A "how to" guide for applying statistical methods to biomarker data analysis Presenting a solid foundation for the statistical methods that are used to analyze biomarker data, Analysis of Biomarker Data: A Practical Guide features preferred techniques for biomarker validation. The authors provide descriptions of select elementary statistical methods that are traditionally used to analyze biomarker data with a focus on the proper application of each method, including necessary assumptions, software recommendations, and proper interpretation of computer output. In addition, the book discusses frequently encountered challenges in analyzing biomarker data and how to deal with them, methods for the quality assessment of biomarkers, and biomarker study designs. Covering a broad range of statistical methods that have been used to analyze biomarker data in published research studies, Analysis of Biomarker Data: A Practical Guide also features: A greater emphasis on the application of methods as opposed to the underlying statistical and mathematical theory The use of SAS(R), R, and other software throughout to illustrate the presented calculations for each example Numerous exercises based on real-world data as well as solutions to the problems to aid in reader comprehension The principles of good research study design and the methods for assessing the quality of a newly proposed biomarker A companion website that includes a software appendix with multiple types of software and complete data sets from the book's examples Analysis of Biomarker Data: A Practical Guide is an ideal upper-undergraduate and graduate-level textbook for courses in the biological or environmental sciences. An excellent reference for statisticians who routinely analyze and interpret biomarker data, the book is also useful for researchers who wish to perform their own analyses of biomarker data, such as toxicologists, pharmacologists, epidemiologists, environmental and clinical laboratory scientists, and other professionals in the health and environmental sciences.

Oracle 10g Data Warehousing is a guide to using the Data Warehouse features in the latest version of Oracle -Oracle Database 10g. Written by people on the Oracle development team that designed and implemented the code and by people with industry experience implementing warehouses using Oracle technology, this thoroughly updated and extended edition provides an insider's view of how the Oracle Database 10g software is best used for your application.
It provides a detailed look at the new features of Oracle Database 10g and other Oracle products and how these are used in the data warehouse. This book will show you how to deploy the Oracle database and correctly use the new Oracle Database 10g features for your data warehouse. It contains walkthroughs and examples on how to use tools such as Oracle Discoverer and Reports to query the warehouse and generate reports that can be deployed over the web and gain better insight into your business.
This how-to guide provides step by step instructions including screen captures to make it easier to design, build and optimize performance of the data warehouse or data mart. It is a 'must have' reference for database developers, administrators and IT professionals who want to get to work now with all of the newest features of Oracle Database 10g.
It provides a detailed look at the new features of Oracle Database 10g and other Oracle products and how these are used in the data warehouse, including:
* How to use the Summary Management features, including Materialized Views and query rewrite, to best effect to radically improve query performance
* How to deploy business intelligence to the Web to satisfy today's changing and demandingbusiness requirements
* Using Oracle OLAP and Data Mining options
* How to understand the warehouse hardware environment and how it is used by new features in the database including how to implement a high availability warehouse
environment
* Using the new management infrastructure in Oracle Database 10g and how this helps you to manage your warehouse environment

This beginner's introduction to MATLAB teaches a sufficient subset of the functionality and gives the reader practical experience on how to find more information. A forty-page appendix contains unique user-friendly summaries and tables of MATLAB functions enabling the reader to find appropriate functions, understand their syntax and get a good overview. The large number of exercises, tips, and solutions mean that the course can be followed with or without a computer. Recent development in MATLAB to advance programming is described using realistic examples in order to prepare students for larger programming projects.  Revolutionary step by step 'guided tour' eliminates the steep learning curve encountered in learning new programming languages. Each chapter corresponds to an actual engineering course, where examples in MATLAB illustrate the typical theory, providing a practical understanding of these courses. Complementary homepage contains exercises, a take-home examination, and an automatic marking that grades the solution. End of chapter exercises with selected solutions in an appendix. The development of MATLAB programming and the rapid increase in the use of MATLAB in engineering courses makes this a valuable self-study guide for both engineering students and practising engineers. Readers will find that this time-less material can be used throughout their education and into their career.

Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics investigates and presents the many applications that have arisen in the last ten years using neutrosophic statistics in bioinformatics, medicine, agriculture and cognitive science. This book will be very useful to the scientific community, appealing to audiences interested in fuzzy, vague concepts from which uncertain data are collected, including academic researchers, practicing engineers and graduate students. Neutrosophic statistics is a generalization of classical statistics. In classical statistics, the data is known, formed by crisp numbers. In comparison, data in neutrosophic statistics has some indeterminacy. This data may be ambiguous, vague, imprecise, incomplete, and even unknown. Neutrosophic statistics refers to a set of data, such that the data or a part of it are indeterminate in some degree, and to methods used to analyze the data.

