A Low Power Application-Specific Integrated Circuit (ASIC) Implementation of Wavelet Transform/Inverse Transform
A Low Power Application-Specific Integrated Circuit (ASIC) Implementation of Wavelet Transform/Inverse Transform
Machine Translation and Translation Theory
Pervasive and ubiquitous, machine translation systems have been transforming communication and understanding across languages and cultures on a historical scale. Focused on both Neural Machine Translation tools, such as Google Translate, and generative AI tools, such as ChatGPT, Omri Asscher pursues the juncture between machine translation and the diverse, often competing, frameworks of human translation theory. He shines a light on the subtleties of the intersection between the two: the places where machine translation corresponds well with the ideas that have been developed on human translation throughout the years, and the places where machine translation seems to challenge translation theory, and perhaps even require that we rethink some of its basic assumptions.Machine Translation and Translation Theory reflects the need for an accessible, panoramic view on the subject. It offers a detailed discussion of various points of theoretical interest: definitions of translation; equivalence in translation; aesthetics of translation; translation ethics; translation as cross-cultural communication; and translation as a historical agent.This is key reading for researchers and students in translation studies, as well as scholars of AI-mediated communication, and computer scientists interested in how machine translation architectures correspond with the understanding of translation in the humanities.
Machine Translation and Translation Theory
Pervasive and ubiquitous, machine translation systems have been transforming communication and understanding across languages and cultures on a historical scale. Focused on both Neural Machine Translation tools, such as Google Translate, and generative AI tools, such as ChatGPT, Omri Asscher pursues the juncture between machine translation and the diverse, often competing, frameworks of human translation theory. He shines a light on the subtleties of the intersection between the two: the places where machine translation corresponds well with the ideas that have been developed on human translation throughout the years, and the places where machine translation seems to challenge translation theory, and perhaps even require that we rethink some of its basic assumptions.Machine Translation and Translation Theory reflects the need for an accessible, panoramic view on the subject. It offers a detailed discussion of various points of theoretical interest: definitions of translation; equivalence in translation; aesthetics of translation; translation ethics; translation as cross-cultural communication; and translation as a historical agent.This is key reading for researchers and students in translation studies, as well as scholars of AI-mediated communication, and computer scientists interested in how machine translation architectures correspond with the understanding of translation in the humanities.
Fuzzy Decision Support Systems for Efficient Energy Management
Transforming Healthcare
This comprehensive volume explores cutting-edge technologies, groundbreaking methodologies, and insightful ethical considerations. It brings together leading minds and research across diverse domains, offering readers a glimpse into the future of healthcare. From leveraging AI in diagnostics and personalized treatments to advancing telemedicine and remote patient monitoring, the text addresses real-world challenges and opportunities in the rapidly evolving healthcare industry.Key features: Innovative approaches to early disease detection, including Alzheimer's and cancer, using machine learning and deep learning techniques. State-of-the-art applications of design thinking, meta-heuristics, and federated learning in healthcare. Ethical perspectives on the use of AI technologies and their impact on businesses and patient care. A deep dive into the role of IoT, NLP, and AI-driven image processing in revolutionizing healthcare delivery. Generalized models analyzing trade credits and their implications for healthcare supply chains. Whether you're a researcher, healthcare professional, or technology enthusiast, this book serves as an invaluable resource for understanding and shaping the future of health technologies. Packed with diverse perspectives and actionable insights, it's a must-read for anyone passionate about making a difference in healthcare.
Robotics
Robotics: From Theory to Practice introduces robotic theories and technologies to audiences, including university students, professionals with engineering backgrounds, and even high-school students interested in building their own robots. We aim to bridge the gap between classic theories and real-world applications of robotic manipulators, which, to date, have far exceeded the domain of conventional industry.The contents are divided into three parts. The former two cover classic theories of robotics, including kinematics, dynamics, path planning, control, and programming. Specifically, Part I is an introduction targeting junior students, featuring more simplistic topics and examples. Part II provides the senior students and professionals with more in-depth discussions on critical topics and more comprehensive examples. In Part III, we demonstrate how classic robotics theory can be extended to more advanced theoretical frameworks and adopted in real-world applications beyond conventional industries.This textbook is valuable to broad readers, including those who have limited background in general engineering and wish to explore non-conventional applications of robotic manipulators. The scaffolded contents from Part I to Part III are created to lower the prerequisites and smooth the learning curve.
