Veljko Milutinovic – författare

Advances in Computers, Volume 116, presents innovations in computer hardware, software, theory, design, and applications, with this updated volume including new chapters on Teaching Graduate Students How to Review Research Articles and How to Respond to Reviewer Comments, ALGATOR - An Automatic Algorithm Evaluation System, Graph Grammar Induction, Asymmetric Windows in Digital Signal Processing, Intelligent Agents in Games: Review With an Open-Source Tool, Using Clickstream Data to Enhance Reverse Engineering of Web Applications, and more.

Contains novel subject matter that is relevant to computer science Includes the expertise of contributing authors Presents an easy to comprehend writing style

The rapidly growing field of Electronic Business on the Internet (EBI) includes a number of subfields, such as electronic commerce, electronic multimedia, workflow technologies, and collaboration technologies. The term electronic business implies a synergistic interaction between a number of different fields with the purpose of maximizing not only the short term profit, but the long term profit as well. In order to establish technical prerequisites for efficient electronic business on the Internet, appropriate system support is needed. This work discusses the topic of system support and its main bottlenecks, stressing explanations that link the newly emerging problems with those found in the general computer architecture field. Attention is dedicated to both hardware and software issues and their symbiotic interactions. "Infrastructure for Electronic Business on the Internet" is a useful reference for researchers and practitioners and may also be used as a text for advanced courses on the topic.

The rapidly growing field of Electronic Business on the Internet (EBI) includes a number of subfields, such as electronic commerce, electronic multimedia, workflow technologies, and collaboration technologies. The term electronic business implies a synergistic interaction between a number of different fields with the purpose of maximizing not only the short term profit, but the long term profit as well. If you are entering the e-business arena, this book should prove a useful starting point. As well as covering all the basics, you can also read about technology details that are the core of every modern e-Business infrastructure (like Digital Signatures and Certificates, SSL, Ad Hoc Networks and the Wireless Internet, Denial of Service attacks and so forth). "Mastering E-Business Infrastucture", an edited volume, is related to the six best tutorials of the SSGRR (International Conference on Advances in Infrastructure for E-Business, E-Education, E-Science, and E-Medicine on the Internet, organized by Telecom Italia Learning Services).

It is a general trend in computing that computers are becoming ever smaller and ever more interconnected. Sensor networks – large networks of small, simple devices – are a logical extreme of this trend. Wireless sensor networks (WSNs) are attracting an increasing degree of research interest, with a growing number of industrial applications starting to emerge. Two of these applications, personal health monitoring and emergency/disaster recovery, are the focus of the European Commission project ProSense: Promote, Mobilize, Reinforce and Integrate Wireless Sensor Networking Research and Researchers.This hands-on introduction to WSN systems development presents a broad coverage of topics in the field, contributed by researchers involved in the ProSense project. An emphasis is placed on the practical knowledge required for the successful implementation of WSNs. Divided into four parts, the first part covers basic issues of sensors, software, and position-based routing protocols. Part two focuses on multidisciplinary issues, including sensor network integration, mobility aspects, georouting, medical applications, and vehicular sensor networks. The remaining two parts present case studies and further applications.Topics and features: presents a broad overview of WSN technology, including an introduction to sensor and sensing technologies; contains an extensive section on case studies, providing details of the development of a number of WSN applications; discusses frameworks for WSN systems integration, through which WSN technology will become fundamental to the Future Internet concept; investigates real-world applications of WSN systems in medical and vehicular sensor networks; with a Foreword by the Nobel Laurate Professor Martin Perl of Stanford University.Providing holistic coverage of WSN technology, this text/reference will enable graduate students of computer science, electrical engineering and telecommunications to master the specific domains ofthis emerging area. The book will also be a valuable resource for researchers and practitioners interested in entering the field.

As a foreword, here we publish an email letter of Late Professor Herb Simon, Nobel Laureate, that he wrote on the occasion ofthe death of the fatherofa friend. This letterofcondolence, more than any other wisdom, tells about the essence of the process of scientific creation, which is so important for both, the specific subject being covered by this book, and for the general science. When asked to address an SSGRR conference in Italy, prior to his death, Professor Herb Simon agreed that these lines be presented to all those who are interested in understanding the real essence oftheir own scientific struggle. Dear Professor Milutinovic: I want to extend my deepest sympathy to you and your family on the death of your father. His career was a very distinguished one, and his life spanned a most complex and difficult sequence of epochs in your country's history. Our generation (I am just a year younger than he was), like all its predecessors, leaves many tasks - hopefully no more than it inherited - for the next generation to take up; but even knowing that it must be so does not remove one's senseofloss in the parting.

