Bücher der Reihe SpringerBriefs in Electrical and Computer Engineering

This book first introduces the background of spatial audio reproduction, with different types of audio content and for different types of playback systems.

Using confluencity and relative optimization, the author classifies states as confluent or branching and shows how the under-selectivity issue of the long-run average can be easily addressed, multi-class optimization implemented, and Nth biases and Blackwell optimality conditions derived.

This book presents a novel methodology for the computation of RCS of metallic structures using a parallelized version of NEC in conjunction with a finite element preprocessor which has been strategically incorporated for simplifying geometry modelling catering to NEC guidelines.

This book summarizes the latest research on cognitive network-layer methods and smart adaptive physical-layer methods in underwater networks.

This book will first introduce classic graph-cut segmentation algorithms and then discuss state-of-the-art techniques, including graph matching methods, region merging and label propagation, clustering methods, and segmentation methods based on edge detection.

This book gives a comprehensive and systematic review of secure compressive sensing (CS) for applications in various fields such as image processing, pattern recognition, Internet of things (IoT), and cloud computing.

This book will provide a comprehensive overview on human action analysis with randomized trees. We describe how the randomized trees can be used for action classification, action detection, action search, and action prediction.

This book provides a classification of current and future applications for the domain of Cooperating Objects. The book has been created with a very strong participation of the industry and taking into account current research trends and industrial roadmaps

The Annual BCI Research Awards are international prizes that recognize the top new projects in brain-computer interface (BCI) research. Each article is authored by the group of researchers who developed the project, and articles have been updated with new progress achieved since 2018.

This book provides a detailed description of network science concepts applied to power systems and electricity markets, offering an appropriate blend of theoretical background and practical applications for operation and power system planning.

This SpringerBrief details various techniques employed for enhancing the transmission efficiency of radomes by modifying the radome wall configurations.

The Annual BCI Research Awards are international prizes that recognize the top new projects in brain-computer interface (BCI) research.

This brief describes the basics of Riemannian optimization¿optimization on Riemannian manifolds¿introduces algorithms for Riemannian optimization problems, discusses the theoretical properties of these algorithms, and suggests possible applications of Riemannian optimization to problems in other fields.To provide the reader with a smooth introduction to Riemannian optimization, brief reviews of mathematical optimization in Euclidean spaces and Riemannian geometry are included. Riemannian optimization is then introduced by merging these concepts. In particular, the Euclidean and Riemannian conjugate gradient methods are discussed in detail. A brief review of recent developments in Riemannian optimization is also provided. Riemannian optimization methods are applicable to many problems in various fields. This brief discusses some important applications including the eigenvalue and singular value decompositions in numericallinear algebra, optimal model reduction in control engineering, and canonical correlation analysis in statistics.

This book provides a detailed survey of the methods that were recently developed to handle advanced versions of the blind source separation problem, which involve several types of nonlinear mixtures.

This book presents an interdisciplinary paradigms of computational intelligence techniques and biomedical signal processing. The computational intelligence techniques outlined in the book will help to develop various ways to enhance and utilize signal processing algorithms in the field of biomedical signal processing.

The authors show how the proposed algorithm is able to detect and track 2D & 3D objects in monocular sequences for both indoor and outdoor surveillance environments and at the same time, also able to work satisfactorily in a dynamic background and with challenging constraints.

The book presents the analysis and design of integrated automotive radar receivers in Silicon-Germanium technology, for use in complex multi-channel radar transceiver front-ends in the 77GHz frequency band. The main emphasis of the work is the realization of high-linearity and low-power modular receiver channels as well as the investigation of millimeter-wave integrated test concepts for the receiver front-end.

