The role of soft computing in intelligent machines.

Science.gov (United States)

de Silva, Clarence W

2003-08-15

An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.

Computing Nash equilibria through computational intelligence methods

Science.gov (United States)

Pavlidis, N. G.; Parsopoulos, K. E.; Vrahatis, M. N.

2005-03-01

Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as, differential evolution, to compute Nash equilibria of finite strategic games, as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection.

Computational Foundations of Natural Intelligence.

Science.gov (United States)

van Gerven, Marcel

2017-01-01

New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

Application of computational intelligence to biology

CERN Document Server

Sekhar, Akula

2016-01-01

This book is a contribution of translational and allied research to the proceedings of the International Conference on Computational Intelligence and Soft Computing. It explains how various computational intelligence techniques can be applied to investigate various biological problems. It is a good read for Research Scholars, Engineers, Medical Doctors and Bioinformatics researchers.

Computational intelligence techniques in health care

CERN Document Server

Zhou, Wengang; Satheesh, P

2016-01-01

This book presents research on emerging computational intelligence techniques and tools, with a particular focus on new trends and applications in health care. Healthcare is a multi-faceted domain, which incorporates advanced decision-making, remote monitoring, healthcare logistics, operational excellence and modern information systems. In recent years, the use of computational intelligence methods to address the scale and the complexity of the problems in healthcare has been investigated. This book discusses various computational intelligence methods that are implemented in applications in different areas of healthcare. It includes contributions by practitioners, technology developers and solution providers.

Computational Foundations of Natural Intelligence

Directory of Open Access Journals (Sweden)

Marcel van Gerven

2017-12-01

Full Text Available New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

7th International Symposium on Intelligent Distributed Computing

CERN Document Server

Jung, Jason; Badica, Costin

2014-01-01

This book represents the combined peer-reviewed proceedings of the Seventh International Symposium on Intelligent Distributed Computing - IDC-2013, of the Second Workshop on Agents for Clouds - A4C-2013, of the Fifth International Workshop on Multi-Agent Systems Technology and Semantics - MASTS-2013, and of the International Workshop on Intelligent Robots - iR-2013. All the events were held in Prague, Czech Republic during September 4-6, 2013. The 41 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: agent-based data processing, ambient intelligence, bio-informatics, collaborative systems, cryptography and security, distributed algorithms, grid and cloud computing, information extraction, intelligent robotics, knowledge management, linked data, mobile agents, ontologies, pervasive computing, self-organizing systems, peer-to-peer computing, social networks and trust, and swarm intelligence.  .

A Distributed Snapshot Protocol for Efficient Artificial Intelligence Computation in Cloud Computing Environments

Directory of Open Access Journals (Sweden)

JongBeom Lim

2018-01-01

Full Text Available Many artificial intelligence applications often require a huge amount of computing resources. As a result, cloud computing adoption rates are increasing in the artificial intelligence field. To support the demand for artificial intelligence applications and guarantee the service level agreement, cloud computing should provide not only computing resources but also fundamental mechanisms for efficient computing. In this regard, a snapshot protocol has been used to create a consistent snapshot of the global state in cloud computing environments. However, the existing snapshot protocols are not optimized in the context of artificial intelligence applications, where large-scale iterative computation is the norm. In this paper, we present a distributed snapshot protocol for efficient artificial intelligence computation in cloud computing environments. The proposed snapshot protocol is based on a distributed algorithm to run interconnected multiple nodes in a scalable fashion. Our snapshot protocol is able to deal with artificial intelligence applications, in which a large number of computing nodes are running. We reveal that our distributed snapshot protocol guarantees the correctness, safety, and liveness conditions.

9th International Symposium on Intelligent Distributed Computing

CERN Document Server

Camacho, David; Analide, Cesar; Seghrouchni, Amal; Badica, Costin

2016-01-01

This book represents the combined peer-reviewed proceedings of the ninth International Symposium on Intelligent Distributed Computing – IDC’2015, of the Workshop on Cyber Security and Resilience of Large-Scale Systems – WSRL’2015, and of the International Workshop on Future Internet and Smart Networks – FI&SN’2015. All the events were held in Guimarães, Portugal during October 7th-9th, 2015. The 46 contributions published in this book address many topics related to theory and applications of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

A computer architecture for intelligent machines

Science.gov (United States)

Lefebvre, D. R.; Saridis, G. N.

1992-01-01

The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Applied Computational Intelligence for finance and economics

OpenAIRE

Isasi Viñuela, Pedro; Quintana Montero, David; Sáez Achaerandio, Yago; Mochón, Asunción

2007-01-01

This article introduces some relevant research works on computational intelligence applied to finance and economics. The objective is to offer an appropriate context and a starting point for those who are new to computational intelligence in finance and economics and to give an overview of the most recent works. A classification with five different main areas is presented. Those areas are related with different applications of the most modern computational intelligence techniques showing a ne...

New challenges in computational collective intelligence

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Ngoc Thanh; Katarzyniak, Radoslaw Piotr [Wroclaw Univ. of Technology (Poland). Inst. of Informatics; Janiak, Adam (eds.) [Wroclaw Univ. of Technology (Poland). Inst. of Computer Engineering, Control and Robotics

2009-07-01

The book consists of 29 chapters which have been selected and invited from the submissions to the 1{sup st} International Conference on Collective Intelligence - Semantic Web, Social Networks and Multiagent Systems (ICCCI 2009). All chapters in the book discuss various examples of applications of computational collective intelligence and related technologies to such fields as semantic web, information systems ontologies, social networks, agent and multiagent systems. The editors hope that the book can be useful for graduate and Ph.D. students in Computer Science, in particular participants to courses on Soft Computing, Multi-Agent Systems and Robotics. This book can also be useful for researchers working on the concept of computational collective intelligence in artificial populations. It is the hope of the editors that readers of this volume can find many inspiring ideas and use them to create new cases intelligent collectives. Many such challenges are suggested by particular approaches and models presented in particular chapters of this book. (orig.)

Symmetry Groups for the Decomposition of Reversible Computers, Quantum Computers, and Computers in between

Directory of Open Access Journals (Sweden)

Alexis De Vos

2011-06-01

Full Text Available Whereas quantum computing circuits follow the symmetries of the unitary Lie group, classical reversible computation circuits follow the symmetries of a finite group, i.e., the symmetric group. We confront the decomposition of an arbitrary classical reversible circuit with w bits and the decomposition of an arbitrary quantum circuit with w qubits. Both decompositions use the control gate as building block, i.e., a circuit transforming only one (qubit, the transformation being controlled by the other w−1 (qubits. We explain why the former circuit can be decomposed into 2w − 1 control gates, whereas the latter circuit needs 2w − 1 control gates. We investigate whether computer circuits, not based on the full unitary group but instead on a subgroup of the unitary group, may be decomposable either into 2w − 1 or into 2w − 1 control gates.

1st International Conference on Intelligent Computing and Communication

CERN Document Server

Satapathy, Suresh; Sanyal, Manas; Bhateja, Vikrant

2017-01-01

The book covers a wide range of topics in Computer Science and Information Technology including swarm intelligence, artificial intelligence, evolutionary algorithms, and bio-inspired algorithms. It is a collection of papers presented at the First International Conference on Intelligent Computing and Communication (ICIC2) 2016. The prime areas of the conference are Intelligent Computing, Intelligent Communication, Bio-informatics, Geo-informatics, Algorithm, Graphics and Image Processing, Graph Labeling, Web Security, Privacy and e-Commerce, Computational Geometry, Service Orient Architecture, and Data Engineering.

Computational Intelligence in Image Processing

CERN Document Server

Siarry, Patrick

2013-01-01

Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the atten­tion of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research prob­lems and in real-world problems. Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can ...

Application of computational intelligence in emerging power systems

African Journals Online (AJOL)

... in the electrical engineering applications. This paper highlights the application of computational intelligence methods in power system problems. Various types of CI methods, which are widely used in power system, are also discussed in the brief. Keywords: Power systems, computational intelligence, artificial intelligence.

Computational Intelligence and Decision Making Trends and Applications

CERN Document Server

Madureira, Ana; Marques, Viriato

2013-01-01

This book provides a general overview and original analysis of new developments and applications in several areas of Computational Intelligence and Information Systems. Computational Intelligence has become an important tool for engineers to develop and analyze novel techniques to solve problems in basic sciences such as physics, chemistry, biology, engineering, environment and social sciences.   The material contained in this book addresses the foundations and applications of Artificial Intelligence and Decision Support Systems, Complex and Biological Inspired Systems, Simulation and Evolution of Real and Artificial Life Forms, Intelligent Models and Control Systems, Knowledge and Learning Technologies, Web Semantics and Ontologies, Intelligent Tutoring Systems, Intelligent Power Systems, Self-Organized and Distributed Systems, Intelligent Manufacturing Systems and Affective Computing. The contributions have all been written by international experts, who provide current views on the topics discussed and pr...

16th UK Workshop on Computational Intelligence

CERN Document Server

Gegov, Alexander; Jayne, Chrisina; Shen, Qiang

2017-01-01

The book is a timely report on advanced methods and applications of computational intelligence systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, evolving systems and machine learning. The individual chapters are based on peer-reviewed contributions presented at the 16th Annual UK Workshop on Computational Intelligence, held on September 7-9, 2016, in Lancaster, UK. The book puts a special emphasis on novels methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.

Efficient computation of argumentation semantics

CERN Document Server

Liao, Beishui

2013-01-01

Efficient Computation of Argumentation Semantics addresses argumentation semantics and systems, introducing readers to cutting-edge decomposition methods that drive increasingly efficient logic computation in AI and intelligent systems. Such complex and distributed systems are increasingly used in the automation and transportation systems field, and particularly autonomous systems, as well as more generic intelligent computation research. The Series in Intelligent Systems publishes titles that cover state-of-the-art knowledge and the latest advances in research and development in intelligen

Life system modeling and intelligent computing. Pt. I. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Li, Kang; Irwin, George W. (eds.) [Belfast Queen' s Univ. (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Fei, Minrui; Jia, Li [Shanghai Univ. (China). School of Mechatronical Engineering and Automation

2010-07-01

This book is part I of a two-volume work that contains the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2010 and the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, held in Wuxi, China, in September 2010. The 194 revised full papers presented were carefully reviewed and selected from over 880 submissions and recommended for publication by Springer in two volumes of Lecture Notes in Computer Science (LNCS) and one volume of Lecture Notes in Bioinformatics (LNBI). This particular volume of Lecture Notes in Computer Science (LNCS) includes 55 papers covering 7 relevant topics. The 55 papers in this volume are organized in topical sections on intelligent modeling, monitoring, and control of complex nonlinear systems; autonomy-oriented computing and intelligent agents; advanced theory and methodology in fuzzy systems and soft computing; computational intelligence in utilization of clean and renewable energy resources; intelligent modeling, control and supervision for energy saving and pollution reduction; intelligent methods in developing vehicles, engines and equipments; computational methods and intelligence in modeling genetic and biochemical networks and regulation. (orig.)

Case studies in intelligent computing achievements and trends

CERN Document Server

Issac, Biju

2014-01-01

Although the field of intelligent systems has grown rapidly in recent years, there has been a need for a book that supplies a timely and accessible understanding of this important technology. Filling this need, Case Studies in Intelligent Computing: Achievements and Trends provides an up-to-date introduction to intelligent systems.This edited book captures the state of the art in intelligent computing research through case studies that examine recent developments, developmental tools, programming, and approaches related to artificial intelligence (AI). The case studies illustrate successful ma

2nd International Conference on Intelligent Computing and Applications

CERN Document Server

Dash, Subhransu; Das, Swagatam; Panigrahi, Bijaya

2017-01-01

Second International Conference on Intelligent Computing and Applications was the annual research conference aimed to bring together researchers around the world to exchange research results and address open issues in all aspects of Intelligent Computing and Applications. The main objective of the second edition of the conference for the scientists, scholars, engineers and students from the academia and the industry is to present ongoing research activities and hence to foster research relations between the Universities and the Industry. The theme of the conference unified the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in computational intelligence and bridges theoretical research concepts with applications. The conference covered vital issues ranging from intelligent computing, soft computing, and communication to machine learning, industrial automation, process technology and robotics. This conference also provided variety of opportunities for ...

Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

Science.gov (United States)

Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

2015-01-01

Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

Intelligent computational systems for space applications

Science.gov (United States)

Lum, Henry; Lau, Sonie

Intelligent computational systems can be described as an adaptive computational system integrating both traditional computational approaches and artificial intelligence (AI) methodologies to meet the science and engineering data processing requirements imposed by specific mission objectives. These systems will be capable of integrating, interpreting, and understanding sensor input information; correlating that information to the "world model" stored within its data base and understanding the differences, if any; defining, verifying, and validating a command sequence to merge the "external world" with the "internal world model"; and, controlling the vehicle and/or platform to meet the scientific and engineering mission objectives. Performance and simulation data obtained to date indicate that the current flight processors baselined for many missions such as Space Station Freedom do not have the computational power to meet the challenges of advanced automation and robotics systems envisioned for the year 2000 era. Research issues which must be addressed to achieve greater than giga-flop performance for on-board intelligent computational systems have been identified, and a technology development program has been initiated to achieve the desired long-term system performance objectives.

Computational intelligence, medicine and biology selected links

CERN Document Server

Zaitseva, Elena

2015-01-01

This book contains an interesting and state-of the art collection of chapters presenting several examples of attempts to developing modern tools utilizing computational intelligence in different real life problems encountered by humans. Reasoning, prediction, modeling, optimization, decision making, etc. need modern, soft and intelligent algorithms, methods and methodologies to solve, in the efficient ways, problems appearing in human activity. The contents of the book is divided into two parts. Part I, consisting of four chapters, is devoted to selected links of computational intelligence, medicine, health care and biomechanics. Several problems are considered: estimation of healthcare system reliability, classification of ultrasound thyroid images, application of fuzzy logic to measure weight status and central fatness, and deriving kinematics directly from video records. Part II, also consisting of four chapters, is devoted to selected links of computational intelligence and biology. The common denominato...

Computational intelligence in digital forensics forensic investigation and applications

CERN Document Server

Choo, Yun-Huoy; Abraham, Ajith; Srihari, Sargur

2014-01-01

Computational Intelligence techniques have been widely explored in various domains including forensics. Analysis in forensic encompasses the study of pattern analysis that answer the question of interest in security, medical, legal, genetic studies and etc. However, forensic analysis is usually performed through experiments in lab which is expensive both in cost and time. Therefore, this book seeks to explore the progress and advancement of computational intelligence technique in different focus areas of forensic studies. This aims to build stronger connection between computer scientists and forensic field experts.   This book, Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, is the first volume in the Intelligent Systems Reference Library series. The book presents original research results and innovative applications of computational intelligence in digital forensics. This edited volume contains seventeen chapters and presents the latest state-of-the-art advancement ...

Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

Science.gov (United States)

1991-06-01

Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

International Conference on Computational Intelligence, Cyber Security, and Computational Models

CERN Document Server

Ramasamy, Vijayalakshmi; Sheen, Shina; Veeramani, C; Bonato, Anthony; Batten, Lynn

2016-01-01

This book aims at promoting high-quality research by researchers and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security, and Computational Models ICC3 2015 organized by PSG College of Technology, Coimbatore, India during December 17 – 19, 2015. This book enriches with innovations in broad areas of research like computational modeling, computational intelligence and cyber security. These emerging inter disciplinary research areas have helped to solve multifaceted problems and gained lot of attention in recent years. This encompasses theory and applications, to provide design, analysis and modeling of the aforementioned key areas.

Soft computing for business intelligence

CERN Document Server

Pérez, Rafael; Cobo, Angel; Marx, Jorge; Valdés, Ariel

2014-01-01

The book Soft Computing for Business Intelligence is the remarkable output of a program based on the idea of joint trans-disciplinary research as supported by the Eureka Iberoamerica Network and the University of Oldenburg. It contains twenty-seven papers allocated to three sections: Soft Computing, Business Intelligence and Knowledge Discovery, and Knowledge Management and Decision Making. Although the contents touch different domains they are similar in so far as they follow the BI principle “Observation and Analysis” while keeping a practical oriented theoretical eye on sound methodologies, like Fuzzy Logic, Compensatory Fuzzy Logic (CFL), Rough Sets and other softcomputing elements. The book tears down the traditional focus on business, and extends Business Intelligence techniques in an impressive way to a broad range of fields like medicine, environment, wind farming, social collaboration and interaction, car sharing and sustainability.