Design is an art form in which the designer selects from a myriad of alternatives to bring an "optimum" choice to a user. In many complex of "optimum" is difficult to define. Indeed, the users systems the notion themselves will not agree, so the "best" system is simply the one in which the designer and the user have a congruent viewpoint. Compounding the design problem are tradeoffs that span a variety of technologies and user requirements. The electronic business system is a classically complex system whose tradeoff criteria and user views are constantly changing with rapidly developing underlying technology. Professor Milutinovic has chosen this area for his capstone contribution to the computer systems design. This book completes his trilogy on design issue in computer systems. His first work, "Surviving the Design of a 200 MHz RISC Microprocessor" (1997) focused on the tradeoffs and design issues within a processor. His second work, "Surviving the Design of Microprocessor and Multiprocessor Systems" (2000) considers the design issues involved with assembling a number of processors into a coherent system. Finally, this book generalizes the system design problem to electronic commerce on the Internet, a global system of immense consequence.

Recording knowledge in a common framework that would make it possible to seamlessly share global knowledge remains an important challenge for researchers. This brief examines several ideas about the representation of knowledge addressing this challenge. A widespread general agreement is followed that states uniform knowledge representation should be achievable by using ontologies populated with concepts. A separate chapter is dedicated to each of the three introduced topics, following a uniform outline: definition, organization, and use. This brief is intended for those who want to get to know the field of knowledge representation quickly, or would like to be up to date with current developments in the field. It is also useful for those dealing with implementation as examples of numerous operational systems are also given.

This book presents an overview of a variety of contemporary statistical, mathematical and computer science techniques which are used to further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets of clinical data typically found in patient’s medical records, image mining, medical mining, data mining and machine learning applied to generic genomic data and more.This work also introduces modeling behavior of cancer cells, multi-scale computational models and simulations of blood flow through vessels by using patient-specific models. The authors cover different imaging techniques used to generate patient-specific models. This is used in computational fluid dynamics software to analyze fluid flow. Case studies are provided at the end of each chapter.Professionals and researchers with quantitative backgrounds will find Computational Medicine in Data Mining and Modeling useful as a reference. Advanced-level students studying computer science, mathematics, statistics and biomedicine will also find this book valuable as a reference or secondary text book.

This book presents an overview of a variety of contemporary statistical, mathematical and computer science techniques which are used to further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets of clinical data typically found in patient’s medical records, image mining, medical mining, data mining and machine learning applied to generic genomic data and more.This work also introduces modeling behavior of cancer cells, multi-scale computational models and simulations of blood flow through vessels by using patient-specific models. The authors cover different imaging techniques used to generate patient-specific models. This is used in computational fluid dynamics software to analyze fluid flow. Case studies are provided at the end of each chapter.Professionals and researchers with quantitative backgrounds will find Computational Medicine in Data Mining and Modeling useful as a reference. Advanced-level students studying computer science, mathematics, statistics and biomedicine will also find this book valuable as a reference or secondary text book.

It is a general trend in computing that computers are becoming ever smaller and ever more interconnected. Sensor networks – large networks of small, simple devices – are a logical extreme of this trend. Wireless sensor networks (WSNs) are attracting an increasing degree of research interest, with a growing number of industrial applications starting to emerge. Two of these applications, personal health monitoring and emergency/disaster recovery, are the focus of the European Commission project ProSense: Promote, Mobilize, Reinforce and Integrate Wireless Sensor Networking Research and Researchers.This hands-on introduction to WSN systems development presents a broad coverage of topics in the field, contributed by researchers involved in the ProSense project. An emphasis is placed on the practical knowledge required for the successful implementation of WSNs. Divided into four parts, the first part covers basic issues of sensors, software, and position-based routing protocols. Part two focuses on multidisciplinary issues, including sensor network integration, mobility aspects, georouting, medical applications, and vehicular sensor networks. The remaining two parts present case studies and further applications.Topics and features: presents a broad overview of WSN technology, including an introduction to sensor and sensing technologies; contains an extensive section on case studies, providing details of the development of a number of WSN applications; discusses frameworks for WSN systems integration, through which WSN technology will become fundamental to the Future Internet concept; investigates real-world applications of WSN systems in medical and vehicular sensor networks; with a Foreword by the Nobel Laurate Professor Martin Perl of Stanford University.Providing holistic coverage of WSN technology, this text/reference will enable graduate students of computer science, electrical engineering and telecommunications to master the specific domains ofthis emerging area. The book will also be a valuable resource for researchers and practitioners interested in entering the field.

