . . . . . . . . . . . . . . . . . 140 Create a process using the wizard: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Configuring the Workspace start point . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 Configure the Workspace start point: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .142 Configuring the Mobile start point (Deprecated) . . . . . . . . . . . . . . . . . . . . . 143 Configure the Mobile start point (Deprecated): . . . . . . . . . . . . . . . . . . . . . . . . . . .144 Configuring the Email start point . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Configure the Email start point: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .145 Configuring the Watched Folder start point . . . . . . . . . . . . . . . . . . . . . . . . 145 vii。

人工智能时代人文学科的重要性英语作文

人工智能时代人文学科的重要性英语作文

人工智能时代人文学科的重要性英语作文The Importance of Humanities in the Era of Artificial Intelligence。

In the era of artificial intelligence, the importance of humanities cannot be overstated. While the development of AI brings about numerous advancements and opportunities, it also presents challenges and ethical considerations that require a deep understanding of human values and perspectives. This is where the humanities come into play, providing critical insights and fostering a well-rounded approach to the integration of AI in our society.Firstly, the humanities help us understand the impact of AI on human society. As AI technologies continue to advance, they have the potential to reshape various aspects of our lives, including education, healthcare, and employment. However, the integration of AI must be done with caution and consideration for its social implications. By studying the humanities, we gain a deeper understanding of the historical, cultural, and ethical contexts in which AI operates, allowing us to make informed decisions about its implementation.Moreover, the humanities foster critical thinking and ethical reasoning, which are essential in navigating the ethical challenges posed by AI. As AI systems become increasingly autonomous, questions of accountability, bias, and privacy arise. Humanities disciplines such as philosophy, ethics, and law provide frameworks for addressing these concerns. They encourage us to ask important questions about the impact of AI on human rights, fairness, and social justice. By engaging with these disciplines, we can ensure that AI is developed and used in a way that aligns with our moral values.Furthermore, the humanities emphasize the importance of empathy and human connection. While AI can enhance efficiency and productivity, it cannot replace the human experience. The study of literature, art, and history reminds us of the richness and complexity of human emotions, relationships, and experiences. By incorporating the humanities into the development of AI, we can ensure that technology is designed toenhance human well-being and foster meaningful connections, rather than alienating or dehumanizing individuals.In addition, the humanities provide a unique perspective on the potential risks and limitations of AI. While AI has the capacity to revolutionize industries and improve lives, it also raises concerns about job displacement, inequality, and the concentration of power. By studying the humanities, we can critically evaluate the long-term implications of AI and develop strategies to mitigate these risks. This includes exploring alternative economic models, ensuring equitable access to AI technologies, and promoting transparency and accountability in AI decision-making processes.In conclusion, the humanities play a crucial role in the era of artificial intelligence. They provide us with the necessary tools to understand the social, ethical, and cultural implications of AI, foster critical thinking and ethical reasoning, emphasize the importance of human connection, and assess the risks and limitations of AI. By integrating the humanities into AI development and decision-making processes, we can ensure that technology serves humanity's best interests and contributes to a more inclusive and sustainable future.。

