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Wireless Sensor Networks
Information processing in sensor networks is a rapidly emerging area of computer science and electrical engineering research. Because of advances in micro-sensors, wireless networking and embedded processing, ad hoc networks of sensor are becoming increasingly available for commercial, military, and homeland security applications. Examples include monitoring (e.g., traffic, habitat, security), industrail sensing and diagnostics (e.g., factory, appliances), infrastructures (i.e., power grid, water distribution, waste disposal) and battle awareness (e.g., multi-target tracking). This book introduces practitioners to the fundamental issues and technology constraints concerning various aspects o...
Algorithms - ESA 2006
This book constitutes the refereed proceedings of the 14th Annual European Symposium on Algorithms, ESA 2006, held in Zurich, Switzerland, in September 2006, in the context of the combined conference ALGO 2006. The 70 revised full papers presented together with abstracts of 3 invited lectures were carefully reviewed and selected from 287 submissions. The papers address all current subjects in algorithmics, reaching from design and analysis issues of algorithms over to real-world applications and engineering of algorithms in various fields.
Communications Engineering e-Mega Reference
A one-stop Desk Reference, for R&D engineers involved in communications engineering; this is a book that will not gather dust on the shelf. It brings together the essential professional reference content from leading international contributors in the field. Material covers a wide scope of topics including voice, computer, facsimile, video, and multimedia data technologies * A fully searchable Mega Reference Ebook, providing all the essential material needed by Communications Engineers on a day-to-day basis. * Fundamentals, key techniques, engineering best practice and rules-of-thumb together in one quick-reference.* Over 2,500 pages of reference material, including over 1,500 pages not included in the print edition
Topology for Computing
The emerging field of computational topology utilizes theory from topology and the power of computing to solve problems in diverse fields. Recent applications include computer graphics, computer-aided design (CAD), and structural biology, all of which involve understanding the intrinsic shape of some real or abstract space. A primary goal of this book is to present basic concepts from topology and Morse theory to enable a non-specialist to grasp and participate in current research in computational topology. The author gives a self-contained presentation of the mathematical concepts from a computer scientist's point of view, combining point set topology, algebraic topology, group theory, differential manifolds, and Morse theory. He also presents some recent advances in the area, including topological persistence and hierarchical Morse complexes. Throughout, the focus is on computational challenges and on presenting algorithms and data structures when appropriate.
Handbook of Data Structures and Applications
Although there are many advanced and specialized texts and handbooks on algorithms, until now there was no book that focused exclusively on the wide variety of data structures that have been reported in the literature. The Handbook of Data Structures and Applications responds to the needs of students, professionals, and researchers who need a mainstream reference on data structures by providing a comprehensive survey of data structures of various types. Divided into seven parts, the text begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next ana...
Machine Learning and Knowledge Discovery in Databases, Part II
This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.
Spectral Geometry of Shapes
Spectral Geometry of Shapes presents unique shape analysis approaches based on shape spectrum in differential geometry. It provides insights on how to develop geometry-based methods for 3D shape analysis. The book is an ideal learning resource for graduate students and researchers in computer science, computer engineering and applied mathematics who have an interest in 3D shape analysis, shape motion analysis, image analysis, medical image analysis, computer vision and computer graphics. Due to the rapid advancement of 3D acquisition technologies there has been a big increase in 3D shape data that requires a variety of shape analysis methods, hence the need for this comprehensive resource. P...
Applied Computational Geometry. Towards Geometric Engineering
Content Description #Anthology selected from contributions to the First ACM Workshop on Applied Computational Geometry.#Includes bibliographical references and index.
Spectral Methods for Isometric Shape Matching and Symmetry Detection
Shape matching and symmetry detection are among the most basic operations in digital geometry processing with applications ranging from medical imaging to industrial design and inspection. While the majority of prior work has concentrated on rigid or extrinsic matching and symmetry detection, many real objects are non-rigid and can exhibit a variety of poses and deformations. In this thesis, we present several methods for analyzing and matching such deformable shapes. In particular, we restrict our attention to shapes undergoing changes that can be well approximated by intrinsic isometries, i.e. deformations that preserve geodesic distances between all pairs of points. This class of deformat...
