This book describes analytical techniques for optimizing knowledge acquisition, processing, and propagation, especially in the contexts of cyber-infrastructure and big data. Further, it presents easy-to-use analytical models of knowledge-related processes and their applications. The need for such methods stems from the fact that, when we have to decide where to place sensors, or which algorithm to use for processing the data-we mostly rely on experts´ opinions. As a result, the selected knowledge-related methods are often far from ideal. To make better selections, it is necessary to first create easy-to-use models of knowledge-related processes. This is especially important for big data, where traditional numerical methods are unsuitable. The book offers a valuable guide for everyone interested in big data applications: students looking for an overview of related analytical techniques, practitioners interested in applying optimization techniques, and researchers seeking to improve and expand on these techniques.
This book provides a unified view on a new methodology for Machine Translation (MT). This methodology extracts information from widely available resources (extensive monolingual corpora) while only assuming the existence of a very limited parallel corpus, thus having a unique starting point to Statistical Machine Translation (SMT). In this book, a detailed presentation of the methodology principles and system architecture is followed by a series of experiments, where the proposed system is compared to other MT systems using a set of established metrics including BLEU, NIST, Meteor and TER. Additionally, a free-to-use code is available, that allows the creation of new MT systems. The volume is addressed to both language professionals and researchers. Prerequisites for the readers are very limited and include a basic understanding of the machine translation as well as of the basic tools of natural language processing.
This brief book presents the strong fractional analysis of Banach space valued functions of a real domain. The book´s results are abstract in nature: analytic inequalities, Korovkin approximation of functions and neural network approximation. The chapters are self-contained and can be read independently. This concise book is suitable for use in related graduate classes and many research projects. An extensive list of references is provided for each chapter. The book´s results are relevant for many areas of pure and applied mathematics. As such, it offers a unique resource for researchers, and a valuable addition to all science and engineering libraries.
This book constitutes the proceedings of the Third International Conference on Technologies and Innovation, CITI 2017, held in Guayaquil, Ecuador, in October 2017. The 24 papers presented in this volume were carefully reviewed and selected from 68 submissions. They were organized in topical sections named: cloud and mobile computing; knowledge based and expert systems; applications in healthcare and wellness; e-learning; and ICT in agronomy.
These two volumes constitute the Proceedings of the 7th International Workshop on Soft Computing Applications (SOFA 2016), held on 24-26 August 2016 in Arad, Romania. This edition was organized by Aurel Vlaicu University of Arad, Romania, University of Belgrade, Serbia, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics (SRAIT) - Arad Section, General Association of Engineers in Romania - Arad Section, and BTM Resources Arad. The soft computing concept was introduced by Lotfi Zadeh in 1991 and serves to highli ght the emergence of computing methodologies in which the accent is on exploiting the tolerance for imprecision and uncertainty to achieve tractability, robustness and lower costs. Soft computing facilitates the combined use of fuzzy logic, neurocomputing, evolutionary computing and probabilistic computing, leading to the concept of hybrid intelligent systems. The rapid emergence of new tools and applications calls for a synergy of scientific and technological disciplines in order to reveal the great potential of soft computing in all domains. The conference papers included in these proceedings, published post-conference, were grouped into the following areas of research: - Methods and Applications in Electrical Engineering - Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks - Biomedical Applications - Image, Text and Signal Processing - Machine Learning and Applications - &nb sp; Business Process Management - Fuzzy Applications, Theory and Fuzzy Control - Computational Intelligence in Education - Soft Computing & Fuzzy Logic i n Biometrics (SCFLB) - Soft Computing Algorithms Applied in Economy, Industry and Communication Technology - Modelling and Applications in Textiles The book helps to disseminate advances in selected active research directions in the field of soft computing, along with current issues and applications of related topics. As such, it provides valuable information for professors, researchers and graduate students in the area of soft computing techniques and applications.