智能机器会让人的大脑变懒吗英语作文

智能机器会让人的大脑变懒吗英语作文

智能机器会让人的大脑变懒吗英语作文全文共5篇示例,供读者参考篇1Will AI Make Our Brains Lazy?Hi there! My name is Tommy and I'm going to write about artificial intelligence (AI) and if it will make our brains lazy. AI is really cool technology where computers can think and learn just like humans! But some people worry that if we rely on AI too much, our brains won't have to work as hard. Let me tell you what I think.First off, what even is AI? Well, it's computers and robots that can do smart things like understand language, see patterns, make decisions and even create stuff! Instead of just following a set of instructions, AI can figure things out on its own using mathematics and lots of data. Wild, right?AI is being used for all sorts of stuff already. Virtual assistants like Siri and Alexa use AI to understand our voices and help with tasks. Self-driving cars use AI to sense their surroundings and navigate safely. And AI algorithms give us movierecommendations and filter spam emails. Pretty neat if you ask me!But the really amazing AI is stuff like language models that can write whole essays or computer programs after just getting a basic prompt. Or AI artists that can create photorealistic images just from a text description. It's almost like magic! No wonder some people think AI will make us lazier and dumber if we become overly dependent on it.I can kinda see their point. If an AI could just do all my homework and writing for me, why would I need to use my brain at all? And what if AI gets so good that it makes most human jobs obsolete? We'd have nothing to do but veg out all day while the robots do everything. Yikes, talk about lazy!However, I don't think AI will актуалли make our brains dumber and lazier. In fact, I think it will be just the opposite! Let me explain.For one thing, we already use tools and technology to help our brains all the time and no one says that makes us lazy. Calculators let us do math way faster, but no one calls them a "crutch" that makes us worse at arithmetic. Search engines give us access to all human knowledge in an instant, yet they inspire us to be more curious and learn more, not less.AI will be just another tool that enhances our capabilities rather than replaces them entirely. Sure, an AI could do your math homework for you. But wouldn't you still need to understand the concepts to use the AI properly and double check its work? AI may handle the drudgery, but critiquing its output and figuring out how to apply it would engage our brains just as much as before, if not more!AI could also unlock amazing new frontiers of creativity and discovery that actually make our minds work harder than ever. AI art tools don't just barf out finished artwork; they're a co-creative partner where the user has to finesse the prompts and provide direction to get desired results. And AI coding assistants don't just hand you finished programs; you have to understand theAI's suggestions and modify them intelligently based on your own knowledge and objectives.Instead of turning us into couch potatoes, I think AI will stretch our imaginations to their limits as we explore entirely new modes of work and expression through this technology. We'll have to learn whole new domains of knowledge just to keep up and make the most of AI's potential.Plus, AI will create so many new jobs and opportunities that we'd hardly have time to be lazy even if we wanted to! We'll needAI trainers to optimize these systems for different tasks. AI researchers to continue pushing the boundaries of what's possible. AI ethicists to ensure this tech develops responsibly. And workers across every field will have to upskill and rethink their roles to take advantage of AI augmentation.There's also something to be said for how AI could make certain intellectual activities more engaging and fun. Math exercises that adapt to your skill level and learning style inreal-time. Tutoring from an AI teacher who knows all the ways to explain a concept until you understand. AI assistants that turn things like writing and coding into more of a dialogue and collaboration rather than a solitary effort. If AI makes mental work more immersive and rewarding, we may find ourselves exercising our brains more from sheer enjoyment rather than out of a laborious obligation.So no, I don't think AI will reduce our intelligence to pure mush. Quite the opposite - I reckon it will spark an amazing renaissance of creativity, productivity, and human flourishing the likes of which we've never experienced! AI may do the grunt work for us, but it will also open up vast new horizons that will stretch our gray matter to its absolute limits.Of course, we'll have to be thoughtful about how we apply this technology. We shouldn't just blindly offload all thinking to the machines. And we'll need to work hard at integrating AI into our education and workforce so it genuinely augments human cognition rather than replaces it entirely.But as a young student, I'm really excited about growing up in an AI-powered future. The technology seems poised to unleash our potential rather than undermine it. So let's stop worrying about AI making us lazy and get cracking on putting these amazing tools to work! Our brains have their best days still ahead.篇2Will AI Make Our Brains Lazy?Hi everyone! Today I want to talk about something super cool but also a little bit scary – artificial intelligence (AI for short). AI is like really smart computer programs that can learn and think like humans. Pretty amazing, right? But some people are worried that AI might make our brains lazy because the machines can do so much for us. Let's explore this idea together!First off, what even is AI? Well, it's kind of like having a robot helper that can understand things, solve problems, and even getsmarter over time by learning from experience. Kinda like how you learn new stuff every day at school. AI programs can do incredible things like play games, answer questions, write stories, and even code other computer programs! Wild, huh?Some examples of AI you might have seen are smart assistants like Siri, Alexa or the Google Assistant. You can talk to them and ask them questions or tell them to do things for you. They use AI to try and understand what you're saying and give you a useful response. Another example is those chatbots some websites have to answer common customer questions. That's AI too!So why might some people think AI could make our brains lazy? Well, imagine if you had an AI assistant that was super smart and could do all your homework for you. You might be tempted to just let the AI do everything while you kick back and relax. After all, it's way easier than having to use your own brain power, right? But here's the thing – that would be super unhelpful for actually learning and growing your mind!The human brain is like a muscle. If you never use it or challenge it, it'll get weak and lazy over time. That's why doing hard work, like solving tough math problems or writing a big essay, actually helps strengthen your brain's thinking abilities. Itkeeps that muscle nice and strong! If you always let an AI do those kinds of hard tasks for you, your brain might get lazy and rusty.However, I don't think AI necessarily has to make us lazy. It all depends on how we use and interact with the AI. For example, an AI writing assistant could actually help exercize your brain in some ways. It might give you feedback to improve your writing, point out areas to expand on, and challenge you to be more clear and creative with your words and ideas. As long as you're still doing the hard work of writing and thinking yourself, the AI could be a useful tool to make you an even better writer and thinker.AI tutors could work the same way. Instead of just giving you all the answers, a good AI tutor would guide you and give you hints to figure things out on your own. It would push you to actively use your brain, not just passively absorb information. That way, you're developing your critical thinking abilities with the AI's help, rather than letting it do all the heavy lifting for you.Ultimately, I think AI will only make us lazy if we allow ourselves to become too dependent on it doing everything for us. We have to remember that AI is just a tool, like a calculator or search engine. It can make some tasks easier or faster, but itshouldn't replace us actually using our own mental muscles. As long as we keep actively learning, thinking critically, and challenging ourselves, AI can be an awesome assistant without making our brains go to mush!What's really cool is that as AI gets even smarter, we'll be able to use it in more creative ways to supercharge our brainpower. Maybe AI writing aids could help students brainstorm ideas they never would have thought of. Or AI coding tutors could guide kids through building amazing programs and games. Instead of making us lazy, AI could unlock our minds' full potential if we use it as a supportive tool, not a crutch.So in the end, I don't believe AI will inherently make our brains lazy. It's all about how we incorporate it into our lives. If we just use AI as an occasional shortcut for everything, then yeah, our thinking abilities might get rusty. But if we use AI as a learning buddy to take our skills to new heights, then our brains will stay healthy, active and super-powered! The key is keeping our minds engaged and using AI to enhance our abilities, not replace them entirely.What do you think? Are you excited about all the possibilities of AI? Or are you a little worried it might make humans too lazy and dependent? I'd love to hear your thoughts!Maybe you have some great ideas for how to use AI in a way that exercises our brains. AI is just getting started, so it's up to our generation to figure out how to use this powerful technology responsibly. Let's flex those thinking muscles!