Service-oriented computing has become one of the predominant factors in IT research and development efforts over the last few years. In spite of several standardization efforts that advanced from research labs into industrial-strength technologies and tools, there is still much human effort required in the process of finding and executing Web services. Here, Dieter Fensel and his team lay the foundation for understanding the Semantic Web Services infrastructure, aimed at eliminating human intervention and thus allowing for seamless integration of information systems. They focus on the currently most advanced SWS infrastructure, namely SESA and related work such as the Web Services Execution Environment (WSMX) activities and the Semantic Execution Environment (OASIS SEE TC) standardization effort. Their book is divided into four parts: Part I provides an introduction to the field and its history, covering basic Web technologies and the state of research and standardization in the Semantic Web field. Part II presents the SESA architecture. The authors detail its building blocks and show how they are consolidated into a coherent software architecture that can be used as a blueprint for implementation. Part III gives more insight into middleware services, describing the necessary conceptual functionality that is imposed on the architecture through the basic principles. Each such functionality is realized using a number of so-called middleware services. Finally, Part IV shows how the SESA architecture can be applied to real-world scenarios, and provides an overview of compatible and related systems. The book targets professionals as well as academic and industrial researchers working on various aspects of semantic integration of distributed information systems. They will learn how to apply the Semantic Web Services infrastructure to automate and semi-automate tasks, by using existing integration technologies. In addition, the book is also suitable for advanced graduate students enrolled in courses covering knowledge management, the Semantic Web, or integration of information systems, as it will educate them about basic technologies for Semantic Web Services and general issues related to integration of information systems.
This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
This book constitutes the proceedings of the 17th IFIP WG 8.5 International Conference on Electronic Government, EGOV 2018, held in Krems, Austria, in September 2018, in conjunction with the 10th International Conference on eParticipation, ePart 2018. The 22 revised full papers presented were carefully reviewed and selected from 48 submissions. The papers are clustered under the following topical sections: General E-Government and Open Government; Open Data, Linked Data, and Semantic Web; Smart Governance (Government, Cities and Regions); and Artificial Intelligence, Data Analytics and Automated Decision-Making.
This book constitutes the refereed proceedings of the 7th International Conference on Electronic Government and the Information Systems Perspective, EGOVIS 2018, held in Regensburg, Germany, in September 2018. The 19 revised full papers presented were carefully reviewed and selected from 22 submissions. The papers are organized in the following topical sections: digitalization and transparency; challenges in e-government technology and e-voting; knowledge management in the context of e-government; semantic technologies and the legal aspects; open data and open innovation; and e-government cases - data and knowledge management.