The revised and extended papers collected in this volume represent the cutting-edge of research at the nexus of electrical engineering and intelligent systems. They were selected from well over 1000 papers submitted to the high-profile international World Congress on Engineering held in London in July 2011. The chapters cover material across the full spectrum of work in the field, including computational intelligence, control engineering, network management, and wireless networks. Readers will also find substantive papers on signal processing, Internet computing, high performance computing, and industrial applications.
The Electrical Engineering and Intelligent Systems conference, as part of the 2011 World Congress on Engineering was organized under the auspices of the non-profit International Association of Engineers (IAENG). With more than 30 nations represented on the conference committees alone, the Congress features the best and brightest scientific minds from a multitude of disciplines related to engineering. These peer-reviewed papers demonstrate the huge strides currently being taken in this rapidly developing field and reflect the excitement of those at the frontiers of this research.

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Scientists today collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modelling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis.
Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis; they are drwan from growth analysis, meterology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology while keeping the mathematical level widely accessible. It is designed to appeal to students, to applied data analysts, and to experienced researchers; it will have value both within statistics and across a broad spectrum of other fields. Much of the material is based on the authors’ own work, some of which appears here for the first time. Jim Ramsay is Professor of Psychology at McGill University and is an international authority on many aspects of multivariate analysis. He draws on his collaboration with researchers in speech articulation, motor control, meteorology, psychology, and human physiology to illustrate his technical contributions to functional data analysis in a wide range of statistical and application journals. Bernard Silverman, author of the highly regarded “Density Estimation for Statistics and Data Analysis,” and coauthor of “Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach,” is Professor of Statistics at Bristol University. His published work on smoothing methods and other aspects of applied, computational, and theoretical statistics has been recognized by the Presidents’ Award of the Committee of Presidents of Statistical Societies, and the award of two Guy Medals by the Royal Statistical Society.

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DI John Rebus is a hard drinking, unkempt, womanizing police officer whose job is his whole life. He is the most senior and most experienced DI at his station. He has a mysterious past that his partner DS Siobhan Clarke learns about from time to time through various comments Rebus makes. She is a young woman who wants to succeed, but does not have much of a personal life. She feels being paired with Rebus jeopardizes her career because of his unorthodox methods, but she is also fascinated by the man and is extremely loyal. DI Rebus’ boss is Chief Superintendent Templar, a woman who was one of Rebus’ lovers in a distant past. Their relationship is now one where they barely tolerate each other.

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A 30-year-old writer (Elizabeth Lail) spends a wild weekend in Palm Springs and wakes up to find she has magically transformed into her 70-year-old self (Diane Keaton).

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In the aftermath of a huge scandal, Trinitie Childs, the first lady of a prominent Southern Baptist Mega Church, attempts to help her pastor-husband, Lee-Curtis Childs, rebuild their congregation.

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Set in high-end San Francisco, Surface follows Sophie, a woman who has suffered a traumatic head injury that has left her with extreme memory loss, believed to be a result of a suicide attempt. As Sophie embarks on a quest to put the pieces of her life back together with the help of her husband and friends, she begins to question whether or not the truth she is told is in fact the truth she has lived. Through twists and turns and a shocking love triangle, this sexy, elevated thriller asks: What if you woke up one day and didn’t know your own secrets?

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All Jason and Nikki want is a baby. But it’s the one thing they just can’t have.

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Naked News is the only fully nude news program of its kind in the world that is real news, breaking news from around the world, sports, entertainment and infotainment programs delivered by a roster of completely naked, attractive and intelligent women. But nude news, nude weather, nude sports and nude entertainment is not all we are about. We have nude amateur auditions, nude celebrity models and our famous Naked in the Street interviews. Nude women reporting all the nude news you need to know to be informed and entertained at the same time. Very simply, Naked News is unique, there is nothing like us anywhere.

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Scientists and others today often collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modeling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis. Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis; they are drawn from growth analysis, meteorology, biomechanics, equine science, economics, and medicine.
The book presents novel statistical technology, much of it based on the authors’ own research work, while keeping the mathematical level widely accessible. It is designed to appeal to students, to applied data analysts, and to experienced researchers; it will have value both within statistics and across a broad spectrum of other fields.

This second edition is aimed at a wider range of readers, and especially those who would like to apply these techniques to their research problems. It complements the authors’ other recent volume Applied Functional Data Analysis: Methods and Case Studies. In particular, there is an extended coverage of data smoothing and other matters arising in the preliminaries to a functional data analysis. The chapters on the functional linear model and modeling of the dynamics of systems through the use of differential equations and principal differential analysis have been completely rewritten and extended to include new developments. Other chapters have been revised substantially, often to give more weight to examples and practical considerations.

