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Software Engineering and Information Technology
This book contains the proceedings of the 4TH International Conference on Computational Methods in Science and Technology (ICCMST 2024). The proceedings explores research and innovation in the field of Internet of things, Cloud Computing, Machine Learning, Networks, System Design and Methodologies, Big Data Analytics and Applications, ICT for Sustainable Environment, Artificial Intelligence and it provides real time assistance and security for advanced stage learners, researchers and academicians has been presented. This will be a valuable read to researchers, academicians, undergraduate students, postgraduate students, and professionals within the fields of Computer Science, Sustainability and Artificial Intelligence.
This book constitutes the refereed proceedings of the Second International Conference on Formal Concept Analysis, ICFCA 2004, held in Sydney, Australia in February 2004. The 27 revised full papers presented together with 7 invited papers were carefully reviewed and selected for inclusion in the book. Formal concept analysis emerged out of efforts to restructure lattice theory and has been extended into attribute exploration, Boolean judgment, and contextual logics in order to create a powerful general framework for knowledge representation and formal reasoning; among the application areas of formal concept analysis are data and knowledge processing, data visualization, information retrieval, machine learning, data analysis, and knowledge management. The papers in this book address all current issues in formal concept analysis, ranging from foundational and methodological issues to applications in various fields.
This book brings together three great motifs of the network society: the seeking and using of information by individuals and groups; the creation and application of knowledge in organizations; and the fundamental transformation of these activities as they are enacted on the Internet and the World Wide Web. Of the three, the study of how individuals and groups seek information probably has the longest history, beginning with the early "information needs and uses" studies soon after the Second World War. The study of organizations as knowledge-based social systems is much more recent, and really gained momentum only within the last decade or so. The study of the World Wide Web as information and communication media is younger still, but has generated tremendous excitement, partly because it has the potential to reconfigure the ways in which people seek information and use knowledge, and partly because it offers new methods of analyzing and measuring how in fact such information and knowledge work gets done. As research endeavors, these streams overlap and share conceptual constructs, perspectives, and methods of analysis. Although these overlaps and shared concerns are sometimes apparent in the published research, there have been few attempts to connect these ideas explicitly and identify cross-disciplinary themes. This book is an attempt to fill this void. The three authors of this book possess contrasting backgrounds and thus adopt complementary vantage points to observe information seeking and knowledge work.
Secure Electronic Voting is an edited volume, which includes chapters authored by leading experts in the field of security and voting systems. The chapters identify and describe the given capabilities and the strong limitations, as well as the current trends and future perspectives of electronic voting technologies, with emphasis in security and privacy. Secure Electronic Voting includes state-of-the-art material on existing and emerging electronic and Internet voting technologies, which may eventually lead to the development of adequately secure e-voting systems. This book also includes an overview of the legal framework with respect to voting, a description of the user requirements for the development of a secure e-voting system, and a discussion on the relevant technical and social concerns. Secure Electronic Voting includes, also, three case studies on the use and evaluation of e-voting systems in three different real world environments.
Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.