Mathematical modeling and computational intelligence in engineering applications

CERN Document Server

Silva Neto, Antônio José da; Silva, Geraldo Nunes

2016-01-01

This book brings together a rich selection of studies in mathematical modeling and computational intelligence, with application in several fields of engineering, like automation, biomedical, chemical, civil, electrical, electronic, geophysical and mechanical engineering, on a multidisciplinary approach. Authors from five countries and 16 different research centers contribute with their expertise in both the fundamentals and real problems applications based upon their strong background on modeling and computational intelligence. The reader will find a wide variety of applications, mathematical and computational tools and original results, all presented with rigorous mathematical procedures. This work is intended for use in graduate courses of engineering, applied mathematics and applied computation where tools as mathematical and computational modeling, numerical methods and computational intelligence are applied to the solution of real problems.

2010 IEEE World Congress on Computational Intelligence (IEEE WCCI 2010)

CERN Document Server

Solanas, Agusti; Martinez-Balleste, Antoni; Computational Intelligence for Privacy and Security

2012-01-01

The book is a collection of invited papers on Computational Intelligence for Privacy and Security. The majority of the chapters are extended versions of works presented at the special session on Computational Intelligence for Privacy and Security of the International Joint Conference on Neural Networks (IJCNN-2010) held July 2010 in Barcelona, Spain. The book is devoted to Computational Intelligence for Privacy and Security. It provides an overview of the most recent advances on the Computational Intelligence techniques being developed for Privacy and Security. The book will be of interest to researchers in industry and academics and to post-graduate students interested in the latest advances and developments in the field of Computational Intelligence for Privacy and Security.

Computational intelligence applications in modeling and control

CERN Document Server

Vaidyanathan, Sundarapandian

2015-01-01

The development of computational intelligence (CI) systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. The essence of the systems based on computational intelligence is to process and interpret data of various nature so that that CI is strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Developed theories of computational intelligence were quickly applied in many fields of engineering, data analysis, forecasting, biomedicine and others. They are used in images and sounds processing and identifying, signals processing, multidimensional data visualization, steering of objects, analysis of lexicographic data, requesting systems in banking, diagnostic systems, expert systems and many other practical implementations. This book consists of 16 contributed chapters by subject experts who are specialized in the various topics addressed in this book. The special chapters have been brought ...

Intelligent Support for a Computer Aided Design Optimisation Cycle

OpenAIRE

B. Dolšak; M. Novak; J. Kaljun

2006-01-01

It is becoming more and more evident that  adding intelligence  to existing computer aids, such as computer aided design systems, can lead to significant improvements in the effective and reliable performance of various engineering tasks, including design optimisation. This paper presents three different intelligent modules to be applied within a computer aided design optimisation cycle to enable more intelligent and less experience-dependent design performance. 

Computational Intelligence Agent-Oriented Modelling

Czech Academy of Sciences Publication Activity Database

Neruda, Roman

2006-01-01

Roč. 5, č. 2 (2006), s. 430-433 ISSN 1109-2777 R&D Projects: GA MŠk 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : multi-agent systems * adaptive agents * computational intelligence Subject RIV: IN - Informatics, Computer Science

Computational intelligence in nuclear engineering

International Nuclear Information System (INIS)

Uhrig, Robert E.; Hines, J. Wesley

2005-01-01

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several Changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations

Intelligent Buildings and pervasive computing

DEFF Research Database (Denmark)

Grønbæk, Kaj; Kyng, Morten; Krogh, Peter Gall

2001-01-01

computers are everywhere, for everyone, at all times. Where IT becomes a still more integrated part of our environments with processors, sensors, and actuators connected via high-speed networks and combined with new visualiza-tion devices ranging from projections directly in the eye to large panorama......Intelligent Buildings have been the subject of research and commercial interest for more than two decades. The different perspectives range from monitoring and controlling energy consumption over interactive rooms supporting work in offices and leisure in the home, to buildings providing...... information to by-passers in plazas and urban environments. This paper puts forward the hypothesis that the coming decade will witness a dramatic increase in both quality and quantity of intelligent buildings due to the emerging field of pervasive computing: the next generation computing environments where...

Computational Intelligence Techniques for New Product Design

CERN Document Server

Chan, Kit Yan; Dillon, Tharam S

2012-01-01

Applying computational intelligence for product design is a fast-growing and promising research area in computer sciences and industrial engineering. However, there is currently a lack of books, which discuss this research area. This book discusses a wide range of computational intelligence techniques for implementation on product design. It covers common issues on product design from identification of customer requirements in product design, determination of importance of customer requirements, determination of optimal design attributes, relating design attributes and customer satisfaction, integration of marketing aspects into product design, affective product design, to quality control of new products. Approaches for refinement of computational intelligence are discussed, in order to address different issues on product design. Cases studies of product design in terms of development of real-world new products are included, in order to illustrate the design procedures, as well as the effectiveness of the com...

Artificial intelligence in robot control systems

Science.gov (United States)

Korikov, A.

2018-05-01

This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

International Conference on Frontiers of Intelligent Computing : Theory and Applications

CERN Document Server

Udgata, Siba; Biswal, Bhabendra

2014-01-01

This volume contains the papers presented at the Second International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA-2013) held during 14-16 November 2013 organized by Bhubaneswar Engineering College (BEC), Bhubaneswar, Odisha, India. It contains 63 papers focusing on application of intelligent techniques which includes evolutionary computation techniques like genetic algorithm, particle swarm optimization techniques, teaching-learning based optimization etc  for various engineering applications such as data mining, Fuzzy systems, Machine Intelligence and ANN, Web technologies and Multimedia applications and Intelligent computing and Networking etc.

Intelligent computing for sustainable energy and environment

Energy Technology Data Exchange (ETDEWEB)

Li, Kang [Queen' s Univ. Belfast (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Li, Shaoyuan; Li, Dewei [Shanghai Jiao Tong Univ., Shanghai (China). Dept. of Automation; Niu, Qun (eds.) [Shanghai Univ. (China). School of Mechatronic Engineering and Automation

2013-07-01

Fast track conference proceedings. State of the art research. Up to date results. This book constitutes the refereed proceedings of the Second International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2012, held in Shanghai, China, in September 2012. The 60 full papers presented were carefully reviewed and selected from numerous submissions and present theories and methodologies as well as the emerging applications of intelligent computing in sustainable energy and environment.

Advances in soft computing, intelligent robotics and control

CERN Document Server

Fullér, Robert

2014-01-01

Soft computing, intelligent robotics and control are in the core interest of contemporary engineering. Essential characteristics of soft computing methods are the ability to handle vague information, to apply human-like reasoning, their learning capability, and ease of application. Soft computing techniques are widely applied in the control of dynamic systems, including mobile robots. The present volume is a collection of 20 chapters written by respectable experts of the fields, addressing various theoretical and practical aspects in soft computing, intelligent robotics and control. The first part of the book concerns with issues of intelligent robotics, including robust xed point transformation design, experimental verification of the input-output feedback linearization of differentially driven mobile robot and applying kinematic synthesis to micro electro-mechanical systems design. The second part of the book is devoted to fundamental aspects of soft computing. This includes practical aspects of fuzzy rule ...

International Conference on Computational Intelligence in Data Mining

CERN Document Server

Mohapatra, Durga

2017-01-01

The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 – 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science. .

THE COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR PREDICTIONS - ARTIFICIAL NEURAL NETWORKS

OpenAIRE

Mary Violeta Bar

2014-01-01

The computational intelligence techniques are used in problems which can not be solved by traditional techniques when there is insufficient data to develop a model problem or when they have errors.Computational intelligence, as he called Bezdek (Bezdek, 1992) aims at modeling of biological intelligence. Artificial Neural Networks( ANNs) have been applied to an increasing number of real world problems of considerable complexity. Their most important advantage is solving problems that are too c...

Life system modeling and intelligent computing. Pt. II. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Li, Kang; Irwin, George W. (eds.) [Belfast Queen' s Univ. (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Fei, Minrui; Jia, Li [Shanghai Univ. (China). School of Mechatronical Engineering and Automation

2010-07-01

This book is part II of a two-volume work that contains the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2010 and the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, held in Wuxi, China, in September 2010. The 194 revised full papers presented were carefully reviewed and selected from over 880 submissions and recommended for publication by Springer in two volumes of Lecture Notes in Computer Science (LNCS) and one volume of Lecture Notes in Bioinformatics (LNBI). This particular volume of Lecture Notes in Computer Science (LNCS) includes 55 papers covering 7 relevant topics. The 56 papers in this volume are organized in topical sections on advanced evolutionary computing theory and algorithms; advanced neural network and fuzzy system theory and algorithms; modeling and simulation of societies and collective behavior; biomedical signal processing, imaging, and visualization; intelligent computing and control in distributed power generation systems; intelligent methods in power and energy infrastructure development; intelligent modeling, monitoring, and control of complex nonlinear systems. (orig.)

1st International Conference on Computational Intelligence and Informatics

CERN Document Server

Prasad, V; Rani, B; Udgata, Siba; Raju, K

2017-01-01

The book covers a variety of topics which include data mining and data warehousing, high performance computing, parallel and distributed computing, computational intelligence, soft computing, big data, cloud computing, grid computing, cognitive computing, image processing, computer networks, wireless networks, social networks, wireless sensor networks, information and network security, web security, internet of things, bioinformatics and geoinformatics. The book is a collection of best papers submitted in the First International Conference on Computational Intelligence and Informatics (ICCII 2016) held during 28-30 May 2016 at JNTUH CEH, Hyderabad, India. It was hosted by Department of Computer Science and Engineering, JNTUH College of Engineering in association with Division V (Education & Research) CSI, India. .

Integrating Human and Computer Intelligence. Technical Report No. 32.

Science.gov (United States)

Pea, Roy D.

This paper explores the thesis that advances in computer applications and artificial intelligence have important implications for the study of development and learning in psychology. Current approaches to the use of computers as devices for problem solving, reasoning, and thinking--i.e., expert systems and intelligent tutoring systems--are…

Contemporary cybernetics and its facets of cognitive informatics and computational intelligence.

Science.gov (United States)

Wang, Yingxu; Kinsner, Witold; Zhang, Du

2009-08-01

This paper explores the architecture, theoretical foundations, and paradigms of contemporary cybernetics from perspectives of cognitive informatics (CI) and computational intelligence. The modern domain and the hierarchical behavioral model of cybernetics are elaborated at the imperative, autonomic, and cognitive layers. The CI facet of cybernetics is presented, which explains how the brain may be mimicked in cybernetics via CI and neural informatics. The computational intelligence facet is described with a generic intelligence model of cybernetics. The compatibility between natural and cybernetic intelligence is analyzed. A coherent framework of contemporary cybernetics is presented toward the development of transdisciplinary theories and applications in cybernetics, CI, and computational intelligence.

1st International Conference on Intelligent Computing, Communication and Devices

CERN Document Server

Patnaik, Srikanta; Ichalkaranje, Nikhil

2015-01-01

In the history of mankind, three revolutions which impact the human life are the tool-making revolution, agricultural revolution and industrial revolution. They have transformed not only the economy and civilization but the overall development of the society. Probably, intelligence revolution is the next revolution, which the society will perceive in the next 10 years. ICCD-2014 covers all dimensions of intelligent sciences, i.e. Intelligent Computing, Intelligent Communication and Intelligent Devices. This volume covers contributions from Intelligent Communication which are from the areas such as Communications and Wireless Ad Hoc & Sensor Networks, Speech & Natural Language Processing, including Signal, Image and Video Processing and Mobile broadband and Optical networks, which are the key to the ground-breaking inventions to intelligent communication technologies. Secondly, Intelligent Device is any type of equipment, instrument, or machine that has its own computing capability. Contributions from ...

[INVITED] Computational intelligence for smart laser materials processing

Science.gov (United States)

Casalino, Giuseppe

2018-03-01

Computational intelligence (CI) involves using a computer algorithm to capture hidden knowledge from data and to use them for training ;intelligent machine; to make complex decisions without human intervention. As simulation is becoming more prevalent from design and planning to manufacturing and operations, laser material processing can also benefit from computer generating knowledge through soft computing. This work is a review of the state-of-the-art on the methodology and applications of CI in laser materials processing (LMP), which is nowadays receiving increasing interest from world class manufacturers and 4.0 industry. The focus is on the methods that have been proven effective and robust in solving several problems in welding, cutting, drilling, surface treating and additive manufacturing using the laser beam. After a basic description of the most common computational intelligences employed in manufacturing, four sections, namely, laser joining, machining, surface, and additive covered the most recent applications in the already extensive literature regarding the CI in LMP. Eventually, emerging trends and future challenges were identified and discussed.

Wind power systems. Applications of computational intelligence

Energy Technology Data Exchange (ETDEWEB)

Wang, Lingfeng [Toledo Univ., OH (United States). Dept. of Electrical Engineering and Computer Science; Singh, Chanan [Texas A and M Univ., College Station, TX (United States). Electrical and Computer Engineering Dept.; Kusiak, Andrew (eds.) [Iowa Univ., Iowa City, IA (United States). Mechanical and Industrial Engineering Dept.

2010-07-01

Renewable energy sources such as wind power have attracted much attention because they are environmentally friendly, do not produce carbon dioxide and other emissions, and can enhance a nation's energy security. For example, recently more significant amounts of wind power are being integrated into conventional power grids. Therefore, it is necessary to address various important and challenging issues related to wind power systems, which are significantly different from the traditional generation systems. This book is a resource for engineers, practitioners, and decision-makers interested in studying or using the power of computational intelligence based algorithms in handling various important problems in wind power systems at the levels of power generation, transmission, and distribution. Researchers have been developing biologically-inspired algorithms in a wide variety of complex large-scale engineering domains. Distinguished from the traditional analytical methods, the new methods usually accomplish the task through their computationally efficient mechanisms. Computational intelligence methods such as evolutionary computation, neural networks, and fuzzy systems have attracted much attention in electric power systems. Meanwhile, modern electric power systems are becoming more and more complex in order to meet the growing electricity market. In particular, the grid complexity is continuously enhanced by the integration of intermittent wind power as well as the current restructuring efforts in electricity industry. Quite often, the traditional analytical methods become less efficient or even unable to handle this increased complexity. As a result, it is natural to apply computational intelligence as a powerful tool to deal with various important and pressing problems in the current wind power systems. This book presents the state-of-the-art development in the field of computational intelligence applied to wind power systems by reviewing the most up

Ubiquitous fuzzy computing in open ambient intelligence environments

NARCIS (Netherlands)

Acampora, G.; Loia, V.

2006-01-01

Ambient intelligence (AmI) is considered as the composition of three emergent technologies: ubiquitous computing, ubiquitous communication and intelligent user interfaces. The aim of integration of aforesaid technologies is to make wider the interaction between human beings and information

4th International Joint Conference on Computational Intelligence

CERN Document Server

Correia, António; Rosa, Agostinho; Filipe, Joaquim

2015-01-01

The present book includes extended and revised versions of a set of selected papers from the Fourth International Joint Conference on Computational Intelligence (IJCCI 2012)., held in Barcelona, Spain, from 5 to 7 October, 2012. The conference was sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC) and was organized in cooperation with the Association for the Advancement of Artificial Intelligence (AAAI). The conference brought together researchers, engineers and practitioners in computational technologies, especially those related to the areas of fuzzy computation, evolutionary computation and neural computation. It is composed of three co-located conferences, each one specialized in one of the aforementioned -knowledge areas. Namely: - International Conference on Evolutionary Computation Theory and Applications (ECTA) - International Conference on Fuzzy Computation Theory and Applications (FCTA) - International Conference on Neural Computation Theory a...

Intelligent decision support systems for sustainable computing paradigms and applications

CERN Document Server

Abraham, Ajith; Siarry, Patrick; Sheng, Michael

2017-01-01

This unique book dicusses the latest research, innovative ideas, challenges and computational intelligence (CI) solutions in sustainable computing. It presents novel, in-depth fundamental research on achieving a sustainable lifestyle for society, either from a methodological or from an application perspective. Sustainable computing has expanded to become a significant research area covering the fields of computer science and engineering, electrical engineering and other engineering disciplines, and there has been an increase in the amount of literature on aspects sustainable computing such as energy efficiency and natural resources conservation that emphasizes the role of ICT (information and communications technology) in achieving system design and operation objectives. The energy impact/design of more efficient IT infrastructures is a key challenge in realizing new computing paradigms. The book explores the uses of computational intelligence (CI) techniques for intelligent decision support that can be explo...

