SpringerBriefs in Electrical and Computer Engineering – serie

This book will introduce design methodologies, known as Built-in-Self-Test (BiST) and Built-in-Self-Calibration (BiSC), which enhance the robustness of radio frequency (RF) and millimeter wave (mmWave) integrated circuits (ICs). These circuits are used in current and emerging communication, computing, multimedia and biomedical products and microchips. The design methodologies presented will result in enhancing the yield (percentage of working chips in a high volume run) of RF and mmWave ICs which will enable successful manufacturing of such microchips in high volume.

Speech Processing and Soft Computing includes coverage of synergy between speech technology and bio-inspired soft computing methods. Through practical cases, the author explores, dissects and examines how soft computing may complement conventional techniques in speech enhancement and speech recognition in order to provide robust systems. The material is especially useful to graduate students and experienced researchers who are interested in expanding their horizons and investigating new research directions through review of the theoretical and practical settings of soft computing methods in very recent speech applications.

This book introduces the concept of voltage-controlled-oscillator (VCO)-based analog-to-digital converters (ADCs). Detailed explanation is given of this promising new class of high resolution and low power ADCs, which use time quantization as opposed to traditional analog-based (i.e. voltage) ADCs.

Distributed-order differential equations, a generalization of fractional calculus, are of increasing importance in many fields of science and engineering from the behaviour of complex dielectric media to the modelling of nonlinear systems. This Brief will broaden the toolbox available to researchers interested in modeling, analysis, control and filtering. It contains contextual material outlining the progression from integer-order, through fractional-order to distributed-order systems. Stability issues are addressed with graphical and numerical results highlighting the fundamental differences between constant-, integer-, and distributed-order treatments. The power of the distributed-order model is demonstrated with work on the stability of noncommensurate-order linear time-invariant systems. Generic applications of the distributed-order operator follow: signal processing and viscoelastic damping of a mass–spring set up. A new general approach to discretization of distributed-order derivatives and integrals is described. The Brief is rounded out with a consideration of likely future research and applications and with a number of MATLAB® codes to reduce repetitive coding tasks and encourage new workers in distributed-order systems.

Progressive reductions in vehicle emission requirements have forced the automotive industry to invest in research and development of alternative control strategies. Continual control action exerted by a dedicated electronic control unit ensures that best performance in terms of pollutant emissions and power density is married with driveability and diagnostics. Gasoline direct injection (GDI) engine technology is a way to attain these goals. This brief describes the functioning of a GDI engine equipped with a common rail (CR) system, and the devices necessary to run test-bench experiments in detail. The text should prove instructive to researchers in engine control and students are recommended to this brief as their first approach to this technology. Later chapters of the brief relate an innovative strategy designed to assist with the engine management system; injection pressure regulation for fuel pressure stabilization in the CR fuel line is proposed and validated by experiment. The resulting control scheme is composed of a feedback integral action and a static model-based feed-forward action, the gains of which are scheduled as a function of fundamental plant parameters. The tuning of closed-loop performance is supported by an analysis of the phase-margin and the sensitivity function. Experimental results confirm the effectiveness of the control algorithm in regulating the mean-value rail pressure independently from engine working conditions (engine speed and time of injection) with limited design effort.

This brief introduces people with a basic background in probability theory to various problems in cancer biology that are amenable to analysis using methods of probability theory and statistics.  The title mentions “cancer biology” and the specific illustrative applications reference cancer data but the methods themselves are more broadly applicable to all aspects of computational biology. Aside from providing a self-contained introduction to basic biology and to cancer, the brief describes four specific problems in cancer biology that are amenable to the application of probability-based methods.  The application of these methods is illustrated by applying each of them to actual data from the biology literature. After reading the brief, engineers and mathematicians should be able to collaborate fruitfully with their biologist colleagues on a wide variety of problems.

The subject of this brief is the application of linear parameter-varying (LPV) control to  a class of dynamic systems to provide a systematic synthesis of gain-scheduling controllers with guaranteed stability and performance. An important step in LPV control design, which is not well covered in the present literature, is the selection of weighting functions. The proper selection of weighting functions tunes the controller to obtain the desired closed-loop response. The selection of appropriate weighting functions is difficult and sometimes appears arbitrary. In this brief, gain-scheduling control with engineering applications is covered in detail, including the LPV modeling, the control problem formulation, and the weighting function optimization. In addition, an iterative algorithm for obtaining optimal output weighting functions with respect to the H2 norm bound is presented in this brief. Using this algorithm, the selection of appropriate weighting functions becomes an automatic process. The LPV design and control synthesis procedures in this brief are illustrated using: • air-to-fuel ratio control for port-fuel-injection engines; • variable valve timing control; and • application to a vibration control problem. After reading this brief, the reader will be able to apply its concepts to design gain-scheduling controllers for their own engineering applications. This brief provides detailed step-by-step LPV modeling and control design strategies along with an automatic weight-selection algorithm so that engineers can apply state-of-the-art LPV control synthesis to solve their own engineering problems. In addition, this brief should serve as a bridge between the H-infinity and H2 control theory and the real-world application of gain-scheduling control.