Given the explosion of interest in mathematical methods for solving problems in finance and trading, a great deal of research and development is taking place in universities, large brokerage firms, and in the supporting trading software industry. Mathematical advances have been made both analytically and numerically in finding practical solutions.

This book provides a comprehensive overview of existing and original material, about what mathematics when allied with Mathematica can do for finance. Sophisticated theories are presented systematically in a user-friendly style, and a powerful combination of mathematical rigor and Mathematica programming. Three kinds of solution methods are emphasized: symbolic, numerical, and Monte-- Carlo. Nowadays, only good personal computers are required to handle the symbolic and numerical methods that are developed in this book.

Key features: * No previous knowledge of Mathematica programming is required * The symbolic, numeric, data management and graphic capabilities of Mathematica are fully utilized * Monte--Carlo solutions of scalar and multivariable SDEs are developed and utilized heavily in discussing trading issues such as Black--Scholes hedging * Black--Scholes and Dupire PDEs are solved symbolically and numerically * Fast numerical solutions to free boundary problems with details of their Mathematica realizations are provided * Comprehensive study of optimal portfolio diversification, including an original theory of optimal portfolio hedging under non-Log-Normal asset price dynamics is presented

The book is designed for the academic community of instructors and students, and most importantly, will meet the everyday trading needs of quantitatively inclined professional and individual investors.

The recent pursuits emerging in the realm of big data processing, interpretation, collection and organization have emerged in numerous sectors including business, industry and government organizations. Data sets such as customer transactions for a mega-retailer, weathermonitoring, intelligence gathering, quickly outpace the capacities of traditional techniques and tools of data analysis. The 3V (volume, variability and velocity) challenges led to the emergence of new techniques and tools in data visualization, acquisition, and serialization. Soft Computing being regarded as a plethora of technologies of fuzzy sets (or Granular Computing), neurocomputing and evolutionary optimization brings forward a number of unique features that might be instrumental to the development of concepts and algorithms to deal with big data.

This carefully edited volume provides the reader with an updated, in-depth material on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of big data architectures, analysis, and interpretation as well as data analytics. The book is aimed at a broad audience of researchers and practitioners including those active in various disciplines in which big data, their analysis and optimization are of genuine relevance. One focal point is the systematic exposure of the concepts, design methodology, and detailed algorithms. In general, the volume adheres to the top-down strategy starting with the concepts and motivation and then proceeding with the detailed design that materializes in specific algorithms and representative applications. The material is self-contained and provides the reader with all necessary prerequisites and augments some parts with a step-by-step explanation of more advanced concepts supported by a significant amount of illustrative numeric material and some application scenarios to motivate the reader and make some abstract concepts more tangible."

Correcting the Great Mistake People often mistake one thing for another. That's human nature. However, one would expect the leaders in a particular ?eld of endeavour to have superior ab- ities to discriminate among the developments within that ?eld. That is why it is so perplexing that the technology elite - supposedly savvy folk such as software developers, marketers and businessmen - have continually mistaken Web-based graphics for something it is not. The ?rst great graphics technology for the Web, VRML, has been mistaken for something else since its inception. Viewed variously as a game system, a format for architectural walkthroughs, a platform for multi-user chat and an augmentation of reality, VRML may qualify as the least understood invention in the history of inf- mation technology. Perhaps it is so because when VRML was originally introduced it was touted as a tool for putting the shopping malls of the world online, at once prosaic and horrifyingly mundane to those of us who were developing it. Perhaps those ?rst two initials,"VR,"created expectations of sprawling, photorealistic f- tasy landscapes for exploration and play across the Web. Or perhaps the magnitude of the invention was simply too great to be understood at the time by the many, ironically even by those spending the money to underwrite its development. Regardless of the reasons, VRML suffered in the mainstream as it was twisted to meet unintended ends and stretched far beyond its limitations.

This book contains a selection of papers from the 16th International Symposium on Spatial Data Handling (SDH), the premier long-running forum in geographical information science. This collection offers readers exemplary contributions to geospatial scholarship and practice from the conference's 30th anniversary.