篇3Will Smart Machines Make Our Brains Lazy?Hi there! My name is Alex, and I'm a 5th grader. Today I want to tell you about something that's been on my mind a lot lately - smart machines and whether they might make our brains lazy.You've probably heard about artificial intelligence or AI. That's where scientists create super smart computer programs that can think and learn just like humans! AI is getting crazier and crazier these days. There are AI assistants that can answer almost any question, write stories and essays, code software programs, and even create images from just a text description!At first, I thought having AI do all this stuff for us would be so awesome. Like, why would I need to memorize stuff like the capitals of countries or how to spell crazy long words when an AI could just tell me? And instead of spending hours working on a writing assignment, I could get the AI to whip up an essay for me in no time flat!But then I started wondering - if we let AI do all the thinking and creating for us, will it make our own brains get lazy? After all, if you never practice things like spelling, math, or writing, you'll probably get rusty at them over time. It's like if you stopped exercising - eventually you'd get out of shape!Some grown-ups think letting AI take over all the mental work could make kids' brains get kinda flabby and make it harder for us to learn new things on our own. They say it might even hurt our creativity if we always lean on AI instead of using our own imaginations.On the other hand, other people argue that AI is just another tool, kind of like how calculators help us do complex math without tiring out our brains. As long as we still use our own thinking for lots of stuff, AI can actually make us smarter by taking over the boring mental tasks and giving our brains more free time to be creative!Personally, I go back and forth on this issue. I definitely see how AI could make us lazy if we abuse it and use it as a crutch for everything. But I also think it would be silly not to take advantage of such powerful thinking tools that could expand what we're capable of and free us up to focus on the fun, creative stuff.I think the key is finding a good balance. We should use AI to handle tedious tasks and look up simple facts, but we should still exercise our brains regularly by doing plenty of writing, problem-solving, analysis, and creative projects theold-fashioned way. That way, we get the best of both worlds - our brains stay in shape, but we also have awesome AI assistants to help us go even further!What do you think? Will you let AI make you lazy, or will you use it in a balanced way to boost your productivity while still giving your brain a workout? Let me know!Thanks for reading my essay. I know it's a pretty deep topic for a kid, but I think it's an important one as AI gets smarter and smarter. I'll leave you with one last thought - sure, AI might be super intelligent, but it can never replicate the awesomeness of an human kid's imagination...at least not yet! See ya!篇4Will AI Make Our Brains Lazy?Hi there! My name is Emma and I'm 10 years old. Today I want to talk to you about artificial intelligence (AI) and if it will make our brains lazy. It's a really interesting topic that a lot of smart people are talking about.First, let me explain what AI is. Basically, it refers to computers and robots that can think and learn kind of like humans. They can look at information, figure things out, and make decisions without being programmed for every single task. Some examples are virtual assistants like Siri and Alexa that can understand your voice and answer questions. Or self-driving cars that can see the road and navigate without a human driver.AI is getting smarter and smarter every day. Scientists and engineers are working hard to create AI systems that are more powerful than the human brain at certain tasks. Maybe one day AI will even be smarter than humans at everything!So will all this super smart AI cause our brains to get lazy and not think as much? I can see why some people might think that. With AI assistants to answer our questions, do our math for us, and remind us about our schedule, it could make us rely on them too much. We might stop using our own brains as much.Or what about AI that can read books and websites and summarize them for us? Or AI writing tools that can draft essays and stories? If the AI does most of the thinking for us, our brain muscles could get flabby from not exercising them enough.However, I don't think AI will make our brains totally lazy. I actually think it will exercise our brains in new and different ways!Just like how calculators didn't make our math brains lazy, I believe AI will be a tool that frees up our brains to think about other things.For example, with AI to handle routine tasks like scheduling appointments and answering simple questions, we can spend more of our brain power on creative thinking and solving hard problems. An AI could be like a super smart teacher's assistant who handles the boring busywork so the teacher (a human) can spend more time on the really engaging, thought-provoking lessons.AI could also make us smarter by helping feed information to our brains. We can learn things faster with AI tutors customizing the lessons for how we learn best. Or ask an AI to explain a complex topic in a way we can understand. Our brains will have to work hard to take in and make sense of all that new knowledge!Plus, as AI gets smarter, we'll have to get smarter at communicating with it, evaluating the information it gives us, and making sure it aligns with our human values and ethics. Keeping AI's powers in check and only using them for good purposes will take a lot of brainpower from us humans.Whenever a new invention comes along, some people worry it will make us lazy or replace us completely. But I think every new technology is an opportunity for humans to be lazier OR to use our amazing brains in new ways. It's up to us to choose!Take the internet and smartphones, for instance. Some people zombie out watching silly videos all day. But others use these tools to explore the world, create amazing things to share online, and connect with people across the globe. Their brains are working overtime!I think AI will be the same way. Yeah, maybe some people will just use it as a crutch and let their brains get out of shape. But I'm excited to see all the new ways we can flex our gray matter by using AI assistants to achieve more than we could on our own. AI plus human intelligence could be an unstoppable combination!Of course, we need to be careful with AI and make sure it doesn't go too far. We always have to be in control and ensure AI's only purpose is to help and empower humans, not replace us. As long as we're the ones calling the shots and deciding how to use AI, it can make our brains stronger, not lazier.I, for one, can't wait to see what awesome things my brain and future AI buddies can dream up together. The possibilitiesare endless when we combine the creativity, curiosity and consciousness of humans with the infinite knowledge and ultrafast processing power of AI. Bring it on!So in summary, I don't think we have to worry about AI making our brains lazy. If we use it the right way, AI can be like a brand new exercise machine for our minds. We just have to choose to put in the work and keep flexing those brilliant human brains of ours. What great things will your brain and AI create together? I can't wait to find out!篇5Will AI Make Our Brains Lazy?Hi there! My name is Jamie and I'm a 4th grader. Today I want to talk to you about something really cool but also a little bit scary - artificial intelligence (AI)! AI is like really smart computer programs that can do all sorts of amazing things like play games, answer questions, and even create art and music.Some grown-ups are worried that AI will make our brains lazy because the machines can do so much for us. But I don't think that's true at all! In fact, I think AI can actually make us smarter if we use it the right way. Let me explain...First of all, AI is super helpful for learning new things. Like when I'm stuck on a tough math problem, I can ask an AI tutoring program to walk me through step-by-step on how to solve it. Or if I'm writing a big report on dinosaurs, an AI can quickly give me all sorts of facts and information to get me started. With AI, I don't have to spend hours looking things up in books or websites - I can just ask the AI and it will tell me what I need to know.But here's the important part - the AI doesn't just give me the final answers. It shows me HOW to find the answers myself. It explains things in a way I can understand and lets me practice along the way. So I'm not just copying down facts, I'm actually learning and my brain is getting a workout!AI also makes learning way more fun. There are these cool AI language models that can storytell or rap or joke around with you. When I'm trying to learn new vocabulary words, I can make my AI teacher turn it into a silly story or song to help me remember. Or if I'm learning about history, the AI can create amazing virtual reality adventures to make me feel like I'm really there. It's like having the most entertaining tutor ever!And get this - some AI programs can even look at my homework and tests to figure out exactly what concepts I'mstruggling with. Then they can give my human teachers customized lessons and activities to help me in the areas I need to work on most. That's like getting a personal learning plan just for me!With all this AI help, you might be thinking - won't that make me just rely on the machines for everything? Won't my brain get lazy from not having to work as hard?No way! The AI is just a tool, like a calculator or encyclopedia book. It's there to support my learning, not do it all for me. I still have to put in the hard work of understanding ideas, making connections, solving problems, and building knowledge in my own noggin'. The AI doesn't make my brain lazy, it actually pushes me to think harder because it shows me new ways to approach tricky subjects.Plus, humans will always be needed to come up with creative ideas and decide how to use AI responsibly. We have imaginations and life experiences that no machine can ever fully copy.For example, a human inventor has to dream up the original concept for a new AI system in the first place! And humans like my parents and teachers have to make wise choices about how AI gets used in my education - what it should help with, what itshouldn't do, and how to keep me from just blindly trusting every AI output.So in the end, AI is just another tool that can help make my brain sharper and smarter, if I use it the right way alongside human wisdom and guidance. It's an awesome partner for learning, not something that makes me lazy!As long as I keep working hard, staying curious, and thinking for myself, AI isn't going to make my brain lazy at all. In fact, I'm excited for an amazing future where kids like me can use AI to become the smartest, most creative humans yet!What do you think? Are you also excited about the possibilities of AI in education? I'd love to hear your thoughts!。

