Books in Computer science

51-60 of 3080 results in All results

Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition

1st Edition
August 1, 2024
Mohammadali Ahmadi
English
Paperback
9 7 8 - 0 - 4 4 3 - 2 4 0 1 0 - 2
eBook
9 7 8 - 0 - 4 4 3 - 2 4 0 1 1 - 9

Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition: Case Studies and Code Examples presents a package for academic researchers and industries working on water resources and carbon capture and storage. This book contains fundamental knowledge on artificial intelligence related to oil and gas sustainability and the industry’s pivot to support the energy transition and provides practical applications through case studies and coding flowcharts, addressing gaps and questions raised by academic and industrial partners, including energy engineers, geologists, and environmental scientists. This timely publication provides fundamental and extensive information on advanced AI applications geared to support sustainability and the energy transition for the oil and gas industry.

Towards Neuromorphic Machine Intelligence

1st Edition
August 1, 2024
Hong Qu
English
Paperback
9 7 8 - 0 - 4 4 3 - 3 2 8 2 0 - 6
eBook
9 7 8 - 0 - 4 4 3 - 3 2 8 2 1 - 3

Towards Neuromorphic Machine Intelligence: Spike-Based Representation, Learning and Applications provides readers with in-depth understanding of Spiking Neural Networks (SNN), which is a burgeoning research branch of Artificial Neural Networks (ANN), AI, and Machine Learning that sits at the heart of the integration between Computer Science and Neural Engineering. In recent years, neural networks have re-emerged in relation to AI, representing a well-grounded paradigm rooted in disciplines from physics and psychology to information science and engineering. This book represents one of the established cross-over areas where neurophysiology, cognition, and neural engineering coincide with the development of new Machine Learning and AI paradigms. There are many excellent theoretical achievements in neuron models, learning algorithms, network architecture and so on. But these achievements are numerous and scattered, with a lack of straightforward systematic integration, making it difficult for researchers to assimilate and apply. As the third generation of Artificial Neural Networks (ANN), Spiking Neural Networks (SNN) simulate the neuron dynamics and information transmission in a biological neural system in more detail, which is a cross-product of computer science and neuroscience. The primary target audience of this book is divided into two categories: artificial intelligence researchers who know nothing about SNN, and researchers who know a lot about SNN. The former needs to acquire fundamental knowledge of SNN, but the challenge is that a large number of existing literatures on SNN only slightly mention the basic knowledge of SNN, or are too superficial, and this book gives a systematic explanation from scratch. The latter needs to learn about some novel research achievements in the field of SNN, and this book introduces the latest research results on different aspects of SNN and provides detailed simulation processes to facilitate readers' replication. In addition, the book introduces neuromorphic hardware architecture as a further extension of the SNN system. The book starts with the birth and development of SNN, and then introduces the main research hotspots, including spiking neuron models, learning algorithms, network architectures, and neuromorphic hardware. Therefore, the book provides readers with easy access to both the foundational concepts and recent research findings in SNN.

Information Modeling and Relational Databases

3rd Edition
July 1, 2024
Terry Halpin + 1 more
English
Hardback
9 7 8 - 0 - 4 4 3 - 2 3 7 9 0 - 4
eBook
9 7 8 - 0 - 4 4 3 - 2 3 7 9 1 - 1

Information Modeling and Relational Databases, Third Edition, provides thorough coverage of information modeling approaches, including object-role modeling (ORM), entity-relationship (ER) modeling, and the unified modeling language (UML). It shows how to map models developed with those approaches to a variety of relational and nonrelational database systems, including document databases, column-oriented databases, graph databases, and deductive databases. Process and state modeling, ontological modeling, and metamodeling are also covered. For this new edition, the coverage of ORM, ER, UML, SQL, OWL, and BPMN has been thoroughly updated to include their latest versions. A significant amount of new material has been added. Various data file formats such as CSV, XML, JSON, YAML, and some other markup languages are now covered, and a more thorough treatment is provided for nonrelational databases, especially NoSQL. One of the major features of the book is its large number of exercises, which have been thoroughly class-tested. This book is intended for anyone with a stake in the accuracy and efficacy of databases such as systems analysts, information modelers, database designers and administrators, and programmers.

Gesture Recognition

1st Edition
July 1, 2024
Qiguang Miao + 3 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 2 8 9 5 9 - 0
eBook
9 7 8 - 0 - 4 4 3 - 2 8 9 6 0 - 6

Gesture Recognition: Theory and Applications covers this important topic in computer science and language technology that has a goal of interpreting human gestures via mathematical algorithms. The book begins by examining the computer vision-based gesture recognition method, focusing on the theory and related research results of various recent gesture recognition technologies. The book takes the evolutions of gesture recognition technology as a clue, systematically introducing gesture recognition methods based on handcrafted features, convolutional neural networks, recurrent neural networks, multimodal data fusion, and visual attention mechanisms.Three gesture recognition-based HCI (Human Computer Interaction) practical cases are introduced. Finally, the book looks at emerging research trends and application.

Pathophysiology and Treatment of Atherosclerotic Disease in Peripheral Arteries

1st Edition
June 26, 2024
Aloke Virmani Finn
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 3 5 9 3 - 4
eBook
9 7 8 - 0 - 4 4 3 - 1 3 5 9 4 - 1

Pathophysiology and Treatment of Atherosclerotic Disease in Peripheral Arteries is a thorough review of the disease written by experts studying its detection and treatment. These state-of-the-art chapters summarize emerging knowledge about this important area of medicine. The pathophysiology and treatment of peripheral artery (PAD) disease remains poorly understood even by practitioners. Often it is assumed that PAD should be treated in a similar fashion to coronary artery disease (CAD), when in fact recent data suggest a distinct pathophysiology with genetic risk having some but not complete overlap with CAD.This is a novel reference of emerging data on the factors behind its development and progression, detection, and treatment suggest an emerging paradigm for this disease.

Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing

1st Edition
June 17, 2024
Rajesh Kumar Tripathy + 1 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 4 1 4 1 - 6
eBook
9 7 8 - 0 - 4 4 3 - 1 4 1 4 0 - 9

Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing features recent advances in machine learning coupled with new signal processing-based methods for cardiovascular data analysis. Topics in this book include machine learning methods such as supervised learning, unsupervised learning, semi-supervised learning, and meta-learning combined with different signal processing techniques such as multivariate data analysis, time-frequency analysis, multiscale analysis, and feature extraction techniques for the detection of cardiovascular diseases, heart valve disorders, hypertension, and activity monitoring using ECG, PPG, and PCG signals.In addition, this book also includes the applications of digital signal processing (time-frequency analysis, multiscale decomposition, feature extraction, non-linear analysis, and transform domain methods), machine learning and deep learning (convolutional neural network (CNN), recurrent neural network (RNN), transformer and attention-based models, etc.) techniques for the analysis of cardiac signals. The interpretable machine learning and deep learning models combined with signal processing for cardiovascular data analysis are also covered.

Federated Learning for Digital Healthcare Systems

1st Edition
June 3, 2024
Agbotiname Lucky Imoize + 3 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 3 8 9 7 - 3
eBook
9 7 8 - 0 - 4 4 3 - 1 3 8 9 6 - 6

Federated Learning for Digital Healthcare Systems critically examines the key factors that contribute to the problem of applying machine learning in healthcare systems and investigates how federated learning can be employed to address the problem. The book discusses, examines, and compares the applications of federated learning solutions in emerging digital healthcare systems, providing a critical look in terms of the required resources, computational complexity, and system performance.In the first section, chapters examine how to address critical security and privacy concerns and how to revamp existing machine learning models. In subsequent chapters, the book's authors review recent advances to tackle emerging efficient and lightweight algorithms and protocols to reduce computational overheads and communication costs in wireless healthcare systems. Consideration is also given to government and economic regulations as well as legal considerations when federated learning is applied to digital healthcare systems.

Computational Intelligence Techniques for Sustainable Supply Chain Management

1st Edition
June 3, 2024
Sanjoy Kumar Paul + 1 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 8 4 6 4 - 2
eBook
9 7 8 - 0 - 4 4 3 - 1 8 4 6 5 - 9

Computational Intelligence Techniques for Sustainable Supply Chain Management presents state-of-the-art computational intelligence techniques and applications for supply chain sustainability issues and logistic problems, filling the gap between general textbooks on sustainable supply chain management and more specialized literature dealing with methods for computational intelligence techniques. This book focuses on addressing problems in advanced topics in the sustainable supply chain and will appeal to practitioners, managers, researchers, students, and professionals interested in sustainable logistics, procurement, manufacturing, inventory and production management, scheduling, transportation, and supply chain network design.

Advances in Artificial Intelligence

1st Edition
June 3, 2024
Kunal Pal + 2 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 9 0 7 3 - 5
eBook
9 7 8 - 0 - 4 4 3 - 1 5 3 9 2 - 1

Artificial intelligence in healthcare has become one of the best assisting techniques for clinicians in proper diagnosis and surgery. In biomedical applications, artificial intelligence algorithms are explored for bio-signals, such as electrocardiogram (ECG/EKG), electrooculogram (EOG), electromyogram (EMG), electroencephalogram (EEG), blood pressure, heart rate, and nerve conduction, and for bio-imaging modalities, such as computed tomography (CT), cone-beam computed tomography (CBCT), and MRI (magnetic resonance imaging). Advancements in artificial intelligence and big data have increased the development of innovative medical devices in healthcare applications. Advances in Artificial Intelligence: Biomedical Engineering Applications in Signals and Imaging provides an overview of artificial intelligence in biomedical applications, including both bio-signals and bio-imaging modalities. The chapters contain a mathematical formulation of algorithms and their applications in the biomedical eld, including case studies. Biomedical engineers, advanced students, and researchers can use this book to apply their knowledge in artificial intelligence-based processes to biological signals, implement mathematical models and advanced algorithms, and develop AI-based medical devices.

Medical Modelling

3rd Edition
June 1, 2024
Richard Bibb + 2 more
English
Paperback
9 7 8 - 0 - 3 2 3 - 9 5 7 3 3 - 5
eBook
9 7 8 - 0 - 3 2 3 - 9 5 7 3 4 - 2

Medical Modelling: The Application of Advanced Design and Rapid Prototyping Techniques in Medicine, Third Edition provides readers with a thorough update of the core contents, along with key information on innovative imaging techniques, additive manufacturing technologies, and a range of applied case studies. This comprehensive new edition includes new coverage of advanced technologies, such as selective laser melting, electron beam melting, multi jet fusion, and more. The extensive section of peer-reviewed case studies is thoroughly updated and includes additional clinical examples, describing the practical applications of advanced design technologies in surgical, prosthetic, orthotic, dental and research applications.Finally, the book explores the future potential of medical modeling, such as in simulations for training, the development of new medical devices, and more.