This is a book about the scientific process and how you apply it to data in ecology. You will learn how to plan for data collection, how to assemble data, how to analyze data and finally how to present the results. The book uses Microsoft Excel and the powerful Open Source R program to carry out data handling as well as producing graphs. Statistical approaches covered include: data exploration; tests for difference - t-test and U-test; correlation - Spearman's rank test and Pearson product-moment; association including Chi-squared tests and goodness of fit; multivariate testing using analysis of variance (ANOVA) and Kruskal-Wallis test; and multiple regression. Key skills taught in this book include: how to plan ecological projects; how to record and assemble your data; how to use R and Excel for data analysis and graphs; how to carry out a wide range of statistical analyses including analysis of variance and regression; how to create professional looking graphs; and how to present your results. New in this edition: a completely revised chapter on graphics including graph types and their uses, Excel Chart Tools, R graphics commands and producing different chart types in Excel and in R; an expanded range of support material online, including; example data, exercises and additional notes & explanations; a new chapter on basic community statistics, biodiversity and similarity; chapter summaries and end-of-chapter exercises. Praise for the first edition: This book is a superb way in for all those looking at how to design investigations and collect data to support their findings. - Sue Townsend, Biodiversity Learning Manager, Field Studies Council [M]akes it easy for the reader to synthesise R and Excel and there is extra help and sample data available on the free companion webpage if needed. I recommended this text to the university library as well as to colleagues at my student workshops on R. Although I initially bought this book when I wanted to discover R I actually also learned new techniques for data manipulation and management in Excel - Mark Edwards, EcoBlogging A must for anyone getting to grips with data analysis using R and excel. - Amazon 5-star review It has been very easy to follow and will be perfect for anyone. - Amazon 5-star review A solid introduction to working with Excel and R. The writing is clear and informative, the book provides plenty of examples and figures so that each string of code in R or step in Excel is understood by the reader. - Goodreads, 4-star review

This book is a collection of writings by active researchers in the field of Artificial General Intelligence, on topics of central importance in the field. Each chapter focuses on one theoretical problem, proposes a novel solution, and is written in sufficiently non-technical language to be understandable by advanced undergraduates or scientists in allied fields. This book is the very first collection in the field of Artificial General Intelligence (AGI) focusing on theoretical, conceptual, and philosophical issues in the creation of thinking machines. All the authors are researchers actively developing AGI projects, thus distinguishing the book from much of the theoretical cognitive science and AI literature, which is generally quite divorced from practical AGI system building issues. And the discussions are presented in a way that makes the problems and proposed solutions understandable to a wide readership of non-specialists, providing a distinction from the journal and conference-proceedings literature. The book will benefit AGI researchers and students by giving them a solid orientation in the conceptual foundations of the field (which is not currently available anywhere); and it would benefit researchers in allied fields by giving them a high-level view of the current state of thinking in the AGI field. Furthermore, by addressing key topics in the field in a coherent way, the collection as a whole may play an important role in guiding future research in both theoretical and practical AGI, and in linking AGI research with work in allied disciplines

This book is a compilation of a selected subset of research articles presented at the Eighth INFORMS Computing Society Conference, held in Chandler, Arizona, from January 8 to 10, 2003. The articles in this book represent the diversity and depth of the interface between ORiMS (operations research and the management sciences) and CS/AI (computer science and artificial intelligence ). This volume starts with two papers that represent the reflective and integrative thinking that is critical to any scientific discipline. These two articles present philosophical perspectives on computation, covering a variety of traditional and newer methods for modeling, solving, and explaining mathematical models. The next set includes articles that study machine learning and computational heuristics, and is followed by articles that address issues in performance testing of solution algorithms and heuristics. These two sets of papers demonstrate the richness of thought that takes place at the ORiMS and CSI AI interface. The final set of articles demonstrates the usefulness of these and other methods at the interface towards solving problems in the real world, covering e-commerce, workflow, electronic negotiation, music, parallel computation, and telecommunications. The articles in this collection represent the results of cross-fertilization between ORiMS and CSI AI, making possible advances that could have not been achieved in isolation. The continuing aim ofthe INFORMS Computing Society and this research conference is to invigorate and further develop this interface.