人工智能专用名词

人工智能专用名词

人工智能专用名词1. 机器学习 (Machine Learning)2. 深度学习 (Deep Learning)3. 神经网络 (Neural Network)4. 自然语言处理 (Natural Language Processing)5. 计算机视觉 (Computer Vision)6. 强化学习 (Reinforcement Learning)7. 数据挖掘 (Data Mining)8. 数据预处理 (Data Preprocessing)9. 特征工程 (Feature Engineering)10. 模型训练 (Model Training)11. 模型评估 (Model Evaluation)12. 监督学习 (Supervised Learning)13. 无监督学习 (Unsupervised Learning)14. 半监督学习 (Semi-Supervised Learning)15. 迁移学习 (Transfer Learning)16. 生成对抗网络 (Generative Adversarial Networks, GANs)17. 强化学习 (Reinforcement Learning)18. 聚类 (Clustering)19. 分类 (Classification)20. 回归 (Regression)21. 泛化能力 (Generalization)22. 正则化 (Regularization)23. 自动编码器 (Autoencoder)24. 支持向量机 (Support Vector Machine, SVM)25. 随机森林 (Random Forest)26. 梯度下降 (Gradient Descent)27. 前向传播 (Forward Propagation)28. 反向传播 (Backpropagation)29. 混淆矩阵 (Confusion Matrix)30. ROC曲线 (Receiver Operating Characteristic Curve, ROC Curve)31. AUC指标 (Area Under Curve, AUC)32. 噪声 (Noise)33. 过拟合 (Overfitting)34. 欠拟合 (Underfitting)35. 超参数 (Hyperparameters)36. 网格搜索 (Grid Search)37. 交叉验证 (Cross Validation)38. 降维 (Dimensionality Reduction)39. 卷积神经网络 (Convolutional Neural Network, CNN)40. 循环神经网络 (Recurrent Neural Network, RNN)。

计算机技术与人工智能的深度融合研究

计算机技术与人工智能的深度融合研究

I G I T C W产业 观察Industry Observation172DIGITCW2023.11在现代科技研究广度和深度的有效拓展下,计算机技术的应用范围不断扩大,为人类文明发展和社会进步提供了强劲推动力,构建了高效的计算机思维。

人工智能和计算机技术的深度融合使二者的优势得到了最大化拓展,为现代科技和工业建设提供了持久动力。

1 人工智能技术概述1.1 人工智能的概念人工智能是指计算机系统通过模拟人类智能、推理、学习、理解和创造等能力,实现自主决策和执行任务的能力。

它是计算机科学中的一个重要研究领域,也是未来科技发展的重要方向。

作为计算机科学的一个重要分支,人工智能融合了信息、语言、哲学等多项学科内容,在计算机思维支撑下,体现出了极高的学习、记忆优势,能结合相关指令,深层挖掘数据信息。

在现阶段发展中,人工智能的核心技术包括机器学习、深度学习、自然语言处理、计算机视觉、智能控制等,其中,机器学习是一种通过数据和算法,让计算机自主学习的技术;深度学习是机器学习的一个重要分支,它能通过多层神经网络,实现对大量数据的自动分析和处理;自然语言处理则能让计算机理解和生成自然语言,并将智能对话和交互变为可能。

