Springer Handbook of Bio-/Neuro-Informatics


Book Description

The Springer Handbook of Bio-/Neuro-Informatics is the first published book in one volume that explains together the basics and the state-of-the-art of two major science disciplines in their interaction and mutual relationship, namely: information sciences, bioinformatics and neuroinformatics. Bioinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. Neuroinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. The text contains 62 chapters organized in 12 parts, 6 of them covering topics from information science and bioinformatics, and 6 cover topics from information science and neuroinformatics. Each chapter consists of three main sections: introduction to the subject area, presentation of methods and advanced and future developments. The Springer Handbook of Bio-/Neuroinformatics can be used as both a textbook and as a reference for postgraduate study and advanced research in these areas. The target audience includes students, scientists, and practitioners from the areas of information, biological and neurosciences. With Forewords by Shun-ichi Amari of the Brain Science Institute, RIKEN, Saitama and Karlheinz Meier of the University of Heidelberg, Kirchhoff-Institute of Physics and Co-Director of the Human Brain Project.




Springer Handbook of Computational Intelligence


Book Description

The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.




The Road from Nanomedicine to Precision Medicine


Book Description

The enormous advances in nanomedicine and precision medicine in the past two decades necessitated this comprehensive reference, which can be relied upon by researchers, clinicians, pharmaceutical scientists, regulators, policymakers, and lawyers alike. This standalone, full-color resource broadly surveys innovative technologies and advances pertaining to nanomedicine and precision medicine. In addition, it addresses often-neglected yet crucial areas such as translational medicine, intellectual property law, ethics, policy, FDA regulatory issues, nano-nomenclature, and artificial nano-machines—all accomplished in a user-friendly, broad yet interconnected format. The book is essential reading for the novice and the expert alike in diverse fields such as medicine, law, pharmacy, genomics, biomedical sciences, ethics, and regulatory science. The book’s multidisciplinary approach will attract a global audience and serve as a valuable reference resource for industry, academia, and government.




Principles of Institutional and Evolutionary Political Economy


Book Description

This is the very first book to explicitly both detail the core general principles of institutional and evolutionary political economy and also apply the principles to current world problems such as the coronavirus crisis, climate change, corruption, AI-Robotics, policy-governance, money and financial instability, terrorism, AIDS-HIV and the nurturance gap. No other book has ever detailed explicitly such core principles and concepts nor ever applied them explicitly to numerous current major problems. The core general principles and concepts in this book, which are outlined and detailed include historical specificity & evolution; hegemony & uneven development; circular & cumulative causation; heterogeneous groups & agents; contradiction & creative destruction; uncertainty; innovation; and policy & governance. This book details the nature of how these principles and concepts can be used to explain current critical issues and problems throughout the world. This book includes updated chapters that have won two journal research Article of the Year Awards on climate change (one from the European Association for Evolutionary Political Economy, EAEPE); as well as a Presidential address to the Association for Evolutionary Economics (AFEE) on corruption. The structure of the book starts with two chapters on the principles of institutional and evolutionary political economy: firstly their history, and secondly a chapter on the contemporary nature of the principles and concepts. This is followed by nine chapters applying some of the core principles to current world problems such as the coronacrisis, climate change, corruption, AI-robotics, policy, money & financial instability, terrorism, HIV-AIDS and the nurturance gap. The book finishes with a conclusion, a glossary of major terms and an index. The author’s principles are well established in the literature and this book provides a detailed exposition of them and their application.




Neural Information Processing


Book Description

The seven-volume set of LNCS 11301-11307 constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The 5th volume, LNCS 11305, is organized in topical sections on prediction; pattern recognition; and word, text and document processing.




Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence


Book Description

Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.




Analyzing Network Data in Biology and Medicine


Book Description

Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.




Artificial Intelligence in the Age of Neural Networks and Brain Computing


Book Description

Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. - Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN - Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making - Edited by high-level academics and researchers in intelligent systems and neural networks - Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks




Neural Information Processing


Book Description

The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.




Springer Handbook of Nanotechnology


Book Description

This comprehensive handbook has become the definitive reference work in the field of nanoscience and nanotechnology, and this 4th edition incorporates a number of recent new developments. It integrates nanofabrication, nanomaterials, nanodevices, nanomechanics, nanotribology, materials science, and reliability engineering knowledge in just one volume. Furthermore, it discusses various nanostructures; micro/nanofabrication; micro/nanodevices and biomicro/nanodevices, as well as scanning probe microscopy; nanotribology and nanomechanics; molecularly thick films; industrial applications and nanodevice reliability; societal, environmental, health and safety issues; and nanotechnology education. In this new edition, written by an international team of over 140 distinguished experts and put together by an experienced editor with a comprehensive understanding of the field, almost all the chapters are either new or substantially revised and expanded, with new topics of interest added. It is an essential resource for anyone working in the rapidly evolving field of key technology, including mechanical and electrical engineers, materials scientists, physicists, and chemists.