This book includes 23 papers dealing with the impact of modern information and communication technologies that support a wide variety of communities: local communities, virtual communities, and communities of practice, such as knowledge communities and scientific communities. The volume is the result of the second multidisciplinary "Communities and Technologies Conference," a major event in this emerging research field. The various chapters discuss how communities are affected by technologies, and how understanding of the way that communities function can be used in improving information systems design. This state of the art overview will be of interest to computer and information scientists, social scientists and practitioners alike.

Software for complex problem solving can dazzle people with advanced features and alluring visuals, but when actually put to use it often disappoints and even frustrates users. This software rarely follows the user's own work methods, nor does it give people the degree of control and choice that they truly need.
This book presents a groundbreaking approach to interaction design for complex problem solving applications. The author uses her vast field experience to present a new way of looking at the whole process, and treats complex problem solving software and web applications as a distinct class with its own set of usefulness demands and design criteria. This approach highlights integrated interactions rather than discrete actions, clearly defines what makes problem solving complex, and explores strategies for analyzing, modeling, and designing for exploratory inquiries.
-In depth case studies ranging from IT troubleshooting to marketing analysis to risk assessments in healthcare show exactly where and what goes wrong in real world activities and how to improve them.
-Presents a system and framework for analyzing complex work and takes the mystery out of eliciting patterns of work and their meanings.
-Offers new perspectives for support and new design strategies for building the right models into programs so that they effectively address users' dynamic work.
-Allows designers to turn findings into useful designs for problems that require users to create new knowledge but with no one right answer and with many methods of reaching solutions.

The heart of any system that simulates the physical interaction between objects is collision detection-the ability to detect when two objects have come into contact. This system is also one of the most difficult aspects of a physical simulation to implement correctly, and invariably it is the main consumer of CPU cycles. Practitioners, new to the field or otherwise, quickly discover that the attempt to build a fast, accurate, and robust collision detection system takes them down a long path fraught with perils and pitfalls unlike most they have ever encountered. Without in-depth knowledge and understanding of the issues associated with engineering a collision detection system, the end of that path is an abyss that has swallowed many a good programmer!
Gino van den Bergen's new book is the story of his successful journey down that path. The outcome is his well-known collision detection system, the SOftware Library for Interference Detection (SOLID). Along the way, he covers the topics of vector algebra and geometry, the various geometric primitives of interest in a collision system, the powerful method of separating axes for the purposes of intersection testing, and the equally powerful Gilbert-Johnson-Keerthi (GJK) algorithm for computing the distance between convex objects. But this book provides much more than a good compendium of the ideas that go into building a collision system. The curse of practical computational geometry is floating-point arithmetic. Algorithms with straightforward implementations when using exact arithmetic can have catastrophic failures in a floating-point system. Specifically, intersection and distance algorithms implemented in a floating-point systemtend to fail exactly in the most important case in a collision system-when two objects are just touching. Great care must be taken to properly handle floating-point round off errors. Gino's ultimate accomplishment in this book is his presentation on how to correctly implement the GJK distance algorithm in the presence of single-precision floating-point arithmetic. And what better way to illustrate this than with a case study, the final chapter on the design and implementation of SOLID.
About the CD-ROM
The companion CD-ROM includes the full C++ source code of SOLID 3.5 as well as API documentation in HTML and PDF formats. Both single (32bit) and double (64bit) precision versions of the SOLID SDK plus example programs can be compiled for Linux platforms using GNU g++ version 2.95 to 3.3 and for Win32 platforms using Microsoft Visual C++ version 6.0 to 7.1. Use of the SOLID source code is governed by the terms of either the GNU GPL or the Trolltech QPL (see CD-ROM documentation for details).
About the Author
Gino van den Bergen is a game developer living and working in The Netherlands. He is the creator of SOLID and holds a Ph.D. in computing science from Eindhoven University of Technology. Gino implemented collision detection and physics in NaN Technologies' Blender, a creation suite for interactive 3D content.
*Explains the fundamental geometric and numerical concepts that underlie the key algorithms of collision detection.
*CD-ROM includes the full C++ source code of SOLID, a well-known library for collision detection, plus binaries and example programs for Win32.
*Discusses algorithms for commonly used primitive types, such as spheres, boxes, cylinders, cones, triangles, rays, and convex polyhedra.
*Presents techniques for accelerating collision detection for complex models and scenes.

This comprehensive book draws together experts to explore how knowledge technologies can be exploited to create new multimedia applications, and how multimedia technologies can provide new contexts for the use of knowledge technologies. Thorough coverage of all relevant topics is given. The step-by-step approach guides the reader from fundamental enabling technologies of ontologies, analysis and reasoning, through to applications which have hitherto had less attention.