人工智能技术旨在研究如何让计算机具备思考、学习、推理、理解自然语言等能力,通过与计算机技术的深度融合,实现智能化应用系统的不断挖掘。

1.2 人工智能的特点人工智能是以计算机技术为基础的新型科学技术,通过深度发展和研究,能够模拟人类思维、推计算机技术与人工智能的深度融合研究赵 严(太原学院,山西 太原 030000)摘要:随着国际竞争局势日趋白热化,竞争方向的转变与现代科技更新换代速度的提升,使得计算机技术与人工智能的深度融合显得更加紧迫。

这种融合不仅成为了大势所趋,也成为推动科技创新与持续发展不可或缺的因素。

人工智能的特点和计算机技术的广泛应用为其融合提供了得天独厚的优势,能够促进智能服务业务的发展,实现科技向生产力的快速转化。

英语演讲中英文版:开幕式上的致辞

英语演讲中英文版:开幕式上的致辞

英语演讲中英文版:开幕式上的致辞女士们、先生们,Ladies and Gentlemen,人人得享人权,这是中国政府和人民不懈奋斗的目标。

新中国成立以来,中国人民在中国共产党的领导下,上下求索,创造了人类历史上的发展奇迹,开辟了现代化的东方路径。

Human rights for all is what the Chinese government and people have been striving for. Since the founding of the People’s Republic of China, under the leadership of the CPC and through unremitting efforts, the Chinese people have scored unprecedented achievements in human history and blazed an oriental pathway toward modernization.中国解决了13亿多人的温饱,减少了8亿多贫困人口,为7.7亿人提供了就业,建成世界最大规模的教育体系、最大规模的社保体系、最大规模的基层民主选举体系,谱写了中国人权进步的历史篇章,拓宽了国际人权保障的现实方案。

China has managed to meet the basic living needs of its 1.3 billion-plus people, lifted more than 800 million people out of poverty, and created 770 million jobs. We have put in place the world’s largest education system, social welfare system and community-level democratic election system, making historic progress in human rights development in China. China’s endeavors have also provided new viable solutions to challenges in the protection of human rights worldwide.中国的实践表明:人权保障并非只有一种途径,各国都可以根据自己的国情和人民需要,找到适合自己的人权保障模式。

关于ai改变我们的生活的英语作文

关于ai改变我们的生活的英语作文

关于ai改变我们的生活的英语作文Artificial Intelligence: Shaping the Future of Our LivesArtificial Intelligence (AI) has been a subject of fascination and speculation for decades, and its impact on our lives has become increasingly profound. As technology continues to advance at a rapid pace, AI has emerged as a transformative force, reshaping the way we live, work, and interact with the world around us.One of the most significant ways in which AI has transformed our lives is in the realm of personal assistants. Virtual assistants like Siri, Alexa, and Google Assistant have become ubiquitous, seamlessly integrating into our daily routines. These AI-powered helpers can perform a wide range of tasks, from setting reminders and managing our schedules to providing weather forecasts and controlling our smart home devices. With a simple voice command, we can access a wealth of information and automate various aspects of our lives, freeing up time and mental energy for other pursuits.Moreover, AI has revolutionized the way we consume and interact with content. Platforms like Netflix, Spotify, and Amazon utilize AI algorithms to provide personalized recommendations, anticipatingour preferences and suggesting content that aligns with our tastes. This personalization not only enhances our entertainment experience but also exposes us to a diverse array of content that we might not have discovered otherwise. AI-powered search engines, like Google and Bing, have also transformed the way we access and navigate information, delivering highly relevant and tailored results to our queries.In the realm of healthcare, AI has emerged as a powerful tool, revolutionizing the way we approach medical diagnosis and treatment. AI-powered algorithms can analyze vast amounts of medical data, identifying patterns and anomalies that might be overlooked by human clinicians. This has led to more accurate and timely diagnoses, enabling early intervention and improved patient outcomes. Additionally, AI-driven robotics and automation have enhanced surgical precision, reduced recovery times, and improved the overall quality of healthcare delivery.The impact of AI extends beyond our personal lives and into the professional realm as well. In the workplace, AI is automating mundane and repetitive tasks, freeing up employees to focus on more strategic and creative work. AI-powered chatbots and virtual assistants are handling customer inquiries and providing 24/7 support, improving efficiency and customer satisfaction. Furthermore, AI-driven analytics and predictive models are enabling businesses tomake data-driven decisions, optimize operations, and gain a competitive edge in their respective industries.As AI continues to evolve, it is also transforming the way we learn and educate ourselves. Adaptive learning platforms powered by AI can personalize the educational experience, adjusting the pace and content to the individual needs of each student. AI-powered tutoring systems and virtual classrooms are making education more accessible and inclusive, particularly in underserved communities. Moreover, AI is being used to grade assignments, provide feedback, and identify areas where students may need additional support, enhancing the overall educational experience.However, the rise of AI has also raised important ethical and societal concerns. Issues around data privacy, algorithmic bias, and the potential displacement of human labor have become the subject of ongoing debates and policy discussions. As we embrace the benefits of AI, it is crucial that we also address these challenges and ensure that the development and deployment of AI systems are guided by ethical principles and responsible governance.In conclusion, the impact of AI on our lives is undeniable. From personal assistants to healthcare, from the workplace to education, AI has transformed the way we live, work, and learn. As we continue to harness the power of AI, it is essential that we do so in athoughtful and responsible manner, ensuring that the benefits of this technology are equitably distributed and that its potential pitfalls are mitigated. The future that AI is shaping is one of great promise, but it is up to us, as a society, to ensure that it is a future that aligns with our values and serves the greater good.。