Passivity-based Model Predictive Control for Mobile Vehicle Navigation represents a complete theoretical approach to the adoption of passivity-based model predictive control (MPC) for autonomous vehicle navigation in both indoor and outdoor environments. The brief also introduces analysis of the worst-case scenario that might occur during the task execution. Some of the questions answered in the text include: • how to use an MPC optimization framework for the mobile vehicle navigation approach; • how to guarantee safe task completion even in complex environments including obstacle avoidance and sideslip and rollover avoidance; and• what to expect in the worst-case scenario in which the roughness of the terrain leads the algorithm to generate the longest possible path to the goal. The passivity-based MPC approach provides a framework in which a wide range of complex vehicles can be accommodated to obtain a safer and more realizable tool during the path-planning stage. During task execution, the optimization step is continuously repeated to take into account new local sensor measurements. These ongoing changes make the path generated rather robust in comparison with techniques that fix the entire path prior to task execution. In addition to researchers working in MPC, engineers interested in vehicle path planning for a number of purposes: rescued mission in hazardous environments; humanitarian demining; agriculture; and even planetary exploration, will find this SpringerBrief to be instructive and helpful.

Iterative learning control (ILC) has its origins in the control of processes that perform a task repetitively with a view to improving accuracy from trial to trial by using information from previous executions of the task. This brief shows how a classic application of this technique – trajectory following in robots – can be extended to neurological rehabilitation after stroke. Regaining upper limb movement is an important step in a return to independence after stroke, but the prognosis for such recovery has remained poor. Rehabilitation robotics provides the opportunity for repetitive task-oriented movement practice reflecting the importance of such intense practice demonstrated by conventional therapeutic research and motor learning theory. Until now this technique has not allowed feedback from one practice repetition to influence the next, also implicated as an important factor in therapy. The authors demonstrate how ILC can be used to adjust external functional electrical stimulation of patients’ muscles while they are repeatedly performing a task in response to the known effects of stimulation in previous repetitions. As the motor nerves and muscles of the arm reaquire the ability to convert an intention to move into a motion of accurate trajectory, force and rapidity, initially intense external stimulation can now be scaled back progressively until the fullest possible independence of movement is achieved.

This SpringerBrief deals with the control and optimization problem in hybrid electric vehicles. Given that there are two (or more) energy sources (i.e., battery and fuel) in hybrid vehicles, it shows the reader how to implement an energy-management strategy that decides how much of the vehicle’s power is provided by each source instant by instant.Hybrid Electric Vehicles:•introduces methods for modeling energy flow in hybrid electric vehicles;•presents a standard mathematical formulation of the optimal control problem;•discusses different optimization and control strategies for energy management, integrating the most recent research results; and•carries out an overall comparison of the different control strategies presented.Chapter by chapter, a case study is thoroughly developed, providing illustrative numerical examples that show the basic principles applied to real-world situations. The brief is intended as a straightforward tool for learning quickly about state-of-the-art energy-management strategies. It is particularly well-suited to the needs of graduate students and engineers already familiar with the basics of hybrid vehicles but who wish to learn more about their control strategies.

Discrete Event Systems: Diagnosis and Diagnosability addresses the problem of fault diagnosis of Discrete Event Systems (DESs). This book provides the basic techniques and approaches necessary for the design of an efficient fault diagnosis system for a wide range of modern engineering applications. This book classifies the different techniques and approaches according to several criteria such as: modeling tools (Automata, Petri nets, Templates) that is used to construct the model; the information (qualitative based on events occurrences and/or states outputs, quantitative based on signal processing, data analysis) that is needed to analyze and achieve the diagnosis; the decision structure (centralized, decentralized) that is required to achieve the diagnosis; as well as the complexity (polynomial, exponential) of the algorithm that is used to determine the set of faults that the proposed approach is able to diagnose as well as the delay time required for this diagnosis. The goal of this classification is to select the efficient method to achieve the fault diagnosis according to the application constraints. This book will include illustrated examples of the presented methods and techniques as well as a discussion on the application of these methods on several real-world problems.

This book describes the design of low-voltage analog integrated filters using current mirrors, one of the most common building blocks both in analog and mixed-signal VLSI circuits, offering the advantages of low-voltage operation, derivation of resistorless topologies and electronic adjustment capability of their frequency characteristics.  Several design examples are described, using current mirrors that fulfill the requirements of modern low-power wireless and biomedical applications, such as universal biquadratic filter topologies, complex filters for Bluetooth/ZigBee low-IF receivers and Wavelet filters for cardiac signal detection. The experimental results from the fabricated chips will also be presented, showing their utility in modern low-voltage low-power portable devices.

