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In computer science, the primary application of visualization technology is software visualization: the use of graphics to portray information obtained from a static or dynamic analysis of a program. Software visualization is used in several phases of the software development lifecycle, but it is of particular interest in the "e;back- end"e; tasks of debugging, performance tuning, and understanding complex systems in order to maintain them. Software visualization is expected to improve the back end of the software development process which can result in huge cost savings. Debugging, tuning and maintaining programs comprise the majority of the high costs associated with software development. Unfortunately, the rate at which these software technologies have improved has been gradual. The task of writing software visualization tools is difficult, and most existing systems are limited to a narrow scope, such as the visualization of a single well-understood algorithm from a hand-instrumented source program. This book presents software visualization at a level suitable for a senior level undergraduate or graduate course or for the interested technical professional. The approach is to give a survey of the field, and then present a specific research framework designed to reduce the effort required to write visualization tools. A wide range of simple program control flow and data structure visualizations are then presented as examples of how to obtain information about program behavior, and how to present it graphically. Source code fragments and screen images illustrate each example.

The field of cellular, molecular, and developmental neuroscience repre- sents the interface between the three large, well established fields of neu- roscience, cell biology, and molecular biology. In the last 10 to 15 years, this new field has emerged as one of the most rapidly growing and exciting subdisciplines of neuroscience. It is now becoming possible to understand many aspects of nervous system function at the molecular level, and there already are dramatic applications of this information to the treatment of nervous system injury, disease, and genetic disorders. Moreover, there is great optimism that new strategies will emerge soon as a result of the explosion of information. This book was written to introduce students to the major issues, ex- perimental strategies, and current knowledge base in cellular, molecular, and developmental neuroscience. The concept for the book arose from a section of an introductory neuroscience course given to first-year medical students at the University of Virginia School of Medicine. The text pre- sumes a basic, but not detailed, understanding of nervous system orga- nization and function, and a background in biology. It is intended as an appropriate introductory text for first-year medical students or graduate students in neuroscience, neurobiology, psychobiology, or related pro- grams;**and for advanced undergraduate students with appropriate back- ground in biology and neuroscience. While some of the specific information presented undoubtedly will be outdated rapidly, the "e;gestalt"e; of this emerging field of inquiry as presented here should help the beginning stu- dent organize new information.

A mathematician, a real one, one for whom mathematical objects are abstract and exist only in his mind or in some remote Platonic universe, never "sees" a curve. A curve is infinitely narrow and invisible. Yet, we all have "seen" straight lines, circles, parabolas, etc. when many years ago (for some of us) we were taught elementary geometry at school. E. Mach wanted to suppress from physics everything that could not be perceived: physics and metaphysics must not exist together. Many a scientist was deeply influenced by his philosophy. In his book Claude Tricot tells us that a curve has a non-vanishing width. Its width is that of the pencil or of the pen on the paper, or of the chalk on the blackboard. The abstract curve which cannot be seen and which does not really concern us here is the intersection of all those thick curves that contain it. For Claude Tricot it is only the thick curves that are pertinent. He describes in detail the way bumps, peaks, and irregularities appear on the curve as its width decreases. This is not a new point of view. Indeed Hausdorff and Bouligand initiated the idea at the beginning of this century. However, Claude Tricot manages to refine the theory extensively and interestingly. His approach is both realistic and mathematically rigorous. Mathematicians who only feed on abstractions as well as engineers who tackle tangible problems will enjoy reading this book.

Driven by the increasing demand for capacity and Quality of Service in wireless cellular networks and motivated by the distributed antenna system, the authors proposed a cooperative communication architecture-Group Cell architecture, which was initially brought forward in 2001. Years later, Coordinated Multiple-Point Transmission and Reception (CoMP) for LTE-Advanced was put forward in April 2008, as a tool to improve the coverage of cells having high data rates, the cell-edge throughput and/or to increase system throughput. This book mainly focuses on the Group Cell architecture with multi-cell generalized coordination, Contrast Analysis between Group Cell architecture and CoMP, Capacity Analysis, Slide Handover Strategy, Power Allocation schemes of Group Cell architecture to mitigate the inter-cell interference and maximize system capacity and the trial network implementation and performance evaluations of Group Cell architecture.