ai科技的英语作文

ai科技的英语作文

ai科技的英语作文The Role of AI Technology in Shaping Our FutureIn the rapidly evolving landscape of technology, Artificial Intelligence (AI) has emerged as a transformative force, redefining the way we interact with the world around us. From everyday tasks to complex problem-solving, AI has become an integral part of our lives, seamlessly integrating with various industries and sectors. As we delve deeper into the realm of AI, it is crucial to explore its multifaceted impact on our society and the potential it holds for shaping our collective future.One of the most significant advancements in AI technology is its ability to process and analyze vast amounts of data. By leveraging machine learning algorithms, AI systems can identify patterns, extract insights, and make informed decisions with remarkable efficiency. This capability has revolutionized numerous industries, from healthcare to finance, enabling more accurate diagnoses, personalized treatment plans, and data-driven investment strategies. The integration of AI in these domains has the potential to enhance the quality of life, improve decision-making, and drive innovation.Furthermore, AI has made remarkable strides in the field of natural language processing (NLP). This technology enables machines to understand, interpret, and generate human language, opening up new avenues for seamless communication and collaboration between humans and machines. The applications of NLP range from virtual assistants and chatbots to language translation and content generation, facilitating more intuitive and personalized interactions. As AI-powered language models continue to evolve, the potential for enhanced human-computer interaction and the democratization of information becomes increasingly evident.Another crucial aspect of AI technology is its ability to automate tasks and streamline workflows. By delegating repetitive or labor-intensive tasks to AI systems, businesses and individuals can free up valuable time and resources, allowing them to focus on higher-level strategic planning and creative problem-solving. This automation has the potential to revolutionize various industries, from manufacturing and logistics to customer service and administrative processes. As AI-powered automation continues to advance, it will undoubtedly reshape the job market, necessitating a shift in the skills and competencies required for the workforce of the future.Beyond its practical applications, AI also holds immense potential in the realm of scientific research and discovery. AI-powered simulations, predictive modeling, and data analysis can acceleratethe pace of scientific breakthroughs, enabling researchers to explore complex phenomena and test hypotheses with greater efficiency. From drug development to climate modeling, the integration of AI in scientific pursuits can lead to groundbreaking discoveries and advancements that have the power to transform our understanding of the world and improve the human condition.However, the rise of AI technology also brings forth a range of ethical and societal considerations that must be addressed. Issues such as algorithmic bias, privacy concerns, and the potential displacement of human labor require careful deliberation and the development of robust governance frameworks. As AI systems become more sophisticated and integrated into our daily lives, it is crucial to ensure that they are designed and deployed in a manner that upholds principles of fairness, transparency, and accountability.In conclusion, the impact of AI technology on our future is both profound and multifaceted. From enhancing our decision-making capabilities to revolutionizing entire industries, AI holds the potential to unlock new frontiers of innovation and progress. As we navigate this technological landscape, it is essential to strike a delicate balance between embracing the transformative power of AI and addressing the ethical challenges that arise. By doing so, we can harness the full potential of AI to shape a future that is more efficient, equitable, and beneficial for all.。

汽车博物馆珍藏馆英文作文

汽车博物馆珍藏馆英文作文

汽车博物馆珍藏馆英文作文Title: A Journey Through the Vault of Automobile History The automobile museum stands as a monument to human ingenuity and progress, a place where history is preserved and celebrated. Within its walls, one can traverse the evolution of the automobile, from the earliest models to the modern marvels of engineering that define our world today. It is both a repository of knowledge and a showcase of art, technology, and design.Upon entering the museum, visitors are greeted by a breathtaking display of automobiles from various eras. Each vehicle tells a unique story, reflecting the social, cultural, and technological advancements of its time. The collection ranges from the early horseless carriages of the late 19th century to the luxurious models of the roaring twenties, through to the sleek, high-performance vehicles of the modern age.One of the most striking sections of the museum is dedicated to the classic cars of the 20th century. These vehicles embody an era when automobiles were more than just a means of transportation; they were symbols of status, power, and freedom. Shiny chrome details, elegant lines, and vibrant colors make these classics truly captivating. They serveas a testament to the craftsmanship and style that defined their time.The museum also dedicates ample space to the evolution of technology and safety in automobiles. Exhibits showcase how innovations such as the seat belt, airbag, and anti-lock braking system have saved countless lives and improved driving comfort. Visitors can witness the transformation of cars from mere conveyances into sophisticated systems integrating advanced electronics, materials science, and environmental considerations.Moreover, the museum does not shy away from highlighting the impact of automobiles on society and the environment. It presents thought-provoking displays on the challenges faced by our cities due to increasing traffic congestion and pollution. At the same time, it offers insights into the efforts being made to address these issues through sustainable designs and alternative fuel technologies.For enthusiasts and novices alike, the automobile museum provides an immersive experience. Interactive exhibits allow visitors to engage with the technology directly, from virtual reality tours of factories to hands-on displays of engine components. Educational programs for children andworkshops for adults further extend the learning experience beyond the static displays.In conclusion, the automobile museum is far more than a static collection of historical objects. It is a dynamic institution that celebrates the evolution of the automobile while educating the public about its impact on our lives. As we look to the future of transportation, these museums serve as a reminder of our journey thus far and the limitless potential of innovation to shape the world we live in.。

