Smart Synergy
Cyber-Physical Systems (CPS) merge advanced computational algorithms with physical healthcare processes, creating real-time, interactive systems that revolutionize medical practices. These systems integrate sensors, data processing units, communication networks, and control systems to monitor, analyze, and respond to patient needs. Applications include remote patient monitoring, personalized medicine, telemedicine, and smart implants, which enhance accuracy, accessibility, and cost-efficiency. While challenges like data security and interoperability persist, CPS's transformative potential lies in its ability to deliver precise, patient-centric care, optimize resources, and address global healthcare challenges. With advancing technologies, CPS is poised to redefine the future of healthcare delivery.
Optical Character Recognition of Sanskrit Manuscripts using Convolution Neural Networks
Optical Character Recognition of Sanskrit Manuscripts Using Convolution Neural Networks delves into the cutting-edge application of deep learning for deciphering Sanskrit manuscripts written in Devanagari script. Tackling one of the most challenging tasks in OCR-recognizing Sanskrit's intricate characters and symbols-this work presents a robust system designed to enhance recognition accuracy for scanned text images. By employing advanced architectures such as Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM, alongside traditional classifiers like k-Nearest Neighbors (KNN) and Support Vector Machines (SVM), the research achieves remarkable accuracy rates. Beyond single-touching characters, it innovatively addresses overlapping lines, connected letters, and half-characters, providing solutions to limitations in existing systems. With a peak recognition accuracy of 98.64% for mixed Sanskrit text, this study is a vital contribution to the preservation and digitization of ancient literature. It opens new doors to computational linguistics, ensuring Sanskrit's cultural heritage thrives in the digital age.
The Behavioural Study of Stocks and LSTM Algorithm
"Unlock the secrets of the stock market with the power of machine learning. This comprehensive guide explores cutting-edge techniques for predicting stock prices using advanced algorithms and data analysis. From feature engineering to model optimization, you'll discover practical strategies to gain an edge in trading and investing. Whether you're a finance enthusiast, data scientist, or aspiring trader, this book equips you with the tools to make data-driven decisions in the fast-paced world of the stock market. Take the first step toward mastering predictive analytics and achieving financial success!"
Beyond Single Modalities
In an era where secure authentication is paramount, multimodal biometrics stands at the forefront of innovation, combining multiple physiological and behavioral traits to create robust and reliable systems. This comprehensive guide, ""Beyond Single Modalities: A Guide to Multimodal Biometrics,"" delves into the science and technology behind integrating diverse modalities, such as fingerprint, face, iris, voice, and gait, to overcome the limitations of single-modal systems. From foundational concepts to cutting-edge advancements, this book explores the design, implementation, and real-world applications of multimodal biometric systems, offering insights into their role in enhancing security, reducing vulnerabilities, and shaping the future of authentication. Ideal for researchers, students, and professionals, this guide paves the way for understanding the potential and challenges of this transformative technology.
Notes on Agent-based Applications
This book is a comprehensive guide designed to lead readers through the fascinating world of programming, machine learning, and artificial intelligence, from the very basics to cutting-edge applications. Beginning with foundational Python concepts, it gradually introduces readers to the intricacies of machine learning, neural networks, and deep learning architectures like convolutional neural networks. As the journey unfolds, the book delves into more advanced topics such as natural language understanding and the transformative power of large language models (LLMs), including modern developments like transformers and GPT models towards Agentic AI framework. Readers will not only learn how to implement these models but will also explore practical, agent-based applications, enabling machines to act intelligently and autonomously-writing and executing code, solving complex tasks, and interacting with APIs in dynamic environments. With a clear, structured approach and step-by-step tutorials, this book offers both beginners and experienced AI enthusiasts an accessible yet deeply insightful dive into one of the most exciting fields of technology today. Whether you're aiming to understand the basics or build real-world applications, this book provides a roadmap to mastering AI. It is always amazing to connect with my audience. Please feel free to connect with me from my personal site: https: //www.y-yin.io/. Both LinkedIn and YouTube can be accessed from the personal site.