This book provides a conceptual and computational framework to study how the nervous system exploits the anatomical properties of limbs to produce mechanical function. The study of the neural control of limbs has historically emphasized the use of optimization to find solutions to the muscle redundancy problem. That is, how does the nervous system select a specific muscle coordination pattern when the many muscles of a limb allow for multiple solutions? I revisit this problem from the emerging perspective of neuromechanics that emphasizes finding and implementing families of feasible solutions, instead of a single and unique optimal solution. Those families of feasible solutions emerge naturally from the interactions among the feasible neural commands, anatomy of the limb, and constraints of the task. Such alternative perspective to the neural control of limb function is not only biologically plausible, but sheds light on the most central tenets and debates in the fields of neural control, robotics, rehabilitation, and brain-body co-evolutionary adaptations. This perspective developed from courses I taught to engineers and life scientists at Cornell University and the University of Southern California, and is made possible by combining fundamental concepts from mechanics, anatomy, mathematics, robotics and neuroscience with advances in the field of computational geometry. Fundamentals of Neuromechanics is intended for neuroscientists, roboticists, engineers, physicians, evolutionary biologists, athletes, and physical and occupational therapists seeking to advance their understanding of neuromechanics. Therefore, the tone is decidedly pedagogical, engaging, integrative, and practical to make it accessible to people coming from a broad spectrum of disciplines. I attempt to tread the line between making the mathematical exposition accessible to life scientists, and convey the wonder and complexity of neuroscience to engineers and computational scientists. While no one approach can hope to definitively resolve the important questions in these related fields, I hope to provide you with the fundamental background and tools to allow you to contribute to the emerging field of neuromechanics.

The importance of knowledge and information technology management has been emphasized both by researchers and practitioners in order for companies to compete in the global market. Now such technologies have become crucial in a sense that there is a need to understand the business and operations strategies, as well as how the development of IT would contribute to knowledge management and therefore increase competitiveness. Knowledge and Information Technology Management: Human and Social Perspectives strives to explore the human resource and social dimensions of knowledge and IT management, to discuss the opportunities and major issues related to the management of people along the supply chain in Internet marketing, and to provide an understanding of how the human resource and the IT management should complement each other for improved communication and competitiveness.

Here is a thorough, not-overly-complex introduction to the three technical foundations for multimedia applications across the Internet: communications (principles, technologies and networking); compressive encoding of digital media; and Internet protocol and services. All the contributing systems elements are explained through descriptive text and numerous illustrative figures; the result is a book well-suited toward non-specialists, preferably with technical background, who need well-composed tutorial introductions to the three foundation areas. The text discusses the latest advances in digital audio and video encoding, optical and wireless communications technologies, high-speed access networks, and IP-based media streaming, all crucial enablers of the multimedia Internet.

Understanding how the human brain represents, stores, and processes information is one of the greatest unsolved mysteries of science today. The cerebral cortex is the seat of most of the mental capabilities that distinguish humans from other animals and, once understood, it will almost certainly lead to a better knowledge of other brain nuclei. Although neuroscience research has been underway for 150 years, very little progress has been made. What is needed is a key concept that will trigger a full understanding of existing information, and will also help to identify future directions for research. This book aims to help identify this key concept. Including contributions from leading experts in the field, it provides an overview of different conceptual frameworks that indicate how some pieces of the neuroscience puzzle fit together. It offers a representative selection of current ideas, concepts, analyses, calculations and computer experiments, and also looks at important advances such as the application of new modeling methodologies. Computational Models for Neuroscience will be essential reading for anyone who needs to keep up-to-date with the latest ideas in computational neuroscience, machine intelligence, and intelligent systems. It will also be useful background reading for advanced undergraduates and postgraduates taking courses in neuroscience and psychology.

Over the past 80 years, the way that citation frequency was counted and analyzed changed dramatically from the early manual transcribing and statistical computation of citation data to computer-based citation data creation and its manipulation.""Author Cocitation Analysis: Quantitative Methods for Mapping the Intellectual Structure of an Academic Discipline"" provides a blueprint for researchers to follow in a wide variety of investigations. Pertinent to faculty, researchers, and graduate students in any academic field, this book introduces an alternative approach to conducting author cocitation analysis (ACA) without relying on commercial citation databases.