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الصفحة 5
Machine learning for biomedical application
Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images.
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Logics of Specification Languages
Dedicated chapters address : the use of ASM (Abstract State Machines) in the classroom; the Event-B modelling method; a methodological guide to CafeOBJ logic; CASL, the Common Algebraic Specification Language; the Duration Calculus; the logic of the RAISE specification language (RSL); the specification language TLA+; the typed logic of partial functions and the Vienna Development Method (VDM); and Z logic and its applications. Each chapter is self-contained, with references, and symbol and concept indexes. Finally, in a unique feature, the book closes with short commentaries on the specification languages written by researchers closely associated with their original development.
List decoding of error-correcting codes : Winning thesis of the 2002 ACM doctoral dissertation competition
Presents some spectacular new results in the area of decoding algorithms for error-correcting codes. Specifically, it shows how the notion of “list-decoding” can be applied to recover from far more errors, for a wide variety of err- correcting codes, than achievable before. A brief bit of background : error-correcting codes are combinatorial str- tures that show how to represent (or “encode”) information so that it is - silient to a moderate number of errors. Speci?cally, an error-correcting code takes a short binary string, called the message, and shows how to transform it into a longer binary string, called the codeword, so that if a small number of bits of the codewordare ?ipped, the resulting string does not look like any other codeword. The maximum number of errorsthat the code is guaranteed to detect, denoted d, is a central parameter in its design. A basic property of such a code is that if the number of errors that occur is known to be smaller than d/2, the message is determined uniquely. This poses a computational problem, called the decoding problem : compute the message from a corrupted codeword, when the number of errors is less than d/2.
Linked Open Data -- Creating Knowledge Out of Interlinked Data : Results of the LOD2 Project
Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 -- Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised leading Linked Open Data research groups, companies, and service providers from across 11 European countries and South Korea.
Laser additive manufacturing: design, materials, processes and applications
Laser-based additive manufacturing (LAM) is a revolutionary advanced digital manufacturing technology developed in recent decades, which is also a key strategic technology for technological innovation and industrial sustainability. This technology unlocks the design and constraints of traditional manufacturing and meets the needs of complex geometry fabrication and high-performance part fabrication. A deeper understanding of the design, materials, processes, structures, properties and applications is desired to produce novel functional devices, as well as defect-free structurally sound and reliable LAM parts.The topics in this Special Issue reprint include macro- and micro-scale additive manufacturing with lasers, such as structure/material design, fabrication, modeling and simulation, in situ characterization of additive manufacturing processes and ex situ materials characterization and performance, with an overview that covers various applications in aerospace, biomedicine, optics and energy.
Java Methods for Financial Engineering : Applications in Finance and Investment
This book is structured around the main theories and models used by practitioners to engineer finance and investment tools. The methods developed and implemented in the text are organized as chapters which cover the core areas.
Computation and the humanities : Towards an oral history of digital humanities
This book addresses the application of computing to cultural heritage and the discipline of Digital Humanities that formed around it. Digital Humanities research is transforming how the Human record can be transmitted, shaped, understood, questioned and imagined and it has been ongoing for more than 70 years. However, we have no comprehensive histories of its research trajectory or its disciplinary development. The authors make a first contribution towards remedying this by uncovering, documenting, and analysing a number of the social, intellectual and creative processes that helped to shape this research from the 1950s until the present day.
Compilers : Principles, techniques & tools
This introduction to compilers is the direct descendant of the well-known book by Aho and Ullman, Principles of Compiler Design. The authors present updated coverage of compilers based on research and techniques that have been developed in the field over the past few years. The book provides a thorough introduction to compiler design and covers topics such as context-free grammars, fine state machines, and syntax-directed translation.
Biomimetic neural learning for intelligent robots : Intelligent systems, cognitive robotics, and neuroscience
This book presents research performed as part of the EU project on biomimeticmultimodal learning in a mirror neuron-based robot (MirrorBot) and contribu-tions presented at the International AI-Workshop on NeuroBotics. The over-all aim of the book is to present a broad spectrum of current research intobiomimetic neural learning for intelligent autonomous robots. In this book we show the development of newtechniques using cell assemblies, associative neural networks, and Hebbian-typelearning in order to associate vision, language and motor concepts. We havedeveloped biomimetic multimodal learning and language instruction in a robotto investigate the task of searching for objects. As well as the research performedin this area for the MirrorBot project, the second part of this book incorporatessignificant contributions from other research in the field of biomimetic robotics.This second part of the book concentrates on the progress made in neuroscienceinspired robotic learning approaches (in short: NeuroBotics). We hope that this book stimulates and encourages new research in this in-teresting and dynamic area.
