This proceedings book presents selected papers from the 4th Conference on Signal and Information Processing, Networking and Computers (ICSINC) held in Qingdao, China on May 23-25, 2018. It focuses on the current research in a wide range of areas related to information theory, communication systems, computer science, signal processing, aerospace technologies, and other related technologies. With contributions from experts from both academia and industry, it is a valuable resource anyone interested in this field.

This book describes a systematic approach to scattering of transient fields which can be introduced in undergraduate or graduate courses. The initial boundary value problems considered describe the transient electromagnetic fields formed by open periodic, compact, and waveguide resonators. The methods developed and the mathematical and physical results obtained provide a basis on which a modern theory for the scattering of resonant non-harmonic waves can be developed.

This book introduces the methods for predicting the future behavior of a system's health and the remaining useful life to determine an appropriate maintenance schedule. The authors introduce the history, industrial applications, algorithms, and benefits and challenges of PHM (Prognostics and Health Management) to help readers understand this highly interdisciplinary engineering approach that incorporates sensing technologies, physics of failure, machine learning, modern statistics, and reliability engineering. It is ideal for beginners because it introduces various prognostics algorithms and explains their attributes, pros and cons in terms of model definition, model parameter estimation, and ability to handle noise and bias in data, allowing readers to select the appropriate methods for their fields of application.Among the many topics discussed in-depth are:* Prognostics tutorials using least-squares* Bayesian inference and parameter estimation* Physics-based prognostics algorithms including nonlinear least squares, Bayesian method, and particle filter* Data-driven prognostics algorithms including Gaussian process regression and neural network* Comparison of different prognostics algorithms The authors also present several applications of prognostics in practical engineering systems, including wear in a revolute joint, fatigue crack growth in a panel, prognostics using accelerated life test data, fatigue damage in bearings, and more. Prognostics tutorials with a Matlab code using simple examples are provided, along with a companion website that presents Matlab programs for different algorithms as well as measurement data. Each chapter contains a comprehensive set of exercise problems, some of which require Matlab programs, making this an ideal book for graduate students in mechanical, civil, aerospace, electrical, and industrial engineering and engineering mechanics, as well as researchers and maintenance engineers in the above fields.

The use of fibre optic sensors in structural health monitoring has rapidly accelerated in recent years. By embedding fibre optic sensors in structures (e.g. buildings, bridges and pipelines) it is possible to obtain real time data on structural changes such as stress or strain. Engineers use monitoring data to detect deviations from a structure's original design performance in order to optimise the operation, repair and maintenance of a structure over time.

"Fibre Optic Methods for Structural Health Monitoring" is organised as a step-by-step guide to implementing a monitoring system and includes examples of common structures and their most-frequently monitored parameters. This book: presents a universal method for static structural health monitoring, using a technique with proven effectiveness in hundreds of applications worldwide; discusses a variety of different structures including buildings, bridges, dams, tunnels and pipelines; features case studies which describe common problems and offer solutions to those problems; provides advice on establishing mechanical parameters to monitor (including deformations, rotations and displacements) and on placing sensors to achieve monitoring objectives; identifies methods for interpreting data according to construction material and shows how to apply numerical concepts and formulae to data in order to inform decision making.

"Fibre Optic Methods for Structural Health Monitoring" is an invaluable reference for practising engineers in the fields of civil, structural and geotechnical engineering. It will also be of interest to academics and undergraduate/graduate students studying civil and structural engineering.

This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today's problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation.

This book examines theoretical and applied aspects of wavelet analysis in neurophysics, describing in detail different practical applications of the wavelet theory in the areas of neurodynamics and neurophysiology and providing a review of fundamental work that has been carried out in these fields over the last decade. Chapters 1 and 2 introduce and review the relevant foundations of neurophysics and wavelet theory, respectively, pointing on one hand to the various current challenges in neuroscience and introducing on the other the mathematical techniques of the wavelet transform in its two variants (discrete and continuous) as a powerful and versatile tool for investigating the relevant neuronal dynamics. Chapter 3 then analyzes results from examining individual neuron dynamics and intracellular processes. The principles for recognizing neuronal spikes from extracellular recordings and the advantages of using wavelets to address these issues are described and combined with approaches based on wavelet neural networks (chapter 4). The features of time-frequency organization of EEG signals are then extensively discussed, from theory to practical applications (chapters 5 and 6). Lastly, the technical details of automatic diagnostics and processing of EEG signals using wavelets are examined (chapter 7). The book will be a useful resource for neurophysiologists and physicists familiar with nonlinear dynamical systems and data processing, as well as for graduat e students specializing in the corresponding areas.