Artificial intelligence and computer vision

CERN Document Server

Li, Yujie

2017-01-01

This edited book presents essential findings in the research fields of artificial intelligence and computer vision, with a primary focus on new research ideas and results for mathematical problems involved in computer vision systems. The book provides an international forum for researchers to summarize the most recent developments and ideas in the field, with a special emphasis on the technical and observational results obtained in the past few years.

Domain Decomposition: A Bridge between Nature and Parallel Computers

Science.gov (United States)

1992-09-01

B., "Domain Decomposition Algorithms for Indefinite Elliptic Problems," S"IAM Journal of S; cientific and Statistical (’omputing, Vol. 13, 1992, pp...AD-A256 575 NASA Contractor Report 189709 ICASE Report No. 92-44 ICASE DOMAIN DECOMPOSITION: A BRIDGE BETWEEN NATURE AND PARALLEL COMPUTERS DTIC dE...effectively implemented on dis- tributed memory multiprocessors. In 1990 (as reported in Ref. 38 using the tile algo- rithm), a 103,201-unknown 2D elliptic

5th International Conference on Computational Collective Intelligence

CERN Document Server

Trawinski, Bogdan; Nguyen, Ngoc

2014-01-01

The book consists of 19 extended and revised chapters based on original works presented during a poster session organized within the 5th International Conference on Computational Collective Intelligence that was held between 11 and 13 of September 2013 in Craiova, Romania. The book is divided into three parts. The first part is titled “Agents and Multi-Agent Systems” and consists of 8 chapters that concentrate on many problems related to agent and multi-agent systems, including: formal models, agent autonomy, emergent properties, agent programming, agent-based simulation and planning. The second part of the book is titled “Intelligent Computational Methods” and consists of 6 chapters. The authors present applications of various intelligent computational methods like neural networks, mathematical optimization and multistage decision processes in areas like cooperation, character recognition, wireless networks, transport, and metal structures. The third part of the book is titled “Language and Knowled...

2nd International Conference on Computational Intelligence in Data Mining

CERN Document Server

Mohapatra, Durga

2016-01-01

The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December 2015. The two-volume Proceedings address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

Adaptation and hybridization in computational intelligence

CERN Document Server

Jr, Iztok

2015-01-01

  This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.  

Domain decomposition methods and parallel computing

International Nuclear Information System (INIS)

Meurant, G.

1991-01-01

In this paper, we show how to efficiently solve large linear systems on parallel computers. These linear systems arise from discretization of scientific computing problems described by systems of partial differential equations. We show how to get a discrete finite dimensional system from the continuous problem and the chosen conjugate gradient iterative algorithm is briefly described. Then, the different kinds of parallel architectures are reviewed and their advantages and deficiencies are emphasized. We sketch the problems found in programming the conjugate gradient method on parallel computers. For this algorithm to be efficient on parallel machines, domain decomposition techniques are introduced. We give results of numerical experiments showing that these techniques allow a good rate of convergence for the conjugate gradient algorithm as well as computational speeds in excess of a billion of floating point operations per second. (author). 5 refs., 11 figs., 2 tabs., 1 inset

Visualizing the Computational Intelligence Field

NARCIS (Netherlands)

L. Waltman (Ludo); J.H. van den Berg (Jan); U. Kaymak (Uzay); N.J.P. van Eck (Nees Jan)

2006-01-01

textabstractIn this paper, we visualize the structure and the evolution of the computational intelligence (CI) field. Based on our visualizations, we analyze the way in which the CI field is divided into several subfields. The visualizations provide insight into the characteristics of each subfield

International Conference on Frontiers of Intelligent Computing : Theory and Applications

CERN Document Server

Bhateja, Vikrant; Udgata, Siba; Pattnaik, Prasant

2017-01-01

The book is a collection of high-quality peer-reviewed research papers presented at International Conference on Frontiers of Intelligent Computing: Theory and applications (FICTA 2016) held at School of Computer Engineering, KIIT University, Bhubaneswar, India during 16 – 17 September 2016. The book presents theories, methodologies, new ideas, experiences and applications in all areas of intelligent computing and its applications to various engineering disciplines like computer science, electronics, electrical and mechanical engineering.

Intelligent systems and soft computing for nuclear science and industry

International Nuclear Information System (INIS)

Ruan, D.; D'hondt, P.; Govaerts, P.; Kerre, E.E.

1996-01-01

The second international workshop on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS) addresses topics related to intelligent systems and soft computing for nuclear science and industry. The proceedings contain 52 papers in different fields such as radiation protection, nuclear safety (human factors and reliability), safeguards, nuclear reactor control, production processes in the fuel cycle, dismantling, waste and disposal, decision making, and nuclear reactor control. A clear link is made between theory and applications of fuzzy logic such as neural networks, expert systems, robotics, man-machine interfaces, and decision-support techniques by using modern and advanced technologies and tools. The papers are grouped in three sections. The first section (Soft computing techniques) deals with basic tools to treat fuzzy logic, neural networks, genetic algorithms, decision-making, and software used for general soft-computing aspects. The second section (Intelligent engineering systems) includes contributions on engineering problems such as knowledge-based engineering, expert systems, process control integration, diagnosis, measurements, and interpretation by soft computing. The third section (Nuclear applications) focusses on the application of soft computing and intelligent systems in nuclear science and industry

Computational intelligence for decision support in cyber-physical systems

CERN Document Server

Ali, A; Riaz, Zahid

2014-01-01

This book is dedicated to applied computational intelligence and soft computing techniques with special reference to decision support in Cyber Physical Systems (CPS), where the physical as well as the communication segment of the networked entities interact with each other. The joint dynamics of such systems result in a complex combination of computers, software, networks and physical processes all combined to establish a process flow at system level. This volume provides the audience with an in-depth vision about how to ensure dependability, safety, security and efficiency in real time by making use of computational intelligence in various CPS applications ranging from the nano-world to large scale wide area systems of systems. Key application areas include healthcare, transportation, energy, process control and robotics where intelligent decision support has key significance in establishing dynamic, ever-changing and high confidence future technologies. A recommended text for graduate students and researche...

Cloud Computing Boosts Business Intelligence of Telecommunication Industry

Science.gov (United States)

Xu, Meng; Gao, Dan; Deng, Chao; Luo, Zhiguo; Sun, Shaoling

Business Intelligence becomes an attracting topic in today's data intensive applications, especially in telecommunication industry. Meanwhile, Cloud Computing providing IT supporting Infrastructure with excellent scalability, large scale storage, and high performance becomes an effective way to implement parallel data processing and data mining algorithms. BC-PDM (Big Cloud based Parallel Data Miner) is a new MapReduce based parallel data mining platform developed by CMRI (China Mobile Research Institute) to fit the urgent requirements of business intelligence in telecommunication industry. In this paper, the architecture, functionality and performance of BC-PDM are presented, together with the experimental evaluation and case studies of its applications. The evaluation result demonstrates both the usability and the cost-effectiveness of Cloud Computing based Business Intelligence system in applications of telecommunication industry.

Advanced intelligent computational technologies and decision support systems

CERN Document Server

Kountchev, Roumen

2014-01-01

This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.

Fundamentals of computational intelligence neural networks, fuzzy systems, and evolutionary computation

CERN Document Server

Keller, James M; Fogel, David B

2016-01-01

This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basi function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzz...

Computational intelligence in automotive applications

Energy Technology Data Exchange (ETDEWEB)

Prokhorov, Danil (ed.) [Toyota Motor Engineering and Manufacturing (TEMA), Ann Arbor, MI (United States). Toyota Technical Center

2008-07-01

What is computational intelligence (CI)? Traditionally, CI is understood as a collection of methods from the fields of neural networks (NN), fuzzy logic and evolutionary computation. This edited volume is the first of its kind, suitable to automotive researchers, engineers and students. It provides a representative sample of contemporary CI activities in the area of automotive technology. The volume consists of 13 chapters, including but not limited to these topics: vehicle diagnostics and vehicle system safety, control of vehicular systems, quality control of automotive processes, driver state estimation, safety of pedestrians, intelligent vehicles. All chapters contain overviews of state of the art, and several chapters illustrate their methodologies on examples of real-world systems. About the Editor: Danil Prokhorov began his technical career in St. Petersburg, Russia, after graduating with Honors from Saint Petersburg State University of Aerospace Instrumentation in 1992 (MS in Robotics). He worked as a research engineer in St. Petersburg Institute for Informatics and Automation, one of the institutes of the Russian Academy of Sciences. He came to the US in late 1993 for Ph.D. studies. He became involved in automotive research in 1995 when he was a Summer intern at Ford Scientific Research Lab in Dearborn, MI. Upon his graduation from the EE Department of Texas Tech University, Lubbock, in 1997, he joined Ford to pursue application-driven research on neural networks and other machine learning algorithms. While at Ford, he took part in several production-bound projects including neural network based engine misfire detection. Since 2005 he is with Toyota Technical Center, Ann Arbor, MI, overseeing important mid- and long-term research projects in computational intelligence. (orig.)

Convergence Analysis of a Class of Computational Intelligence Approaches

Directory of Open Access Journals (Sweden)

Junfeng Chen

2013-01-01

Full Text Available Computational intelligence approaches is a relatively new interdisciplinary field of research with many promising application areas. Although the computational intelligence approaches have gained huge popularity, it is difficult to analyze the convergence. In this paper, a computational model is built up for a class of computational intelligence approaches represented by the canonical forms of generic algorithms, ant colony optimization, and particle swarm optimization in order to describe the common features of these algorithms. And then, two quantification indices, that is, the variation rate and the progress rate, are defined, respectively, to indicate the variety and the optimality of the solution sets generated in the search process of the model. Moreover, we give four types of probabilistic convergence for the solution set updating sequences, and their relations are discussed. Finally, the sufficient conditions are derived for the almost sure weak convergence and the almost sure strong convergence of the model by introducing the martingale theory into the Markov chain analysis.

An intelligent multi-media human-computer dialogue system

Science.gov (United States)

Neal, J. G.; Bettinger, K. E.; Byoun, J. S.; Dobes, Z.; Thielman, C. Y.

1988-01-01

Sophisticated computer systems are being developed to assist in the human decision-making process for very complex tasks performed under stressful conditions. The human-computer interface is a critical factor in these systems. The human-computer interface should be simple and natural to use, require a minimal learning period, assist the user in accomplishing his task(s) with a minimum of distraction, present output in a form that best conveys information to the user, and reduce cognitive load for the user. In pursuit of this ideal, the Intelligent Multi-Media Interfaces project is devoted to the development of interface technology that integrates speech, natural language text, graphics, and pointing gestures for human-computer dialogues. The objective of the project is to develop interface technology that uses the media/modalities intelligently in a flexible, context-sensitive, and highly integrated manner modelled after the manner in which humans converse in simultaneous coordinated multiple modalities. As part of the project, a knowledge-based interface system, called CUBRICON (CUBRC Intelligent CONversationalist) is being developed as a research prototype. The application domain being used to drive the research is that of military tactical air control.

A proposal of ubiquitous fuzzy computing for ambient Intelligence

NARCIS (Netherlands)

Acampora, G.; Loia, V.

2008-01-01

Ambient Intelligence is considered as the composition of three emergent technologies: Ubiquitous Computing, Ubiquitous Communication and Intelligent User Interfaces. The aim of integration of aforesaid technologies is to make wider the interaction between human beings and information technology

Distributed computing and artificial intelligence : 10th International Conference

CERN Document Server

Neves, José; Rodriguez, Juan; Santana, Juan; Gonzalez, Sara

2013-01-01

The International Symposium on Distributed Computing and Artificial Intelligence 2013 (DCAI 2013) is a forum in which applications of innovative techniques for solving complex problems are presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. This conference is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and industry se...

4th INNS Symposia Series on Computational Intelligence in Information Systems

CERN Document Server

Au, Thien

2015-01-01

This book constitutes the refereed proceedings of the Fourth International Neural Network Symposia series on Computational Intelligence in Information Systems, INNS-CIIS 2014, held in Bandar Seri Begawan, Brunei in November 2014. INNS-CIIS aims to provide a platform for researchers to exchange the latest ideas and present the most current research advances in general areas related to computational intelligence and its applications in various domains. The 34 revised full papers presented in this book have been carefully reviewed and selected from 72 submissions. They cover a wide range of topics and application areas in computational intelligence and informatics.  

FTRA 4th International Conference on Mobile, Ubiquitous, and Intelligent Computing

CERN Document Server

Adeli, Hojjat; Park, Namje; Woungang, Isaac

2014-01-01

MUSIC 2013 will be the most comprehensive text focused on the various aspects of Mobile, Ubiquitous and Intelligent computing. MUSIC 2013 provides an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of intelligent technologies in mobile and ubiquitous computing environment. MUSIC 2013 is the next edition of the 3rd International Conference on Mobile, Ubiquitous, and Intelligent Computing (MUSIC-12, Vancouver, Canada, 2012) which was the next event in a series of highly successful International Workshop on Multimedia, Communication and Convergence technologies MCC-11 (Crete, Greece, June 2011), MCC-10 (Cebu, Philippines, August 2010).

Optimization and Assessment of Wavelet Packet Decompositions with Evolutionary Computation

Directory of Open Access Journals (Sweden)

Schell Thomas

2003-01-01

Full Text Available In image compression, the wavelet transformation is a state-of-the-art component. Recently, wavelet packet decomposition has received quite an interest. A popular approach for wavelet packet decomposition is the near-best-basis algorithm using nonadditive cost functions. In contrast to additive cost functions, the wavelet packet decomposition of the near-best-basis algorithm is only suboptimal. We apply methods from the field of evolutionary computation (EC to test the quality of the near-best-basis results. We observe a phenomenon: the results of the near-best-basis algorithm are inferior in terms of cost-function optimization but are superior in terms of rate/distortion performance compared to EC methods.

Correlation between crystallographic computing and artificial intelligence research

Energy Technology Data Exchange (ETDEWEB)

Feigenbaum, E A [Stanford Univ., CA; Engelmore, R S; Johnson, C K

1977-01-01

Artificial intelligence research, as a part of computer science, has produced a variety of programs of experimental and applications interest: programs for scientific inference, chemical synthesis, planning robot control, extraction of meaning from English sentences, speech understanding, interpretation of visual images, and so on. The symbolic manipulation techniques used in artificial intelligence provide a framework for analyzing and coding the knowledge base of a problem independently of an algorithmic implementation. A possible application of artificial intelligence methodology to protein crystallography is described. 2 figures, 2 tables.

International conference on Advances in Intelligent Control and Innovative Computing

CERN Document Server

Castillo, Oscar; Huang, Xu; Intelligent Control and Innovative Computing

2012-01-01

In the lightning-fast world of intelligent control and cutting-edge computing, it is vitally important to stay abreast of developments that seem to follow each other without pause. This publication features the very latest and some of the very best current research in the field, with 32 revised and extended research articles written by prominent researchers in the field. Culled from contributions to the key 2011 conference Advances in Intelligent Control and Innovative Computing, held in Hong Kong, the articles deal with a wealth of relevant topics, from the most recent work in artificial intelligence and decision-supporting systems, to automated planning, modelling and simulation, signal processing, and industrial applications. Not only does this work communicate the current state of the art in intelligent control and innovative computing, it is also an illuminating guide to up-to-date topics for researchers and graduate students in the field. The quality of the contents is absolutely assured by the high pro...

Hierarchical Decompositions for the Computation of High-Dimensional Multivariate Normal Probabilities

KAUST Repository

Genton, Marc G.

2017-09-07

We present a hierarchical decomposition scheme for computing the n-dimensional integral of multivariate normal probabilities that appear frequently in statistics. The scheme exploits the fact that the formally dense covariance matrix can be approximated by a matrix with a hierarchical low rank structure. It allows the reduction of the computational complexity per Monte Carlo sample from O(n2) to O(mn+knlog(n/m)), where k is the numerical rank of off-diagonal matrix blocks and m is the size of small diagonal blocks in the matrix that are not well-approximated by low rank factorizations and treated as dense submatrices. This hierarchical decomposition leads to substantial efficiencies in multivariate normal probability computations and allows integrations in thousands of dimensions to be practical on modern workstations.

