River Publishers Series in Information Science and Technology – serie

Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions.This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

The concept of digitalization captures the widespread adoption of digital technologies in our lives, in the structure and functioning of organizations and in the transformation of our economy and society. Digital technologies for data processing and communication underly high-impact innovations including the Internet of Things, wireless multimedia, artificial intelligence, big data, enterprise platforms, social networks and blockchain. These digital innovations not only bring new opportunities for prosperity and wellbeing but also affect our behaviors, activities, and daily lives. They enable and shape new forms of production and new working practices in sectors such as manufacturing, healthcare, logistics and supply chains, energy, and public and business services. Digital innovations are not purely technological but form part of comprehensive systemic innovations of a sociotechnical and networked nature, requiring the alignment of technology, processes, organizations, and humans. Examples are platform-based work, customer driven value creating networks, and urban public service systems. Building on widespread networking, algorithmic decisions and sharing of personal data, these innovations raise intensive societal and ethical debates regarding key issues such as data sovereignty and privacy intrusion, business models based on data surveillance and negative externalization, quality of work and jobs, and market dominance versus regulation. In this context, this book focuses on the implications of digitalization for the domain of work. The book studies the changing nature of work as well as new forms of digitally enabled organizations, work practices and cooperation. The book sheds light on the technological, economic, and political forces shaping the new world of work and on the prospects for human-centric and responsible innovations.

Over the recent years, a considerable amount of effort has been devoted, both in industry and academia, towards the performance modelling, evaluation and prediction of convergent multi-service heterogeneous networks, such as wireless and optical networks, towards the design and dimensioning of the next and future generation Internets.This book follows Heterogeneous Networks: Traffic Engineering, Performance Evaluation Studies and Tools and presents recent advances in networks of diverse technology reflecting the state-of-the-art technology and research achievements in performance modelling, analysis and applications worldwide.Technical topics discussed in the book include:• Multiservice Switching Networks;• Multiservice Switching Networks;• Wireless Ad Hoc Networks;• Wireless Sensor Networks;• Wireless Cellular Networks;• Optical Networks;Heterogeneous Networks:- Performance Modelling and Analysis contains recently extended research papers, which have their roots in the series of the HET-NETs International Working Conferences focusing on the 'Performance Modelling and Evaluation of Heterogeneous Networks' under the auspices of the EU Networks of Excellence Euro-NGI and Euro-FGI.Heterogeneous Networks: Performance Modelling and Analysis is ideal for personnel in computer/communication industries as well as academic staff and master/research students in computer science, operational research, electrical engineering and telecommunication systems and the Internet.KeywordsHeterogeneous networks, performance modelling and analysis, wired networks, wireless networks: ad hoc, sensor and cellular, optical networks, next and future generation Internets.

Considerable attention is currently devoted worldwide towards mobility issues and challenges such as those arising from the integration of the next generation Internet over terrestrial digital TV, mobile user location management and multi-service mobile networks subject to quality of service (QoS) routing.This book follows Heterogeneous Networks: Performance Modelling and Analysis, describes recent advances in mobile and wireless networks and the Internet reflecting the state-of-the-art technology and research achievements in mobility management, performance enhancement, optimal admission control and QoS worldwide.Technical topics discussed in the book include• Mobility Management;• Optimal Admission Control;• Performance Modelling Studies;• Access Network Coverage;• Quality of Service (QoS);Heterogeneous Networks: Mobility Management and Quality of Service contains recently extended research papers, which have their roots in the series of the HET-NETs International Working Conferences focusing on the 'Performance Modelling and Evaluation of Heterogeneous Networks' under the auspices of the EU Networks of Excellence Euro-NGI and Euro-FGI.Heterogeneous Networks: Mobility Management and Quality of Service, is ideal for personnel in computer/communication industries as well as academic staff and master/research students in computer science, operational research, electrical engineering and telecommunication systems.ContentsPreface; Participants of the Reviewing Process;• Traffic Modelling and Characterisation;• Queueing and Interconnection Networks;• Performance Evaluation Studies;• TCP Performance Analysis;• Congestion Control;• Application Layer Multicast;• Numerical and Software Tools; Author Index; Keyword Index.