This book introduces double-prism multi-mode scanning theory and technology, focusing on double Risley-prism, multi-mode scanning models, methods and key techniques applied in multi-mode optical scanning and target tracking fields. It is first book to systematically and comprehensively describe basic multi-mode scanning theory and practical implementation techniques utilizing double Risley prisms. It includes rigorous modeling of double Risley-prism multi-mode scanning systems and high-efficiency solution algorithms for inverse problems with abundant illustrative examples and scanning error analyses, along with design guidance and performance test on specific scanning devices. Further, it presents the latest research results for forward scanning models and inverse tracking algorithms, sub-microradian fine scanning modeling with tilting double Risley prisms, nonlinear control strategy for double prism motion, calibration and experiment techniques for various double-prism layouts, as well as opto-mechanical system design and analysis. Featuring rigorous theoretical derivations illustrated with corresponding examples and original scanning apparatus, the book is a valuable reference resource for those developing and applying multi-mode scanning techniques in photoelectric scanning and tracking areas.

The Laser world consists basically of two areas, which are necessary and in many cases also sufficient for effective innovation: The right laser for the right application. For the individual application that means the determination of optimized process parameters in terms of laser power, peak power/ intensity, focus geometry and dimension, pulse length, pulse repetition rate and wavelength to name only the six most important ones. Once these parameters are identified, the corresponding Laser has to be selected on the basis of commercial availability. Obviously there is no such thing than "One Laser for all." The situation is rather comparable with electrical power, were depending on the demand of the application in terms of voltage, current and time corresponding power supplies need to be tailored, however, with the difference that in the case of the Laser the variety of parameters is even higher, thus the technology is more complex but on the other hand much more flexible in terms optimizing the source to the application.As a consequence it is suggested to generate two volumes on Lasers and Applications named "Tailored Light."

Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the latest advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph, and graph in vector spaces. Real-world applications of these theories are spanned broadly in dimensionality reduction, subspace learning, manifold learning, clustering, classification, and feature selection. A selective group of experts contribute to different chapters of this book which provides a comprehensive perspective of this field.

Wireless Sensor Network Technologies for Information Explosion Era The amount and value of information available due to rapid spread of information technology is exploding. Typically, large enterprises have approximately a petabyte of operational data stored in hundreds of data repositories supporting thousands of applications. Data storage volumes grow in excess of 50% annually. This growth is expected to continue due to vast proliferation of existing infor- tion systems and the introduction of new data sources. Wireless Sensor Networks (WSNs) represent one of the most notable examples of such new data sources. In recent few years, various types of WSNs have been deployed and the amount of information generated by wireless sensors increases rapidly. The information - plosion requires establishing novel data processing and communication techniques for WSNs. This volume aims to cover both theoretical and practical aspects - lated to this challenge, and it explores directions for future research to enable ef- cient utilization of WSNs in the information-explosion era. The book is organized in three main parts that consider (1) technical issues of WSNs, (2) the integration of multiple WSNs, and (3) the development of WSNs systems and testbeds for conducting practical experiments. Each part consists of three chapters.

This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.

The generation of radiation with well-defined frequency and wavelength, and the ability to precisely determine these quantities, are of fundamental importance in physics and other natural sciences. Monochromatic radiation enables both very accurate structure determinations and studies of the dynamics of living and non-living matter. It is crucial for the realization of standards of time and length, for the determination of fundamental constants, and for many other aspects of basic research.

Bragg backscattering from perfect crystals is a tool for creating, manipulating, and analyzing x-rays with highest spectral purity. It has the unique feature of selecting x-rays with narrow spectral bandwidth. This book describes the theoretical foundations and principles of x-ray crystal optics with high spectral resolution. Various experimental studies and applications are presented and the author also addresses the development of instrumentation, such as high-resolution x-ray monochromators, analyzers, wavelength meters, resonators, and interferometers. The book will be a valuable source of information for all students and researchers working in the field of x-ray optics.