Advancing Responsible AI in Public Sector Application
Responsible use of AI in public sector applications requires engagement with various technical and non-technical areas such as human rights, inclusion, diversity, innovation, and economic growth. The book covers topics spanning the technological socio-economic spectrum including potential of AI/ML technologies to address social and political inequities, privacy enhancing technologies for datasets, friction less data sharing and data stewardship models, regional/geographical inequities in extraction and so forth.Features: Focuses on technical aspects of responsible AI in the public sector. Covers a wide range of topics spanning the technological socio-economic spectrum. Presents viewpoints from the public sector agencies as well as from practitioners. Discusses privacy enhancing technologies for collecting, processing and storing datasets, and friction. Reviews frameworks to identify and address biased AI outcomes in the design, development and use of AI. This book is aimed at professionals, researchers and students in artificial intelligence, computer science and engineering, policy makers, social scientists, economists, and lawyers.
Anti-Tamper Method for Field Programmable Gate Arrays Through Dynamic Reconfiguration and Decoy Circuits
Load Balancing Using Time Series Analysis for Soft Real Time Systems With Statistically Periodic Loads
Load Balancing Using Time Series Analysis for Soft Real Time Systems With Statistically Periodic Loads
An FPGA-Based System for Tracking Digital Information Transmitted via Peer-to-Peer Protocols
An FPGA-Based System for Tracking Digital Information Transmitted via Peer-to-Peer Protocols
High-Performance Automation Methods for Computational Intelligent Systems
Computational methods are necessary for the proper execution of the applications for the benefit of society and technological development. Technological development makes life easier by constructing powerful systems with the help of computational methods. The nature of computational methods changes from time to time and retains only efficient applicable theories. Researchers take the idea of existing computational systems and advance them as per possible future needs. Efficient computational methods solve complex problems and also help to make the system more intelligent. Automation process requires decision-making computational systems. A more intelligent system contains an efficient computational method, which is described by powerful algorithm development. The aim of this book is to identify the technological development for future computational systems, which ultimately reflects the more intelligent system. Automation has become the need of the hour in today's world, and hence, the computational systems need to be upgraded to that level to perform the required tasks. The most efficient computational algorithm acts like a human being and offers a full sense of intelligent automation.This book: Presents the latest research trends for the upcoming computational intelligent systems in a comprehensive manner Focuses on the integration of multi-purpose and multi-dimension natural language into intelligent systems Elaborates on nature-inspired and intelligent behaviour-based computational methods to deal with the observation of nature Illustrates applications of quantum cellular energy-efficient computing methods for automation and applications of genetic algorithms in multidisciplinary fields Discusses aspects of intelligent automation like technology-based, architecture-based, logic implementation-based, and the different algorithms-based concepts It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
Cybersecurity 2050
This book explores the critical intersection of human behavior, cybersecurity, and the transformative potential of quantum technologies. It delves into the vulnerabilities and resilience of human intelligence in the face of cyber threats, examining how cognitive biases, social dynamics, and mental health can be exploited in the digital age.Cybersecurity 2050: Protecting Humanity in a Hyper-Connected World explores the cutting-edge applications of quantum computing in cybersecurity, discussing the efficiency of quantum security algorithms on Earth and over space communications such as those needed to inhabit Mars. The challenges and opportunities of human life on extraterrestrial worlds, such as Mars, will further shape the evolution of human intelligence. The isolated and confined environment of a Martian habitat, coupled with the reliance on advanced technologies for survival, will demand new forms of adaptability, resilience, and social cooperation. The author addresses the imminent revolution in cybersecurity regulations and transforms the attention of the bright minds of businesses and policymakers for the challenges and opportunities of quantum advancements. This book attempts to bridge the gap between social intelligence and cybersecurity, offering a holistic and nuanced understanding of these interconnected domains. Through real-world case studies, the author provides practical insights and strategies for adapting to the evolving technological landscape and building a more secure digital future.This book is intended for futuristic minds, computer engineers, policymakers, or regulatory experts interested in the implications of the revolution of human intelligence on cybersecurity laws and regulations. It will be of interest to cybersecurity professionals and researchers looking for a historic and comprehensive understanding of the evolving landscape, including social intelligence, quantum computing, and algorithm design.
