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  • BSZ  (3)
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  • English  (3)
  • Italian
  • 2020-2024  (3)
  • 1990-1994
  • 2023  (3)
  • Tsihrintzis, George A.  (3)
  • Cham : Springer International Publishing  (3)
  • Cambridge : Polity Press
  • Cham : Springer International Publishing AG
  • Artificial intelligence.  (3)
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  • English  (3)
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  • 2020-2024  (3)
  • 1990-1994
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  • 1
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Imprint: Springer
    ISBN: 9783031205859
    Language: English
    Pages: 1 Online-Ressource(XIII, 372 p. 214 illus., 191 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Artificial Intelligence-Enhanced Software and Systems Engineering 4
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence. ; Software engineering.
    Abstract: Introduction -- e-Government: The concept, the environment & critical issues for the Back-Office systems -- Semantic Web: The evolution of the Web & the opportunities for the e-Government -- Representation and knowledge management for the benefit of e-Government - Opportunities through the tools of the Semantic Web -- Towards Open Data and Open Governance – Representation of knowledge and Triplification of data in the field of the Greek Open Government Data -- Production and publication of linked open data: The case of open ontologies -- Education and E-Government - The case of a Moodle based platform for the education and evaluation of civil servants -- Conclusions – Future Work.
    Abstract: Evolving technological advances in Artificial Intelligence-empowered Software present significant potential to lead e-Government towards more collective efforts, exchange of experiences on best practices both at national and international levels and dissemination of secluded administrative knowledge. In this book, novel semantic web-based and linked open data-based approaches are developed for the modelling and management of the huge volume of administrative data and the procedures followed by public sector bodies and for the production and management of relevant administrative knowledge. The book consists of eight chapters, each of which includes relevant bibliographic references for deeper probing. Appendices complement this work with sections of configuration files of the applications developed and used. Professors, researchers, scientists, engineers and students in artificial intelligence, e-government and other computer science-related disciplines are expected to benefit greatly from it, along with non-specialist readers from other disciplines who are interested in getting versed in the recent developments in e-government.
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    ISBN: 9783031223716
    Language: English
    Pages: 1 Online-Ressource(XII, 193 p. 78 illus., 59 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Intelligent Systems Reference Library 236
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence. ; Machine learning. ; Data protection.
    Abstract: Editorial Note -- Artificial Intelligence as Dual-Use Technology -- Diabetic Retinopathy Detection using Transfer and Reinforcement Learning with effective image preprocessing and data augmentation techniques. .
    Abstract: This book aims at updating the relevant computer science-related research communities, including professors, researchers, scientists, engineers and students, as well as the general reader from other disciplines, on the most recent advances in applications of methods based on Fusing Machine Learning Paradigms. Integrated or Hybrid Machine Learning methodologies combine together two or more Machine Learning approaches achieving higher performance and better efficiency when compared to those of their constituent components and promising major impact in science, technology and the society. The book consists of an editorial note and an additional eight chapters and is organized into two parts, namely: (i) Recent Application Areas of Fusion of Machine Learning Paradigms and (ii) Applications that can clearly benefit from Fusion of Machine Learning Paradigms. This book is directed toward professors, researchers, scientists, engineers and students in Machine Learning-related disciplines, as the hybridism presented, and the case studies described provide researchers with successful approaches and initiatives to efficiently address complex classification or regression problems. It is also directed toward readers who come from other disciplines, including Engineering, Medicine or Education Sciences, and are interested in becoming versed in some of the most recent Machine Learning-based technologies. Extensive lists of bibliographic references at the end of each chapter guide the readers to probe further into the application areas of interest to them.
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  • 3
    ISBN: 9783031054914
    Language: English
    Pages: 1 Online-Ressource(XVIII, 398 p. 150 illus., 107 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Smart Innovation, Systems and Technologies 314
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Engineering—Data processing. ; Computational intelligence. ; Artificial intelligence. ; Big data. ; Engineering mathematics. ; Engineering
    Abstract: Reversible Data Hiding in Encrypted Image Based on MSB Inversion -- Comments on the Visual Binary QR Code -- NLP-based Hardware Solution for Censoring Audio on Over-the-top (OTT) Media Services -- Efficient Steganographic Method Based on Modulo Cube -- Reversible Data Hiding Based on Bidirectional Generalized Integer Transform -- An RFID Ownership Transfer based on Multiple Owners with Different Weights -- Fuzzy C-Means based Feature Selection Mechanism for Wireless Intrusion Detection -- Real Time Drowsiness Detection Based on Facial Dynamic Features -- Collision Avoidance in Crowded Zone using Adversarial Reinforcement Learning -- Reconfigurable PM2.5 Sensor Green Deployment Mechanism Based on Blockchain Technology.
    Abstract: This book aims to attract researchers and practitioners who are working in information technology and computer science. This edited book is about basics and high-level concepts regarding blockchain technology and application, multimedia security, information processing, security of network, cloud and IoT, cryptography and information hiding, cyber-security and evidence investigations, and learning and intelligent computing. It is becoming increasingly important to develop adaptive, intelligent computing-centric, energy-aware, secure, and privacy-aware mechanisms in high-performance computing and IoT applications. The book serves as a useful guide for industry persons and also helps beginners to learn things from basic to advance in the area of better computing paradigm. Our aim is intended to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results in security-related areas. We believe that this book not only presents novel and interesting ideas but also will stimulate interesting discussions from the participants and inspire new ideas.
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