eBooks de Informática práctica, página 2 de 141

This book is a detailed reference guide on deep learning and its applications. It aims to provide a basic understanding of deep learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters contributed by computer science academics and researchers. By the end of the book, the reader will become familiar with different deep learning approaches and models, and understand how to implement various deep learning algorithms using multiple frameworks and libraries. This book is divided into three parts. The first part explains the basic operating understanding, history, evolution, and challenges associated with deep learning. The basic concepts of mathematics and the hardware requirements for deep learning implementation, and some of its popular frameworks for medical applications are also covered. The second part is dedicated to sentiment analysis using deep learning and machine learning techniques. This book section covers the experimentation and application of deep learning techniques and architectures in real-world applications. It details the salient approaches, issues, and challenges in building ethically aligned machines. An approach inspired by traditional Eastern thought and wisdom is also presented. The final part covers artificial intelligence approaches used to explain the machine learning models that enhance transparency for the benefit of users. A review and detailed description of the use of knowledge graphs in generating explanations for black-box recommender systems and a review of ethical system design and a model for sustainable education is included in this section. An additional chapter demonstrates how a semi-supervised machine learning technique can be used for cryptocurrency portfolio management. The book is a timely reference for academicians, professionals, researchers and students at engineering and medical institutions working on artificial intelligence applications.

Advanced Mathematical Applications in Data Science comprehensively explores the crucial role mathematics plays in the field of data science. Each chapter is contributed by scientists, researchers, and academicians. The 13 chapters cover a range of mathematical concepts utilized in data science, enabling readers to understand the intricate connection between mathematics and data analysis. The book covers diverse topics, including, machine learning models, the Kalman filter, data modeling, artificial neural networks, clustering techniques, and more, showcasing the application of advanced mathematical tools for effective data processing and analysis. With a strong emphasis on real-world applications, the book offers a deeper understanding of the foundational principles behind data analysis and its numerous interdisciplinary applications. This reference is an invaluable resource for graduate students, researchers, academicians, and learners pursuing a research career in mathematical computing or completing advanced data science courses. Key Features: Comprehensive coverage of advanced mathematical concepts and techniques in data scienceContributions from established scientists, researchers, and academiciansReal-world case studies and practical applications of mathematical methodsFocus on diverse areas, such as image classification, carbon emission assessment, customer churn prediction, and healthcare data analysisIn-depth exploration of data sciences connection with mathematics, computer science, and artificial intelligenceScholarly references for each chapterSuitable for readers with high school-level mathematical knowledge, making it accessible to a broad audience in academia and industry.

A coletânea Narrativas em foco: estudos interdisciplinares em humanidades – Volume 3 reúne reflexões plurais que atravessam política, educação, linguagem, psicologia, religião e cultura, explorando a

This book is a comprehensive review of technologies and data in healthcare services. It features a compilation of 10 chapters that inform readers about the recent research and developments in this field. Each chapter focuses on a specific aspect of healthcare services, highlighting the potential impact of technology on enhancing practices and outcomes. The main features of the book include 1) referenced contributions from healthcare and data analytics experts, 2) a broad range of topics that cover healthcare services, and 3) demonstration of deep learning techniques for specific diseases. Key topics: - Federated learning in analysis of sensitive healthcare data while preserving privacy and security. - Artificial intelligence for 3-D bone image reconstruction. - Detection of disease severity and creating personalized treatment plans using machine learning and software tools - Case studies for disease detection methods for different disease and conditions, including dementia, asthma, eye diseases - Brain-computer interfaces - Data mining for standardized electronic health records - Data collection, management, and analysis in epidemiological research The book is a resource for learners and professionals in healthcare service training programs and health administration departments. ReadershipLearners and professionals in healthcare service training programs and health administration departments.