Development of Efficient Bio-Inspired Computing Algorithm for Image Classification
Route Optimization and Congestion Control in Wireless Network
ConVision- A Context-based Deep Learning Algorithm for Efficient Lane Detection
Integration of Cloud Computing with Emerging Technologies
This book gives a complete overview of cloud computing: its importance, its trends, innovations, and its amalgamation with other technologies.Key Features: In-depth explanation of emerging technologies utilizing cloud computing Supplemented with visuals, flow charts, and diagrams Real-time examples included Caters to beginners, as well as advanced researchers, by explaining implications, innovations, issues, and challenges of cloud computing Highlights the need for cloud computing and the true benefits derived by its application and integration in emerging technologies Simple, easy language
Smart Embedded Systems
"Smart Embedded Systems: Advances and Applications" is a comprehensive guide that demystifies the complex world of embedded technology. The book journeys through a wide range of topics from healthcare to energy management, autonomous robotics, and wireless communication, showcasing the transformative potential of intelligent embedded systems in these fields. This concise volume introduces readers to innovative techniques and their practical applications, offers a comparative analysis of wireless protocols, and provides efficient resource allocation strategies in IoT-based ecosystems. With real-world examples and in-depth case studies, it serves as an invaluable resource for students and professionals seeking to harness the power of embedded technology to shape our digital future.Salient Features: The book provides a comprehensive coverage of various aspects of smart embedded systems, exploring their design, implementation, optimization, and a range of applications. This is further enhanced by in-depth discussions on hardware and software optimizations aimed at improving overall system performance. A detailed examination of machine learning techniques specifically tailored for data analysis and prediction within embedded systems. This complements the exploration of cutting-edge research on the use of AI to enhance wireless communications. Real-world applications of these technologies are extensively discussed, with a focus on areas such as seizure detection, noise reduction, health monitoring, diabetic care, autonomous vehicles, and communication systems. This includes a deep-dive into different wireless protocols utilized for data transfer in IoT systems. This book highlights key IoT technologies and their myriad applications, extending from environmental data collection to health monitoring. This is underscored by case studies on the integration of AI and IoT in healthcare, spanning topics from anomaly detection to informed clinical decision-making. Also featured is a detailed evaluation and comparison of different system implementations and methodologies This book is an essential read for anyone interested in the field of embedded systems. Whether you're a student looking to broaden your knowledge base, researchers looking in-depth insights, or professionals planning to use this cutting-edge technology in real-world applications, this book offers a thorough grounding in the subject.
Artificial Intelligence in Telemedicine
This book explores the role of artificial Intelligence in Telemedicine. It explains the concepts through the detailed study and processing of biosignals, physiological parameters, and medical images. The book focuses on computational algorithms in telemedicine for the processing of biosignals, physiological parameters, and medical Images. The book is presented in two section. The first section presents the role of computational algorithms in the processing of biosignal and medical images for disease diagnosis and treatment planning. Noise removal in ECG signal using an improved adaptive learning approach, classification of ECG signals using CNN for cardiac arrhythmia detection, EEG signal analysis for stroke detection, and EMG signal analysis for gesture classification were discussed in this section. Application of CNN in pertussis Diagnosis by temperature monitoring, physician handwriting recognition using deep learning model, melanoma detection using ABCD parameters, and transfer learning enabled heuristic approach for pneumonia detection was also discussed in this section The second section focus on the role of IoT and artificial intelligence in the healthcare sector. IoT in smart health care and applications of artificial intelligence in disease diagnosis and prediction was discussed in this section. The importance of 5G/6G in the pandemic scenario for telemedicine applications, wireless capsule endoscopy image compression, leukemia detection from the microscopic cell images, and genomic signal processing using numerical mapping techniques was also discussed in this section. This book can be used by a wide range of users including students, research scholars, faculty, and practitioners in the field of engineering for applications in biomedical signal, image analysis, and diagnosis.
Computer Organization, Design, and Architecture
This unique and classroom-proven text provides a hands-on introduction to the design of computer systems. It depicts, step by step, the design and programming of a simple but complete hypothetical computer, followed by detailed architectural features of existing computer systems as enhancements to the structure of the simple computer. This treatment integrates the four categories of digital systems architecture: logic design, computer organization, computer hardware, and computer system architecture.This edition incorporates updates to reflect contemporary organizations and devices, including graphics processing units (GPUs), quantum computing, and the latest supercomputer systems. It also includes a description of the two popular Instruction Set Architectures (ARM and RISC-V).The book is suitable for a one-or two-semester undergraduate or beginning graduate course in computer science and computer engineering; its previous editions have been adopted by 120+ universities around the world.The book covers the topics suggested by the recent IEEE/ACM curriculum for "computer architecture and organization."
Handbook on Federated Learning
Mobile, wearable, and self-driving telephones are just a few examples of modern distributed networks that generate enormous amount of information every day. Due to the growing computing capacity of these devices as well as concerns over the transfer of private information, it has become important to process the part of the data locally by moving the learning methods and computing to the border of devices. Federated learning has developed as a model of education in these situations. Federated learning (FL) is an expert form of decentralized machine learning (ML). It is essential in areas like privacy, large-scale machine education and distribution. It is also based on the current stage of ICT and new hardware technology and is the next generation of artificial intelligence (AI). In FL, central ML model is built with all the data available in a centralised environment in the traditional machine learning. It works without problems when the predictions can be served by a central server. Users require fast responses in mobile computing, but the model processing happens at the sight of the server, thus taking too long. The model can be placed in the end-user device, but continuous learning is a challenge to overcome, as models are programmed in a complete dataset and the end-user device lacks access to the entire data package. Another challenge with traditional machine learning is that user data is aggregated at a central location where it violates local privacy policies laws and make the data more vulnerable to data violation. This book provides a comprehensive approach in federated learning for various aspects.
