This book constitutes the refereed proceedings of the 13th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2018, held in Beijing, China in April, 2018. The 64 papers presented were carefully reviewed and selected from 138 submissions. They provide a forum for sharing progresses in the areas of image processing technology; image analysis and understanding; computer vision and pattern recognition; big data mining, computer graphics and VR; as well as image technology applications.
This volume of Advances in Intelligent Systems and Computing contains papers presented in the main track of IITI 2016, the First International Conference on Intelligent Information Technologies for Industry held in May 16-21 in Sochi, Russia. The conference was jointly co-organized by Rostov State Transport University (Russia) and VŠB – Technical University of Ostrava (Czech Republic) with the participation of Russian Association for Artificial Intelligence (RAAI) and Russian Association for Fuzzy Systems and Soft Computing (RAFSSC). The volume is devoted to practical models and industrial applications related to intelligent information systems. The conference has been a meeting point for researchers and practitioners to enable the implementation of advanced information technologies into various industries. Nevertheless, some theoretical talks concerning the-state-of-the-art in intelligent systems and soft computing are included in the proceedings as well.
This volume aims to review some of the recent developments and trends that seem especially relevant to any attempt to understand near-term-future possibilities; to consider what a variety of knowledgeable people are saying about changes and developments that could occur; and to relate the possibilities to needs and opportunities for human factors research. Human factors, in this case, includes not only the implications of human capabilities and limitations for the design of equipment and machines intended for human use, but also applied psychology in a more general sense. In particular, it is taken to involve social systems as well as physical ones, the interaction of people with the environment as well as with machines, the facilitation of communication between people as well as between people and computers, and the design of policies and procedures as well as the design of equipment. The author's intention is to focus on anticipated problems -- including opportunities as well as difficulties -- and ask how human factors research might contribute to solutions. It is assumed that there are ways in which such research could be useful in addressing societal problems that the profession has not yet realized and that these are more likely to be recognized in the future if the community is actively seeking to identify them.
This book is an essential reference to cutting-edge issues and future directions in information retrieval Information retrieval (IR) can be defined as the process of representing, managing, searching, retrieving, and presenting information. Good IR involves understanding information needs and interests, developing an effective search technique, system, presentation, distribution and delivery. The increased use of the Web and wider availability of information in this environment led to the development of Web search engines. This change has brought fresh challenges to a wider variety of users’ needs, tasks, and types of information. Today, search engines are seen in enterprises, on laptops, in individual websites, in library catalogues, and elsewhere. Information Retrieval: Searching in the 21st Century focuses on core concepts, and current trends in the field. This book focuses on: Information Retrieval Models User-centred Evaluation of Information Retrieval Systems Multimedia Resource Discovery Image Users’ Needs and Searching Behaviour Web Information Retrieval Mobile Search Context and Information Retrieval Text Categorisation and Genre in Information Retrieval Semantic Search The Role of Natural Language Processing in Information Retrieval: Search for Meaning and Structure Cross-language Information Retrieval Performance Issues in Parallel Computing for Information Retrieval This book is an invaluable reference for graduate students on IR courses or courses in related disciplines (e.g. computer science, information science, human-computer interaction, and knowledge management), academic and industrial researchers, and industrial personnel tracking information search technology developments to understand the business implications. Intermediate-advanced level undergraduate students on IR or related courses will also find this text insightful. Chapters are supplemented with exercises to stimulate further thinking.
The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.
The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic.
Perfectly-secure cryptography is a branch of information-theoretic cryptography. A perfectly-secure cryptosystem guarantees that the malicious third party cannot guess anything regarding the plain text or the key, even in the case of full access to the cipher text. Despite this advantage, there are only a few real-world implementations of perfect secrecy due to some well-known limitations. Any simple, straightforward modeling can pave the way for further advancements in the implementation, especially in environments with time and resource constraints such as IoT. This book takes one step towards this goal via presenting a hybrid combinatorial-Boolean model for perfectly-secure cryptography in IoT. In this book, we first present an introduction to information-theoretic cryptography as well as perfect secrecy and its real-world implementations. Then we take a systematic approach to highlight information-theoretic cryptography as a convergence point for existing trends in research on cryptography in IoT. Then we investigate combinatorial and Boolean cryptography and show how they are seen almost everywhere in the ecosystem and the life cycle of information-theoretic IoT cryptography. We finally model perfect secrecy in IoT using Boolean functions, and map the Boolean functions to simple, well-studied combinatorial designs like Latin squares. This book is organized in two parts. The first part studie s information-theoretic cryptography and the promise it holds for cryptography in IoT. The second part separately discusses combinatorial and Boolean cryptography, and then presents the hybrid combinatorial-Boolean model for perfect secrecy in IoT.