The research presented in Aspects of Kolmogorov Complexity addresses the fundamental standard of defining randomness as measured by a Martin-Lof level of randomness as found in random sequential binary strings. A classical study of statistics that addresses both a fundamental standard of statistics as well as an applied measure for statistical communication theory. The research points to compression levels in a random state that are greater than is found in current literature. A historical overview of the field of Kolmogorov Complexity and Algorithmic Information Theory, a subfield of Information Theory, is given as well as examples using a radix 3, radix 4, and radix 5 base numbers for both random and non-random sequential strings. The text also examines monochromatic and chromatic symbols and both theoretical and applied aspects of data compression as they relate to the transmission and storage of information. The appendix contains papers on the subject given at conferences and the references are current.ContentsTechnical topics addressed in Aspects of Kolmogorov Complexity include:• Statistical Communication Theory• Algorithmic Information Theory• Kolmogorov Complexity• Martin-Lof Randomness• Compression, Transmission and Storage of Information

At a time when the applications of sensors are in high demand and environmental issues are international priorities, this book on biomedical and environmental sensing provides the technical basis for researchers and students to understand the requirements for biomedical computing and also environmental sensing and to develop solutions in their areas of interests. The book deals with key techniques that need to be understood and also examples of applications of the techniques.Biomedical and environmental sensing are helping to extend the life span of human beings and infrastructures as it has become more and more sensible to understand what is happening for example inside a person, an aircraft, a road network or a bridge and to provide quick response. Several chapters of the book have dealt with the state of the art in biomedical decision support systems in therapeutic medicine. A data driven decision support system and a prototype support system for anaesthetics are major enablers for doctors and nurses to provide efficient and timely response not only to diagnose ailments but also to decide on the preferred approach for solving the problems.The analyses in the chapters are coherently detailed and easy to comprehend. There is a chapter on hypothermia therapy and a hardware probe was also developed and described. Classification of chromosomes is a major aid in DNA analysis and recognition. Thisvaluable insight into a DNA analysis method is provided. Information on heart diseases, onset of heart attacks and failure can be detected through reconstructing electrophysiological information about the surface of the heart. A reconstruction method is described in this book and provides strong foundation for research and training in this life determining area. The remaining chapters on sensing of driver conditions including fatigue peeks into tools and methodologies for understanding both the onset of fatigue and its forms for prevention of accidents in vehicles. The rest of the book gives techniques for planning biomedical and environmental sensor networks and their security.The book will no doubt greatly serve the needs of health professionals, researchers in the health andenvironmental industry and policy makers.Content• Data Driven Therapy Decision Support System• A Prototype Decision Support System for Anesthetists• Development and Testing of a Low Cost, Minimally Invasive Radiofrequency Thermal Probe For Hyperthermia Therapy• Comparative Functional Magnetic Resonance Imaging With Functional Brain Imaging Modalities• Design of a Neural Network Classifier for Separation of Images With Chromosomes• De-Noising of Body Surface Potential Signals• Single Channel Wireless EEG: Proposed Application in Train Drivers• Algorithm of remote monitoring ECG using mobile phone: Conception and implementation• Statistical validation of physiological indicators for non-invasive and hybrid driver drowsiness detection system• Security and Privacy of Wireless Sensor Networks for Biomedical• Key Establishment Scheme for Clustered Distributed Sensor Networks• Planning and Addressing of Wireless Sensor Networks• Sensor Scheduling and Redeployment Mechanisms in Wireless Sensor Networks• On the combination of logistic regression and local probability estimates• Stochastic Deterioration Processes for Bridge Lifetime Assessment