如何发现新现象英语作文

如何发现新现象英语作文

如何发现新现象英语作文Title: Discovering New Phenomena。

Introduction:The pursuit of knowledge and understanding ofteninvolves the discovery of new phenomena. Whether in the realms of science, art, or society, uncovering something previously unknown is a thrilling endeavor. In this essay, we will explore the process of discovering new phenomenaand the significance it holds in various fields.Understanding Observation:Observation is the cornerstone of discovering new phenomena. It involves keenly observing the world around us, paying attention to details, patterns, and anomalies. By observing carefully, researchers and enthusiasts can notice deviations from the norm or unexpected occurrences that may lead to groundbreaking discoveries.Curiosity and Inquiry:Curiosity is another vital aspect of discovering new phenomena. It is the driving force that motivates individuals to question, explore, and seek answers. When we encounter something unfamiliar or intriguing, curiosity compels us to delve deeper, prompting us to ask questions and embark on a journey of discovery.Interdisciplinary Connections:New phenomena often emerge at the intersections of different disciplines. Collaborations between scientists, artists, engineers, and scholars from diverse fields can spark innovative ideas and facilitate the exploration of uncharted territories. By integrating knowledge and perspectives from various disciplines, researchers can approach problems from multiple angles and uncover unexpected connections.Utilizing Technology and Tools:Advancements in technology have revolutionized the process of discovering new phenomena. Cutting-edge tools such as telescopes, microscopes, sensors, and computational models enable researchers to observe, measure, and analyze phenomena with unprecedented precision and efficiency. These technological innovations expand the scope of exploration and open up new possibilities for discovery.The Role of Serendipity:Serendipity, or the occurrence of fortunate discoveries by chance, plays a significant role in uncovering new phenomena. Sometimes, breakthroughs occur when researchers stumble upon unexpected findings while pursuing unrelated inquiries. Serendipitous discoveries often challenge existing assumptions, leading to paradigm shifts and new avenues of exploration.Challenges and Limitations:Despite the excitement of discovery, the process is notwithout its challenges and limitations. Researchers may encounter obstacles such as funding constraints, logistical difficulties, and ethical considerations. Moreover, the complexity of phenomena and the limitations of current methodologies may hinder our ability to fully understand and explain certain phenomena.Ethical Considerations:The pursuit of new phenomena raises important ethical considerations, particularly in fields such as scientific research and technology development. Researchers must navigate ethical dilemmas related to privacy, safety, and the potential consequences of their discoveries. It is essential to approach the exploration of new phenomena with integrity, responsibility, and a commitment to the well-being of individuals and society.Conclusion:In conclusion, discovering new phenomena is a multifaceted process that involves observation, curiosity,interdisciplinary collaboration, technological innovation, serendipity, and ethical considerations. Whether unraveling the mysteries of the universe, uncovering hidden patternsin data, or unveiling the complexities of human behavior, the pursuit of discovery enriches our understanding of the world and fuels progress and innovation. As we continue to explore the unknown, let us embrace the spirit of curiosity, inquiry, and ethical responsibility to unlock the secrets that await us.。

英语作文模板人工智能

英语作文模板人工智能

英语作文模板人工智能英文回答:Introduction: The Rise of AI and Language Models。

Artificial intelligence (AI) has emerged as a transformative technology, revolutionizing various industries and domains. Among its many applications, AI has found particular prominence in the field of natural language processing (NLP). NLP involves the interaction between computers and human (natural) languages, enabling machines to understand, generate, and translate language in ways that were once thought impossible. This has led to the development of advanced language models that can perform a wide range of tasks, including text summarization, machine translation, and dialogue generation.Language Model Techniques and Architectures。

Language models are statistical models that learn theunderlying patterns and structures of a language from a vast corpus of text data. The most commonly used language model techniques include:n-grams: Sequences of n words that co-occur frequently in the training data.Recurrent neural networks (RNNs): Neural networks that can process sequential data, such as text, by maintaining an internal state.Transformers: Neural networks that use attention mechanisms to model long-range dependencies between wordsin a sentence.Applications of Language Models。