Hierarchical Decompositions for the Computation of High-Dimensional Multivariate Normal Probabilities

KAUST Repository

Genton, Marc G.; Keyes, David E.; Turkiyyah, George

2017-01-01

We present a hierarchical decomposition scheme for computing the n-dimensional integral of multivariate normal probabilities that appear frequently in statistics. The scheme exploits the fact that the formally dense covariance matrix can be approximated by a matrix with a hierarchical low rank structure. It allows the reduction of the computational complexity per Monte Carlo sample from O(n2) to O(mn+knlog(n/m)), where k is the numerical rank of off-diagonal matrix blocks and m is the size of small diagonal blocks in the matrix that are not well-approximated by low rank factorizations and treated as dense submatrices. This hierarchical decomposition leads to substantial efficiencies in multivariate normal probability computations and allows integrations in thousands of dimensions to be practical on modern workstations.

Computational intelligence and quantitative software engineering

CERN Document Server

Succi, Giancarlo; Sillitti, Alberto

2016-01-01

In a down-to-the earth manner, the volume lucidly presents how the fundamental concepts, methodology, and algorithms of Computational Intelligence are efficiently exploited in Software Engineering and opens up a novel and promising avenue of a comprehensive analysis and advanced design of software artifacts. It shows how the paradigm and the best practices of Computational Intelligence can be creatively explored to carry out comprehensive software requirement analysis, support design, testing, and maintenance. Software Engineering is an intensive knowledge-based endeavor of inherent human-centric nature, which profoundly relies on acquiring semiformal knowledge and then processing it to produce a running system. The knowledge spans a wide variety of artifacts, from requirements, captured in the interaction with customers, to design practices, testing, and code management strategies, which rely on the knowledge of the running system. This volume consists of contributions written by widely acknowledged experts ...

International Conference on Frontiers of Intelligent Computing : Theory and Applications

CERN Document Server

Udgata, Siba; Biswal, Bhabendra

2013-01-01

The volume contains the papers presented at FICTA 2012: International Conference on Frontiers in Intelligent Computing: Theory and Applications held on December 22-23, 2012 in Bhubaneswar engineering College, Bhubaneswar, Odissa, India. It contains 86 papers contributed by authors from the globe. These research papers mainly focused on application of intelligent techniques which includes evolutionary computation techniques like genetic algorithm, particle swarm optimization techniques, teaching-learning based optimization etc  for various engineering applications such as data mining, image processing, cloud computing, networking etc.

Advances in neural networks computational intelligence for ICT

CERN Document Server

Esposito, Anna; Morabito, Francesco; Pasero, Eros

2016-01-01

This carefully edited book is putting emphasis on computational and artificial intelligent methods for learning and their relative applications in robotics, embedded systems, and ICT interfaces for psychological and neurological diseases. The book is a follow-up of the scientific workshop on Neural Networks (WIRN 2015) held in Vietri sul Mare, Italy, from the 20th to the 22nd of May 2015. The workshop, at its 27th edition became a traditional scientific event that brought together scientists from many countries, and several scientific disciplines. Each chapter is an extended version of the original contribution presented at the workshop, and together with the reviewers’ peer revisions it also benefits from the live discussion during the presentation. The content of book is organized in the following sections. 1. Introduction, 2. Machine Learning, 3. Artificial Neural Networks: Algorithms and models, 4. Intelligent Cyberphysical and Embedded System, 5. Computational Intelligence Methods for Biomedical ICT in...

Operator support system using computational intelligence techniques

International Nuclear Information System (INIS)

Bueno, Elaine Inacio; Pereira, Iraci Martinez

2015-01-01

Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

Operator support system using computational intelligence techniques

Energy Technology Data Exchange (ETDEWEB)

Bueno, Elaine Inacio, E-mail: ebueno@ifsp.edu.br [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Sao Paulo, SP (Brazil); Pereira, Iraci Martinez, E-mail: martinez@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2015-07-01

Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

9th International conference on distributed computing and artificial intelligence

CERN Document Server

Santana, Juan; González, Sara; Molina, Jose; Bernardos, Ana; Rodríguez, Juan; DCAI 2012; International Symposium on Distributed Computing and Artificial Intelligence 2012

2012-01-01

The International Symposium on Distributed Computing and Artificial Intelligence 2012 (DCAI 2012) is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. This conference is a forum in which  applications of innovative techniques for solving complex problems will be presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and indus...

Unified Computational Intelligence for Complex Systems

CERN Document Server

Seiffertt, John

2010-01-01

Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to e

Exact complexity: The spectral decomposition of intrinsic computation

International Nuclear Information System (INIS)

Crutchfield, James P.; Ellison, Christopher J.; Riechers, Paul M.

2016-01-01

We give exact formulae for a wide family of complexity measures that capture the organization of hidden nonlinear processes. The spectral decomposition of operator-valued functions leads to closed-form expressions involving the full eigenvalue spectrum of the mixed-state presentation of a process's ϵ-machine causal-state dynamic. Measures include correlation functions, power spectra, past-future mutual information, transient and synchronization informations, and many others. As a result, a direct and complete analysis of intrinsic computation is now available for the temporal organization of finitary hidden Markov models and nonlinear dynamical systems with generating partitions and for the spatial organization in one-dimensional systems, including spin systems, cellular automata, and complex materials via chaotic crystallography. - Highlights: • We provide exact, closed-form expressions for a hidden stationary process' intrinsic computation. • These include information measures such as the excess entropy, transient information, and synchronization information and the entropy-rate finite-length approximations. • The method uses an epsilon-machine's mixed-state presentation. • The spectral decomposition of the mixed-state presentation relies on the recent development of meromorphic functional calculus for nondiagonalizable operators.

Social networks a framework of computational intelligence

CERN Document Server

Chen, Shyi-Ming

2014-01-01

This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms.  The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling.  Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social network...

Expertik: Experience with Artificial Intelligence and Mobile Computing

Directory of Open Access Journals (Sweden)

José Edward Beltrán Lozano

2013-06-01

Full Text Available This article presents the experience in the development of services based in Artificial Intelligence, Service Oriented Architecture, mobile computing. It aims to combine technology offered by mobile computing provides techniques and artificial intelligence through a service provide diagnostic solutions to problems in industrial maintenance. It aims to combine technology offered by mobile computing and the techniques artificial intelligence through a service to provide diagnostic solutions to problems in industrial maintenance. For service creation are identified the elements of an expert system, the knowledge base, the inference engine and knowledge acquisition interfaces and their consultation. The applications were developed in ASP.NET under architecture three layers. The data layer was developed conjunction in SQL Server with data management classes; business layer in VB.NET and the presentation layer in ASP.NET with XHTML. Web interfaces for knowledge acquisition and query developed in Web and Mobile Web. The inference engine was conducted in web service developed for the fuzzy logic model to resolve requests from applications consulting knowledge (initially an exact rule-based logic within this experience to resolve requests from applications consulting knowledge. This experience seeks to strengthen a technology-based company to offer services based on AI for service companies Colombia.

Computational Intelligence. Mortality Models for the Actuary

NARCIS (Netherlands)

Willemse, W.J.

2001-01-01

This thesis applies computational intelligence to the field of actuarial (insurance) science. In particular, this thesis deals with life insurance where mortality modelling is important. Actuaries use ancient models (mortality laws) from the nineteenth century, for example Gompertz' and Makeham's

Computational Intelligence : International Joint Conference

CERN Document Server

Rosa, Agostinho; Cadenas, José; Dourado, António; Madani, Kurosh; Filipe, Joaquim

2016-01-01

The present book includes a set of selected extended papers from the sixth International Joint Conference on Computational Intelligence (IJCCI 2014), held in Rome, Italy, from 22 to 24 October 2014. The conference was composed by three co-located conferences:  The International Conference on Evolutionary Computation Theory and Applications (ECTA), the International Conference on Fuzzy Computation Theory and Applications (FCTA), and the International Conference on Neural Computation Theory and Applications (NCTA). Recent progresses in scientific developments and applications in these three areas are reported in this book. IJCCI received 210 submissions, from 51 countries, in all continents. After a double blind paper review performed by the Program Committee, 15% were accepted as full papers and thus selected for oral presentation. Additional papers were accepted as short papers and posters. A further selection was made after the Conference, based also on the assessment of presentation quality and audience in...

Computational Intelligence : International Joint Conference

CERN Document Server

Dourado, António; Rosa, Agostinho; Filipe, Joaquim; Kacprzyk, Janusz

2016-01-01

The present book includes a set of selected extended papers from the fifth International Joint Conference on Computational Intelligence (IJCCI 2013), held in Vilamoura, Algarve, Portugal, from 20 to 22 September 2013. The conference was composed by three co-located conferences:  The International Conference on Evolutionary Computation Theory and Applications (ECTA), the International Conference on Fuzzy Computation Theory and Applications (FCTA), and the International Conference on Neural Computation Theory and Applications (NCTA). Recent progresses in scientific developments and applications in these three areas are reported in this book. IJCCI received 111 submissions, from 30 countries, in all continents. After a double blind paper review performed by the Program Committee, only 24 submissions were accepted as full papers and thus selected for oral presentation, leading to a full paper acceptance ratio of 22%. Additional papers were accepted as short papers and posters. A further selection was made after ...

Intelligent computer-aided training and tutoring

Science.gov (United States)

Loftin, R. Bowen; Savely, Robert T.

1991-01-01

Specific autonomous training systems based on artificial intelligence technology for use by NASA astronauts, flight controllers, and ground-based support personnel that demonstrate an alternative to current training systems are described. In addition to these specific systems, the evolution of a general architecture for autonomous intelligent training systems that integrates many of the features of traditional training programs with artificial intelligence techniques is presented. These Intelligent Computer-Aided Training (ICAT) systems would provide, for the trainee, much of the same experience that could be gained from the best on-the-job training. By integrating domain expertise with a knowledge of appropriate training methods, an ICAT session should duplicate, as closely as possible, the trainee undergoing on-the-job training in the task environment, benefitting from the full attention of a task expert who is also an expert trainer. Thus, the philosophy of the ICAT system is to emulate the behavior of an experienced individual devoting his full time and attention to the training of a novice - proposing challenging training scenarios, monitoring and evaluating the actions of the trainee, providing meaningful comments in response to trainee errors, responding to trainee requests for information, giving hints (if appropriate), and remembering the strengths and weaknesses displayed by the trainee so that appropriate future exercises can be designed.

1st International Conference on Computational Intelligence in Data Mining

CERN Document Server

Behera, Himansu; Mandal, Jyotsna; Mohapatra, Durga

2015-01-01

The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of relate...

Intelligent Buildings and pervasive computing - research perspectives and discussions

DEFF Research Database (Denmark)

Grønbæk, Kaj; Krogh, Peter Gall; Kyng, Morten

2001-01-01

computers are everywhere, for everyone, at all times. Where IT becomes a still more integrated part of our environments with processors, sensors, and actuators connected via high-speed networks and combined with new visualization devices ranging from projections directly in the eye to large panorama......Intelligent Buildings have been the subject of research and commercial interest for more than two decades. The different perspectives range from monitoring and controlling energy consumption over interactive rooms supporting work in offices and leisure in the home, to buildings providing...... information to by-passers in plazas and urban environments. This paper puts forward the hypothesis that the coming decade will witness a dramatic increase in both quality and quantity of intelligent buildings due to the emerging field of pervasive computing: the next generation computing environments where...

Distributed Computing and Artificial Intelligence, 12th International Conference

CERN Document Server

Malluhi, Qutaibah; Gonzalez, Sara; Bocewicz, Grzegorz; Bucciarelli, Edgardo; Giulioni, Gianfranco; Iqba, Farkhund

2015-01-01

The 12th International Symposium on Distributed Computing and Artificial Intelligence 2015 (DCAI 2015) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the Osaka Institute of Technology, Qatar University and the University of Salamanca.

Ambient Intelligence and Wearable Computing: Sensors on the Body, in the Home, and Beyond

OpenAIRE

Cook, Diane J.; Song, WenZhan

2009-01-01

Ambient intelligence has a history of focusing on technologies that are integrated into a person’s environment. However, ambient intelligence can be found on a person’s body as well. In this thematic issue we examine the role of wearable computing in the field of ambient intelligence. In this article we provide an overview of the field of wearable computing and discuss its relationship to the fields of smart environments and ambient intelligence. In addition, we introduce the papers presented...

The Intelligent Safety System: could it introduce complex computing into CANDU shutdown systems

International Nuclear Information System (INIS)

Hall, J.A.; Hinds, H.W.; Pensom, C.F.; Barker, C.J.; Jobse, A.H.

1984-07-01

The Intelligent Safety System is a computerized shutdown system being developed at the Chalk River Nuclear Laboratories (CRNL) for future CANDU nuclear reactors. It differs from current CANDU shutdown systems in both the algorithm used and the size and complexity of computers required to implement the concept. This paper provides an overview of the project, with emphasis on the computing aspects. Early in the project several needs leading to an introduction of computing complexity were identified, and a computing system that met these needs was conceived. The current work at CRNL centers on building a laboratory demonstration of the Intelligent Safety System, and evaluating the reliability and testability of the concept. Some fundamental problems must still be addressed for the Intelligent Safety System to be acceptable to a CANDU owner and to the regulatory authorities. These are also discussed along with a description of how the Intelligent Safety System might solve these problems

BRAIN. Broad Research in Artificial Intelligence and Neuroscience-Review of Recent Trends in Measuring the Computing Systems Intelligence

OpenAIRE

Laszlo Barna Iantovics; Adrian Gligor; Muaz A. Niazi; Anna Iuliana Biro; Sandor Miklos Szilagyi; Daniel Tokody

2018-01-01

Many difficult problems, from the philosophy of computation point of view, could require computing systems that have some kind of intelligence in order to be solved. Recently, we have seen a large number of artificial intelligent systems used in a number of scientific, technical and social domains. Usage of such an approach often has a focus on healthcare. These systems can provide solutions to a very large set of problems such as, but not limited to: elder patient care; medica...

APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

DEFF Research Database (Denmark)

Sonnenwald, Diane H.

1988-01-01

A description is given of UIMS (User Interface Management System), a system using a variety of artificial intelligence techniques to build knowledge-based user interfaces combining functionality and information from a variety of computer systems that maintain, test, and configure customer telephone...... and data networks. Three artificial intelligence (AI) techniques used in UIMS are discussed, namely, frame representation, object-oriented programming languages, and rule-based systems. The UIMS architecture is presented, and the structure of the UIMS is explained in terms of the AI techniques....

Application of computational intelligence techniques for load shedding in power systems: A review

International Nuclear Information System (INIS)

Laghari, J.A.; Mokhlis, H.; Bakar, A.H.A.; Mohamad, Hasmaini

2013-01-01

Highlights: • The power system blackout history of last two decades is presented. • Conventional load shedding techniques, their types and limitations are presented. • Applications of intelligent techniques in load shedding are presented. • Intelligent techniques include ANN, fuzzy logic, ANFIS, genetic algorithm and PSO. • The discussion and comparison between these techniques are provided. - Abstract: Recent blackouts around the world question the reliability of conventional and adaptive load shedding techniques in avoiding such power outages. To address this issue, reliable techniques are required to provide fast and accurate load shedding to prevent collapse in the power system. Computational intelligence techniques, due to their robustness and flexibility in dealing with complex non-linear systems, could be an option in addressing this problem. Computational intelligence includes techniques like artificial neural networks, genetic algorithms, fuzzy logic control, adaptive neuro-fuzzy inference system, and particle swarm optimization. Research in these techniques is being undertaken in order to discover means for more efficient and reliable load shedding. This paper provides an overview of these techniques as applied to load shedding in a power system. This paper also compares the advantages of computational intelligence techniques over conventional load shedding techniques. Finally, this paper discusses the limitation of computational intelligence techniques, which restricts their usage in load shedding in real time

Training Software in Artificial-Intelligence Computing Techniques

Science.gov (United States)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Secure data exchange between intelligent devices and computing centers

Science.gov (United States)

Naqvi, Syed; Riguidel, Michel

2005-03-01

The advent of reliable spontaneous networking technologies (commonly known as wireless ad-hoc networks) has ostensibly raised stakes for the conception of computing intensive environments using intelligent devices as their interface with the external world. These smart devices are used as data gateways for the computing units. These devices are employed in highly volatile environments where the secure exchange of data between these devices and their computing centers is of paramount importance. Moreover, their mission critical applications require dependable measures against the attacks like denial of service (DoS), eavesdropping, masquerading, etc. In this paper, we propose a mechanism to assure reliable data exchange between an intelligent environment composed of smart devices and distributed computing units collectively called 'computational grid'. The notion of infosphere is used to define a digital space made up of a persistent and a volatile asset in an often indefinite geographical space. We study different infospheres and present general evolutions and issues in the security of such technology-rich and intelligent environments. It is beyond any doubt that these environments will likely face a proliferation of users, applications, networked devices, and their interactions on a scale never experienced before. It would be better to build in the ability to uniformly deal with these systems. As a solution, we propose a concept of virtualization of security services. We try to solve the difficult problems of implementation and maintenance of trust on the one hand, and those of security management in heterogeneous infrastructure on the other hand.