This book provides an overview of advanced digital image and signal processing techniques that are currently being applied in the realm of measurement systems. The book is a selection of extended versions of the best papers presented at the Sixth IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2011 related to this topic and encompass applications that go from multidimensional imaging to evoked potential detection in brain computer interfaces. The objective was to provide a broad spectrum of measurement applications so that the different techniques and approaches could be presented.Digital Image and Signal Processing for Measurement Systems concentrates on signal processing for measurement systems and its objective is to provide a general overview of the area and an appropriate introduction to the topics considered. This is achieved through 10 chapters devoted to current topics of research addressed by different research groups within this area. These 10 chapters reflect advances corresponding to signals of different dimensionality. They go from mostly one dimensional signals in what would be the most traditional area of signal processing realm to RGB signals and to signals of very high dimensionality such as hyperspectral signals that can go up to dimensionalities of more than one thousand. The chapters have been thought out to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area. They provide an overview of some of the problems in the area of signal and image processing for measurement systems and the approaches and techniques that relevant research groups within this area are employing to try to solve them which, in many instances are the state of the art of some of these topics.

In recent years, there has been a growing interest in the fields of pattern recognition and machine vision in academia and industries. New theories have been developed, with new design of technology and systems in both hardware and software. They are widely applied to our daily life to solve real problems in such diverse areas as science, engineering, agriculture, e-commerce, education, robotics, government, medicine, games and animation, medical imaging analysis and diagnosis, military, and national security.The foundation of all this field can be traced back to the late Prof. King-Sun Fu, one of the founding fathers of pattern recognition, who, with visionary insight founded the International Association for Pattern Recognition around 1980. In the almost 30 years since then, the world has witnessed the rapid growth and development of this field. It is probably true to say that most people are affected by, or use applications of pattern recognition in daily life.Today, on the eve of 25th anniversary of the unfortunate and untimely passing of Prof. Fu, we are proud to produce this volume of collected works from world renowned professionals and experts in pattern recognition and machine vision, in honor and memory of the late Prof. King-Sun Fu. We hope this book will help promote further the course, not only of fundamental principles, systems and technologies, but also its vast range of applications to help in solving problems in daily life.ContentsBasic Foundations of Pattern Recognition and Artificial Intelligence, Methodologies of Machine Vision and Image Processing, Intelligent Pattern Recognition Systems, 3-D Object Pattern Analysis, Modelling and Simulation, Analysis of DNA Microarray Gene Expression Data based on Pattern Recognition Methods, PRMV Applications.

India is showing incredibly strong appearance in Information Technology (IT) sector worldwide, but the benefits of IT revolution have not actually percolated into the everyday life of the common man, particularly in rural areas. National E Governance Plan is a major initiative of the Government of India, the first time under which a concerted effort is being made to take Information Technology to the masses in areas of concern to the common man. It aims to make services available online, ensuring that all citizens would have access to them, thereby improving the quality of basic governance on an unprecedented scale.This book attempts to disseminate information about several E Governance projects and possible Data Mining benefits which are the future of good governance in India. Strategic Management of these projects through Data Mining would certainly encourage policy makers to understand better models of E Governance, thorough evaluation of projects, perceptive interrelations between projects, keeping track of the objectives and outcomes and to develop a more collaborative approach towards implementation of the National e- Governance Plan. This revolutionary approach will help the government in assessing the upcoming requirements and developing competencies for further project management, thereby making a difference in the lives of millions. It will help innovators to find out optimum solutions to achieve the end objectives of E Governance. Technical topics discussed in the book include:• E Governance• Fundamental of Data, Data Warehousing, Data Mining, E Governance• World Wide Status of E Governance• Status of E Governance projects in India• E Governance Data Management Framework• E Governance Data Center• Perspective Application of Data Warehousing and Data Mining in E Governance• Case Studies on Education and Health Data Mining• E Governance Data Mining Applications in Various Government Departments, Public Sector, Private Sector• SWOT and PESTLE Analysis for Data Warehousing, Data Mining, E GovernanceData Warehousing and Data Mining are related technologies which have seen a significant boost in the last decades, in a way that many of their concepts and techniques have reached a significant level of maturity. They are applied today in most fields of human activity, from commercial to scientific or industrial areas. Today, decision support, data mining, trend analysis and pattern discovery have a large impact on businesses and science alike. Given this evolution, it is important to understand the potential advantages of Data Mining and Data Warehousing and their positive effects on E Governance applications.The book “E Governance Data Center, Data Warehousing and Data Mining: Vision to Realities” is useful for students, application developers, government officials, policy makers, as well as researchers involved in E Governance and Data Mining Applications. This book presents an overall picture of the E Governance Data Mining applications, including Data Management Framework, Data Center and Data Warehousing applications along with possible research directions. An important motivation for writing this book was the need to build an organized framework for E Governance using Data Mining—a challenging task, owing to the extensive multidisciplinary nature of this fastdeveloping field. We hope that this book will encourage people with different backgrounds and experiences to exchange their views regarding Data Mining applications in E Governance so as to contribute toward the establishment of good governance for the developed society.