以新质生产力推动高质量发展英语作文

以新质生产力推动高质量发展英语作文

以新质生产力推动高质量发展英语作文Harnessing New-Type Productivity for High-Quality Development.In an era marked by unprecedented technological advancements and global economic shifts, it has become imperative for nations to embrace new paradigms of productivity to drive sustainable and high-quality economic development. The concept of "new-type productivity" has emerged as a bedrock for this transformation, offering a comprehensive framework to enhance productivity levels while fostering inclusiveness and innovation.New-type productivity encompasses a multifaceted approach that transcends traditional notions of labor-intensive and capital-intensive production models. It emphasizes the synergistic integration of human capital, technological innovation, and organizational efficiency to create value and drive economic growth.Human capital, comprising the skills, knowledge, and competencies of the workforce, serves as the cornerstone of new-type productivity. By investing in education, training, and lifelong learning, nations can cultivate a highlyskilled labor force that can adapt to evolving market demands. This includes fostering creativity, problem-solving abilities, and technological literacy, empowering individuals to contribute effectively to value creation.Technological innovation holds immense potential for boosting productivity and driving economic growth. Advances in artificial intelligence, automation, and robotics can enhance efficiency, reduce production costs, and create new opportunities for value-added services. By embracing these technologies and integrating them into production processes, businesses can unlock new sources of productivity andremain competitive in the global marketplace.Organizational efficiency plays a critical role in ensuring that resources are utilized optimally and value is generated effectively. Streamlining processes, implementing lean management practices, and fostering a culture ofcontinuous improvement can significantly enhance productivity and reduce waste. By creating a conducive work environment that encourages innovation and collaboration, organizations can foster an environment where productivity thrives.The pursuit of new-type productivity must be driven by a commitment to inclusiveness and equity, ensuring that the benefits of increased productivity are shared across society. This includes investing in infrastructure, healthcare, and education to create an environment where everyone has the opportunity to contribute to and benefit from economic growth.Moreover, it is essential to foster a conducive policy environment that supports innovation, entrepreneurship, and market competition. Governments can play a pivotal role in providing incentives for research and development, promoting technology transfer, and creating a regulatory framework that encourages risk-taking and innovation. By fostering a vibrant ecosystem that nurtures new ideas and encourages collaboration, nations can unlock the fullpotential of new-type productivity.Embracing new-type productivity has far-reaching implications for economic development. It leads to increased production output, reduced costs, and improved quality of goods and services. This, in turn, stimulates economic growth, creates new employment opportunities, and enhances living standards for citizens. Furthermore, it promotes innovation, technological advancements, and a culture of continuous improvement, driving a virtuous cycle of productivity and economic prosperity.However, the transition to new-type productivity requires a concerted effort from all stakeholders. Governments, businesses, and individuals must work together to create an environment that supports and nurtures productivity. This includes providing the necessary infrastructure, investing in education and training, and embracing an innovation-friendly mindset. By cultivating a shared understanding of the importance of new-type productivity, we can collectively harness itstransformative power to drive high-quality economic development and secure a brighter future for all.。

道德 英语作文

道德 英语作文
5. Cultivating morality in a diverse society
In today's increasingly diverse and interconnected world, the cultivation of morality becomes more complex, as individuals from different cultural backgrounds may hold varying beliefs and values. In such a context, it is essential to promote universal moral principles that transcend cultural and religious boundaries, such as respect for human dignity, fairness, and empathy. By recognizing the common humanity that binds all people, individuals can embrace diversity while upholding shared moral standards that foster understanding and harmony.
1. The significance of morality
Morality serves as the foundation for ethical decision-making and responsible conduct. It encompasses a set of principles that govern how individuals should behave towards others and what is considered right or wrong. Without a moral compass, society would descend into chaos, as there would be no guiding principles to regulate behavior and resolve conflicts. Therefore, the cultivation of moral values is essential for building a harmonious and prosperous community.
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Model Integration
Integrated models may be either multitask or singletask models. Multitask models involve two or more goals. For example, a model of driving and a model of cell-phone use can be integrated to predict the effect of cell phone use of driving [4]. Single-task models involve two or more strategies for accomplishing the same goal. For example, a model of the effect of word meaning on visual search and a model of the effect of a menu hierarchy on visual search can be integrated to predict the effect of the meaning of hierarchical group labels on visual search. This dissertation proposes principles for integrating models of visual search that will extend and expand the principles proposed by Kieras et al. [5]. Kieras et al. investigate methods of multitask model integration (which they call managerial styles) that differ in the amount of temporal overlap in execution of the
Accepted for the Conference on Human Factors in Computing Systems, Doctoral Consortium, Montréal, Québec, Canada, April 22-27, 2006.
Integrating Models of Human-Computer Visual Interaction
integrated models. The temporal overlap can be either conservative (i.e. serial) or liberal (i.e. parallel). Either one, however, assumes that the processes will be competitive. That is, there are two independent tasks that compete for the same resources and do not participate in a common task. With the integration of models for tasks like visual search, the integrated processes may cooperate on a single task. Another aspect of model integration method, that of cooperation level, will be investigated in this dissertation. The models to be integrated can either work in cooperation or competition towards a common goal. Cooperative models work together to decide where to move the eyes next. Competitive models work independently to decide where to move the eyes next. Using both temporal overlap and degree of cooperation produces four possible methods of integrating models of visual search shown in Table 1: conservativecooperative, conservative-competitive, liberalcooperative, and liberal-competitive. These four methods of integration will be used in this dissertation to integrate existing cognitive models of humancomputer visual interaction. Figure 1 illustrates two of these integration methods.
Abstract
Predicting visual search behavior in human-computer interaction is a challenging problem. It is important for predictive modeling of human-computer interaction to integrate the visual search strategies identified in individual models in order to predict users’ visual interaction with a variety of complex, real-world layouts. Individual research efforts have done well in developing models that predict users’ visual search behavior for a single well-defined task. Considering the large variety of visual layouts users can encounter, many visual search strategies can come into play during visual search. This dissertation investigates principles for integrating strategies of visual search. These principles will be used to integrate four models of visual search from HCI literature.
ACM Classification Keywords
H.5.2. [Information interfaces and presentation (e.g., HCI)]: User Interfaces—evaluation/methodology, graphical user interfaces, theory and methods; H.1.2. [Models and Principles]: User/Machine Systems— human information processing; I.6.5. [Simulation and Modeling]: Model Development—modeling methodologies; General Terms: Design, Human Factors, Measurement, Theory, Verification
Copyright is held by the author/owner(s). CHI 2006, April 22–27, 2006, Montréal, Québec, Canada. ACM 1-59593-298-4/06/0004.
Introduction
Computational cognitive models — computer programs that simulate some aspects of human cognition and action — have been used to better understand how and why design decisions affect human-computer visual interaction. For example, the effects of icon complexity [1], hierarchical organization [2], and the relevance of link labels [3] have been investigated with cognitive modeling to better understand how these factors affect visual search. However, most existing cognitive models of visual search account for just one visual search strategy (the plans people use to visually search based on properties of the objects searched and the actual or expected layout being searched) at a time.
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