Intelligent computational control of multi-fingered dexterous robotic hand

OpenAIRE

Chen, Disi; Li, Gongfa; Jiang, Guozhang; Fang, Yinfeng; Ju, Zhaojie; Liu, Honghai

2015-01-01

We discuss the intelligent computational control theory and introduce the hardware structure of HIT/DLR II dexterous robotic hand, which is the typical dexterous robotic hand. We show that how DSP or FPGA controller can be used in the dexterous robotic hand. A popular intelligent dexterous robotic hand control system, which named Electromyography (EMG) control is investigated. We introduced some mathematical algorithms in EMG controlling, such as Gauss mixture model (GMM), artificial neural n...

Accelerating artificial intelligence with reconfigurable computing

Science.gov (United States)

Cieszewski, Radoslaw

Reconfigurable computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated by placing the computationally intense portions of an algorithm into reconfigurable hardware. Reconfigurable computing combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be changed over the lifetime of the system. Similar to an ASIC, reconfigurable systems provide a method to map circuits into hardware. Reconfigurable systems therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Such a field, where there is many different algorithms which can be accelerated, is an artificial intelligence. This paper presents example hardware implementations of Artificial Neural Networks, Genetic Algorithms and Expert Systems.

4th International Conference on Frontiers in Intelligent Computing : Theory and Applications

CERN Document Server

Pal, Tandra; Kar, Samarjit; Satapathy, Suresh; Mandal, Jyotsna

2016-01-01

The proceedings of the 4th International Conference on Frontiers in Intelligent Computing: Theory and Applications 2015 (FICTA 2015) serves as the knowledge centre not only for scientists and researchers in the field of intelligent computing but also for students of post-graduate level in various engineering disciplines. The book covers a comprehensive overview of the theory, methods, applications and tools of Intelligent Computing. Researchers are now working in interdisciplinary areas and the proceedings of FICTA 2015 plays a major role to accumulate those significant works in one arena. The chapters included in the proceedings inculcates both theoretical as well as practical aspects of different areas like Nature Inspired Algorithms, Fuzzy Systems, Data Mining, Signal Processing, Image processing, Text Processing, Wireless Sensor Networks, Network Security and Cellular Automata. .

Recent advances in swarm intelligence and evolutionary computation

CERN Document Server

2015-01-01

This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference f...

Projection decomposition algorithm for dual-energy computed tomography via deep neural network.

Science.gov (United States)

Xu, Yifu; Yan, Bin; Chen, Jian; Zeng, Lei; Li, Lei

2018-03-15

Dual-energy computed tomography (DECT) has been widely used to improve identification of substances from different spectral information. Decomposition of the mixed test samples into two materials relies on a well-calibrated material decomposition function. This work aims to establish and validate a data-driven algorithm for estimation of the decomposition function. A deep neural network (DNN) consisting of two sub-nets is proposed to solve the projection decomposition problem. The compressing sub-net, substantially a stack auto-encoder (SAE), learns a compact representation of energy spectrum. The decomposing sub-net with a two-layer structure fits the nonlinear transform between energy projection and basic material thickness. The proposed DNN not only delivers image with lower standard deviation and higher quality in both simulated and real data, and also yields the best performance in cases mixed with photon noise. Moreover, DNN costs only 0.4 s to generate a decomposition solution of 360 × 512 size scale, which is about 200 times faster than the competing algorithms. The DNN model is applicable to the decomposition tasks with different dual energies. Experimental results demonstrated the strong function fitting ability of DNN. Thus, the Deep learning paradigm provides a promising approach to solve the nonlinear problem in DECT.

Artificial Intelligence, Computational Thinking, and Mathematics Education

Science.gov (United States)

Gadanidis, George

2017-01-01

Purpose: The purpose of this paper is to examine the intersection of artificial intelligence (AI), computational thinking (CT), and mathematics education (ME) for young students (K-8). Specifically, it focuses on three key elements that are common to AI, CT and ME: agency, modeling of phenomena and abstracting concepts beyond specific instances.…

Artificial Intelligence, Evolutionary Computing and Metaheuristics In the Footsteps of Alan Turing

CERN Document Server

2013-01-01

Alan Turing pioneered many research areas such as artificial intelligence, computability, heuristics and pattern formation.  Nowadays at the information age, it is hard to imagine how the world would be without computers and the Internet. Without Turing's work, especially the core concept of Turing Machine at the heart of every computer, mobile phone and microchip today, so many things on which we are so dependent would be impossible. 2012 is the Alan Turing year -- a centenary celebration of the life and work of Alan Turing. To celebrate Turing's legacy and follow the footsteps of this brilliant mind, we take this golden opportunity to review the latest developments in areas of artificial intelligence, evolutionary computation and metaheuristics, and all these areas can be traced back to Turing's pioneer work. Topics include Turing test, Turing machine, artificial intelligence, cryptography, software testing, image processing, neural networks, nature-inspired algorithms such as bat algorithm and cuckoo sear...

Applied Computational Intelligence in Engineering and Information Technology Revised and Selected Papers from the 6th IEEE International Symposium on Applied Computational Intelligence and Informatics SACI 2011

CERN Document Server

Precup, Radu-Emil; Preitl, Stefan

2012-01-01

This book highlights the potential of getting benefits from various applications of computational intelligence techniques. The present book is structured such that to include a set of selected and extended papers from the 6th IEEE International Symposium on Applied Computational Intelligence and Informatics SACI 2011, held in Timisoara, Romania, from 19 to 21 May 2011. After a serious paper review performed by the Technical Program Committee only 116 submissions were accepted, leading to a paper acceptance ratio of 65 %. A further refinement was made after the symposium, based also on the assessment of the presentation quality. Concluding, this book includes the extended and revised versions of the very best papers of SACI 2011 and few invited papers authored by prominent specialists. The readers will benefit from gaining knowledge of the computational intelligence and on what problems can be solved in several areas; they will learn what kind of approaches is advised to use in order to solve these problems. A...

Artificial and Computational Intelligence for Games on Mobile Platforms

OpenAIRE

Congdon, Clare Bates; Hingston, Philip; Kendall, Graham

2013-01-01

In this chapter, we consider the possibilities of creating new and innovative games that are targeted for mobile devices, such as smart phones and tablets, and that showcase AI (Artificial Intelligence) and CI (Computational Intelligence) approaches. Such games might take advantage of the sensors and facilities that are not available on other platforms, or might simply rely on the "app culture" to facilitate getting the games into users' hands. While these games might be profitable in themsel...

SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

OpenAIRE

Jerzy Balicki

2015-01-01

The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to p...

7th International Joint Conference on Computational Intelligence

CERN Document Server

Rosa, Agostinho; Cadenas, José; Correia, António; Madani, Kurosh; Ruano, António; Filipe, Joaquim

2017-01-01

This book includes a selection of revised and extended versions of the best papers from the seventh International Joint Conference on Computational Intelligence (IJCCI 2015), held in Lisbon, Portugal, from 12 to 14 November 2015, which was composed of three co-located conferences: The International Conference on Evolutionary Computation Theory and Applications (ECTA), the International Conference on Fuzzy Computation Theory and Applications (FCTA), and the International Conference on Neural Computation Theory and Applications (NCTA). The book presents recent advances in scientific developments and applications in these three areas, reflecting the IJCCI’s commitment to high quality standards.

Seismic activity prediction using computational intelligence techniques in northern Pakistan

Science.gov (United States)

Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

2017-10-01

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

A proposal of an open ubiquitous fuzzy computing system for Ambient Intelligence

NARCIS (Netherlands)

Acampora, G.; Loia, V.; Lee, R.S.T.; Lioa, V.

2007-01-01

Ambient Intelligence (AmI) is considered as the composition of three emergent technologies: Ubiquitous Computing, Ubiquitous Communication and Intelligent User Interfaces. The aim of integration of aforesaid technologies is to make wider the interaction between human beings and information

Computational Intelligence Paradigms in Advanced Pattern Classification

CERN Document Server

Jain, Lakhmi

2012-01-01

This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of cognitive systems for image computer understanding, moving object detection, advanced image filtration and intelligent multi-object labelling and classification. It is directed to the scientists, application engineers, professors, professors and students will find this book useful.

The BioIntelligence Framework: a new computational platform for biomedical knowledge computing.

Science.gov (United States)

Farley, Toni; Kiefer, Jeff; Lee, Preston; Von Hoff, Daniel; Trent, Jeffrey M; Colbourn, Charles; Mousses, Spyro

2013-01-01

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic relationships in unstructured biomedical information, introducing barriers to realizing such solutions. We propose a scalable computational framework for addressing this need, which leverages a hypergraph-based data model and query language that may be better suited for representing complex multi-lateral, multi-scalar, and multi-dimensional relationships. We also discuss how this framework can be used to create rapid learning knowledge base systems to intelligently capture and relate complex patient data to biomedical knowledge in order to automate the recovery of clinically actionable information.

Artificial intelligence

CERN Document Server

Hunt, Earl B

1975-01-01

Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

Artificial Intelligence and the Teaching of Reading and Writing by Computers.

Science.gov (United States)

Balajthy, Ernest

1985-01-01

Discusses how computers can "converse" with students for teaching purposes, demonstrates how these interactions are becoming more complex, and explains how the computer's role is becoming more "human" in giving intelligent responses to students. (HOD)

A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

DEFF Research Database (Denmark)

Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

2001-01-01

The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

Directory of Open Access Journals (Sweden)

Jerzy Balicki

2015-12-01

Full Text Available The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to prepare investment strategies on the stock exchange market.

Best of Affective Computing and Intelligent Interaction 2013 in Multimodal Interactions

NARCIS (Netherlands)

Soleymani, Mohammad; Soleymani, M.; Pun, T.; Pun, Thierry; Nijholt, Antinus

The fifth biannual Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII 2013) was held in Geneva, Switzerland. This conference featured the recent advancement in affective computing and relevant applications in education, entertainment and health. A number of

Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

Science.gov (United States)

Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

2017-12-01

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

Chips challenging champions games, computers and artificial intelligence

CERN Document Server

Schaeffer, J

2002-01-01

One of the earliest dreams of the fledgling field of artificial intelligence (AI) was to build computer programs that could play games as well as or better than the best human players. Despite early optimism in the field, the challenge proved to be surprisingly difficult. However, the 1990s saw amazing progress. Computers are now better than humans in checkers, Othello and Scrabble; are at least as good as the best humans in backgammon and chess; and are rapidly improving at hex, go, poker, and shogi. This book documents the progress made in computers playing games and puzzles. The book is the

Engineering Courses on Computational Thinking Through Solving Problems in Artificial Intelligence

Directory of Open Access Journals (Sweden)

Piyanuch Silapachote

2017-09-01

Full Text Available Computational thinking sits at the core of every engineering and computing related discipline. It has increasingly emerged as its own subject in all levels of education. It is a powerful cornerstone for cognitive development, creative problem solving, algorithmic thinking and designs, and programming. How to effectively teach computational thinking skills poses real challenges and creates opportunities. Targeting entering computer science and engineering undergraduates, we resourcefully integrate elements from artificial intelligence (AI into introductory computing courses. In addition to comprehension of the essence of computational thinking, practical exercises in AI enable inspirations of collaborative problem solving beyond abstraction, logical reasoning, critical and analytical thinking. Problems in machine intelligence systems intrinsically connect students to algorithmic oriented computing and essential mathematical foundations. Beyond knowledge representation, AI fosters a gentle introduction to data structures and algorithms. Focused on engaging mental tool, a computer is never a necessity. Neither coding nor programming is ever required. Instead, students enjoy constructivist classrooms designed to always be active, flexible, and highly dynamic. Learning to learn and reflecting on cognitive experiences, they rigorously construct knowledge from collectively solving exciting puzzles, competing in strategic games, and participating in intellectual discussions.

DEMAID - A DESIGN MANAGER'S AID FOR INTELLIGENT DECOMPOSITION (MACINTOSH VERSION)

Science.gov (United States)

Rogers, J. L.

1994-01-01

Many engineering systems are large and multi-disciplinary. Before the design of new complex systems such as large space platforms can begin, the possible interactions among subsystems and their parts must be determined. Once this is completed the proposed system can be decomposed to identify its hierarchical structure. DeMAID (A Design Manager's Aid for Intelligent Decomposition) is a knowledge-based system for ordering the sequence of modules and identifying a possible multilevel structure for the design problem. DeMAID displays the modules in an N x N matrix format (called a design structure matrix) where a module is any process that requires input and generates an output. (Modules which generate an output but do not require an input, such as an initialization process, are also acceptable.) Although DeMAID requires an investment of time to generate and refine the list of modules for input, it could save a considerable amount of money and time in the total design process, particularly in new design problems where the ordering of the modules has not been defined. The decomposition of a complex design system into subsystems requires the judgement of the design manager. DeMAID reorders and groups the modules based on the links (interactions) among the modules, helping the design manager make decomposition decisions early in the design cycle. The modules are grouped into circuits (the subsystems) and displayed in an N x N matrix format. Feedback links, which indicate an iterative process, are minimized and only occur within a subsystem. Since there are no feedback links among the circuits, the circuits can be displayed in a multilevel format. Thus, a large amount of information is reduced to one or two displays which are stored for later retrieval and modification. The design manager and leaders of the design teams then have a visual display of the design problem and the intricate interactions among the different modules. The design manager could save a substantial

DEMAID - A DESIGN MANAGER'S AID FOR INTELLIGENT DECOMPOSITION (SUN VERSION)

Science.gov (United States)

Rogers, J. L.

1994-01-01

Many engineering systems are large and multi-disciplinary. Before the design of new complex systems such as large space platforms can begin, the possible interactions among subsystems and their parts must be determined. Once this is completed the proposed system can be decomposed to identify its hierarchical structure. DeMAID (A Design Manager's Aid for Intelligent Decomposition) is a knowledge-based system for ordering the sequence of modules and identifying a possible multilevel structure for the design problem. DeMAID displays the modules in an N x N matrix format (called a design structure matrix) where a module is any process that requires input and generates an output. (Modules which generate an output but do not require an input, such as an initialization process, are also acceptable.) Although DeMAID requires an investment of time to generate and refine the list of modules for input, it could save a considerable amount of money and time in the total design process, particularly in new design problems where the ordering of the modules has not been defined. The decomposition of a complex design system into subsystems requires the judgement of the design manager. DeMAID reorders and groups the modules based on the links (interactions) among the modules, helping the design manager make decomposition decisions early in the design cycle. The modules are grouped into circuits (the subsystems) and displayed in an N x N matrix format. Feedback links, which indicate an iterative process, are minimized and only occur within a subsystem. Since there are no feedback links among the circuits, the circuits can be displayed in a multilevel format. Thus, a large amount of information is reduced to one or two displays which are stored for later retrieval and modification. The design manager and leaders of the design teams then have a visual display of the design problem and the intricate interactions among the different modules. The design manager could save a substantial

16th International Conference on Hybrid Intelligent Systems and the 8th World Congress on Nature and Biologically Inspired Computing

CERN Document Server

Haqiq, Abdelkrim; Alimi, Adel; Mezzour, Ghita; Rokbani, Nizar; Muda, Azah

2017-01-01

This book presents the latest research in hybrid intelligent systems. It includes 57 carefully selected papers from the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) and the 8th World Congress on Nature and Biologically Inspired Computing (NaBIC 2016), held on November 21–23, 2016 in Marrakech, Morocco. HIS - NaBIC 2016 was jointly organized by the Machine Intelligence Research Labs (MIR Labs), USA; Hassan 1st University, Settat, Morocco and University of Sfax, Tunisia. Hybridization of intelligent systems is a promising research field in modern artificial/computational intelligence and is concerned with the development of the next generation of intelligent systems. The conference’s main aim is to inspire further exploration of the intriguing potential of hybrid intelligent systems and bio-inspired computing. As such, the book is a valuable resource for practicing engineers /scientists and researchers working in the field of computational intelligence and artificial intelligence.