This useful text/reference describes the implementation of a varied selection of algorithms in the DataFlow paradigm, highlighting the exciting potential of DataFlow computing for applications in such areas as image understanding, biomedicine, physics simulation, and business.The mapping of additional algorithms onto the DataFlow architecture is also covered in the following Springer titles from the same team: DataFlow Supercomputing Essentials: Research, Development and Education, DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, and Guide to DataFlow Supercomputing.Topics and Features: introduces a novel method of graph partitioning for large graphs involving the construction of a skeleton graph; describes a cloud-supported web-based integrated development environment that can develop and run programs without DataFlow hardware owned by the user; showcases a new approach for the calculation of the extrema of functions in one dimension, by implementing the Golden Section Search algorithm; reviews algorithms for a DataFlow architecture that uses matrices and vectors as the underlying data structure; presents an algorithm for spherical code design, based on the variable repulsion force method; discusses the implementation of a face recognition application, using the DataFlow paradigm; proposes a method for region of interest-based image segmentation of mammogram images on high-performance reconfigurable DataFlow computers; surveys a diverse range of DataFlow applications in physics simulations, and investigates a DataFlow implementation of a Bitcoin mining algorithm.This unique volume will prove a valuable reference for researchers and programmers of DataFlow computing, and supercomputing in general. Graduate and advanced undergraduate students will also find that the book serves as an ideal supplementary text for courses on Data Mining, Microprocessor Systems, and VLSISystems.

This useful text/reference describes the implementation of a varied selection of algorithms in the DataFlow paradigm, highlighting the exciting potential of DataFlow computing for applications in such areas as image understanding, biomedicine, physics simulation, and business.The mapping of additional algorithms onto the DataFlow architecture is also covered in the following Springer titles from the same team: DataFlow Supercomputing Essentials: Research, Development and Education, DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, and Guide to DataFlow Supercomputing.Topics and Features: introduces a novel method of graph partitioning for large graphs involving the construction of a skeleton graph; describes a cloud-supported web-based integrated development environment that can develop and run programs without DataFlow hardware owned by the user; showcases a new approach for the calculation of the extrema of functions in one dimension, by implementing the Golden Section Search algorithm; reviews algorithms for a DataFlow architecture that uses matrices and vectors as the underlying data structure; presents an algorithm for spherical code design, based on the variable repulsion force method; discusses the implementation of a face recognition application, using the DataFlow paradigm; proposes a method for region of interest-based image segmentation of mammogram images on high-performance reconfigurable DataFlow computers; surveys a diverse range of DataFlow applications in physics simulations, and investigates a DataFlow implementation of a Bitcoin mining algorithm.This unique volume will prove a valuable reference for researchers and programmers of DataFlow computing, and supercomputing in general. Graduate and advanced undergraduate students will also find that the book serves as an ideal supplementary text for courses on Data Mining, Microprocessor Systems, and VLSISystems.

This unique text/reference describes an exciting and novel approach to supercomputing in the DataFlow paradigm. The major advantages and applications of this approach are clearly described, and a detailed explanation of the programming model is provided using simple yet effective examples. The work is developed from a series of lecture courses taught by the authors in more than 40 universities across more than 20 countries, and from research carried out by Maxeler Technologies, Inc. Topics and features: presents a thorough introduction to DataFlow supercomputing for big data problems; reviews the latest research on the DataFlow architecture and its applications; introduces a new method for the rapid handling of real-world challenges involving large datasets; provides a case study on the use of the new approach to accelerate the Cooley-Tukey algorithm on a DataFlow machine; includes a step-by-step guide to the web-based integrated development environment WebIDE.

This unique text/reference describes an exciting and novel approach to supercomputing in the DataFlow paradigm. The major advantages and applications of this approach are clearly described, and a detailed explanation of the programming model is provided using simple yet effective examples. The work is developed from a series of lecture courses taught by the authors in more than 40 universities across more than 20 countries, and from research carried out by Maxeler Technologies, Inc. Topics and features: presents a thorough introduction to DataFlow supercomputing for big data problems; reviews the latest research on the DataFlow architecture and its applications; introduces a new method for the rapid handling of real-world challenges involving large datasets; provides a case study on the use of the new approach to accelerate the Cooley-Tukey algorithm on a DataFlow machine; includes a step-by-step guide to the web-based integrated development environment WebIDE.

