V. Kumar – författare

Conducting polymers were discovered in 1970s in Japan. Since this discovery, there has been a steady flow of new ideas, new understanding, new conducing polymer (organics) structures and devices with enhanced performance. Several breakthroughs have been made in the design and fabrication technology of the organic devices. Almost all properties, mechanical, electrical, and optical, are important in organics. This book describes the recent advances in these organic materials and devices.

Conducting polymers were discovered in 1970s in Japan. Since this discovery, there has been a steady flow of new ideas, new understanding, new conducing polymer (organics) structures and devices with enhanced performance. Several breakthroughs have been made in the design and fabrication technology of the organic devices. Almost all properties, mechanical, electrical, and optical, are important in organics. This book describes the recent advances in these organic materials and devices.

Over the last few decades new data on the distribution, pathogenicity, diagnosis, treatment and control of trematode infections and diseases in man and animals, including zoonotic trematodiasis, have emerged from various geographical regions. These new data are compiled in this book together with existing information to fulfil the present need. Seven major trematode-induced disease groups, namely, schistosomiasis, paragonimiasis, fascioliasis and fasciolopsiasis, dicrocoeliasis and eurytremiasis, clonorchiasis and opisthorchiasis, paramphistomiasis, and diseases due to intestinal trematode infections are dealt with in this book. These diseases still rank as a major cause of morbidity and mortality - both in man and in livestock - mainly in the tropics, and contribute to the socio-economic problems. Many of these diseases are also zoonoses, some major and others potential.The intended readership of this treatise include postgraduate students of medical and veterinary parasitology, research workers as well as medical practitioners, veterinarians, tropical diseases specialists, veterinary public health specialists and teachers concerned with trematode infections and trematodiasis of man and animals.

In spite of the availability of modern broad-spectrum anthelmintic drugs, the prevention and control of helminth zoonoses remain a challenge to human and veterinary parasitologists and to physicians and veterina- rians working on the field. Although the life cycles of most helminths of zoonotic importance are well known, there are still major gaps in our knowledge especially in the fields of epidemiology, diagnosis and treat- ment The International Colloquium on Helminth Zoonoses held at the Institute of Tropical Medicine, Antwerp, 11-12 December 1986, laid emphasis on more recent advances made in the control and epidemiology of these zoonotic diseases. The disease complexes echinococcosis/hydatidosis, taeniasis/cysticercosis and the larva migrans-syndrome were dealth with in considerable detail. In the first chapter the phenomenon of strain variation in Echinococcus spp. is examined in the light of newer findings. The progress made in recent years towards a more specific diagnosis and drug targeting in hydatidosis is reported. In the second chapter recent advances in immunisation and treatment of cysticercosis are dealt with.The possibili- ty of the existence of strain differences in Taenia saginata is also dis- cussed. The third chapter is devoted to trematode zoonoses with particular reference to the situation in South-east Asia, Senegal (schistosomiasis) and Liberia (paragonimiasis). In the last chapter the larva migrans- syndrome is treated in detail with special attention to its etiology and and diagnosis. Reports on lesser known nematode zoonoses like mammomono- gamosis and oesophagostomiasis are included.

Statistical Methods in Customer Relationship Management focuses on the quantitative and modeling aspects of customer management strategies that lead to future firm profitability, with emphasis on developing an understanding of Customer Relationship Management (CRM) models as the guiding concept for profitable customer management. To understand and explore the functioning of CRM models, this book traces the management strategies throughout a customer’s tenure with a firm. Furthermore, the book explores in detail CRM models for customer acquisition, customer retention, customer acquisition and retention, customer churn, and customer win back.

Statistical Methods in Customer Relationship Management:

Provides an overview of a CRM system, introducing key concepts and metrics needed to understand and implement these models. Focuses on five CRM models: customer acquisition, customer retention, customer churn, and customer win back with supporting case studies. Explores each model in detail, from investigating the need for CRM models to looking at the future of the models. Presents models and concepts that span across the introductory, advanced, and specialist levels.

Academics and practitioners involved in the area of CRM as well as instructors of applied statistics and quantitative marketing courses will benefit from this book.

Statistical Methods in Customer Relationship Management focuses on the quantitative and modeling aspects of customer management strategies that lead to future firm profitability, with emphasis on developing an understanding of Customer Relationship Management (CRM) models as the guiding concept for profitable customer management. To understand and explore the functioning of CRM models, this book traces the management strategies throughout a customer’s tenure with a firm. Furthermore, the book explores in detail CRM models for customer acquisition, customer retention, customer acquisition and retention, customer churn, and customer win back.

Statistical Methods in Customer Relationship Management:

Provides an overview of a CRM system, introducing key concepts and metrics needed to understand and implement these models. Focuses on five CRM models: customer acquisition, customer retention, customer churn, and customer win back with supporting case studies. Explores each model in detail, from investigating the need for CRM models to looking at the future of the models. Presents models and concepts that span across the introductory, advanced, and specialist levels.

