To the ancient Greeks the universe consisted of earth, air, fire and water. To Saint Augustine it was the Word of God. To many modern scientists it is the interaction of atoms and waves, and in years to come it may be different again. What then is the real universe? History shows that in every age society constructs its own universe, believing it to be the real and final one. Yet these are only models, or masks covering what is not understood and not known. This book brings together fundamental scientific, philosophical, and religious issues in cosmology, raising thought provoking questions. In every age people have pitied the universes of their ancestors, convinced that they have at last discovered the full truth. Do we now stand at the threshold of knowing everything, or will our latest model also be rejected by our descendants?

Does the weather get warmer in summer because the Earth moves closer to the sun? That many people believe this is a perfect example of common sense leading to scientific misconception, the kind of misconception Neil Comins strives to set straight in Heavenly Errors. Comins is particularly eager to stamp out errors about astronomy, his field, and in his book he explores–and corrects–1,500 "commonly held" astronomical beliefs. Along the way, he investigates the nature of misconceptions, how and why we acquire them, and how to guard against them. He identifies external culprits, such as science fiction films, the Internet, and advertising, and examines how the psychological traits that help humans survive are poor tools for understanding "the real nature of the universe."

In Good and Real, Gary Drescher examines a series of provocative paradoxes about consciousness, choice, ethics, quantum mechanics, and other topics, in an effort to reconcile a purely mechanical view of the universe with key aspects of our subjective impressions of our own existence.

Discover how to streamline complex bioinformatics applications with parallel computing. This publication enables readers to handle more complex bioinformatics applications and larger and richer data sets. As the editor clearly shows, using powerful parallel computing tools can lead to significant breakthroughs in deciphering genomes, understanding genetic disease, designing customized drug therapies, and understanding evolution.

This book provides a basic understanding of the theories, associated algorithms, resources, and tools used in structural bioinformatics. The reader emerges with the ability to make effective use of protein, DNA, RNA, carbohydrate, and complex structures to better understand biological function. Moreover, it draws a clear connection between structural studies and the rational design of new therapies.

"A must read for all of us committed to understanding the interplay of structure and function. The individual chapters outline the suite of major basic life science questions such as the status of efforts to predict protein structure and how proteins carry out cellular functions, and also the applied life science questions such as how structural bioinformatics can improve health care through accelerating drug discovery."

Written by a pioneer of the use of bioinformatics in research, the second edition of Introduction to Bioinformatics introduces the student to the power of bioinformatics as a set of scientific tools. Retaining and enhancing the rich pedagogy and lucid presentation of the first edition, this new edition explains how to access the data archives of genomes and proteins, and the kind of questions these data and tools can answer. It also discusses how to make inferences from the data archives, how to make connections among them, and how to derive useful and interesting predictions.

A quantitative study of the efficiency of computer methods requires an in-depth understanding of both mathematics and computer science. This monograph, derived from an advanced computer science course at Stanford University, builds on the fundamentals of combinatorial analysis and complex variable theory to present many of the major paradigms used in the precise analysis of algorithms, emphasizing the more difficult notions.

Goal Directed Proof Theory presents a uniform and coherent methodology for automated deduction in non-classical logics, the relevance of which to computer science is now widely acknowledged. The methodology is based on goal-directed provability. It is a generalization of the logic programming style of deduction, and it is particularly favourable for proof search.

Every real-world problem from economic to scientific and engineering fields is ultimately confronted with a common task, viz., optimization. Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. The goal of this book is to provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms.

Provides an introduction to dynamic modeling in cell biology, emphasizing computational approaches based on realistic molecular mechanisms. For students in neuroscience, cell biology, and theoretical biology. Contains numerous halftone charts, graphs, and illustrations.

Comprises an imaginative collection of pieces created in tribute to Martin Gardner. Contains pieces as widely varied as Gardner's own interests ranging from limericks to lengthly treatises, from mathematical journal articles to personal stories.

*Note* The title on the cover is different from the title inside the book. The book has both been called Cyber Crime Investigator's Field Guide or Cyber Crime Field Handbook. This is the correct cover.

Provides the details of investigating computer crime from soup to nuts. Covers everything from what to do upon arrival at the scene until the investigation is complete, including the chain of evidence.

Offers valuable information on using the forensic utilities for preserving evidence and searching for hidden information in the process of devising solutions to computer related crime.

The second edition of this critically-acclaimed text continues the standard of excellence set in the first edition by providing a thorough introduction to the fundamentals of telecommunication networks without bogging you down in complex technical jargon or math. Although focusing on the basics, the book has been thoroughly updated with the latest advances in the field, including a new chapter on metropolitan area networks (MANs) and new sections on Mobile Fi, ZigBee and ultrawideband. You’ll learn which choices are now available to an organization, how to evaluate them and how to develop strategies that achieve the best balance among cost, security and performance factors for voice, data, and image communication.

"Pierre Baldi and Søren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed at two types of researchers and students. First are the biologists and biochemists who need to understand new data-driven algorithms, such as neural networks and hidden Markov models, in the context of biological sequences and their molecular structure and function. Second are those with a primary background in physics, mathematics, statistics, or computer science who need to know more about specific applications in molecular biology."