Sebanyak 291 item atau buku ditemukan

Experimentation in Software Engineering

Like other sciences and engineering disciplines, software engineering requires a cycle of model building, experimentation, and learning. Experiments are valuable tools for all software engineers who are involved in evaluating and choosing between different methods, techniques, languages and tools. The purpose of Experimentation in Software Engineering is to introduce students, teachers, researchers, and practitioners to empirical studies in software engineering, using controlled experiments. The introduction to experimentation is provided through a process perspective, and the focus is on the steps that we have to go through to perform an experiment. The book is divided into three parts. The first part provides a background of theories and methods used in experimentation. Part II then devotes one chapter to each of the five experiment steps: scoping, planning, execution, analysis, and result presentation. Part III completes the presentation with two examples. Assignments and statistical material are provided in appendixes. Overall the book provides indispensable information regarding empirical studies in particular for experiments, but also for case studies, systematic literature reviews, and surveys. It is a revision of the authors’ book, which was published in 2000. In addition, substantial new material, e.g. concerning systematic literature reviews and case study research, is introduced. The book is self-contained and it is suitable as a course book in undergraduate or graduate studies where the need for empirical studies in software engineering is stressed. Exercises and assignments are included to combine the more theoretical material with practical aspects. Researchers will also benefit from the book, learning more about how to conduct empirical studies, and likewise practitioners may use it as a “cookbook” when evaluating new methods or techniques before implementing them in their organization.

The introduction to experimentation is provided through a process perspective, and the focus is on the steps that we have to go through to perform an experiment. The book is divided into three parts.

Data Mining

Theory, Methodology, Techniques, and Applications

This volume provides a snapshot of the current state of the art in data mining, presenting it both in terms of technical developments and industrial applications. The collection of chapters is based on works presented at the Australasian Data Mining conferences and industrial forums. Authors include some of Australia's leading researchers and practitioners in data mining. The volume also contains chapters by regional and international authors.

This volume provides a snapshot of the current state of the art in data mining, presenting it both in terms of technical developments and industrial applications.

Applied Multivariate Data Analysis

Regression and Experimental Design

An easy to read survey of data analysis, linear regression models and analysis of variance. The extensive development of the linear model includes the use of the linear model approach to analysis of variance provides a strong link to statistical software packages, and is complemented by a thorough overview of theory. It is assumed that the reader has the background equivalent to an introductory book in statistical inference. Can be read easily by those who have had brief exposure to calculus and linear algebra. Intended for first year graduate students in business, social and the biological sciences. Provides the student with the necessary statistics background for a course in research methodology. In addition, undergraduate statistics majors will find this text useful as a survey of linear models and their applications.

Provides the student with the necessary statistics background for a course in research methodology. In addition, undergraduate statistics majors will find this text useful as a survey of linear models and their applications.

Discrete Multivariate Analysis

Theory and Practice

“A welcome addition to multivariate analysis. The discussion is lucid and very leisurely, excellently illustrated with applications drawn from a wide variety of fields. A good part of the book can be understood without very specialized statistical knowledge. It is a most welcome contribution to an interesting and lively subject.” -- Nature Originally published in 1974, this book is a reprint of a classic, still-valuable text.

Even a mediocre attempt to organize the extensive and widely scattered literature on discrete multivariate analysis would be welcome; happily, this is an excellent such effort, but a group of Harvard statisticians taht has contributed much ...

Multivariate Statistical Quality Control Using R

​​​​​The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.

These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts.

Multivariate Geostatistics

An Introduction with Applications

This fully revised third edition introduces geostatistics by emphasising the multivariate aspects for scientists, engineers and statisticians. Geostatistics offers a variety of models, methods and techniques for the analysis, estimation and display of multivariate data distributed in space or time. The text contains a brief review of statistical concepts, a detailed introduction to linear geostatistics, and an account of 3 basic methods of multivariate analysis. Applications from different areas of science, as well as exercises with solutions, are provided to help convey the general ideas. The introductory chapter has been divided into two separate sections for clarity. The final section deals with non-stationary geostatistics.

This book presents a brief review of statistical concepts, a detailed introduction to linear geostatistics, and an account of three methods of multivariate analysis.

Modern Multivariate Statistical Techniques

Regression, Classification, and Manifold Learning

This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.

This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data.

New Directions in Rough Sets, Data Mining, and Granular-Soft Computing

7th International Workshop, RSFDGrC'99, Yamaguchi, Japan, November 9-11, 1999 Proceedings

This book constitutes the refereed proceedings of the 7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC'99, held in Yamaguchi, Japan, in November 1999. The 45 revised regular papers and 15 revised short papers presented together with four invited contributions were carefully reviewed and selected from 89 submissions. The book is divided into sections on rough computing: foundations and applications, rough set theory and applications, fuzzy set theory and applications, nonclassical logic and approximate reasoning, information granulation and granular computing, data mining and knowledge discovery, machine learning, and intelligent agents and systems.

When people try to communicate their concepts with words, the difference in the
meaning and usage of words can lead to misunderstanding in communication,
which can hinder their collaboration. In our approach each granule of knowledge
 ...

Reliability Data Banks

... distributions, 4 estimation methods used, 22 Pooled reliability data, 219, 276
Population at risk, meaning of term, 12 Power Reactor & Nuclear Fuel
Development Corporation (PNC, Japan) nuclear fuel fabrication reliability data
base.

Data Management and Query Processing in Semantic Web Databases

The Semantic Web, which is intended to establish a machine-understandable Web, is currently changing from being an emerging trend to a technology used in complex real-world applications. A number of standards and techniques have been developed by the World Wide Web Consortium (W3C), e.g., the Resource Description Framework (RDF), which provides a general method for conceptual descriptions for Web resources, and SPARQL, an RDF querying language. Recent examples of large RDF data with billions of facts include the UniProt comprehensive catalog of protein sequence, function and annotation data, the RDF data extracted from Wikipedia, and Princeton University’s WordNet. Clearly, querying performance has become a key issue for Semantic Web applications. In his book, Groppe details various aspects of high-performance Semantic Web data management and query processing. His presentation fills the gap between Semantic Web and database books, which either fail to take into account the performance issues of large-scale data management or fail to exploit the special properties of Semantic Web data models and queries. After a general introduction to the relevant Semantic Web standards, he presents specialized indexing and sorting algorithms, adapted approaches for logical and physical query optimization, optimization possibilities when using the parallel database technologies of today’s multicore processors, and visual and embedded query languages. Groppe primarily targets researchers, students, and developers of large-scale Semantic Web applications. On the complementary book webpage readers will find additional material, such as an online demonstration of a query engine, and exercises, and their solutions, that challenge their comprehension of the topics presented.

During its search, the search engine compares plain text rather than the meaning
of the keywords with the words on a webpage. Consequently, a number of
unwanted webpages are displayed to the user, since for example, the meaning of
a ...