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Data science, data engineering and knowledge engineering requires networking and communication as a backbone and have wide scope of implementation in engineering sciences. Keeping this ideology in preference, this book includes the insights that reflect the advances in these fields from upcoming researchers and leading academicians across the globe. It contains high-quality peer-reviewed papers of ‘International Conference on Recent Advancement in Computer, Communication and Computational Sciences (ICRACCCS 2016)’, held at Janardan Rai Nagar Rajasthan Vidyapeeth University, Udaipur, India, during 25–26 November 2016. The volume covers variety of topics such as Advanced Communication Networks, Artificial Intelligence and Evolutionary Algorithms, Advanced Software Engineering and Cloud Computing, Image Processing and Computer Vision, and Security. The book will help the perspective readers from computer industry and academia to derive the advances of next generation communication and computational technology and shape them into real life applications.
Foreword TAKE 2018 follows with success the two previous editions. We gather 60 papers, presented by scholars from 15 countries which address the complex relation between theory and applications in the realm of the knowledge economy. We address specific aspects of knowledge management, human resource development and management, intellectual capital and many other scientific areas relevant for the economy of today. We hope these proceedings will summarize and illustrate well what happened in the conference and look forward for next years’ edition. Thank you very much for your participation as local organizer, keynote speaker, stream leader, reviewer, author, helper or just participant. Eduardo Tomé, Conference Chair Poznan, July 2018
FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Computational Intelligence for applied research. The contributions to the 10th of FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, both from the foundations and the applications points-of-view.
Being the premier forum for the presentation of new advances and research results in the fields of Industrial Engineering, IEEM 2015 aims to provide a high-level international forum for experts, scholars and entrepreneurs at home and abroad to present the recent advances, new techniques and applications face and face, to promote discussion and interaction among academics, researchers and professionals to promote the developments and applications of the related theories and technologies in universities and enterprises, and to establish business or research relations to find global partners for future collaboration in the field of Industrial Engineering. All the goals of the international conference are to fulfill the mission of the series conference which is to review, exchange, summarize and promote the latest achievements in the field of industrial engineering and engineering management over the past year, and to propose prospects and vision for the further development. This volume is the first of the two proceedings volumes from this conference.
This book constitutes the refereed proceedings of the 23rd International Conference on Knowledge Engineering and Knowledge Management, EKAW 2022, held in Bolzano, Italy, in September 2022. The 11 full papers presented together with 5 short papers were carefully reviewed and selected from 57 submissions The previous event in the series, EKAW 2020, introduced a special theme related to “Ethical and Trustworthy Knowledge Engineering.” This theme is still very relevant in 2022, and thus has remained one of the core topics of the conference. The conference concerned with all aspects about eliciting, acquiring, modeling and managing knowledge, and the construction of knowledge-intensive systems and services for the semantic web, knowledge management, e-business, natural language processing, intelligent information integration, and much more.
In the era of big data, the extraction of meaningful insights from vast datasets is paramount. This paper explores the application of a data mining approach to the domains of classification and knowledge analysis. The methodology involves a systematic process, beginning with the definition of the problem and encompassing data collection, exploration, and pre-processing. Feature selection and model training with various classification algorithms, such as Decision Trees, Support Vector Machines, and Naive Bayes, are integral components. The evaluation of model performance, hyperparameter tuning, and knowledge discovery are critical steps in ensuring the robustness of the classification outcomes. Furthermore, the book emphasizes the significance of visualization techniques, including confusion matrices and ROC curves, to enhance the interpretability of model results. The iterative nature of the approach is highlighted, showcasing the importance of refining models through continuous monitoring and updates. Ethical considerations in the deployment of models, including fairness and transparency, are addressed, ensuring responsible use in decision-making processes. The proposed data mining approach is not only a systematic framework for solving classification problems but also a pathway to uncovering valuable knowledge from complex datasets.
This is the first handbook to cover comprehensively both software engineering and knowledge engineering - two important fields that have become interwoven in recent years. Over 60 international experts have contributed to the book. Each chapter has been written in such a way that a practitioner of software engineering and knowledge engineering can easily understand and obtain useful information. Each chapter covers one topic and can be read independently of other chapters, providing both a general survey of the topic and an in-depth exposition of the state of the art. Practitioners will find this handbook useful when looking for solutions to practical problems. Researchers can use it for quick access to the background, current trends and most important references regarding a certain topic.The handbook consists of two volumes. Volume One covers the basic principles and applications of software engineering and knowledge engineering.Volume Two will cover the basic principles and applications of visual and multimedia software engineering, knowledge engineering, data mining for software knowledge, and emerging topics in software engineering and knowledge engineering.
No one discipline or person can encompass all the knowledge necessary to solve complex, ill-defined problems, or problems for which a solution is not immediately obvious. The concept of Concurrent Engineering (CE) – interdisciplinary, but with an engineering focus – was developed to increase the efficiency and effectiveness of the Product Creation Process (PCP) by conducting different phases of a product’s life concurrently. Transdisciplinary Engineering has transcended CE, emphasizing the crucial importance of interdisciplinary openness and collaboration. This book presents the proceedings of the 28th ISTE International Conference on Transdisciplinary Engineering (TE2021). Held online from 5 – 9 July 2021 and entitled ‘Transdisciplinary Engineering for Resilience: Responding to System Disruptions’, this is the second conference in the series held virtually due to the COVID-19 pandemic. The annual TE conference constitutes an important forum for international scientific exchange on transdisciplinary engineering research, advances, and applications, and is attended by researchers, industry experts and students, as well as government representatives. The book contains 58 peer-reviewed papers, selected from more than 80 submissions and ranging from the theoretical and conceptual to strongly pragmatic and addressing industrial best practice. The papers are grouped under 6 headings covering theory; education and training; PD methods and digital TE; industry and society; product systems; and individuals and teams. Providing an overview of the latest research results and knowledge of product creation processes and related methodologies, the book will be of interest to all researchers, design practitioners, and educators working in the field of Transdisciplinary Engineering.
This book addresses theories and empirical procedures for the application of machine learning and data mining to solve problems in cyber dynamics. It explains the fundamentals of cyber dynamics, and presents how these resilient algorithms, strategies, techniques can be used for the development of the cyberspace environment such as: cloud computing services; cyber security; data analytics; and, disruptive technologies like blockchain. The book presents new machine learning and data mining approaches in solving problems in cyber dynamics. Basic concepts, related work reviews, illustrations, empirical results and tables are integrated in each chapter to enable the reader to fully understand the concepts, methodology, and the results presented. The book contains empirical solutions of problems in cyber dynamics ready for industrial applications. The book will be an excellent starting point for postgraduate students and researchers because each chapter is design to have future research directions.