This book is a comprehensive review of secondary metabolite production from plant tissue culture. The editors have compiled 12 meticulously organized chapters that provide the relevant theoretical and practical frameworks in this subject using empirical research findings. The goal of the book is to explain the rationale behind in vitro production of secondary metabolites from some important medicinal plants. Biotechnological strategies like metabolic engineering and the biosynthesis, transport and modulation of important secondary metabolites are explained along with research studies on specific plants. In addition to the benefits of secondary metabolites, the book also aims to highlight the commercial value of medicinal plants for pharmaceutical and healthcare ventures. Topics covered in this part include: 1. Elicitation Strategies and Metabolic Engineering to boost metabolite production with case studies in metabolic engineering with examples of Scaevola Taccada and Catharanthus Roseus. 2. Stress response investigation and the role of glandular trichomes as bio-cell factories 3. Plant growth regulators and rapid regeneration techniques using swift plantlets regeneration and phytochemical characterization 4. Nutraceuticals, antimicrobials, and genomic applications of in vitro cultures with an example of Hassawi rice and its genomics 5. Sustainable approaches for saving endangered medicinal plants The book caters to a wide readership. It primarily prepares graduate students, researchers, biotechnologists, giving them a grasp of the key methodologies in the secondary metabolite production. It is a secondary reference for support executives, industry professionals, and policymakers at corporate and government levels to understand the importance of plant tissue culture and maximizing its impact in the herbal industry. Readership Graduate students and researchers in plant biotechnology courses; industry professionals and policymakers in the herbal industry.

Basics of Python Programming: A Quick Guide for Beginners is an essential companion to mastering the Python programming language. The book presents information about Python in 12 structured chapters with a strong emphasis on fundamentals and practical information. Starting with basic operators, functions and expressions, contents explain file handling, exception handling and modules. The book concludes with advanced topics such as object oriented programming and machine learning. Key Features: Fundamental Focus: Covers the core concepts of Python programming to build a strong foundation in python programming in an easy-to-understand format.Practical Demonstrations: Learn by doing. This textbook includes hands-on practical demonstrations that reinforce your understanding of Python concepts.IDE Guidance: Includes programming and installation guidance for Python-supporting Integrated Development Environments (IDEs).Explores Python Frameworks: Introduces Python frameworks such as Matplotlib, TensorFlow, PyTorch, Scikit-Learn, and NLTK for complex projects.Python for Machine Learning: Gives a preliminary understanding of Python for machine learning tasks for data science and AI applications. Basics of Python Programming: A Quick Guide for Beginners is the perfect starting point for aspiring students, programmers and tech enthusiasts. Whether youre a student looking to build a solid foundation in Python or an industry professional venturing into machine learning and artificial intelligence, this textbook has you covered. Readership Computer science, engineering and technology students; programming enthusiasts and professionals.

Bioinformatics, and by extension omic sciences the collective disciplines that are dependent on the use of extensive datasets of biological information present a challenge of data management for researchers all over the world. Big data collected as part of research projects and experiments can be complex, with several kinds of variables involved. Coupled with continuously changing bioinformatics and information technology tools, there is a need to bring a multidisciplinary approach into these fields. Advances in Bioinformatics, Biostatistics and Omic Sciences attempts to realize an integrated approach between all omic sciences, exploring innovative bioinformatics and biostatistical methodologies which enable researchers to unveil hidden sides of biological phenomena. This volume presents reviews on the following topics which give a glimpse of recent advances in the field:- New Integrated Mitochondrial DNA Bioinformatics Pipeline to Improve Quality Assessment of Putative Pathogenic Variants from NGS Experiments - Variant Calling on RNA Sequencing Data: State of Art and Future Perspectives - An innovative Gene Prioritization Pipeline for WES analyses - New Integrated Differential Expression Approach for RNA-Seq Data Analysis - Innovations in Data Visualization for Straightforward Interpretation of Nucleic Acid Omics Outcomes This volume serves as a guide for graduate students in bioinformatics as well as researchers planning new projects as a part of their professional and academic activities.

This book is a review of recent artificial intelligence approaches, initiatives and applications in engineering and science fields. It features contributions that highlight the use of techniques such as machine learning, mining engineering, modeling and simulation, and fuzzy logic methods in the fields of communication, networking and information engineering. The collection of chapters should inspire scholars involved in theoretical and applied sciences to contribute to research using computational intelligence principles and methods in their respective research communities. Professionals working on systems engineering, communications, innovative computing systems and adaptive technologies for sustainable growth, will also be able to benefit from the information provided in the book.

Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is a 2-part book set which presents discoveries, innovative ideas, concepts, practical solutions, and novel applications of Human-Computer Interaction (HCI) and related disciplines such as artificial intelligence, machine learning, data mining, computer vision, and natural language processing. The book provides readers with information about HCI trends which are shaping the future of smart, interconnected urban and industrial environments. This is the second of the two volumes of the edited books. The chapters of this volume cover topics like ERP usability in educational settings, the role of AI in enhancing HCI functionality, usability of local mobile healthcare apps, analyzing the usage of social media apps and a review of HCI systems for disaster management and systems for tracking traffic safety violations. Contributions are authored by experts and scientists in the field of HCI and its interrelated disciplines from 9 different countries Albania, China, India, Indonesia, Nigeria, Pakistan, Spain, the United Kingdom, and the United States. Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is an informative reference for scientists, researchers, and developers in both academia and industry who wish to learn, design, implement, and apply these emerging technologies in HCI in different sectors, with the goal of realizing futuristic technology-driven living and functional smart cities and environments.

Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is a 2-part book set which presents discoveries, innovative ideas, concepts, practical solutions, and novel applications of Human-Computer Interaction (HCI) and related disciplines such as artificial intelligence, machine learning, data mining, computer vision, and natural language processing. The book provides readers with information about HCI trends which are shaping the future of smart, interconnected urban and industrial environments. Contributions are authored by experts and scientists in the field of HCI and its interrelated disciplines from 8 different countries Chile, China, Croatia, India, Iran, Malaysia, Peru, and South Korea. The chapters of this volume present novel and state of the art research works conducted at the intersection of HCI aimed at developing trust, increasing user acceptance, augmenting user performance, and fostering human-technology partnerships. Chapters cover usability testing in digital healthcare systems, user experience testing of handicapped children and assistive technologies for visually impaired users and a gamified user experience design for learning. The volume also presents a review of twitter usability testing among Indian users, along with specific cases of arthritis diagnostic systems, meteorological draught analysis and the role of EUPS in improving GUI design to improve the user experience. Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is an informative reference for scientists, researchers, and developers in both academia and industry who wish to learn, design, implement, and apply these emerging technologies in HCI in different sectors, with the goal of realizing futuristic technology-driven living and functional smart cities and environments.

How to Design Optimization Algorithms by Applying Natural Behavioral Patterns is a guide book that introduces readers to optimization algorithms based on natural language processing. Readers will learn about the basic concept of optimization, optimization algorithm fundamentals and the methods employed to formulate natural ideas and behaviors into algorithms. Readers will learn how to create their own algorithm from the information provided in the text. The book is a simple reference for students and programming enthusiasts who are interested in learning about optimization and the process of designing algorithms designed to mimic natural phenomena. The information will also benefit engineers who are learning about optimization techniques.

Artificial Intelligence, Machine Learning and User Interface Design is a forward-thinking compilation of reviews that explores the intersection of Artificial Intelligence (AI), Machine Learning (ML) and User Interface (UI) design. The book showcases recent advancements, emerging trends and the transformative impact of these technologies on digital experiences and technologies. The editors have compiled 14 multidisciplinary topics contributed by over 40 experts, covering foundational concepts of AI and ML, and progressing through intricate discussions on recent algorithms and models. Case studies and practical applications illuminate theoretical concepts, providing readers with actionable insights. From neural network architectures to intuitive interface prototypes, the book covers the entire spectrum, ensuring a holistic understanding of the interplay between these domains. Use cases of AI and ML highlighted in the book include categorization and management of waste, taste perception of tea, bird species identification, content-based image retrieval, natural language processing, code clone detection, knowledge representation, tourism recommendation systems and solid waste management. Advances in Artificial Intelligence, Machine Learning and User Interface Design aims to inform a diverse readership, including computer science students, AI and ML software engineers, UI/UX designers, researchers, and tech enthusiasts. ReadershipComputer science students, AI and ML software engineers, UI/UX designers, researchers, and tech enthusiasts.

