الصفحة 10
الصفحة 10
Hypercomputation : Computing Beyond the Church-Turing Barrier
Hypercomputation is a relatively new theory of computation which treats computing methods and devices that transcend the Church-Turing thesis. This book will provide a thorough description of the field of hypercomputation, covering all attempts at devising conceptual hypermachines and all new promising computational paradigms that may eventually lead to the construction of a hypermachine.Readers will reach a deeper understanding of what computability is and why the Church-Turing thesis poses an arbitrary limit to what actually can be computed. Hypercomputing is quite a novel idea, and therefore the book is interesting to the reader in its own right.
Hydrogen-based Autonomous Power Systems : Techno-economic Analysis of the Integration of Hydrogen in Autonomous Power Systems
Hydrogen-based Autonomous Power Systems contains a review of hydrogen technologies suitable for RES-based autonomous power systems, presents already-existing demonstration hydrogen-based power systems, and provides concrete examples for the integration of hydrogen technologies into existing autonomous power systems.
Hybrid metaheuristics ; 4th International Workshop,HM 2007, Dortmund, Germany, October 8-9, 2007, Proceedings
This book constitutes the refereed proceedings of the 4th International Workshop on Hybrid Metaheuristics, HM 2007, held in Dortmund, Germany. The 14 revised full papers discuss specific aspects of hybridization of metaheuristics, hybrid metaheuristics design, development and testing.
Hybrid Artificial Intelligent Systems ; 15th International Conference, HAIS 2020, Gijón, Spain, November 11-13, 2020, Proceedings
This book constitutes the refereed proceedings of the 15th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2020, held in Gijón, Spain, in November 2020. The 65 regular papers presented in this book were carefully reviewed and selected from 106 submissions. The papers are grouped into these topics: advanced data processing and visualization techniques; bio-inspired models and optimization; learning algorithms; data mining, knowledge discovery and big data; and hybrid artificial intelligence applications.
Human Interaction with Machines ; Proceedings of the 6th International Workshop held at the Shanghai JiaoTong University, March 15-16, 2005
The International Workshop on “Human Interaction with Machines” is the sixth in a successful series of workshops that were established by Shanghai Jiao Tong University and Technische Universität Berlin. The goal of those workshops is to bring together researchers from both universities in order to present research results to an international community. The series of workshops started in 1990 with the International Workshop on “Artificial Intelligence” and was continued with the International Workshop on “Advanced Software Technology” in 1994.
How humans judge machines
80 experimental scenarios help us understand how humans judge AIs as opposed to other humans in the same situation
High-Dynamic-Range (HDR) Vision : Microelectronics, Image Processing, Computer Graphics
This first comprehensive account of high-dynamic-range (HDR) vision focusses on HDR real-time, high-speed digital video recording and also systematically presents HDR video transmission and display. The power of the eye-like, logarithmic optoelectronic conversion concept is demonstrated in machine-vision, medical, automotive, surveillance and cinematic applications, and it is extended to HDR sub-retinal implants for the vision impaired. While the book conveys the overall picture of HDR vision, specific knowledge of microelectronics and image processing is not required. It provides a quantitative summary of the major issues to allow the assessment of the state of the art and a glimpse at future developments. Selected experts share their know-how and expectations in this rapidly evolving art related to the single most powerful of our senses.
High performance computing in science and engineering 06 ; Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2006
In July 2005, the new building for HLRS as well as Stuttgart’s new NEC supercomputer – which is still leading edge in G- many – have been inaugurated. In these days, the SSC Karlsruhe is ?nalizing the installation of a very large high performance system complex from HP, built from hundreds of Intel Itanium processors and more than three th- sand AMD Opteron cores. Additionally, the fast network connection – with a bandwidth of 40Gbit/s and thus one of the frst installations of this kind in Germany – brings the machine rooms of HLRS and SSC Karlsruhe very close together.
High performance computing for drug discovery and biomedicine
Explores the application of high-performance computing (HPC) technologies to computational drug discovery (CDD) and biomedicine. Collects CDD approaches that, together with HPC, can revolutionize and automate drug discovery process, such as knowledge graphs, natural language processing (NLP), Bayesian optimization, automated virtual screening platforms, alchemical free energy workflows, fragment-molecular orbitals (FMO), HPC-adapted molecular dynamic simulation (MD-HPC), and the potential of cloud computing for drug discovery. And delves into computational algorithms and workflows for biomedicine, featuring an HPC framework to assess drug-induced arrhythmic risk, digital patient applications relevant to the clinic, virtual human simulations, cellular and whole-body blood flow modeling for stroke treatments, prediction of the femoral bone strength from CT data, and many more subjects.
High accuracy detection of mobile malware using machine learning
As increasingly sophisticated and evasive malware attacks continue to emerge, more effective detection solutions to tackle the problem are being sought through the application of advanced machine learning techniques. This reprint presents several advances in the field including: a new method of generating adversarial samples through byte sequence feature extraction using deep learning; a state-of-the-art comparative evaluation of deep learning approaches for mobile botnet detection; a novel visualization-based approach that utilizes images for Android botnet detection; a study on the detection of drive-by exploits in images using deep learning; etc. Furthermore, this reprint presents state-of-the-art reviews about machine learning-based detection techniques that will increase researchers' knowledge in the field and enable them to identify future research and development directions.
