Hypothesis Generation and Interpretation


Book Description

This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. The author uses patterns discovered in a collection of big data applications to provide design principles for hypothesis generation, integrating big data processing and management, machine learning and data mining techniques. The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on “social infrastructure” applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases. The novel methods and technologies proposed in Hypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns. Academic investigators and practitioners working on the further development and application of hypothesis generation and interpretation in big data computing, with backgrounds in data science and engineering, or the study of problem solving and scientific methods or who employ those ideas in fields like machine learning will find this book of considerable interest.




Learning Statistics with R


Book Description

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com




Psychology of Intelligence Analysis


Book Description

In this seminal work, published by the C.I.A. itself, produced by Intelligence veteran Richards Heuer discusses three pivotal points. First, human minds are ill-equipped ("poorly wired") to cope effectively with both inherent and induced uncertainty. Second, increased knowledge of our inherent biases tends to be of little assistance to the analyst. And lastly, tools and techniques that apply higher levels of critical thinking can substantially improve analysis on complex problems.




Machine Learning and Image Interpretation


Book Description

In this groundbreaking new volume, computer researchers discuss the development of technologies and specific systems that can interpret data with respect to domain knowledge. Although the chapters each illuminate different aspects of image interpretation, all utilize a common approach - one that asserts such interpretation must involve perceptual learning in terms of automated knowledge acquisition and application, as well as feedback and consistency checks between encoding, feature extraction, and the known knowledge structures in a given application domain. The text is profusely illustrated with numerous figures and tables to reinforce the concepts discussed.




3D Shape Analysis


Book Description

An in-depth description of the state-of-the-art of 3D shape analysis techniques and their applications This book discusses the different topics that come under the title of "3D shape analysis". It covers the theoretical foundations and the major solutions that have been presented in the literature. It also establishes links between solutions proposed by different communities that studied 3D shape, such as mathematics and statistics, medical imaging, computer vision, and computer graphics. The first part of 3D Shape Analysis: Fundamentals, Theory, and Applications provides a review of the background concepts such as methods for the acquisition and representation of 3D geometries, and the fundamentals of geometry and topology. It specifically covers stereo matching, structured light, and intrinsic vs. extrinsic properties of shape. Parts 2 and 3 present a range of mathematical and algorithmic tools (which are used for e.g., global descriptors, keypoint detectors, local feature descriptors, and algorithms) that are commonly used for the detection, registration, recognition, classification, and retrieval of 3D objects. Both also place strong emphasis on recent techniques motivated by the spread of commodity devices for 3D acquisition. Part 4 demonstrates the use of these techniques in a selection of 3D shape analysis applications. It covers 3D face recognition, object recognition in 3D scenes, and 3D shape retrieval. It also discusses examples of semantic applications and cross domain 3D retrieval, i.e. how to retrieve 3D models using various types of modalities, e.g. sketches and/or images. The book concludes with a summary of the main ideas and discussions of the future trends. 3D Shape Analysis: Fundamentals, Theory, and Applications is an excellent reference for graduate students, researchers, and professionals in different fields of mathematics, computer science, and engineering. It is also ideal for courses in computer vision and computer graphics, as well as for those seeking 3D industrial/commercial solutions.







Shape, Structure And Pattern Recognition


Book Description

The book is an extensive compilation of the papers presented at the IAPR International Workshop on Structural and Syntactic Pattern Recognition SSPR'94. It includes a preface by Professor Herbert Freeman, who is the recipient of the IAPR King Sun Fu Award for 1994. The book is divided into four parts and covers state-of-the art topics related to a variety of aspects of pattern recognition.




WISC-III Clinical Use and Interpretation


Book Description

The WISC-III is the most frequently used IQ assessment technique in the United States. This book discusses the clinical use of the WISC-III with respect to specific clinical populations, and covers research findings on the validity and reliability of the test. It also includes standardization data from the Psychological Corporation. Many of the contributors participated in the development of the WISC-III and are in a unique position to discuss the clinical uses of this measure. The book describes the WISC-III from scientist-practitioner perspectives. It provides methods to aid in understanding and interpreting the WISC-III results for various groups of exceptional children. The book also presents detailed descriptions of behavior and achievement as well as recommendations for test interpreting standards.WISC-III Clinical Use and Interpretation has immediate and practical relevance to professionals who administer, interpret, or use the results of the WISC-III. The solid writing by leading experts makes the contents of this book an essential reference for WISC-III users. - Leading experts discuss the clinical use of the WISC-III - Thorough coverage of the literature with many new findings - Covers wide range of exceptionalities from AD/HD to learning disabilities - Direct relevance to practitioners, researchers, and trainers




Transforming Education for Personalized Learning


Book Description

The pressing necessity to overhaul education systems to align with the demands of the contemporary world rises. Transforming Education for Personalized Learning delves into the imminent challenges besieging education, offering pragmatic solutions to metamorphose classrooms into dynamic learning environments with research, real-world illustrations, and expert perspectives. It scrutinizes fundamental shifts required in pedagogical methods, curriculum construction, assessment frameworks, and the judicious integration of technology. Central to its philosophy is the accentuation of personalized learning, the cultivation of critical thinking, and the nurturing of creativity and collaboration among students. Emphasizing an inclusive and equitable educational system, the book discerns the varied needs and strengths of learners. It advocates for a future where educators evolve into facilitators of learning, armed with strategies to adapt teaching styles, embrace innovative pedagogies, and craft engaging and purposeful learning experiences. It underscores the imperative for a paradigm shift in education, cognizant of the demands of the 21st century. It advocates for personalized learning approaches that cater to individual strengths, interests, and learning styles. The book also explores innovative teaching methodologies, instructional design, and the effective integration of technology to enhance critical thinking, collaboration, and creativity. The book targets educators, school leaders, policymakers, teacher educators, parents, educational researchers, students, professional development providers, educational consultants, advocacy groups, and non-profits.




Structured Analytic Techniques for Intelligence Analysis


Book Description

This book takes the relatively new concept of structured analytic techniques and defines its place in a taxonomy of analytic methods. It describes 50 techniques divided into eight categories, each corresponding. to a book chapter. These techniques are especially needed in the field of intelligence analysis where analysts typically deal with incomplete, ambiguous and sometimes deceptive information.