This brief offers a broad, yet concise, coverage of portfolio choice, containing both application-oriented and academic results, along with abundant pointers to the literature for further study. It cuts through many strands of the subject, presenting not only the classical results from financial economics but also approaches originating from information theory, machine learning and operations research. This compact treatment of the topic will be valuable to students entering the field, as well as practitioners looking for a broad coverage of the topic.

Compact Models and Measurement Techniques for High-Speed Interconnects provides detailed analysis of issues related to high-speed interconnects from the perspective of modeling approaches and measurement techniques. Particular focus is laid on the unified approach (variational method combined with the transverse transmission line technique) to develop efficient compact models for planar interconnects. This book will give a qualitative summary of the various reported modeling techniques and approaches and will help researchers and graduate students with deeper insights into interconnect models in particular and interconnect in general. Time domain and frequency domain measurement techniques and simulation methodology are also explained in this book.

This book provides insight into the practical design of VLSI circuits.  It is aimed at novice VLSI designers and other enthusiasts who would like to understand VLSI design flows.  Coverage includes key concepts in CMOS digital design, design of DSP and communication blocks on FPGAs, ASIC front end and physical design, and analog and mixed signal design.  The approach is designed to focus on practical implementation of key elements of the VLSI design process, in order to make the topic accessible to novices. The design concepts are demonstrated using software from Mathworks, Xilinx, Mentor Graphics, Synopsys and Cadence.

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 “noise” 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.

Creating New Medical Ontologies for Image Annotation focuses on the problem of the medical images automatic annotation process, which is solved in an original manner by the authors. All the steps of this process are described in detail with algorithms, experiments and results. The original algorithms proposed by authors are compared with other efficient similar algorithms. In addition, the authors treat the problem of creating ontologies in an automatic way, starting from Medical Subject Headings (MESH). They have presented some efficient and relevant annotation models and also the basics of the annotation model used by the proposed system: Cross Media Relevance Models. Based on a text query the system will retrieve the images that contain objects described by the keywords.

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.

Springer Brief Basics of Computer Networking provides a non-mathematical introduction to the world of networks. This book covers both technology for wired and wireless networks. Coverage includes transmission media, local area networks, wide area networks, and network security. Written in a very accessible style for the interested layman by the author of a widely used textbook with many years of experience explaining concepts to the beginner.

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.

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.

Inferring gene regulatory networks is a difficult problem to solve due to the relative scarcity of data compared to the potential size of the networks. While researchers have developed techniques to find some of the underlying network structure, there is still no one-size-fits-all algorithm for every data set. Network Inference in Molecular Biology examines the current techniques used by researchers, and provides key insights into which algorithms best fit a collection of data. Through a series of in-depth examples, the book also outlines how to mix-and-match algorithms, in order to create one tailored to a specific data situation.Network Inference in Molecular Biology is intended for advanced-level students and researchers as a reference guide. Practitioners and professionals working in a related field will also find this book valuable.

Time-of-Flight Cameras and Microsoft Kinect™ closely examines the technology and general characteristics of time-of-flight range cameras, and outlines the best methods for maximizing the data captured by these devices. This book also analyzes the calibration issues that some end-users may face when using these type of cameras for research, and suggests methods for improving the real-time 3D reconstruction of dynamic and static scenes.Time-of-Flight Cameras and Microsoft Kinect™ is intended for researchers and advanced-level students as a reference guide for time-of-flight cameras. Practitioners working in a related field will also find the book valuable.

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

Agent-based Semantic Web Service Composition closely examines the various aspects of SWS composition, and explores the concept that a Multi-Agent system can serve as an SWS composition system in which its agents can interact with one another to satisfy a high-level goal. In addition to surveying various proposed multi-agent-based SWS composition models, the book also highlights the cognitive parameter-based semantic web service selection models that can be used in multi-agent-based SWS composition, and outlines a new negotiation agreement-based SWS composition that can outperform existing techniques.Agent-based Semantic Web Service Composition is intended for researchers and practitioners as a reference guide for optimizing SWS composition and implementing multi-agent systems. Instructors and other academics working in a related field will also find the book invaluable.

Whether users are likely to accept the recommendations provided by a recommender system is of utmost importance to system designers and the marketers who implement them. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding influential factors in advice seeking relationships, which is abundant in the context of human-human relationships, can provide an important framework for identifying potential influence factors in recommender system context. This book reviews the existing literature on the factors in advice seeking relationships in the context of human-human, human-computer, and human-recommender system interactions. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.

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.

MotionCast for Mobile Wireless Networks provides an overview on the research for mobile ad-hoc networks regarding capacity and connectivity. Wireless ad-hoc networks are useful when there is a lack of infrastructure for communication. The proposed notion “MotionCast” is for the capacity analysis of multicast in MANET. A new kind of connectivity (k;m)-connectivity, is also defined, and its critical transmission range for i.i.d. (independently and identically distributed) and random walk mobility models are derived respectively. This book also investigates the related issues of connectivity in mobile and static circumstances. In addition, it provides a survey of the capacity scaling research, which gives a good summary of this field.