Smarter Cyber Physical Systems
Cyber-Physical Systems (CPS) is featured by the tight integration of cyberand physical components. CPS has made major advances with a broadsocietal impact. Now in the era of Industry Revolution 4.0, CPS isconsidered as an enabling technology. Combined with autonomy, bigdata, machine learning and internet of things, CPS empowers systemswith greater intelligence to address uncertainties, unknowns, attacks, and unexpected events.This book highlights the latest advances and explores the new trends inthe design and implementation of smarter Cyber-Physical systems(CPS). It introduces integrated model-based and data-driven solutions forCPS that demonstrate features including both adaptability andinterpretability. Key topics covered include reinforcement learning, digitaltwin and large-scale networks. The book then presents the latest codesigntechniques that address practical computation, networking, control, and physical constraints. It examines important issues related tohuman CPS, safety, resilience and privacy. The chapters feature the tightintegration of theory and practice, including problems motivated fromapplications, fundamental research development that are generallyapplicable, and implementation in real system applications. A wide rangeof CPS applications are covered, including robotics, autonomous driving, unmanned aerial vehicles and smart cities.
Green Engineering for Optimizing Firm Performance
This book offers a detailed examination of how sustainable technologies are reshaping firm performance. Through an integration of empirical research, expert opinions, and case studies, it explores how green management practices are enhancing business outcomes and contributing to sustainable development. It offers an in-depth understanding of how green technologies and practices, such as green engineering, AI/ML applications, green HRM, and green innovation, impact firm performance. Explores topics such as green engineering, AI/ML applications, green finance, green HRM, and green innovation, showing their collective impact on business performance Presents real-world case studies and empirical findings to demonstrate how organizations across different industries have successfully implemented sustainable technologies Examines regional variations in green management practices, offering insights into the impact of economic, regulatory, and cultural contexts on sustainability initiatives Critically analyzes contemporary challenges with practical strategies for addressing issues effectively Recommends actionable policy and future research directions for sustainable business practices, providing a roadmap for advancing green management This reference book is for academicians, scholars, and practitioners who are interested in emerging technologies that are reshaping firm performance and impacting sustainability.
A Low Power Application-Specific Integrated Circuit (ASIC) Implementation of Wavelet Transform/Inverse Transform
Trajectory Ontology Inference Considering Domain, Temporal and Spatial Dimensions
Estimating Cognitive Function Using Spontaneous Speech in Older People Living in the Community
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 first 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.
Machine Learning for Neuroscience
This book addresses the growing need for machine learning and data mining in neuroscience. The book is replete with fully working machine learning code. It also contains lab assignments and quizzes, making it appropriate for use as a textbook.
Data Science for Civil Engineering
This book explains use of data science-based techniques for modelling and providing optimal solutions to complex problems in civil engineering. It deals with the basics of data science and essential mathematics and covers pertinent applications in structural and environmental engineering, construction management, and transportation.
Big Data Computing
This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services.
ConVision- A Context-based Deep Learning Algorithm for Efficient Lane Detection
Dive into the cutting-edge world of artificial intelligence with ""ConVision- A Context-based Deep Learning Algorithm for Efficient Lane Detection."" This comprehensive volume brings together six groundbreaking research studies, each meticulously designed and implemented with IEEE-level formulas, simulations, and equations. Discover how theoretical insights are seamlessly transformed into practical applications, enhancing various AI domains. From sophisticated simulations to robust implementations, this book showcases innovative approaches that push the boundaries of AI technology. Whether you're a researcher, practitioner, or enthusiast, this book offers a deep understanding of AI's core principles and real-world impact. Authored by experts in the field, this volume is a must-read for anyone seeking to stay at the forefront of AI research and application. Get ready to explore the future of artificial intelligence and its transformative potential. Praise for Advances in Artificial Intelligence: ""A remarkable collection of innovative AI research that bridges the gap between theory and practice."" - Dr. Jane Smith, AI Researcher ""Essential reading for anyone involved in AI development and application."" - TechReview Magazine Target Audience: Researchers, Practitioners, AI Enthusiasts, and Academics.
High Security Network for IOT using Edge Computing
Edge computing and the internet of things (IOT) have revolutionised the manner in which data is handled and analysed, making it possible to cut down on latency while simultaneously increasing energy efficiency. Yet, assuring the integrity of these systems and the security of their data continues to be a difficulty. This research proposes a unique system that addresses these difficulties in edge computing and IOT contexts. It mixes Base64 encoding, trustworthy algorithms, and virtual force mapping by trust value. This architecture not only boosts security and dependability by prioritising trustworthy components and preserving data while it is being sent, but it also adds significantly to reductions in energy usage, which is a huge win for everyone involved. The technique that has been provided provides a strong solution for safe, efficient, and reliable data processing in edge computing and IOT systems. As a result, it paves the way for future improvements in these sectors.