The main purpose of the work is to showcase the interdisciplinary engineering approaches in modeling and understanding human behaviors during interpersonal interactions those that could be typical, distressed, or atypical. The ability to measure human behaviors quantitatively has been a core component and a major research direction in both fields of engineering and psychology – though often with distinct approaches designed for different targeted applications. Engineering methods often strive to achieve high predictive accuracies using behavioral informatics techniques; these techniques employ a combination of behavior measures derived using automated signal based descriptors, and of statistical frameworks modeled using machine learning techniques. These approaches are often distinct from the observational approaches the gold standard for the past three decades in the study of psychology, even in clinical settings. The observational approaches are largely based on human subjective judgments.

Over the period of last few decades, the ‘C’ language has become an icon for computer programmers. The field of computer science has undergone tremendous change, and the rate of obsolescence of concepts, programming platforms, tools and utilities is extremely high. However, in spite of such vast changes, the only thing that has retained its stability is the ‘C’ language. Even today, millions of students, hobbyists and professional programmers enjoy the sturdiness, reliability and user friendliness of the ‘C’ language. Today ‘C’ enjoys the undisputable recognition in the computing paradigm for diversified applications, from the basic programming, microcontrollers, and spreadsheets to system programming. In this book, most of the usual theoretical features have been skipped, for these have been widely published in previous books. Rather than introducing the underpinning theory, the authors approach has been “learning-through-doing”, which is one that often appeals to programmers. Theory is followed by practical implementation, and in this way the book will cover programming aspects in a self-tutor manner providing an excellent overview, from basic to advance programming. Topics discussed include: • GCC interface• First time ‘C’ User• Decision and looping structures• Arrays and pointers• Functions, structures and union• Linear data structures

The availability of many-core computing platforms enables a wide variety of technical solutions for systems across the embedded, high-performance and cloud computing domains. However, large scale manycore systems are notoriously hard to optimise. Choices regarding resource allocation alone can account for wide variability in timeliness and energy dissipation (up to several orders of magnitude). Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing covers dynamic resource allocation heuristics for manycore systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to harmonise the approaches to dynamic allocation across the complete spectrum between systems with little flexibility and strict real-time guarantees all the way to highly dynamic systems with soft performance requirements. Technical topics presented in the book include: • Load and Resource Models• Admission Control• Feedback-based Allocation and Optimisation• Search-based Allocation Heuristics• Distributed Allocation based on Swarm Intelligence• Value-Based AllocationEach of the topics is illustrated with examples based on realistic computational platforms such as Network-on-Chip manycore processors, grids and private cloud environments.

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate.

The development of modern civilization leads to us having to solve new problems which did not exist before. The contemporary world faces a great challenge of aging societies, where the increasing number of citizens requires constant medical attention. To ensure safety and wellbeing of elderly people, patients in hospitals and disabled persons, advanced technologies can be implemented. These include both sophisticated data acquisition systems and data processing algorithms, aiming at the constant and discreet monitoring of persons whilst raising alarm if immediate attention is required.Computer Systems for Healthcare and Medicine presents a novel look at the introduced problems, including proposed solutions in the form of automated data acquisition and processing systems, which were tested in various environments. Characteristic features include a wide range of sensors used to monitor the situation of the person, and accurate decision making algorithms, often based on the computational intelligence domain. Technical topics discussed in the book include application for the healthcare of the following:Infrared sensorsMEMSUltra wideband radarsDeep learningDecision treesArtificial neural networksGabor filtersDecision support systems