In the fall semester of 1979 I gave a course on deformation theory at Berkeley. My goal was to understand completely Grothendieck's local study of the Hilbert scheme using the cohomology of the normal bundle to characterize the Zariski tangent space and the obstructions to deformations. At the same timeIstartedwritinglecturenotesforthecourse.However,thewritingproject soon foundered as the subject became more intricate, and the result was no more than ?ve of a projected thirteen sections, corresponding roughly to s- tions 1, 2, 3, 5, 6 of the present book. These handwritten notes circulated quietly for many years until David Eisenbud urged me to complete them and at the same time (without consu- ing me) mentioned to an editor at Springer, "e;You know Robin has these notes on deformation theory, which could easily become a book."e; When asked by Springer if I would write such a book, I immediately refused, since I was then planning another book on space curves. But on second thought, I decided this was,afterall,aworthyproject,andthatbywritingImight?nallyunderstand the subject myself. So during 2004 I expanded the old notes into a rough draft, which I used to teach a course during the spring semester of 2005. Those notes, rewritten once more, with the addition of exercises, form the book you are now reading. Mygoalinthisbookistointroducethemainideasofdeformationtheoryin algebraicgeometryandtoillustratetheiruseinanumberoftypicalsituations.

Stochastic processes and diffusion theory are the mathematical underpinnings of many scientific disciplines, including statistical physics, physical chemistry, molecular biophysics, communications theory and many more. Many books, reviews and research articles have been published on this topic, from the purely mathematical to the most practical.This book offers an analytical approach to stochastic processes that are most common in the physical and life sciences, as well as in optimal control and in the theory of filltering of signals from noisy measurements. Its aim is to make probability theory in function space readily accessible to scientists trained in the traditional methods of applied mathematics, such as integral, ordinary, and partial differential equations and asymptotic methods, rather than in probability and measure theory.

This self-contained textbook gives a thorough exposition of multivariable calculus. It can be viewed as a sequel to the one-variable calculus text, A Course in Calculus and Real Analysis, published in the same series. The emphasis is on correlating general concepts and results of multivariable calculus with their counterparts in one-variable calculus. For example, when the general definition of the volume of a solid is given using triple integrals, the authors explain why the shell and washer methods of one-variable calculus for computing the volume of a solid of revolution must give the same answer. Further, the book includes genuine analogues of basic results in one-variable calculus, such as the mean value theorem and the fundamental theorem of calculus.This book is distinguished from others on the subject: it examines topics not typically covered, such as monotonicity, bimonotonicity, and convexity, together with their relation to partial differentiation, cubature rules for approximate evaluation of double integrals, and conditional as well as unconditional convergence of double series and improper double integrals. Moreover, the emphasis is on a geometric approach to such basic notions as local extremum and saddle point.Each chapter contains detailed proofs of relevant results, along with numerous examples and a wide collection of exercises of varying degrees of difficulty, making the book useful to undergraduate and graduate students alike. There is also an informative section of "Notes and Comments¿¿ indicating some novel features of the treatment of topics in that chapter as well as references to relevant literature. The only prerequisite for this text is a course in one-variable calculus.

Cooperative transmission aims to improve the reliability of wireless mobile communications through the use of diversity provided by additional relays assisting in the transmission between the source and destination nodes. This is possible as the rationale behind spatio-temporal processing can be easily mapped onto networked systems. Autonomic Cooperative Networking studies the further evolution of this phenomenon by first involving the network layer routines and then additionally incorporating the notion of autonomic system design.