Smart Cities
This book discusses the basic principles of sustainable development in a smart city ecosystem to better serve the life of citizens. It examines smart city systems driven by emerging IoT-powered technologies and the other dependent platforms.Smart Cities: AI, IoT Technologies, Big Data Solutions, Cloud Platforms, and Cybersecurity Techniques discusses the design and implementation of the core components of the smart city ecosystem. The editors discuss the effective management and development of smart city infrastructures, starting with planning and integrating complex models and diverse frameworks into an ecosystem. Specifically the chapters examine the core infrastructure elements, including activities of the public and private services as well as innovative ICT solutions, computer vision, IoT technologies, data tools, cloud services, AR/VR technologies, cybersecurity techniques, treatment solution of the environmental water pollution, and other intelligent devices for supporting sustainable living in the smart environment.The chapters also discuss machine vision models and implementation as well as real-time robotic applications. Upon reading the book, users will be able to handle the challenges and improvements of security for smart systems, and will have the know-how to analyze and visualize data using big data tools and visualization applications. The book will provide the technologies, solutions as well as designs of smart cities with advanced tools and techniques for students, researchers, engineers, and academics.
Computer Organization, Design, and Architecture
This unique and classroom-proven text provides a hands-on introduction to the design of computer systems. It depicts, step by step, the design and programming of a simple but complete hypothetical computer, followed by detailed architectural features of existing computer systems as enhancements to the structure of the simple computer. This treatment integrates the four categories of digital systems architecture: logic design, computer organization, computer hardware, and computer system architecture.This edition incorporates updates to reflect contemporary organizations and devices, including graphics processing units (GPUs), quantum computing, and the latest supercomputer systems. It also includes a description of the two popular Instruction Set Architectures (ARM and RISC-V).The book is suitable for a one-or two-semester undergraduate or beginning graduate course in computer science and computer engineering; its previous editions have been adopted by 120+ universities around the world.The book covers the topics suggested by the recent IEEE/ACM curriculum for "computer architecture and organization."
Advancing Medical Assistance - Hungarian-Language Medical Chatbot with Artificial Intelligence
Integrating LoRa and Direction APIs for High-Performance Machine Vision in Smart Cars
ARM64 Assembly Language and Arcitecture
With the proliferation of IOT, and embedded systems RISC (Reduced Instruction Set Computer) processors are ubiquitous. More recently many computer manufacturers have started to deploy 64-bit ARM based processors within their products. A detailed knowledge of ARM systems can be a distinct advantage for software engineers in today's fast-moving technological marketplace. This book is aimed at computer science students and hobbyists wishing to learn about assembly language concepts and programming using the ARM64 architecture. Experienced programmers that are familiar with high-level language coding, wishing to learn more about system level programming may also find the content beneficial.
Machine Learning Algorithms and Applications in Engineering
Artificial Intelligence in Radiation Oncology and Biomedical Physics
Multi-Criteria Decision Making Theory and Applications in Sustainable Healthcare
Multi-Cloud Administration Guide
As businesses increasingly adopt cloud-first strategies, managing workloads across multiple cloud platforms becomes a critical challenge. This comprehensive book provides practical solutions and in-depth knowledge to efficiently operate in a multi-cloud world. Learn to leverage frameworks from AWS, Azure, GCP, and Alibaba Cloud to maximize the benefits of multi-cloud environments. Understand cloud networking, software-defined networking, and microservices to optimize cloud connectivity. Develop a robust data strategy to ensure data quality, security, and integrity across multiple cloud platforms. Discover how automation and AI can help maintain compliance with governmental and industry regulations in the cloud. Designed for cloud architects, IT administrators, and technical managers, this book is also valuable for anyone looking to deepen their understanding of cloud technologies and multi-cloud strategies. FEATURES- Uses frameworks from AWS, Azure, GCP, and Alibaba Cloud to maximize the benefits of multi-cloud environments- Provides practical instructions and real-world examples for managing multi-cloud environments - Features insights into cloud-native technologies, serverless functions, and container orchestration with Kubernetes- Explores the details of multi-cloud connectivity, storage, compute, data management, security, and compliance- Includes companion files with code samples and color figures available for downloading
Deep Learning and Reinforcement Learning
Deep learning and reinforcement learning are some of the most important and exciting research fields today. With the emergence of new network structures and algorithms such as convolutional neural networks, recurrent neural networks, and self-attention models, these technologies have gained widespread attention and applications in fields such as natural language processing, medical image analysis, and Internet of Things (IoT) device recognition. This book, Deep Learning and Reinforcement Learning examines the latest research achievements of these technologies and provides a reference for researchers, engineers, students, and other interested readers. It helps readers understand the opportunities and challenges faced by deep learning and reinforcement learning and how to address them, thus improving the research and application capabilities of these technologies in related fields.
Convergence of Deep Learning and Artificial Intelligence in Internet of Things