This third edition covers fundamental concepts in creating and manipulating 2D and 3D graphical objects, including topics from classic graphics algorithms to color and shading models. It maintains the style of the two previous editions, teaching each graphics topic in a sequence of concepts, mathematics, algorithms, optimization techniques, and Java coding. Completely revised and updated according to years of classroom teaching, the third edition of this highly popular textbook contains a large number of ready-to-run Java programs and an algorithm animation and demonstration open-source software also in Java. It includes exercises and examples making it ideal for classroom use or self-study, and provides a perfect foundation for programming computer graphics using Java. Undergraduate and graduate students majoring specifically in computer science, computer engineering, electronic engineering, information systems, and related disciplines will use this textbook for their courses. Professionals and industrial practitioners who wish to learn and explore basic computer graphics techniques will also find this book a valuable resource.
The two-volume set, LNCS 10492 and LNCS 10493 constitutes the refereed proceedings of the 22nd European Symposium on Research in Computer Security, ESORICS 2017, held in Oslo, Norway, in September 2017. The 54 revised full papers presented were carefully reviewed and selected from 338 submissions. The papers address issues such as data protection; security protocols; systems; web and network security; privacy; threat modeling and detection; information flow; and security in emerging applications such as cryptocurrencies, the Internet of Things and automotive.
Nowadays data mining and social network analysis techniques are broadly being used for social network analysis to study social structure of the underlying community. Human Social Networks exploration has been an interesting topic for the researchers during past some years. This book is the discovery of such networks using cyber world data. This work is extraction of social groups, social interaction and social structure among a community of people.
This invaluable textbook/reference provides an easy-to-read guide to the fundamentals of formal methods, highlighting the rich applications of formal methods across a diverse range of areas of computing. Topics and features: introduces the key concepts in software engineering, software reliability and dependability, formal methods, and discrete mathematics; presents a short history of logic, from Aristotle´s syllogistic logic and the logic of the Stoics, through Boole´s symbolic logic, to Frege´s work on predicate logic; covers propositional and predicate logic, as well as more advanced topics such as fuzzy logic, temporal logic, intuitionistic logic, undefined values, and the applications of logic to AI; examines the Z specification language, the Vienna Development Method (VDM) and Irish School of VDM, and the unified modelling language (UML); discusses Dijkstra´s calculus of weakest preconditions, Hoare´s axiomatic semantics of programming languages, and the classical approach of Parnas and his tabular expressions; provides coverage of automata theory, probability and statistics, model checking, and the nature of proof and theorem proving; reviews a selection of tools available to support the formal methodist, and considers the transfer of formal methods to industry; includes review questions and highlights key topics in every chapter, and supplies a helpful glossary at the end of the book. This stimulating guide provides a broad and accessible overview of formal methods for students of computer science and mathematics curious as to how formal methods are applied to the field of computing.
This book reviews a blend of artificial intelligence (AI) approaches that can take e-learning to the next level by adding value through customization. It investigates three methods: crowdsourcing via social networks; user profiling through machine learning techniques, and personal learning portfolios using learning analytics. Technology and education have drawn closer together over the years as they complement each other within the domain of e-learning, and different generations of online education reflect the evolution of new technologies as researcher and developers continuously seek to optimize the electronic medium to enhance the effectiveness of e-learning. Artificial intelligence (AI) for e-learning promises personalized online education through a combination of different intelligent techniques that are grounded in established learning theories while at the same time addressing a number of common e-learning issues. This book is intended for education technologists and e-learning researchers as well as for a general readership interested in the evolution of online education based on techniques like machine learning, crowdsourcing, and learner profiling that can be merged to characterize the future of personalized e-learning.
In certain applications, such as speech analysis-synthesis, noise suppression and enhancement, it may be necessary to extract some key properties of the original signal like voiced, unvoiced or noise speech sounds, using specific digital signal processing algorithms. ...performance of such systems, such as speech coding, speech analysis, speech synthesis, automatic speech recognition, noise suppression and enhancement, pitch detection, speaker identification, and the recognition of speech pathologies depends on the ability of the system to detect correct voiced/unvoiced/silence speech segments.