Wireless sensor network (WSN) is an ad-hoc network technology comprising even thousands of autonomic and self-organizing nodes that combine environmental sensing, data processing, and wireless networking. The applications for sensor networks range from home and industrial environments to military uses. Unlike the traditional computer networks, a WSN is application-oriented and deployed for a specific task. WSNs are data centric, which means that messages are not send to individual nodes but to geographical locations or regions based on the data content. A WSN node is typically battery powered and characterized by extremely small size and low cost. As a result, the processing power, memory, and energy resources of an individual sensor node are limited. However, the feasibility of a WSN lies on the collaboration between the nodes. A reference WSN node comprises a Micro-Controller Unit (MCU) having few Million Instructions Per Second (MIPS) processing speed, tens of kilobytes program memory, few kilobytes data memory. In addition, the node contains a short-range radio, and a set of sensors. Supply power is typically obtained with small batteries. Assuming a target lifetime of one year using AA-size batteries, the available power budget is around 1 mW. This book covers the low-power WSNs services ranging from hardware platforms and communication protocols to network deployment, and sensor data collection and actuation. The implications of resource constraints and expected performance in terms of throughput, reliability and latency are explained. As a case study, this book presents experiments with low-energy TUTWSN technology to illustrate the possibilities and limitations of WSN applications.

Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the "e;noise"e; that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.

Stem cells are the building blocks for all other cells in an organism. The human body has about 200 different types of cells and any of those cells can be produced by a stem cell. This fact emphasizes the significance of stem cells in transplantational medicine, regenerative therapy and bioengineering. Whether embryonic or adult, these cells can be used for the successful treatment of a wide range of diseases that were not treatable before, such as osteogenesis imperfecta in children, different forms of leukemias, acute myocardial infarction, some neural damages and diseases, etc. Bioengineering, e.g. successful manipulation of these cells with multipotential capacity of differentiation toward appropriate patterns and precise quantity, are the prerequisites for successful outcome and treatment. By combining in vivo and in vitro techniques, it is now possible to manage the wide spectrum of tissue damages and organ diseases. Although the stem-cell therapy is not a response to all the questions, it provides more and more answers every day. Stem Cells and Tissue Engineering is a concise review on the functional, phenotypic, regenerative, transplantational and curative aspects of a stem cell's entity. It is critical and encouraging at the same time, providing truthful and appropriate samples from the practice and research that can lead toward optimal use of this immense source of adjuvant and curative therapy in human pathology. Written by a clinician and a researcher, who are currently teaching what they are doing, it is recommended as a teaching tool along with an original textbook.

This book explores the challenges and presents best strategies for designing Through-Silicon Vias (TSVs) for 3D integrated circuits. It describes a novel technique to mitigate TSV-induced noise, the GND Plug, which is superior to others adapted from 2-D planar technologies, such as a backside ground plane and traditional substrate contacts. The book also investigates, in the form of a comparative study, the impact of TSV size and granularity, spacing of C4 connectors, off-chip power delivery network, shared and dedicated TSVs, and coaxial TSVs on the quality of power delivery in 3-D ICs. The authors provide detailed best design practices for designing 3-D power delivery networks. Since TSVs occupy silicon real-estate and impact device density, this book provides four iterative algorithms to minimize the number of TSVs in a power delivery network. Unlike other existing methods, these algorithms can be applied in early design stages when only functional block- level behaviors and a floorplan are available. Finally, the authors explore the use of Carbon Nanotubes for power grid design as a futuristic alternative to Copper.

Anonymization of Electronic Medical Records to Support Clinical Analysis closely examines the privacy threats that may arise from medical data sharing, and surveys the state-of-the-art methods developed to safeguard data against these threats. To motivate the need for computational methods, the book first explores the main challenges facing the privacy-protection of medical data using the existing policies, practices and regulations. Then, it takes an in-depth look at the popular computational privacy-preserving methods that have been developed for demographic, clinical and genomic data sharing, and closely analyzes the privacy principles behind these methods, as well as the optimization and algorithmic strategies that they employ. Finally, through a series of in-depth case studies that highlight data from the US Census as well as the Vanderbilt University Medical Center, the book outlines a new, innovative class of privacy-preserving methods designed to ensure the integrity of transferred medical data for subsequent analysis, such as discovering or validating associations between clinical and genomic information. Anonymization of Electronic Medical Records to Support Clinical Analysis is intended for professionals as a reference guide for safeguarding the privacy and data integrity of sensitive medical records. Academics and other research scientists will also find the book invaluable.

This book describes in detail modern technologies for printed electronics, explaining how nanotechnology and modern printing technology are merging to revolutionize electronics fabrication of thin, lightweight, large and inexpensive products. Readers will benefit from the explanations of materials, devices and circuits used to design and implement the latest applications of printed electronics, such as thin flexible OLED displays, organic solar cells, OLED lighting, smart wallpaper, sensors, logic, memory and more.