In this book, the authors describe how Mind Genomics works - a revolutionary marketing method that combines the three sciences of Mathematics, Psychology, and Economics - in a masterful way. Mind Genomics helps the seller of products and services to know what people are thinking about them before one ever commits to an approach by knowing what is important to the people one is trying to influence. Mind Genomics identifies what aspects of a general topic are important to the audience, how different people in the audience will respond to different aspects of that topic, and how to pinpoint the viewpoints of different audience segments to each aspect of the topic.A careful step by step approach explains what activities ought to be taken and what scenarios must be followed while applying this method in order to find the right way to capture the hearts and minds of targeted audiences. This book explains how Mind Genomics plays a matching game with one’s potential audience and various ways one can present the products and ideas resulting in a systematic approach to influencing others, backed by real data; how one can play with ideas, see patterns imposed by the mind and create new, inductive, applied sciences of the mind, measuring the world using the mind of man as the yardstick. In details it describes how everyday thought is transferred into actionable data and results.Whether one is a senior marketer for a large corporation, a professor at a university, or administrator at a hospital, one could use Mind Genomics to learn how to transform available information into actionable steps that will increase the products sales, or increase the number of interested students for a new university program, or the number of satisfied patients in the hospital with their medical conditions kept at highest levels after leaving it.  Mind Genomics was first introduced by Dr. Howard Moskowitz, an alumnus of Harvard University and the father of Horizontal Segmentation - a widely accepted business model for targeted marketing and profit maximization.

This illuminating text/reference reviews the fundamentals of programming for effective DataFlow computing. The DataFlow paradigm enables considerable increases in speed and reductions in power consumption for supercomputing processes, yet the programming model requires a distinctly different approach. The algorithms and examples showcased in this book will help the reader to develop their understanding of the advantages and unique features of this methodology.This work serves as a companion title to DataFlow Supercomputing Essentials: Research, Development and Education, which analyzes the latest research in this area, and the training resources available.Topics and features: presents an implementation of Neural Networks using the DataFlow paradigm, as an alternative to the traditional ControlFlow approach; discusses a solution to the three-dimensional Poisson equation, using the Fourier method and DataFlow technology; examines how the performance of the Binary Search algorithm can be improved through implementation on a DataFlow architecture; reviews the different way of thinking required to best configure the DataFlow engines for the processing of data in space flowing through the devices; highlights how the DataFlow approach can efficiently support applications in big data analytics, deep learning, and the Internet of Things.This indispensable volume will benefit all researchers interested in supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be an invaluable resource.

This informative text/reference highlights the potential of DataFlow computing in research requiring high speeds, low power requirements, and high precision, while also benefiting from a reduction in the size of the equipment. The cutting-edge research and implementation case studies provided in this book will help the reader to develop their practical understanding of the advantages and unique features of this methodology.This work serves as a companion title to DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, which reviews the key algorithms in this area, and provides useful examples.Topics and features: reviews the library of tools, applications, and source code available to support DataFlow programming; discusses the enhancements to DataFlow computing yielded by small hardware changes, different compilation techniques, debugging, and optimizing tools; examines when a DataFlow architecture is best applied, and for which types of calculation; describes how converting applications to a DataFlow representation can result in an acceleration in performance, while reducing the power consumption; explains how to implement a DataFlow application on Maxeler hardware architecture, with links to a video tutorial series available online. This enlightening volume will be of great interest to all researchers investigating supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be a helpful reference.

This illuminating text/reference reviews the fundamentals of programming for effective DataFlow computing. The DataFlow paradigm enables considerable increases in speed and reductions in power consumption for supercomputing processes, yet the programming model requires a distinctly different approach. The algorithms and examples showcased in this book will help the reader to develop their understanding of the advantages and unique features of this methodology.This work serves as a companion title to DataFlow Supercomputing Essentials: Research, Development and Education, which analyzes the latest research in this area, and the training resources available.Topics and features: presents an implementation of Neural Networks using the DataFlow paradigm, as an alternative to the traditional ControlFlow approach; discusses a solution to the three-dimensional Poisson equation, using the Fourier method and DataFlow technology; examines how the performance of the Binary Search algorithm can be improved through implementation on a DataFlow architecture; reviews the different way of thinking required to best configure the DataFlow engines for the processing of data in space flowing through the devices; highlights how the DataFlow approach can efficiently support applications in big data analytics, deep learning, and the Internet of Things.This indispensable volume will benefit all researchers interested in supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be an invaluable resource.