Nottingham Trent University

About: Nottingham Trent University is a education organization based out in Nottingham, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 4702 authors who have published 12862 publications receiving 307430 citations. The organization is also known as: NTU & Trent Polytechnic.

General fuzzy min-max neural network for clustering and classification

Abstract: This paper describes a general fuzzy min-max (GFMM) neural network which is a generalization and extension of the fuzzy min-max clustering and classification algorithms of Simpson (1992, 1993). The GFMM method combines supervised and unsupervised learning in a single training algorithm. The fusion of clustering and classification resulted in an algorithm that can be used as pure clustering, pure classification, or hybrid clustering classification. It exhibits a property of finding decision boundaries between classes while clustering patterns that cannot be said to belong to any of existing classes. Similarly to the original algorithms, the hyperbox fuzzy sets are used as a representation of clusters and classes. Learning is usually completed in a few passes and consists of placing and adjusting the hyperboxes in the pattern space; this is an expansion-contraction process. The classification results can be crisp or fuzzy. New data can be included without the need for retraining. While retaining all the interesting features of the original algorithms, a number of modifications to their definition have been made in order to accommodate fuzzy input patterns in the form of lower and upper bounds, combine the supervised and unsupervised learning, and improve the effectiveness of operations. A detailed account of the GFMM neural network, its comparison with the Simpson's fuzzy min-max neural networks, a set of examples, and an application to the leakage detection and identification in water distribution systems are given.

Re-Turn to Practice: An Introductory Essay

Abstract: The study of practices has a long theoretical history and draws on a wide range of methods. This introductory essay sets the stage for the five articles presented in this Special Issue by explaining its background and providing one narrative of the theoretical background on which both its editors and the authors of its articles, in one way or another, draw and to which the latter make explicit or implicit reference.

Contemporary Trends and Issues in it Adoption and Diffusion Research

Abstract: The high level of investigative activity to date into information systems and information technology acceptance and diffusion has witnessed the use of a wide range of exploratory techniques, examining many different systems and technologies in countless different contexts and geographical locations. The aim of this paper is to provide a comprehensive and systematic review of the literature pertaining to such adoption and diffusion issues in order to observe trends, ascertain the current ‘state of play’, and to highlight promising lines of inquiry including those lacking investigative activity or simply being in need of renewed interest. Previous research activity was analysed along a number dimensions including units of analysis, research paradigms, methodologies, and methods, theories and theoretical constructs, and technologies/contexts examined. Information on these and other variables was extracted during an examination of 345 papers on innovation adoption, acceptance and diffusion appearing in 19 peer-reviewed journals between 1985 and 2007. Findings suggest that the positivist paradigm, empirical and quantitative research, the survey method and Technology Acceptance Model theory (and its associated constructs) were predominantly used in the body of work examined, revealing clear opportunities for researchers to make original contributions by making greater use of the theoretical and methodological variety available to them, and consequently reducing the risk of research in the area moving toward overall homogeneity.

Intelligent systems for engineers and scientists

Abstract: The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself. The first part of the book describes key techniques of artificial intelligence—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance.

Social networking addiction: an overview of preliminary findings

Abstract: Social networking sites (SNSs) are virtual communities where users can create individual public profiles, interact with real-life friends, and meet other people based on shared interests. Anecdotal case study evidence suggests that “addiction” to social networks on the Internet may be a potential mental health problem for some users. However, the contemporary scientific literature addressing the addictive qualities of social networks on the Internet is relatively scarce. This chapter provides empirical and conceptual insight into the emerging phenomenon of addiction to SNSs by examining motivations for SNS usage, examining negative consequences of SNS usage, and exploring potential SNS addiction. The chapter also examines screening and assessment tools, and suggests tentative treatment approaches based on the treatment of other online addictions.