Sobre a obra Direito Digital : Direito Privado e Internet - 5ª edição - 2024"Esta obra coletiva se baseia em três grandes linhas: situações jurídicas existenciais na sociedade da informação, a proteç

O livro "Inteligencia Artificial: Democracia e Impactos Sociais" traz uma preocupaço central: agendas de pesquisas que esto voltadas para impactos humanos e sociais da inteligencia artificial. O grupo de Humanidades do C4AI, responsavel pela organizaço do livro, tem desempenhado um papel fundamental ao pautar assuntos relevantes como o impacto da inteligencia artificial para o futuro do trabalho, o aumento da desigualdade social, os riscos que envolvem segurança e privacidade, a questo da regulaço, os dilemas eticos envolvidos, os problemas ligados a informaço, aos sistemas politico-partidarios e para a propria democracia, e questes relativas a qualidade da interaço entre agentes inteligentes e humanos.O seminario foi motivado pela necessidade de criar um forum brasileiro multidisciplinar de reflexo sobre como a inteligencia artificial pode contribuir para solapar ou fortalecer as instituiçes democraticas e os principios norteadores da vida em sociedade.O seminario aconteceu entre 13 e 14 de dezembro de 2021, de maneira on-line, e foi precedido por um conjunto de oito webinars, com 21 convidados que apresentaram resultados de pesquisa nas areas de legislaço e regulaço, inovaço, desinformaço, robotica social, implicaçes sociais da inteligencia artificial, segurança publica, educaço, vies algoritmico e (des)igualdade. A visibilidade do seminario alcançou 63 paises e teve mais de 5.445 visualizaçes no conteudo publicado em seu website.

Affective computing is an emerging field situated at the intersection of artificial intelligence and behavioral science. Affective computing refers to studying and developing systems that recognize, interpret, process, and simulate human emotions. It has recently seen significant advances from exploratory studies to real-world applications. Multimodal Affective Computing offers readers a concise overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches in applied affective computing systems and social signal processing. It covers affective facial expression and recognition, affective body expression and recognition, affective speech processing, affective text, and dialogue processing, recognizing affect using physiological measures, computational models of emotion and theoretical foundations, and affective sound and music processing. This book identifies future directions for the field and summarizes a set of guidelines for developing next-generation affective computing systems that are effective, safe, and human-centered.The book is an informative resource for academicians, professionals, researchers, and students at engineering and medical institutions working in the areas of applied affective computing, sentiment analysis, and emotion recognition.

Data Science and Interdisciplinary Research: Recent Trends and Applications is a compelling edited volume that offers a comprehensive exploration of the latest advancements in data science and interdisciplinary research. Through a collection of 10 insightful chapters, this book showcases diverse models of machine learning, communications, signal processing, and data analysis, illustrating their relevance in various fields. Key Themes: Advanced Rainfall Prediction: Presents a machine learning model designed to tackle the challenging task of predicting rainfall across multiple countries, showcasing its potential to enhance weather forecasting.Efficient Cloud Data Clustering: Explains a novel computational approach for clustering large-scale cloud data, addressing the scalability of cloud computing and data analysis.Secure In-Vehicle Communication: Explores the critical topic of secure communication in in-vehicle networks, emphasizing message authentication and data integrity.Smart Irrigation 4.0: Details a decision model designed for smart irrigation, integrating agricultural sensor data reliability analysis to optimize water usage in precision agriculture.Smart Electricity Monitoring: Highlights machine learning-based smart electricity monitoring and fault detection systems, contributing to the development of smart cities.Enhanced Learning Environments: Investigates the effectiveness of mobile learning in higher education, shedding light on the role of technology in shaping modern learning environments.Coastal Socio-Economy Study: Presents a case study on the socio-economic conditions of coastal fishing communities, offering insights into the livelihoods and challenges they face.Signal Noise Removal: Shows filtering techniques for removing noise from ECG signals, enhancing the accuracy of medical data analysis and diagnosis.Deep Learning in Biomedical Research: Explores deep learning techniques for biomedical research, particularly in the realm of gene identification using Next Generation Sequencing (NGS) data.Medical Diagnosis through Machine Learning: Concludes with a chapter on breast cancer detection using machine learning concepts, demonstrating the potential of AI-driven diagnostics.