Academics and practitioners involved in the area of CRM as well as instructors of applied statistics and quantitative marketing courses will benefit from this book.

Marketing Research, 13th Edition presents a clear and comprehensive introduction to the field, with a strong focus on methodologies and the role of market research in strategic decision making. Employing a unique macro-micro-macro approach, the text begins with a broad overview of market research and its place within—and value to—an organization, before zooming in to detail the granular view of the research process. Step-by-step explanations cover the latest methodologies and current practices, highlighting advanced techniques as well as their limitations and potential benefits, followed by a high-level discussion of research applications.

An emphasis on real-world processes is underscored by end-of-chapter cases, allowing students to apply what they’ve learned in the context of real-life examples covering a broad range of products and organizations. This practical approach promotes engagement while building essential critical analysis, interpretation, and decision-making skills, preparing students to recognize potential research applications, alternatives where they exist, and the quality of research at hand. By pulling together market intelligence, strategy, theory, and application, this text helps students build a deep understanding while retaining the big picture perspective.  

Marketing Research, 13th Edition presents a clear and comprehensive introduction to the field, with a strong focus on methodologies and the role of market research in strategic decision making. Employing a unique macro-micro-macro approach, the text begins with a broad overview of market research and its place within—and value to—an organization, before zooming in to detail the granular view of the research process. Step-by-step explanations cover the latest methodologies and current practices, highlighting advanced techniques as well as their limitations and potential benefits, followed by a high-level discussion of research applications. An emphasis on real-world processes is underscored by end-of-chapter cases, allowing students to apply what they’ve learned in the context of real-life examples covering a broad range of products and organizations. This practical approach promotes engagement while building essential critical analysis, interpretation, and decision-making skills, preparing students to recognize potential research applications, alternatives where they exist, and the quality of research at hand. By pulling together market intelligence, strategy, theory, and application, this text helps students build a deep understanding while retaining the big picture perspective.

Statistical Methods in Customer Relationship Management focuses on the quantitative and modeling aspects of customer management strategies that lead to future firm profitability, with emphasis on developing an understanding of Customer Relationship Management (CRM) models as the guiding concept for profitable customer management. To understand and explore the functioning of CRM models, this book traces the management strategies throughout a customer’s tenure with a firm. Furthermore, the book explores in detail CRM models for customer acquisition, customer retention, customer acquisition and retention, customer churn, and customer win back. Statistical Methods in Customer Relationship Management: Provides an overview of a CRM system, introducing key concepts and metrics needed to understand and implement these models.Focuses on five CRM models: customer acquisition, customer retention, customer churn, and customer win back with supporting case studies.Explores each model in detail, from investigating the need for CRM models to looking at the future of the models.Presents models and concepts that span across the introductory, advanced, and specialist levels.Academics and practitioners involved in the area of CRM as well as instructors of applied statistics and quantitative marketing courses will benefit from this book.

Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge - methods which enable efficient and flexible processing of semantic networks are expected to have high utility for building large-scale knowledge-based systems. The third section explores the automatic parallel execution of production systems, which are used extensively in building rule-based expert systems - systems containing large numbers of rules are slow to execute and can significantly benefit from automatic parallel execution. The exploitation of parallelism for the mechanization of logic is dealt with in the fourth section. While sequential control aspects pose problems for the parallelization of production systems, logic has a purely declarative interpretation which does not demand a particular evaluation strategy. In this area, therefore, very large search spaces provide significant potential for parallelism. In particular, this is true for automated theorem proving. The fifth section considers the problem of constraint satisfaction, which is a useful abstraction of a number of important problems in AI and other fields of computer science. It also discusses the technique of consistent labeling as a preprocessing step in the constraint satisfaction problem. Section VI consists of two articles, each on a different, important topic. The first discusses parallel formulation for the Tree Adjoining Grammar (TAG), which is a powerful formalism for describing natural languages. The second examines the suitability of a parallel programming paradigm called Linda, for solving problems in artificial intelligence.Each of the areas discussed in the book holds many open problems, but it is believed that parallel processing will form a key ingredient in achieving at least partial solutions. It is hoped that the contributions, sourced from experts around the world, will inspire readers to take on these challenging areas of inquiry.

With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy.This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their subject: architectures (3 papers), languages (4 papers), general algorithms (6 papers), and applications (5 papers). The internationally sourced papers range from purely theoretical work, simulation studies, algorithm and architecture proposals, to implemented systems and their experimental evaluation.Since the book is a second volume in the parallel processing for AI series, it provides a continued documentation of the research and advances made in the field. The editors hope that it will inspire readers to investigate the possiblities for enhancing AI systems by parallel processing and to make new discoveries of their own!