This book presents the theory, analysis, and design of ultra-wideband (UWB) radar and sensor systems (in short, UWB systems) and their components. UWB systems find numerous applications in the military, security, civilian, commercial and medicine fields. This book addresses five main topics of UWB systems: System Analysis, Transmitter Design, Receiver Design, Antenna Design and System Integration and Test. The developments of a practical UWB system and its components using microwave integrated circuits, as well as various measurements, are included in detail to demonstrate the theory, analysis and design technique. Essentially, this book will enable the reader to design their own UWB systems and components.In the System Analysis chapter, the UWB principle of operation as well as the power budget analysis and range resolution analysis are presented. In the UWB Transmitter Design chapter, the design, fabrication and measurement of impulse and monocycle pulse generators are covered. The UWB Receiver Design chapter addresses the design and measurement of the strobe pulse generator, sampling mixer, low-noise amplifier and synchronous sampling receiver. Next, the UWB Antenna Design chapter details the design and measurement of to two UWB antennas: the microstrip quasi-horn antenna and the UWB uniplanar antenna. The System Integration and Test chapter covers the transmission-reception test, signal processing, system integration, and evaluation of the UWB sensor. The final chapter provides a summary and conclusion of the work.

This brief examines issues of spectrum allocation for the limited resources of radio spectrum. It uses a game-theoretic perspective, in which the nodes in the wireless network are rational and always pursue their own objectives. It provides a systematic study of the approaches that can guarantee the system's convergence at an equilibrium state, in which the system performance is optimal or sub-optimal. The author provides a short tutorial on game theory, explains game-theoretic channel allocation in clique and in multi-hop wireless networks and explores challenges in designing game-theoretic mechanisms for dynamic channel redistribution. Since designing a completely secure mechanism is extremely expensive or impossible in most of distributed autonomous systems, it is more beneficial to study misbehavior of the nodes and develop light-weighted game-theoretic channel allocation mechanisms. With a mix of theoretical and hands-on information, the brief traces the concepts of game theory, the current state of spectrum allocation in wireless networks and future competition for resources. Thorough yet accessible, the content is ideal for researchers and practitioners working on spectrum redistribution. It is also a helpful resource for researchers and advanced-level students interested in game theory and wireless communications.

This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students.

Designing a New Class of Distributed Systems closely examines the Distributed Intelligent Managed Element (DIME) Computing Model, a new model for distributed systems, and provides a guide to implementing Distributed Managed Workflows with High Reliability, Availability, Performance and Security. The book also explores the viability of self-optimizing, self-monitoring autonomous DIME-based computing systems. Designing a New Class of Distributed Systems is designed for practitioners as a reference guide for innovative distributed systems design. Researchers working in a related field will also find this book valuable.

Recommender systems are one of the recent inventions to deal with the ever-growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbors, generated from a database made up of the preferences of past users. In the absence of these ratings, trust between the users could be used to choose the neighbor for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world "friend of a friend" recommendations. To extend the boundaries of the neighbor, an effective trust inference technique is required. This book proposes a trust interference technique called Directed Series Parallel Graph (DSPG) that has empirically outperformed other popular trust inference algorithms, such as TidalTrust and MoleTrust. For times when reliable explicit trust data is not available, this book outlines a new method called SimTrust for developing trust networks based on a user's interest similarity. To identify the interest similarity, a user's personalized tagging information is used. However, particular emphasis is given in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbors used in the automated recommender system. Through a series of case studies and empirical results, this book highlights the effectiveness of this tag-similarity based method over the traditional collaborative filtering approach, which typically uses rating data. Trust for Intelligent Recommendation is intended for practitioners as a reference guide for developing improved, trust-based recommender systems. Researchers in a related field will also find this book valuable.

ICT Development for Social and Rural Connectedness provides an introduction to the concept of 'connectedness', and explores how this socio-psychological term has evolved during the age of the Internet. The book surveys the principles of ICT for development (ICTD), and closely examines how ICT has played a pivotal role in the rural community development of various countries. To highlight the continued benefits of ICT in these regions, the book presents an in-depth case study that analyzes the connectedness within the rural internet centers of Malaysia. The book is intended primarily for researchers and practitioners as a reference guide to ICTD in rural environments.