This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techniques such as sentiment mining can be used in real-time to identify posts that contain PTSD-related signals, flag those posts, and bring them to the attention of psychologists, thus providing an automated flag and referral capability. The use of sentiment extraction technologies allows automatic in-depth analysis of opinions and emotions expressed by individuals in their online posts. By training these automated systems with input from academic and clinical experts, the systems can be refined so that the accuracy of their detection of possible PTSD signals is comparable to that of psychologists reading the same online posts. While a portion of the literature on this and related topics explores the correlation between text patterns in archived documents and PTSD, no literature to date describes a system performing real-time analysis. Our system allows analysts to quickly identify, review, and validate online posts which have been flagged as exhibiting signs or symptoms of PTSD and enables follow-up, thus allowing for the presentation of treatment options to the authors of those posts. We describe the ontology of PTSD-related terms (i.e., terms which signal PTSD and related conditions) that need to be tracked, the algorithms used for extraction of the intensity of these signals, and the training process used to fine-tune sentiment analysis algorithms. We then present the results of processing a validation data set, different from the training set, comparing the algorithmic output with opinions of clinical psychologists, and explain how the concept can be extended to detect signals of other psychological conditions. We present a sample system architecture and implementation which can be used to engage users and their families, either anonymously or eponymously, and use the sentiment extraction algorithms as an early screening tool to alert clinicians to participants who may require close monitoring or follow-up. Finally, we describe a user test conducted with users recruited from the Veteran population and present the results of the analyses on the data.

Optimization: Structure and Applications presents selected contributions from renowned researchers in the fields of operations research and industrial engineering. The book is divided into two parts; the first focuses on mathematical structure, and the second, on real-world applications. The work includes recent developments in several optimization-related topics such as decision theory, linear programming, turnpike theory, duality theory, convex analysis, and queuing theory. The applications presented include, but are not limited to, data imaging, network capacity allocation, water system management, and materials design.The 21 self-contained chapters in this volume are devoted to the examination of modern trends and open problems in the field of optimization. This book will be a valuable tool not only to specialists interested in the technical detail and various applications presented, but also to researchers interested in building upon the book¿s theoretical results.

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.

In today's hospitals, the gap between technology and medicine constantly needs to be bridged, both by physicians and engineers. By taking a unique clinical neuroengineering approach, From Neurology to Methodology and Back offers a translational study of neurology and technology from both sides. The fundamental topics covered range from basic concepts such as sampling and simple statistical measures via Fourier analysis to source localization. Providing clinically relevant context and introduce technical concepts, the neurological diseases presented range from epilepsy, brain tumors and cerebrovascular diseases to tremor, MS and neuromuscular diseases. All topics are presented in a true clinical neuroengineering approach.Each chapter begins with one or more patient cases for inspiration. Each case is then presented to illustrate a working example of a distinct neurodiagnostic technique, and the mathematical and physical principles underlying these techniques are explained. Finally, the author returns to the patient, and examines how the presented technology can help provide a diagnosis for each case.From Neurology to Methodology and Back serves as an upper-undergraduate/graduate level guide for those interested in a translational approach between the fields of medicine and technology in neuroengineering. Neurologists and residents in neurology, medical engineers, medical students, biomedical engineers and students, technical medicine students or students of other interdisciplinary fields will therefore all find this book useful. Each chapter begins with one or more patient cases for inspiration. Each case is then presented to illustrate a working example of a distinct neurodiagnostic technique, and the mathematical and physical principles underlying these techniques are explained. Finally, the author returns to the patient, and examines how the presented technology can help provide a diagnosis for each case.From Neurology to Methodology and Back serves as an upper-undergraduate/graduate level guide for those interested in a translational approach between the fields of medicine and technology in neuroengineering. Neurologists and residents in neurology, medical engineers, medical students, biomedical engineers and students, technical medicine students or students of other interdisciplinary fields will therefore all find this book useful.