Trends in ambient intelligent systems the role of computational intelligence

CERN Document Server

Khan, Mohammad; Abraham, Ajith

2016-01-01

This book demonstrates the success of Ambient Intelligence in providing possible solutions for the daily needs of humans. The book addresses implications of ambient intelligence in areas of domestic living, elderly care, robotics, communication, philosophy and others. The objective of this edited volume is to show that Ambient Intelligence is a boon to humanity with conceptual, philosophical, methodical and applicative understanding. The book also aims to schematically demonstrate developments in the direction of augmented sensors, embedded systems and behavioral intelligence towards Ambient Intelligent Networks or Smart Living Technology. It contains chapters in the field of Ambient Intelligent Networks, which received highly positive feedback during the review process. The book contains research work, with in-depth state of the art from augmented sensors, embedded technology and artificial intelligence along with cutting-edge research and development of technologies and applications of Ambient Intelligent N...

Computational intelligence from AI to BI to NI

Science.gov (United States)

Werbos, Paul J.

2015-05-01

This paper gives highlights of the history of the neural network field, stressing the fundamental ideas which have been in play. Early neural network research was motivated mainly by the goals of artificial intelligence (AI) and of functional neuroscience (biological intelligence, BI), but the field almost died due to frustrations articulated in the famous book Perceptrons by Minsky and Papert. When I found a way to overcome the difficulties by 1974, the community mindset was very resistant to change; it was not until 1987/1988 that the field was reborn in a spectacular way, leading to the organized communities now in place. Even then, it took many more years to establish crossdisciplinary research in the types of mathematical neural networks needed to really understand the kind of intelligence we see in the brain, and to address the most demanding engineering applications. Only through a new (albeit short-lived) funding initiative, funding crossdisciplinary teams of systems engineers and neuroscientists, were we able to fund the critical empirical demonstrations which put our old basic principle of "deep learning" firmly on the map in computer science. Progress has rightly been inhibited at times by legitimate concerns about the "Terminator threat" and other possible abuses of technology. This year, at SPIE, in the quantum computing track, we outline the next stage ahead of us in breaking out of the box, again and again, and rising to fundamental challenges and opportunities still ahead of us.

Creating Innovative Solutions for Future Hotel Rooms with Intelligent Multimedia and Pervasive Computing

Science.gov (United States)

Sharda, Nalin K.

Pervasive computing and intelligent multimedia technologies are becoming increasingly important to the modern way of living. However, many of their potential applications have not been fully realized yet. This chapter explores how innovative applications can be developed to meet the needs of the next generation hotels. Futuristic hotel rooms aim to be more than “home-away-from-home,” and as a consequence, offer tremendous opportunities for developing innovative applications of pervasive computing and intelligent multimedia. Next generation hotels will make increased use of technology products to attract new customers. High end TV screens, changeable room ambiance, biometric guest recognition, and electronic check-in facilities are some of the features already being implemented by some hotels. Entirely futuristic hotels in the sea, the stratosphere or the outer space, are also being proposed. All of these provide many novel opportunities for developing innovative solutions using intelligent multimedia and ubiquitous computing.

Decomposition and Cross-Product-Based Method for Computing the Dynamic Equation of Robots

Directory of Open Access Journals (Sweden)

Ching-Long Shih

2012-08-01

Full Text Available This paper aims to demonstrate a clear relationship between Lagrange equations and Newton-Euler equations regarding computational methods for robot dynamics, from which we derive a systematic method for using either symbolic or on-line numerical computations. Based on the decomposition approach and cross-product operation, a computing method for robot dynamics can be easily developed. The advantages of this computing framework are that: it can be used for both symbolic and on-line numeric computation purposes, and it can also be applied to biped systems, as well as some simple closed-chain robot systems.

Intelligent cloud computing security using genetic algorithm as a computational tools

Science.gov (United States)

Razuky AL-Shaikhly, Mazin H.

2018-05-01

An essential change had occurred in the field of Information Technology which represented with cloud computing, cloud giving virtual assets by means of web yet awesome difficulties in the field of information security and security assurance. Currently main problem with cloud computing is how to improve privacy and security for cloud “cloud is critical security”. This paper attempts to solve cloud security by using intelligent system with genetic algorithm as wall to provide cloud data secure, all services provided by cloud must detect who receive and register it to create list of users (trusted or un-trusted) depend on behavior. The execution of present proposal has shown great outcome.

3rd International Conference on Frontiers of Intelligent Computing : Theory and Applications

CERN Document Server

Biswal, Bhabendra; Udgata, Siba; Mandal, JK

2015-01-01

Volume 1 contains 95 papers presented at FICTA 2014: Third International Conference on Frontiers in Intelligent Computing: Theory and Applications. The conference was held during 14-15, November, 2014 at Bhubaneswar, Odisha, India.  This volume contains papers mainly focused on Data Warehousing and Mining, Machine Learning, Mobile and Ubiquitous Computing, AI, E-commerce & Distributed Computing and Soft Computing, Evolutionary Computing, Bio-inspired Computing and its Applications.

Eigenvector decomposition of full-spectrum x-ray computed tomography.

Science.gov (United States)

Gonzales, Brian J; Lalush, David S

2012-03-07

Energy-discriminated x-ray computed tomography (CT) data were projected onto a set of basis functions to suppress the noise in filtered back-projection (FBP) reconstructions. The x-ray CT data were acquired using a novel x-ray system which incorporated a single-pixel photon-counting x-ray detector to measure the x-ray spectrum for each projection ray. A matrix of the spectral response of different materials was decomposed using eigenvalue decomposition to form the basis functions. Projection of FBP onto basis functions created a de facto image segmentation of multiple contrast agents. Final reconstructions showed significant noise suppression while preserving important energy-axis data. The noise suppression was demonstrated by a marked improvement in the signal-to-noise ratio (SNR) along the energy axis for multiple regions of interest in the reconstructed images. Basis functions used on a more coarsely sampled energy axis still showed an improved SNR. We conclude that the noise-resolution trade off along the energy axis was significantly improved using the eigenvalue decomposition basis functions.

13th International Symposium on Distributed Computing and Artificial Intelligence 2016

CERN Document Server

Semalat, Ali; Bocewicz, Grzegorz; Sitek, Paweł; Nielsen, Izabela; García, Julián; Bajo, Javier

2016-01-01

The 13th International Symposium on Distributed Computing and Artificial Intelligence 2016 (DCAI 2016) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the University of Sevilla (Spain), Osaka Institute of Technology (Japan), and the Universiti Teknologi Malaysia (Malaysia).

Artificial intelligence, expert systems, computer vision, and natural language processing

Science.gov (United States)

Gevarter, W. B.

1984-01-01

An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

Third International Joint Conference on Computational Intelligence (IJCCI 2011)

CERN Document Server

Dourado, António; Rosa, Agostinho; Filipe, Joaquim; Computational Intelligence

2013-01-01

The present book includes a set of selected extended papers from the third International Joint Conference on Computational Intelligence (IJCCI 2011), held in Paris, France, from 24 to 26 October 2011. The conference was composed of three co-located conferences:  The International Conference on Fuzzy Computation (ICFC), the International Conference on Evolutionary Computation (ICEC), and the International Conference on Neural Computation (ICNC). Recent progresses in scientific developments and applications in these three areas are reported in this book. IJCCI received 283 submissions, from 59 countries, in all continents. This book includes the revised and extended versions of a strict selection of the best papers presented at the conference.

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

International Nuclear Information System (INIS)

Desai, Ajit; Pettit, Chris; Poirel, Dominique; Sarkar, Abhijit

2017-01-01

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolution in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.

Soft computing in artificial intelligence

CERN Document Server

Matson, Eric

2014-01-01

This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

Information granularity, big data, and computational intelligence

CERN Document Server

Chen, Shyi-Ming

2015-01-01

The recent pursuits emerging in the realm of big data processing, interpretation, collection and organization have emerged in numerous sectors including business, industry, and government organizations. Data sets such as customer transactions for a mega-retailer, weather monitoring, intelligence gathering, quickly outpace the capacities of traditional techniques and tools of data analysis. The 3V (volume, variability and velocity) challenges led to the emergence of new techniques and tools in data visualization, acquisition, and serialization. Soft Computing being regarded as a plethora of technologies of fuzzy sets (or Granular Computing), neurocomputing and evolutionary optimization brings forward a number of unique features that might be instrumental to the development of concepts and algorithms to deal with big data. This carefully edited volume provides the reader with an updated, in-depth material on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligenc...

11th International Conference on Distributed Computing and Artificial Intelligence

CERN Document Server

Bersini, Hugues; Corchado, Juan; Rodríguez, Sara; Pawlewski, Paweł; Bucciarelli, Edgardo

2014-01-01

The 11th International Symposium on Distributed Computing and Artificial Intelligence 2014 (DCAI 2014) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This year’s technical program presents both high quality and diversity, with contributions in well-established and evolving areas of research (Algeria, Brazil, China, Croatia, Czech Republic, Denmark, France, Germany, Ireland, Italy, Japan, Malaysia, Mexico, Poland, Portugal, Republic of Korea, Spain, Taiwan, Tunisia, Ukraine, United Kingdom), representing ...

Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

International Nuclear Information System (INIS)

Laghari, J.A.; Mokhlis, H.; Karimi, M.; Bakar, A.H.A.; Mohamad, Hasmaini

2014-01-01

Highlights: • Unintentional and intentional islanding, their causes, and solutions are presented. • Remote, passive, active and hybrid islanding detection techniques are discussed. • The limitation of these techniques in accurately detect islanding are discussed. • Computational intelligence techniques ability in detecting islanding is discussed. • Review of ANN, fuzzy logic control, ANFIS, Decision tree techniques is provided. - Abstract: Accurate and fast islanding detection of distributed generation is highly important for its successful operation in distribution networks. Up to now, various islanding detection technique based on communication, passive, active and hybrid methods have been proposed. However, each technique suffers from certain demerits that cause inaccuracies in islanding detection. Computational intelligence based techniques, due to their robustness and flexibility in dealing with complex nonlinear systems, is an option that might solve this problem. This paper aims to provide a comprehensive review of computational intelligence based techniques applied for islanding detection of distributed generation. Moreover, the paper compares the accuracies of computational intelligence based techniques over existing techniques to provide a handful of information for industries and utility researchers to determine the best method for their respective system

Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

Science.gov (United States)

Tong, S. S.

1986-01-01

The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

Computational intelligence for big data analysis frontier advances and applications

CERN Document Server

Dehuri, Satchidananda; Sanyal, Sugata

2015-01-01

The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

First International Conference on Intelligent Computing and Applications

CERN Document Server

Kar, Rajib; Das, Swagatam; Panigrahi, Bijaya

2015-01-01

The idea of the 1st International Conference on Intelligent Computing and Applications (ICICA 2014) is to bring the Research Engineers, Scientists, Industrialists, Scholars and Students together from in and around the globe to present the on-going research activities and hence to encourage research interactions between universities and industries. The conference provides opportunities for the delegates to exchange new ideas, applications and experiences, to establish research relations and to find global partners for future collaboration. The proceedings covers latest progresses in the cutting-edge research on various research areas of Image, Language Processing, Computer Vision and Pattern Recognition, Machine Learning, Data Mining and Computational Life Sciences, Management of Data including Big Data and Analytics, Distributed and Mobile Systems including Grid and Cloud infrastructure, Information Security and Privacy, VLSI, Electronic Circuits, Power Systems, Antenna, Computational fluid dynamics & Hea...

Linear stability analysis of detonations via numerical computation and dynamic mode decomposition

KAUST Repository

Kabanov, Dmitry I.

2017-12-08

We introduce a new method to investigate linear stability of gaseous detonations that is based on an accurate shock-fitting numerical integration of the linearized reactive Euler equations with a subsequent analysis of the computed solution via the dynamic mode decomposition. The method is applied to the detonation models based on both the standard one-step Arrhenius kinetics and two-step exothermic-endothermic reaction kinetics. Stability spectra for all cases are computed and analyzed. The new approach is shown to be a viable alternative to the traditional normal-mode analysis used in detonation theory.

Linear stability analysis of detonations via numerical computation and dynamic mode decomposition

KAUST Repository

Kabanov, Dmitry; Kasimov, Aslan R.

2018-01-01

We introduce a new method to investigate linear stability of gaseous detonations that is based on an accurate shock-fitting numerical integration of the linearized reactive Euler equations with a subsequent analysis of the computed solution via the dynamic mode decomposition. The method is applied to the detonation models based on both the standard one-step Arrhenius kinetics and two-step exothermic-endothermic reaction kinetics. Stability spectra for all cases are computed and analyzed. The new approach is shown to be a viable alternative to the traditional normal-mode analysis used in detonation theory.

Linear stability analysis of detonations via numerical computation and dynamic mode decomposition

KAUST Repository

Kabanov, Dmitry

2018-03-20

We introduce a new method to investigate linear stability of gaseous detonations that is based on an accurate shock-fitting numerical integration of the linearized reactive Euler equations with a subsequent analysis of the computed solution via the dynamic mode decomposition. The method is applied to the detonation models based on both the standard one-step Arrhenius kinetics and two-step exothermic-endothermic reaction kinetics. Stability spectra for all cases are computed and analyzed. The new approach is shown to be a viable alternative to the traditional normal-mode analysis used in detonation theory.

Intelligent battery energy management and control for vehicle-to-grid via cloud computing network

International Nuclear Information System (INIS)

Khayyam, Hamid; Abawajy, Jemal; Javadi, Bahman; Goscinski, Andrzej; Stojcevski, Alex; Bab-Hadiashar, Alireza

2013-01-01

Highlights: • The intelligent battery energy management substantially reduces the interactions of PEV with parking lots. • The intelligent battery energy management improves the energy efficiency. • The intelligent battery energy management predicts the road load demand for vehicles. - Abstract: Plug-in Electric Vehicles (PEVs) provide new opportunities to reduce fuel consumption and exhaust emission. PEVs need to draw and store energy from an electrical grid to supply propulsive energy for the vehicle. As a result, it is important to know when PEVs batteries are available for charging and discharging. Furthermore, battery energy management and control is imperative for PEVs as the vehicle operation and even the safety of passengers depend on the battery system. Thus, scheduling the grid power electricity with parking lots would be needed for efficient charging and discharging of PEV batteries. This paper aims to propose a new intelligent battery energy management and control scheduling service charging that utilize Cloud computing networks. The proposed intelligent vehicle-to-grid scheduling service offers the computational scalability required to make decisions necessary to allow PEVs battery energy management systems to operate efficiently when the number of PEVs and charging devices are large. Experimental analyses of the proposed scheduling service as compared to a traditional scheduling service are conducted through simulations. The results show that the proposed intelligent battery energy management scheduling service substantially reduces the required number of interactions of PEV with parking lots and grid as well as predicting the load demand calculated in advance with regards to their limitations. Also it shows that the intelligent scheduling service charging using Cloud computing network is more efficient than the traditional scheduling service network for battery energy management and control

DEMAID - A DESIGN MANAGER'S AID FOR INTELLIGENT DECOMPOSITION (SGI IRIS VERSION)

Science.gov (United States)

Rogers, J. L.