This book presents the cross-layer design and optimization of wake-up receivers for wireless body area networks (WBAN), with an emphasis on low-power circuit design. This includes the analysis of medium access control (MAC) protocols, mixer-first receiver design, and implications of receiver impairments on wideband frequency-shift-keying (FSK) receivers. Readers will learn how the overall power consumption is reduced by exploiting the characteristics of body area networks. Theoretical models presented are validated with two different receiver implementations, in 90nm and 40nm CMOS technology.

Unique blend of asymptotic theory and small sample practice through simulation experiments and data analysis.

Novel reproducing kernel Hilbert space methods for the analysis of smoothing splines and local polynomials. Leading to uniform error bounds and honest confidence bands for the mean function using smoothing splines

Exhaustive exposition of algorithms, including the Kalman filter, for the computation of smoothing splines of arbitrary order.

Optical frequency measurement is an extremely challenging field of experimental physics which is presently undergoing a renaissance driven by the needs of modern high density optical communication systems as well as by requirements of high-resolution laser spectroscopy. This text is the first to discuss the development of traditional and second generation frequency chains together with their enabling technology. Reviews written by some of the most experienced researchers in their respective fields address the technology of frequency metrology such as: low noise microwave oscillators and microwave frequency standards, low noise and high stability optical frequency sources, optical frequency standards, traditional and second-generation optical frequency measurement and synthesis techniques as well as optical frequency comb generators. It should prove useful to researchers just entering the field of frequency metrology or equally well to the experienced practitioner.

Hyperspectral Data Compression provides a survey of recent results in the field of compression of remote sensed 3D data, with a particular interest in hyperspectral imagery. Chapter 1 addresses compression architecture, and reviews and compares compression methods. Chapters 2 through 4 focus on lossless compression (where the decompressed image must be bit for bit identical to the original). Chapter 5, contributed by the editors, describes a lossless algorithm based on vector quantization with extensions to near lossless and possibly lossy compression for efficient browning and pure pixel classification. Chapter 6 deals with near lossless compression while. Chapter 7 considers lossy techniques constrained by almost perfect classification. Chapters 8 through 12 address lossy compression of hyperspectral imagery, where there is a tradeoff between compression achieved and the quality of the decompressed image. Chapter 13 examines artifacts that can arise from lossy compression.

This book provides the reader with a clear overview of the considerable body of research and development work carried out in the last five years on microstructured polymer optical fibres (mPOFs). It discusses new applications which will be opened up by this emerging technology and includes for the first time details about the fabrication process for these fibres. The book provides an excellent introduction to this new technology.

This book presents the selected results of the XI Scientific Conference Selected Issues of Electrical Engineering and Electronics (WZEE) which was held in Rzeszow and Czarna, Poland on September 27-30, 2013. The main aim of the Conference was to provide academia and industry to discuss and present the latest technological advantages and research results and to integrate the new interdisciplinary scientific circle in the field of electrical engineering, electronics and mechatronics. The Conference was organized by the Rzeszow Division of Polish Association of Theoretical and Applied Electrical Engineering (PTETiS) in cooperation with Rzeszow University of Technology, the Faculty of Electrical and Computer Engineering and Rzeszow University, the Faculty of Mathematics and Natural Sciences.

This volume is devoted to the Persistent Scatterer Technique, the latest development in radar interferometric data processing. Using this technique, millimetric displacements can be observed at hundreds of thousands of targets that are affected only slightly from temporal and geometric decorrelation, such as the walls and the roofs of houses, lamp posts, grates, window ledges, etc. All acquired data can be used by this technique, which enables the analysis of displacements since 1992 in any area world-wide, using the archived historical data of the ERS-1 and ERS-2 satellites. Data of other current and future sensors can also be processed using this technique. The original PS algorithm is revisited based on the main literature, and possible weak points are identified. The STUN (spatio-temporal unwrapping network) algorithm, developed to cope with these issues in a robust way, is presented and applied to two test sites.