Hierarchical Bayesian Optimization Algorithm : Toward a New Generation of Evolutionary Algorithms
This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The book focuses on two algorithms that replace traditional variation operators of evolutionary algorithms by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). BOA and hBOA are theoretically and empirically shown to provide robust and scalable solution for broad classes of nearly decomposable and hierarchical problems. A theoretical model is developed that estimates the scalability and adequate parameter settings for BOA and hBOA. The performance of BOA and hBOA is analyzed on a number of artificial problems of bounded difficulty designed to test BOA and hBOA on the boundary of their design envelope.
Hebbian Learning and Negative Feedback Networks
This book is the outcome of a decade’s research into a speci?c architecture and associated learning mechanism for an arti?cial neural network: the - chitecture involves negative feedback and the learning mechanism is simple Hebbian learning. The research began with my own thesis at the University of Strathclyde, Scotland, under Professor Douglas McGregor which culminated with me being awarded a PhD in 1995 [52], the title of which was “Negative Feedback as an Organising Principle for Arti?cial Neural Networks”. Naturally enough, having established this theme, when I began to sup- vise PhD students of my own, we continued to develop this concept and this book owes much to the research and theses of these students at the Applied Computational Intelligence Research Unit in the University of Paisley . All of Chapters 3 to 8 deal with single stream arti?cial neural networks.
Healthcare solutions using machine learning and informatics
Covers novel and innovative solutions for the healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, intelligent IoT-based solutions for medical image analysis, medical big data processing, disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence. The wide variety of topics covered include: Artificial Intelligence in healthcare Machine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19 Big data analytics solutions for healthcare data processing Reliable biomedical applications using AI models Intelligent IoT in healthcare. The book explains fundamental concepts as well as the advanced use cases illustrating how to apply emerging technologies such as machine learning, AI models, data informatics into practice to tackle challenges in the field of healthcare with real-world scenarios. Chapters contributed by noted academicians and professionals examine various solutions, frameworks, applications, case studies, and best practices in the healthcare domain
Health Information Science ; 9th International Conference, HIS 2020, Amsterdam, The Netherlands, October 20–23, 2020, Proceedings
This book constitutes the proceedings of the 9th International Conference on Health Information Science, HIS 2020, which took place in Amsterdam, The Netherlands, during October 20-23, 2020. The 11 full papers and 6 short papers presented in this volume were carefully reviewed and selected from 62 submissions. They were organized in topical sections named: mental health; medical record processing; medical information systems; medical diagnosis with machine learning; and health behavior and medication.
Hands-on question answering systems with BERT : Applications in neural networks and natural language processing
Begins with an overview of the technology landscape behind BERT. It takes you through the basics of NLP, including natural language understanding with tokenization, stemming, and lemmatization, and bag of words. Next, you’ll look at neural networks for NLP starting with its variants such as recurrent neural networks, encoders and decoders, bi-directional encoders and decoders, and transformer models. Along the way, you’ll cover word embedding and their types along with the basics of BERT. After this solid foundation, you’ll be ready to take a deep dive into BERT algorithms such as masked language models and next sentence prediction. You’ll see different BERT variations followed by a hands-on example of a question answering system. You will: Examine the fundamentals of word embeddings / Apply neural networks and BERT for various NLP tasks / Develop a question-answering system from scratch / Train question-answering systems for your own data
Handbook of marketing analytics : Methods and applications in marketing management, public policy, and litigation support
Shows analytical marketing methods and their high-impact real-life applications in marketing management, Public policy, and litigation support. Fourteen chapters present an overview of specific marketing analytic methods in technical detail, While 22 case studies present thorough examples of the use of each method. Multidisciplinary in scope, This handbook covers experimental methods, non-experimental methods, and their digital-era extensions. It explores topics such as : Classical and bayesian econometrics, Causality, Machine learning, Optimization, And recent advancements in conjoint analysis.
Handbook of Geometric Computing : Applications in Pattern Recognition, Computer Vision, Neuralcomputing, and Robotics
Many computer scientists, engineers, applied mathematicians, and physicists use geometry theory and geometric computing methods in the design of perception-action systems, intelligent autonomous systems, and man-machine interfaces. This handbook brings together the most recent advances in the application of geometric computing for building such systems, with contributions from leading experts in the important fields of neuroscience, neural networks, image processing, pattern recognition, computer vision, uncertainty in geometric computations, conformal computational geometry, computer graphics and visualization, medical imagery, geometry and robotics, and reaching and motion planning. For the first time, the various methods are presented in a comprehensive, unified manner.
Handbook of Digital Face Manipulation and Detection: From DeepFakes to Morphing Attacks
Provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area.
Handbook of Biochips : Integrated Circuits and Systems for Biology and Medicine
This book provides a broad survey of the field of biochips, including fundamentals of microelectronics and biomaterials interaction with various, living tissues, as well as numerous, diverse applications. Although a wide variety of biochips will be described, there will be a focus on those at the brain-machine interface. Analysis is included of the relationship between different categories of biochips and their interactions with the body and coverage includes wireless remote control of biochips and arrays of microelectrodes, based on new biomaterials.
Green, pervasive, and cloud computing ; 15th International conference, GPC 2020, Xi'an, China, November 13–15, 2020, Proceedings
This book constitutes the refereed proceedings of the 15th International Conference on Green, Pervasive, and Cloud Computing, GPC 2020, held in Xi'an, China, in November 2020. The 30 full papers presented in this book together with 8 short papers were carefully reviewed and selected from 96 submissions. They cover the following topics: Device-free Sensing; Machine Learning; Recommendation Systems; Urban Computing; Human Computer Interaction; Internet of Things and Edge Computing; Positioning; Applications of Computer Vision; CrowdSensing; and Cloud and Related Technologies.