1994-01-01

Many engineering systems are large and multi-disciplinary. Before the design of new complex systems such as large space platforms can begin, the possible interactions among subsystems and their parts must be determined. Once this is completed the proposed system can be decomposed to identify its hierarchical structure. DeMAID (A Design Manager's Aid for Intelligent Decomposition) is a knowledge-based system for ordering the sequence of modules and identifying a possible multilevel structure for the design problem. DeMAID displays the modules in an N x N matrix format (called a design structure matrix) where a module is any process that requires input and generates an output. (Modules which generate an output but do not require an input, such as an initialization process, are also acceptable.) Although DeMAID requires an investment of time to generate and refine the list of modules for input, it could save a considerable amount of money and time in the total design process, particularly in new design problems where the ordering of the modules has not been defined. The decomposition of a complex design system into subsystems requires the judgement of the design manager. DeMAID reorders and groups the modules based on the links (interactions) among the modules, helping the design manager make decomposition decisions early in the design cycle. The modules are grouped into circuits (the subsystems) and displayed in an N x N matrix format. Feedback links, which indicate an iterative process, are minimized and only occur within a subsystem. Since there are no feedback links among the circuits, the circuits can be displayed in a multilevel format. Thus, a large amount of information is reduced to one or two displays which are stored for later retrieval and modification. The design manager and leaders of the design teams then have a visual display of the design problem and the intricate interactions among the different modules. The design manager could save a substantial

A Multidisciplinary Model for Development of Intelligent Computer-Assisted Instruction.

Science.gov (United States)

Park, Ok-choon; Seidel, Robert J.

1989-01-01

Proposes a schematic multidisciplinary model to help developers of intelligent computer-assisted instruction (ICAI) identify the types of required expertise and integrate them into a system. Highlights include domain types and expertise; knowledge acquisition; task analysis; knowledge representation; student modeling; diagnosis of learning needs;…

Artificial Intelligence Research at the Artificial Intelligence Laboratory, Massachusetts Institute of Technology

OpenAIRE

Winston, Patrick H.

1983-01-01

The primary goal of the Artificial Intelligence Laboratory is to understand how computers can be made to exhibit intelligence. Two corollary goals are to make computers more useful and to understand certain aspects of human intelligence. Current research includes work on computer robotics and vision, expert systems, learning and commonsense reasoning, natural language understanding, and computer architecture.

Prospective EFL Teachers' Emotional Intelligence and Tablet Computer Use and Literacy

Science.gov (United States)

Herguner, Sinem

2017-01-01

The aim of this study was to investigate whether there is a relationship between tablet computer use and literacy, and emotional intelligence of prospective English language teachers. The study used a survey approach. In the study, "Prospective Teachers Tablet Computer Use and Literacy Scale" and an adapted and translated version into…

Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

Science.gov (United States)

Moore, Gwendolyn B.; And Others

The report describes three advanced technologies--robotics, artificial intelligence, and computer simulation--and identifies the ways in which they might contribute to special education. A hybrid methodology was employed to identify existing technology and forecast future needs. Following this framework, each of the technologies is defined,…

Analysis of Computer-Aided and Artificial Intelligence Technologies and Solutions in Service Industries in Russia

OpenAIRE

Rezanov, Vladislav

2013-01-01

The primary objective of this research study was to investigate the relationship between Computer-Aided and Artificial Intelligence Technologies and customer satisfaction in the context of businesses in Russia. The research focuses on methods of Artificial Intelligence technology application in business and its effect on customer satisfaction. The researcher introduces Artificial Intelligence and studies the forecasting approaches in relation to business operations. The rese...

Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

Science.gov (United States)

1987-10-01

include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

The Relationship between Emotional Intelligence and Attitudes toward Computer-Based Instruction of Postsecondary Hospitality Students

Science.gov (United States)

Behnke, Carl; Greenan, James P.

2011-01-01

This study examined the relationship between postsecondary students' emotional-social intelligence and attitudes toward computer-based instructional materials. Research indicated that emotions and emotional intelligence directly impact motivation, while instructional design has been shown to impact student attitudes and subsequent engagement with…

Symmetric Tensor Decomposition

DEFF Research Database (Denmark)

Brachat, Jerome; Comon, Pierre; Mourrain, Bernard

2010-01-01

We present an algorithm for decomposing a symmetric tensor, of dimension n and order d, as a sum of rank-1 symmetric tensors, extending the algorithm of Sylvester devised in 1886 for binary forms. We recall the correspondence between the decomposition of a homogeneous polynomial in n variables...... of polynomial equations of small degree in non-generic cases. We propose a new algorithm for symmetric tensor decomposition, based on this characterization and on linear algebra computations with Hankel matrices. The impact of this contribution is two-fold. First it permits an efficient computation...... of the decomposition of any tensor of sub-generic rank, as opposed to widely used iterative algorithms with unproved global convergence (e.g. Alternate Least Squares or gradient descents). Second, it gives tools for understanding uniqueness conditions and for detecting the rank....

Computational Intelligence in Early Diabetes Diagnosis: A Review

Science.gov (United States)

Shankaracharya; Odedra, Devang; Samanta, Subir; Vidyarthi, Ambarish S.

2010-01-01

The development of an effective diabetes diagnosis system by taking advantage of computational intelligence is regarded as a primary goal nowadays. Many approaches based on artificial network and machine learning algorithms have been developed and tested against diabetes datasets, which were mostly related to individuals of Pima Indian origin. Yet, despite high accuracies of up to 99% in predicting the correct diabetes diagnosis, none of these approaches have reached clinical application so far. One reason for this failure may be that diabetologists or clinical investigators are sparsely informed about, or trained in the use of, computational diagnosis tools. Therefore, this article aims at sketching out an outline of the wide range of options, recent developments, and potentials in machine learning algorithms as diabetes diagnosis tools. One focus is on supervised and unsupervised methods, which have made significant impacts in the detection and diagnosis of diabetes at primary and advanced stages. Particular attention is paid to algorithms that show promise in improving diabetes diagnosis. A key advance has been the development of a more in-depth understanding and theoretical analysis of critical issues related to algorithmic construction and learning theory. These include trade-offs for maximizing generalization performance, use of physically realistic constraints, and incorporation of prior knowledge and uncertainty. The review presents and explains the most accurate algorithms, and discusses advantages and pitfalls of methodologies. This should provide a good resource for researchers from all backgrounds interested in computational intelligence-based diabetes diagnosis methods, and allows them to extend their knowledge into this kind of research. PMID:21713313

Computational intelligence in early diabetes diagnosis: a review.

Science.gov (United States)

Shankaracharya; Odedra, Devang; Samanta, Subir; Vidyarthi, Ambarish S

2010-01-01

The development of an effective diabetes diagnosis system by taking advantage of computational intelligence is regarded as a primary goal nowadays. Many approaches based on artificial network and machine learning algorithms have been developed and tested against diabetes datasets, which were mostly related to individuals of Pima Indian origin. Yet, despite high accuracies of up to 99% in predicting the correct diabetes diagnosis, none of these approaches have reached clinical application so far. One reason for this failure may be that diabetologists or clinical investigators are sparsely informed about, or trained in the use of, computational diagnosis tools. Therefore, this article aims at sketching out an outline of the wide range of options, recent developments, and potentials in machine learning algorithms as diabetes diagnosis tools. One focus is on supervised and unsupervised methods, which have made significant impacts in the detection and diagnosis of diabetes at primary and advanced stages. Particular attention is paid to algorithms that show promise in improving diabetes diagnosis. A key advance has been the development of a more in-depth understanding and theoretical analysis of critical issues related to algorithmic construction and learning theory. These include trade-offs for maximizing generalization performance, use of physically realistic constraints, and incorporation of prior knowledge and uncertainty. The review presents and explains the most accurate algorithms, and discusses advantages and pitfalls of methodologies. This should provide a good resource for researchers from all backgrounds interested in computational intelligence-based diabetes diagnosis methods, and allows them to extend their knowledge into this kind of research.

Investigating AI with Basic and Logo. Teaching Your Computer to Be Intelligent.

Science.gov (United States)

Mandell, Alan; Lucking, Robert

1988-01-01

Discusses artificial intelligence, its definitions, and potential applications. Provides listings of Logo and BASIC versions for programs along with REM statements needed to make modifications for use with Apple computers. (RT)

Artificial intelligence program in a computer application supporting reactor operations

International Nuclear Information System (INIS)

Stratton, R.C.; Town, G.G.

1985-01-01

Improving nuclear reactor power plant operability is an ever-present concern for the nuclear industry. The definition of plant operability involves a complex interaction of the ideas of reliability, safety, and efficiency. This paper presents observations concerning the issues involved and the benefits derived from the implementation of a computer application which combines traditional computer applications with artificial intelligence (AI) methodologies. A system, the Component Configuration Control System (CCCS), is being installed to support nuclear reactor operations at the Experimental Breeder Reactor II

MAINS: MULTI-AGENT INTELLIGENT SERVICE ARCHITECTURE FOR CLOUD COMPUTING

Directory of Open Access Journals (Sweden)

T. Joshva Devadas

2014-04-01

Full Text Available Computing has been transformed to a model having commoditized services. These services are modeled similar to the utility services water and electricity. The Internet has been stunningly successful over the course of past three decades in supporting multitude of distributed applications and a wide variety of network technologies. However, its popularity has become the biggest impediment to its further growth with the handheld devices mobile and laptops. Agents are intelligent software system that works on behalf of others. Agents are incorporated in many innovative applications in order to improve the performance of the system. Agent uses its possessed knowledge to react with the system and helps to improve the performance. Agents are introduced in the cloud computing is to minimize the response time when similar request is raised from an end user in the globe. In this paper, we have introduced a Multi Agent Intelligent system (MAINS prior to cloud service models and it was tested using sample dataset. Performance of the MAINS layer was analyzed in three aspects and the outcome of the analysis proves that MAINS Layer provides a flexible model to create cloud applications and deploying them in variety of applications.

2015 Chinese Intelligent Systems Conference

CERN Document Server

Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15

2016-01-01

This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

Wearable computer for mobile augmented-reality-based controlling of an intelligent robot

Science.gov (United States)

Turunen, Tuukka; Roening, Juha; Ahola, Sami; Pyssysalo, Tino

2000-10-01

An intelligent robot can be utilized to perform tasks that are either hazardous or unpleasant for humans. Such tasks include working in disaster areas or conditions that are, for example, too hot. An intelligent robot can work on its own to some extent, but in some cases the aid of humans will be needed. This requires means for controlling the robot from somewhere else, i.e. teleoperation. Mobile augmented reality can be utilized as a user interface to the environment, as it enhances the user's perception of the situation compared to other interfacing methods and allows the user to perform other tasks while controlling the intelligent robot. Augmented reality is a method that combines virtual objects into the user's perception of the real world. As computer technology evolves, it is possible to build very small devices that have sufficient capabilities for augmented reality applications. We have evaluated the existing wearable computers and mobile augmented reality systems to build a prototype of a future mobile terminal- the CyPhone. A wearable computer with sufficient system resources for applications, wireless communication media with sufficient throughput and enough interfaces for peripherals has been built at the University of Oulu. It is self-sustained in energy, with enough operating time for the applications to be useful, and uses accurate positioning systems.

An Intelligent Computer Assisted Language Learning System for Arabic Learners

Science.gov (United States)

Shaalan, Khaled F.

2005-01-01

This paper describes the development of an intelligent computer-assisted language learning (ICALL) system for learning Arabic. This system could be used for learning Arabic by students at primary schools or by learners of Arabic as a second or foreign language. It explores the use of Natural Language Processing (NLP) techniques for learning…

Artificial Intelligence In Computational Fluid Dynamics

Science.gov (United States)

Vogel, Alison Andrews

1991-01-01

Paper compares four first-generation artificial-intelligence (Al) software systems for computational fluid dynamics. Includes: Expert Cooling Fan Design System (EXFAN), PAN AIR Knowledge System (PAKS), grid-adaptation program MITOSIS, and Expert Zonal Grid Generation (EZGrid). Focuses on knowledge-based ("expert") software systems. Analyzes intended tasks, kinds of knowledge possessed, magnitude of effort required to codify knowledge, how quickly constructed, performances, and return on investment. On basis of comparison, concludes Al most successful when applied to well-formulated problems solved by classifying or selecting preenumerated solutions. In contrast, application of Al to poorly understood or poorly formulated problems generally results in long development time and large investment of effort, with no guarantee of success.

Short-term electric load forecasting using computational intelligence methods

OpenAIRE

Jurado, Sergio; Peralta, J.; Nebot, Àngela; Mugica, Francisco; Cortez, Paulo

2013-01-01

Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence techniques: Random Forest, Nonlinear Autoregressive Neural Networks, Evolutionary Support Vector Machines and Fuzzy Inductive Reasoning. The performance of the suggested methods is experimentally justified with several experiments carried out...

Highway traffic simulation on multi-processor computers

Energy Technology Data Exchange (ETDEWEB)

Hanebutte, U.R.; Doss, E.; Tentner, A.M.

1997-04-01

A computer model has been developed to simulate highway traffic for various degrees of automation with a high level of fidelity in regard to driver control and vehicle characteristics. The model simulates vehicle maneuvering in a multi-lane highway traffic system and allows for the use of Intelligent Transportation System (ITS) technologies such as an Automated Intelligent Cruise Control (AICC). The structure of the computer model facilitates the use of parallel computers for the highway traffic simulation, since domain decomposition techniques can be applied in a straight forward fashion. In this model, the highway system (i.e. a network of road links) is divided into multiple regions; each region is controlled by a separate link manager residing on an individual processor. A graphical user interface augments the computer model kv allowing for real-time interactive simulation control and interaction with each individual vehicle and road side infrastructure element on each link. Average speed and traffic volume data is collected at user-specified loop detector locations. Further, as a measure of safety the so- called Time To Collision (TTC) parameter is being recorded.

Soft computing in intelligent control

CERN Document Server

Jung, Jin-Woo; Kubota, Naoyuki

2014-01-01

Nowadays, people have tendency to be fond of smarter machines that are able to collect data, make learning, recognize things, infer meanings, communicate with human and perform behaviors. Thus, we have built advanced intelligent control affecting all around societies; automotive, rail, aerospace, defense, energy, healthcare, telecoms and consumer electronics, finance, urbanization. Consequently, users and consumers can take new experiences through the intelligent control systems. We can reshape the technology world and provide new opportunities for industry and business, by offering cost-effective, sustainable and innovative business models. We will have to know how to create our own digital life. The intelligent control systems enable people to make complex applications, to implement system integration and to meet society’s demand for safety and security. This book aims at presenting the research results and solutions of applications in relevance with intelligent control systems. We propose to researchers ...

Automating Commercial Video Game Development using Computational Intelligence

OpenAIRE

Tse G. Tan; Jason Teo; Patricia Anthony

2011-01-01

Problem statement: The retail sales of computer and video games have grown enormously during the last few years, not just in United States (US), but also all over the world. This is the reason a lot of game developers and academic researchers have focused on game related technologies, such as graphics, audio, physics and Artificial Intelligence (AI) with the goal of creating newer and more fun games. In recent years, there has been an increasing interest in game AI for pro...

Hidden Hearing Loss and Computational Models of the Auditory Pathway: Predicting Speech Intelligibility Decline

Science.gov (United States)

2016-11-28

Title: Hidden Hearing Loss and Computational Models of the Auditory Pathway: Predicting Speech Intelligibility Decline Christopher J. Smalt...representation of speech intelligibility in noise. The auditory-periphery model of Zilany et al. (JASA 2009,2014) is used to make predictions of...auditory nerve (AN) responses to speech stimuli under a variety of difficult listening conditions. The resulting cochlear neurogram, a spectrogram

Combination of artificial intelligence and procedural language programs in a computer application system supporting nuclear reactor operations

International Nuclear Information System (INIS)

Town, G.G.; Stratton, R.C.

1985-01-01

A computer application system is described which provides nuclear reactor power plant operators with an improved decision support system. This system combines traditional computer applications such as graphics display with artificial intelligence methodologies such as reasoning and diagnosis so as to improve plant operability. This paper discusses the issues, and a solution, involved with the system integration of applications developed using traditional and artificial intelligence languages

Combination of artificial intelligence and procedural language programs in a computer application system supporting nuclear reactor operations

International Nuclear Information System (INIS)

Stratton, R.C.; Town, G.G.

1985-01-01

A computer application system is described which provides nuclear reactor power plant operators with an improved decision support system. This system combines traditional computer applications such as graphics display with artifical intelligence methodologies such as reasoning and diagnosis so as to improve plant operability. This paper discusses the issues, and a solution, involved with the system integration of applications developed using traditional and artificial intelligence languages

Computer Aided Automatic Control - CAAC artificial intelligence block

Energy Technology Data Exchange (ETDEWEB)

Balate, J.; Chramcov, B.; Princ, M. [Brno Univ. of Technology (Czech Republic). Faculty of Technology in Zlin

2000-07-01

The aim of the plan to build up the system CAAC - Computer Aided Automatic Control is to create modular setup of partial computing programs including theory of automatic control, algorithms of programs for processing signals and programs of control algorithms. To approach its informative contents to students and professional public the CAAC system utilizes Internet services http in the form of WWW pages. The CAAC system is being processed at the Institute of Automation and Control Technique of the Faculty of Technology in Zlin of the Brno University of Technology and is determined particularly for pedagogic purposes. Recently also the methods of artificial intelligence have been included to the open CAAC system and that is comprised in this article. (orig.)