Machine learning is a subfield of artificial intelligence, broadly defined as a machines capability to imitate intelligent human behavior. Like humans, machines become capable of making intelligent decisions by learning from their past experiences. Machine learning is being employed in many applications, including fraud detection and prevention, self-driving cars, recommendation systems, facial recognition technology, and intelligent computing. This book helps beginners learn the art and science of machine learning. It presens real-world examples that leverage the popular Python machine learning ecosystem, The topics covered in this book include machine learning basics: supervised and unsupervised learning, linear regression and logistic regression, Support Vector Machines (SVMs). It also delves into special topics such as neural networks, theory of generalisation, and bias and fairness in machine learning. After reading this book, computer science and engineering students - at college and university levels - will receive a complete understanding of machine learning fundamentals and will be able to implement neural network solutions in information systems, and also extend them to their advantage.

Video data analytics is rapidly evolving and transforming the way we live in urban environments. Video Data Analytics for Smart City Applications: Methods and Trends, data science experts present a comprehensive review of the latest advances and trends in video analytics technologies and their extensive applications in smart city planning and engineering. The book covers a wide range of topics including object recognition, action recognition, violence detection, and tracking, exploring deep learning approaches and other techniques for video data analytics. It also discusses the key enabling technologies for smart cities and homes and the scope and application of smart agriculture in smart cities. Moreover, the book addresses the challenges and security issues in terahertz band for wireless communication and the empirical impact of AI and IoT on performance management. One contribution also provides a review of the progress in achieving the Jal Jeevan Mission Goals for institutional capacity building in the Indian State of Chhattisgarh. For researchers, computer scientists, data analytics professionals, smart city planners and engineers, this book provides detailed references for further reading and demonstrates how technologies are serving their use-cases in the smart city. The book highlights the advances and trends in video analytics technologies and extensively addresses key themes, making it an essential resource for anyone looking to gain a comprehensive understanding of video data analytics for smart city applications.

Emerging Technologies for Digital Infrastructure Development is a comprehensive and insightful book that reviews the transformative impact of cutting-edge technologies on the digital landscape. It presents 16 topics, from e-commerce consumer behavior to AI applications in healthcare and cybersecurity, this book offers a detailed overview of the role of technology in shaping the modern world. With a focus on bridging the digital divide in education, the book presents innovative solutions to contemporary challenges. The editors also emphasize the importance of privacy and security in an interconnected world by discussing cybersecurity measures and threat detection strategies. The book serves as a valuable resource for technology professionals, researchers, and academics, offering a deep dive into the latest trends and applications in digital infrastructure. It also caters to business leaders, policy makers, and students seeking to understand the transformative potential of emerging technologies.

Pragmatic Internet of Everything (IOE) has emerged as a powerful paradigm for representing and solving complex problems. This reference demonstrates how to coordinate behaviour among a collection of semi-autonomous problem-solving agents: how they can coordinate their knowledge, goals and plans to act together, to solve joint problems, or to make individually or globally rational decisions in the face of uncertainty and multiple, conflicting perspectives. The book presents a collection of articles surveying several major recent developments in Pragmatic Internet of Everything (IOE). The book focuses on issues and challenges that arise in building IOE systems for smart cities in real-world settings. It also presents solutions to the issues faced by system architects. The synthesis of recent thinking, both theoretical and applied, on major IOE problems makes this essential reading for anyone involved in the design and planning of IOT systems for smart cities. Key Features - Summarizes available literature and practical ventures with references - Merges different perspectives on IoT technology thereby giving a 360-degree perspective to the reader - Gives some tips for implementation of practical ventures in this space - Includes an analysis of information gathered from citizens of smart cities