Biometric systems : Technology, design and performance evaluation
The use of computers to recognize humans from physical and behavioral traits dates back to the digital computer evolution of the 1960s. But even after decades of research and hundreds of major deployments, the field of biometrics remains fresh and exciting as new technologies are developed andoldtechnologiesareimprovedandfieldedinnewapplications.Wor- wide over the past few years,there has been a marked increase in both g- ernment and private sector interest in large-scale biometric deployments for accelerating human–machine processes, efficiently delivering human services, fighting identity fraud and even combating terrorism. The p- pose of this book is to explore the current state of the art in biometrics- tems and it is the system aspect that we have wished to emphasize. By their nature, biometric technologies sit at the exact boundary of the human–machineinterface.Butlikealltechnologies,bythemselvestheycan provide no value until deployed in a system with support hardware, n- work connections, computers, policies and procedures, all tuned together to work withpeople to improve some real business process within a social structure.
Bézier and Splines in image processing and machine vision
Digital image processing and machine vision have grown considerably during the last few decades. Of the various techniques, developed so far splines play a positive and significant role in many of them. This book deals with various image processing and machine vision problems efficiently with splines.
Beginning JBoss Seam : From novice to professional
Reacting to the popularity of Java 2.0 Enterprise Edition™ alternatives such as Ruby on Rails and the enterprise Spring Framework, Red Hat JBoss®, Inc. developed JBoss® Seam, a new open-source lightweight Java™ EE 5-based contextual application development framework. Beginning JBoss® Seam: From Novice to Professional gets you started as the first book on this popular framework.
Balanced Website Design : Optimising Aesthetics, Usability and Purpose
Balanced Website Design (BWD) is a new methodology that fuses the strengths of traditional structured, stepped, and iterative approaches with a sharp focus on defining and achieving the desired characteristics of purpose, usability and aesthetics – absolutely essential requirements for any website. The book includes discussions of new perspectives on usability and aesthetics in the special context of website design. BWD is suitable for all types of websites, for individual and/or team projects, and should prove to be of significant value for even the most experienced of website designers. BWD provides guidance, structure and detailed documentation/process support for the activity of designing and implementing your next website – helping you to maximise its effectiveness and relevance.
Artificial intelligence in image-based screening, diagnostics, and clinical care of cardiopulmonary diseases
In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases.
Artificial intelligence applied to medical imaging and computational biology
Medical imaging and computational biology continuously pose new fundamental medical and biological questions that often give rise to novel challenges in Artificial Intelligence. These research fields present an increasing need for the application of cutting-edge computational approaches that generally involve machine learning or computational intelligence techniques, which can effectively perform bioimage and biosignal processing in different clinical areas.
Application of power electronics converters in smart grids and renewable energy systems
Focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller.
An Integrated Approach to Software Engineering
An Integrated Approach to Software Engineering introduces software engineering to advanced-level undergraduate and graduate students of computer science. It emphasizes a case-study approach whereby a project is developed through the course of the book, illustrating the different activities of software development. The sequence of chapters is essentially the same as the sequence of activities performed during a typical software project. All activities, including quality assurance and control activities, are described in each chapter as integral activities for that phase of development. Similarly, the author carefully introduces appropriate metrics for controlling and assessing the software process. Chapters in this revised edition, updated for today’s standards, include these new features: Software Process, Requirements Analysis and Specification, Software Architecture, Project Planning, Object Oriented Design, Coding,Testing,
Alternative breast imaging : Four model-based approaches
Medical imaging has been transformed over the past 30 years by the advent of computerized tomography (CT), magnetic resonance imaging (MRI), and various advances in x-ray and ultrasonic techniques. An enabling force behind this progress has been the (so far) exponentially increasing power of computers, which has made it practical to explore fundamentally new approaches. In particular, what our group terms "model-based" modalities-which produce tissue property images from data using nonlinear, iterative numerical modeling techniques-have become increasingly feasible. Alternative Breast Imaging: Four Model-Based Approaches explores our research on four such modalities, particularly with regard to imaging of the breast: (1) MR elastography (MRE), (2) electrical impedance spectroscopy (EIS), (3) microwave imaging spectroscopy (MIS), and (4) near infrared spectroscopic imaging (NIS).
Algorithms for Sensor and Ad Hoc Networks : Advanced Lectures
Thousands of mini computers (comparable to a stick of chewing gum in size), equipped with sensors, are deployed in some terrain or other. After activation the sensors form a self-organized network and provide data, for example about a forthcoming earthquake. The trend towards wireless communication increasingly affects electronic devices in almost every sphere of life. Conventional wireless networks rely on infrastructure such as base stations; mobile devices interact with these base stations in a client/server fashion. In contrast, current research is focusing on networks that are completely unstructured, but are nevertheless able to communicate (via several hops) with each other, despite the low coverage of their antennas. Such systems are called sensor or ad hoc networks, depending on the point of view and the application. Wireless ad hoc and sensor networks have gained an incredible research momentum. Computer scientists and engineers of all flavors are embracing the area. Sensor networks have been adopted by researchers in many fields: from hardware technology to operating systems, from antenna design to databases, from information theory to networking, from graph theory to computational geometry.