Jim Ramsay is Professor of Psychology at McGill University and is an international authority on many aspects of multivariate analysis. He was President of the Statistical Society of Canada in 2002-3 and holds the Society’s Gold Medal for his work in functional data analysis.

Bernard Silverman is Master of St Peter’s College and Professor of Statistics at Oxford University. He was President of the Institute of Mathematical Statistics in 2000–1. He is a Fellow of the Royal Society. His main specialty is in computational statistics, and he is the author or editor of several highly regarded books in this area.

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Fundamentals of Structural Engineering provides a balanced, seamless treatment of both classic, analytic methods and contemporary, computer-based techniques for conceptualizing and designing a structure. The book’s principle goal is to foster an intuitive understanding of structural behavior based on problem solving experience for students of civil engineering and architecture who have been exposed to the basic concepts of engineering mechanics and mechanics of materials.
Making it distinct from many other undergraduate textbooks, the authors of this text recognize the notion that engineers reason about behavior using simple models and intuition they acquire through problem solving. The approach adopted in this text develops this type of intuition by presenting extensive, realistic problems and case studies together with computer simulation, which allows rapid exploration of how a structure responds to changes in geometry and physical parameters.

This book also

Emphasizes problem-based understanding of structural behavior
Organizes chapters by structural types
Provides balanced, seamless treatment of both classic and contemporary computer-based analysis methods
Offers extensive sample problems and detailed solutions to problems of structural analysis
Cultivates intuitive thinking about structural behavior
Incorporates input data operable with numerous widely used engineering design software packages
Features 900 figures and graphs
The integrated approach employed in Fundamentals of Structural Engineering makes it an ideal and comprehensive book for students and an authoritative reference for practitioners of structural engineering.
Science Cable Structures Structural Engineering Engineering

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This book has evolved from my experience over the past decade in teaching and doing research in functional analysis and certain of its appli­ cations. These applications are to optimization theory in general and to best approximation theory in particular.
The geometric nature of the subjects has greatly influenced the approach to functional analysis presented herein, especially its basis on the unifying concept of convexity. Most of the major theorems either concern or depend on properties of convex sets; the others generally pertain to conjugate spaces or compactness properties, both of which topics are important for the proper setting and resolution of optimization problems. In consequence, and in contrast to most other treatments of functional analysis, there is no discussion of spectral theory, and only the most basic and general properties of linear operators are established. Some of the theoretical highlights of the book are the Banach space theorems associated with the names of Dixmier, Krein, James, Smulian, Bishop-Phelps, Brondsted-Rockafellar, and Bessaga-Pelczynski. Prior to these (and others) we establish to two most important principles of geometric functional analysis: the extended Krein-Milman theorem and the Hahn­ Banach principle, the latter appearing in ten different but equivalent formula­ tions (some of which are optimality criteria for convex programs). In addition, a good deal of attention is paid to properties and characterizations of conjugate spaces, especially reflexive spaces.

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This introduction to the ideas and methods of linear functional analysis shows how familiar and useful concepts from finite-dimensional linear algebra can be extended or generalized to infinite-dimensional spaces. Aimed at advanced undergraduates in mathematics and physics, the book assumes a standard background of linear algebra, real analysis (including the theory of metric spaces), and Lebesgue integration, although an introductory chapter summarizes the requisite material.
The initial chapters develop the theory of infinite-dimensional normed spaces, in particular Hilbert spaces, after which the emphasis shifts to studying operators between such spaces. Functional analysis has applications to a vast range of areas of mathematics; the final chapters discuss the particularly important areas of integral and differential equations.

Further highlights of the second edition include

a new chapter on the Hahn–Banach theorem and its applications to the theory of duality. This chapter also introduces the basic properties of projection operators on Banach spaces, and weak convergence of sequences in Banach spaces – topics that have applications to both linear and nonlinear functional analysis;

extended coverage of the uniform boundedness theorem;

plenty of exercises, with solutions provided at the back of the book.

Praise for the first edition

“The authors write with a strong narrative thrust and a sensitive appreciation of the needs of the average student so that, by the final chapter, there is a real feeling of having ‘gotten somewhere worth getting’ by a sensibly paced, clearly signposted route.” Mathematical Gazette

“It is a fine book, with material well-organized and well-presented. A particularly useful feature is the material on compact operators and applications to differential equations.” CHOICE

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