Investigation and computer modeling of radiation and thermal decomposition of polystyrene scintillators

Science.gov (United States)

Sakhno, Tamara V.; Pustovit, Sergey V.; Borisenko, Artem Y.; Senchishin, Vitaliy G.; Barashkov, Nikolay N.

2003-12-01

This paper is devoted to the investigation and computer modeling of radiation and thermal decomposition of luminescent polystyrene compositions. It has been shown, that the stability of the optical properties of luminescent polymer composition depends on its material structure. On the basis of quantum-chemical calculation has been obtained the possible products of PS gamma-radiolysis and the effect of formation of fragments with conjugated double bonds and products with quinone structure has been investigated.

Design of tailor-made chemical blend using a decomposition-based computer-aided approach

DEFF Research Database (Denmark)

Yunus, Nor Alafiza; Gernaey, Krist; Manan, Z.A.

2011-01-01

Computer aided techniques form an efficient approach to solve chemical product design problems such as the design of blended liquid products (chemical blending). In chemical blending, one tries to find the best candidate, which satisfies the product targets defined in terms of desired product...... methodology for blended liquid products that identifies a set of feasible chemical blends. The blend design problem is formulated as a Mixed Integer Nonlinear Programming (MINLP) model where the objective is to find the optimal blended gasoline or diesel product subject to types of chemicals...... and their compositions and a set of desired target properties of the blended product as design constraints. This blend design problem is solved using a decomposition approach, which eliminates infeasible and/or redundant candidates gradually through a hierarchy of (property) model based constraints. This decomposition...

New Research Perspectives in the Emerging Field of Computational Intelligence to Economic Modeling

Directory of Open Access Journals (Sweden)

Vasile MAZILESCU

2009-01-01

Full Text Available Computational Intelligence (CI is a new development paradigm of intelligentsystems which has resulted from a synergy between fuzzy sets, artificial neuralnetworks, evolutionary computation, machine learning, etc., broadeningcomputer science, physics, economics, engineering, mathematics, statistics. It isimperative to know why these tools can be potentially relevant and effective toeconomic and financial modeling. This paper presents, after a synergic newparadigm of intelligent systems, as a practical case study the fuzzy and temporalproperties of knowledge formalism embedded in an Intelligent Control System(ICS, based on FT-algorithm. We are not dealing high with level reasoningmethods, because we think that real-time problems can only be solved by ratherlow-level reasoning. Most of the overall run-time of fuzzy expert systems isused in the match phase. To achieve a fast reasoning the number of fuzzy setoperations must be reduced. For this, we use a fuzzy compiled structure ofknowledge, like Rete, because it is required for real-time responses. Solving thematch-time predictability problem would allow us to built much more powerfulreasoning techniques.

Machine learning based Intelligent cognitive network using fog computing

Science.gov (United States)

Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

2017-05-01

In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

Second International Joint Conference on Computational Intelligence (IJCCI 2010)

CERN Document Server

Correia, António; Rosa, Agostinho; Filipe, Joaquim; Computational Intelligence

2012-01-01

The present book includes a set of selected extended papers from the second International Joint Conference on Computational Intelligence (IJCCI 2010), held in Valencia, Spain, from 24 to 26 October 2010. The conference was composed by three co-located conferences:  The International Conference on Fuzzy Computation (ICFC), the International Conference on Evolutionary Computation (ICEC), and the International Conference on Neural Computation (ICNC). Recent progresses in scientific developments and applications in these three areas are reported in this book. IJCCI received 236 submissions, from 49 countries, in all continents. After a double blind paper review performed by the Program Committee, only 30 submissions were accepted as full papers and thus selected for oral presentation, leading to a full paper acceptance ratio of 13%. Additional papers were accepted as short papers and posters. A further selection was made after the Conference, based also on the assessment of presentation quality and audience inte...

Progress and Challenge of Artificial Intelligence

Institute of Scientific and Technical Information of China (English)

Zhong-Zhi Shi; Nan-Ning Zheng

2006-01-01

Artificial Intelligence (AI) is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

Artificial intelligence and other innovative computer applications in the nuclear industry

International Nuclear Information System (INIS)

Majumdar, M.C.; Majumdar, D.; Sackett, J.I.

1987-01-01

This book reviews the applications of artificial intelligence and computers in the nuclear industry and chemical plants. The topics discussed are: Robots applications and reliability in maintenance of nuclear power plants; Advanced information technology and expert systems; Knowledge base alarm systems; Emergency planning and response of accidents; and reactor safety assessment

Foundations of Intelligent Systems : Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering

CERN Document Server

Li, Tianrui

2012-01-01

Proceedings of The Sixth International Conference on Intelligent System and Knowledge Engineering presents selected papers from the conference ISKE 2011, held December 15-17 in Shanghai, China. This proceedings doesn’t only examine original research and approaches in the broad areas of intelligent systems and knowledge engineering, but also present new methodologies and practices in intelligent computing paradigms. The book introduces the current scientific and technical advances in the fields of artificial intelligence, machine learning, pattern recognition, data mining, information retrieval, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, natural-language processing, etc. Furthermore, new computing methodologies are presented, including cloud computing, service computing and pervasive computing with traditional intelligent methods. The proceedings will be beneficial for both researchers and practitioners who want to utilize intelligent methods in their specific resea...

Using artificial intelligence to control fluid flow computations

Science.gov (United States)

Gelsey, Andrew

1992-01-01

Computational simulation is an essential tool for the prediction of fluid flow. Many powerful simulation programs exist today. However, using these programs to reliably analyze fluid flow and other physical situations requires considerable human effort and expertise to set up a simulation, determine whether the output makes sense, and repeatedly run the simulation with different inputs until a satisfactory result is achieved. Automating this process is not only of considerable practical importance but will also significantly advance basic artificial intelligence (AI) research in reasoning about the physical world.

Intelligent Aggregation Based on Content Routing Scheme for Cloud Computing

Directory of Open Access Journals (Sweden)

Jiachen Xu

2017-10-01

Full Text Available Cloud computing has emerged as today’s most exciting computing paradigm for providing services using a shared framework, which opens a new door for solving the problems of the explosive growth of digital resource demands and their corresponding convenience. With the exponential growth of the number of data types and data size in so-called big data work, the backbone network is under great pressure due to its transmission capacity, which is lower than the growth of the data size and would seriously hinder the development of the network without an effective approach to solve this problem. In this paper, an Intelligent Aggregation based on a Content Routing (IACR scheme for cloud computing, which could reduce the amount of data in the network effectively and play a basic supporting role in the development of cloud computing, is first put forward. All in all, the main innovations in this paper are: (1 A framework for intelligent aggregation based on content routing is proposed, which can support aggregation based content routing; (2 The proposed IACR scheme could effectively route the high aggregation ratio data to the data center through the same routing path so as to effectively reduce the amount of data that the network transmits. The theoretical analyses experiments and results show that, compared with the previous original routing scheme, the IACR scheme can balance the load of the whole network, reduce the amount of data transmitted in the network by 41.8%, and reduce the transmission time by 31.6% in the same network with a more balanced network load.

A survey on computational intelligence approaches for predictive modeling in prostate cancer

OpenAIRE

Cosma, G; Brown, D; Archer, M; Khan, M; Pockley, AG

2017-01-01

Predictive modeling in medicine involves the development of computational models which are capable of analysing large amounts of data in order to predict healthcare outcomes for individual patients. Computational intelligence approaches are suitable when the data to be modelled are too complex forconventional statistical techniques to process quickly and eciently. These advanced approaches are based on mathematical models that have been especially developed for dealing with the uncertainty an...

Finite-element-model updating using computational intelligence techniques applications to structural dynamics

CERN Document Server

Marwala, Tshilidzi

2010-01-01

Finite element models (FEMs) are widely used to understand the dynamic behaviour of various systems. FEM updating allows FEMs to be tuned better to reflect measured data and may be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. Finite Element Model Updating Using Computational Intelligence Techniques applies both strategies to the field of structural mechanics, an area vital for aerospace, civil and mechanical engineering. Vibration data is used for the updating process. Following an introduction a number of computational intelligence techniques to facilitate the updating process are proposed; they include: • multi-layer perceptron neural networks for real-time FEM updating; • particle swarm and genetic-algorithm-based optimization methods to accommodate the demands of global versus local optimization models; • simulated annealing to put the methodologies into a sound statistical basis; and • response surface methods and expectation m...

International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems

CERN Document Server

Bhaskar, M; Panigrahi, Bijaya; Das, Swagatam

2016-01-01

The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES -2015) held at Velammal Engineering College (VEC), Chennai, India during 22 – 23 April 2015. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of Communication, Computing and Power Technologies.

Note on Symplectic SVD-Like Decomposition

Directory of Open Access Journals (Sweden)

AGOUJIL Said

2016-02-01

Full Text Available The aim of this study was to introduce a constructive method to compute a symplectic singular value decomposition (SVD-like decomposition of a 2n-by-m rectangular real matrix A, based on symplectic refectors.This approach used a canonical Schur form of skew-symmetric matrix and it allowed us to compute eigenvalues for the structured matrices as Hamiltonian matrix JAA^T.

Practical Applications of Intelligent Systems : Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering

CERN Document Server

Li, Tianrui

2012-01-01

Proceedings of The Sixth International Conference on Intelligent System and Knowledge Engineering presents selected papers from the conference ISKE 2011, held December 15-17 in Shanghai, China. This proceedings doesn’t only examine original research and approaches in the broad areas of intelligent systems and knowledge engineering, but also present new methodologies and practices in intelligent computing paradigms. The book introduces the current scientific and technical advances in the fields of artificial intelligence, machine learning, pattern recognition, data mining, information retrieval, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, natural-language processing, etc. Furthermore, new computing methodologies are presented, including cloud computing, service computing and pervasive computing with traditional intelligent methods. The proceedings will be beneficial for both researchers and practitioners who want to utilize intelligent methods in their specific res...

Seventh International Conference on Intelligent Systems and Knowledge Engineering - Foundations and Applications of Intelligent Systems

CERN Document Server

Li, Tianrui; Li, Hongbo

2014-01-01

These proceedings present technical papers selected from the 2012 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2012), held on December 15-17 in Beijing. The aim of this conference is to bring together experts from different fields of expertise to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new findings and perspectives on future developments. The proceedings introduce current scientific and technical advances in the fields of artificial intelligence, machine learning, pattern recognition, data mining, knowledge engineering, information retrieval, information theory, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, and natural-language processing, etc. Furthermore they include papers on new intelligent computing paradigms, which combine new computing methodologies, e.g., cloud computing, service computing and pervasive computing with traditional intelligent methods. By presenting new method...

Condition Monitoring Using Computational Intelligence Methods Applications in Mechanical and Electrical Systems

CERN Document Server

Marwala, Tshilidzi

2012-01-01

Condition monitoring uses the observed operating characteristics of a machine or structure to diagnose trends in the signal being monitored and to predict the need for maintenance before a breakdown occurs. This reduces the risk, inherent in a fixed maintenance schedule, of performing maintenance needlessly early or of having a machine fail before maintenance is due either of which can be expensive with the latter also posing a risk of serious accident especially in systems like aeroengines in which a catastrophic failure would put lives at risk. The technique also measures responses from the whole of the system under observation so it can detect the effects of faults which might be hidden deep within a system, hidden from traditional methods of inspection. Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, m...

Computational intelligence for technology enhanced learning

Energy Technology Data Exchange (ETDEWEB)

Xhafa, Fatos [Polytechnic Univ. of Catalonia, Barcelona (Spain). Dept. of Languages and Informatics Systems; Caballe, Santi; Daradoumis, Thanasis [Open Univ. of Catalonia, Barcelona (Spain). Dept. of Computer Sciences Multimedia and Telecommunications; Abraham, Ajith [Machine Intelligence Research Labs (MIR Labs), Auburn, WA (United States). Scientific Network for Innovation and Research Excellence; Juan Perez, Angel Alejandro (eds.) [Open Univ. of Catalonia, Barcelona (Spain). Dept. of Information Sciences

2010-07-01

E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners' performance in distributed learning environments. The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others. Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity. (orig.)

International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems

CERN Document Server

Vijayakumar, K; Panigrahi, Bijaya; Das, Swagatam

2017-01-01

The volume is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computation in Engineering Systems (ICAIECES 2016) held at SRM University, Chennai, Tamilnadu, India. This conference is an international forum for industry professionals and researchers to deliberate and state their research findings, discuss the latest advancements and explore the future directions in the emerging areas of engineering and technology. The book presents original work and novel ideas, information, techniques and applications in the field of communication, computing and power technologies.

Intelligent transportation systems data compression using wavelet decomposition technique.

Science.gov (United States)

2009-12-01

Intelligent Transportation Systems (ITS) generates massive amounts of traffic data, which posts : challenges for data storage, transmission and retrieval. Data compression and reconstruction technique plays an : important role in ITS data procession....

Artificial Intelligence Support for Computational Chemistry

Science.gov (United States)

Duch, Wlodzislaw

Possible forms of artificial intelligence (AI) support for quantum chemistry are discussed. Questions addressed include: what kind of support is desirable, what kind of support is feasible, what can we expect in the coming years. Advantages and disadvantages of current AI techniques are presented and it is argued that at present the memory-based systems are the most effective for large scale applications. Such systems may be used to predict the accuracy of calculations and to select the least expensive methods and basis sets belonging to the same accuracy class. Advantages of the Feature Space Mapping as an improvement on the memory based systems are outlined and some results obtained in classification problems given. Relevance of such classification systems to computational chemistry is illustrated with two examples showing similarity of results obtained by different methods that take electron correlation into account.

Artificial Intelligence in Civil Engineering

Directory of Open Access Journals (Sweden)

Pengzhen Lu

2012-01-01

Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

Artificial Intelligence in Civil Engineering

OpenAIRE

Lu, Pengzhen; Chen, Shengyong; Zheng, Yujun

2012-01-01

Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applicati...

Some Steps towards Intelligent Computer Tutoring Systems.

Science.gov (United States)

Tchogovadze, Gotcha G.

1986-01-01

Describes one way of structuring an intelligent tutoring system (ITS) in light of developments in artificial intelligence. A specialized intelligent operating system (SIOS) is proposed for software for a network of microcomputers, and it is postulated that a general learning system must be used as a basic framework for the SIOS. (Author/LRW)

Errors and Intelligence in Computer-Assisted Language Learning: Parsers and Pedagogues. Routledge Studies in Computer Assisted Language Learning

Science.gov (United States)

Heift, Trude; Schulze, Mathias

2012-01-01

This book provides the first comprehensive overview of theoretical issues, historical developments and current trends in ICALL (Intelligent Computer-Assisted Language Learning). It assumes a basic familiarity with Second Language Acquisition (SLA) theory and teaching, CALL and linguistics. It is of interest to upper undergraduate and/or graduate…

Mobile Imaging and Computing for Intelligent Structural Damage Inspection

Directory of Open Access Journals (Sweden)

ZhiQiang Chen

2014-01-01

Full Text Available Optical imaging is a commonly used technique in civil engineering for aiding the archival of damage scenes and more recently for image analysis-based damage quantification. However, the limitations are evident when applying optical imaging in the field. The most significant one is the lacking of computing and processing capability in the real time. The advancement of mobile imaging and computing technologies provides a promising opportunity to change this norm. This paper first provides a timely introduction of the state-of-the-art mobile imaging and computing technologies for the purpose of engineering application development. Further we propose a mobile imaging and computing (MIC framework for conducting intelligent condition assessment for constructed objects, which features in situ imaging and real-time damage analysis. This framework synthesizes advanced mobile technologies with three innovative features: (i context-enabled image collection, (ii interactive image preprocessing, and (iii real-time image analysis and analytics. Through performance evaluation and field experiments, this paper demonstrates the feasibility and efficiency of the proposed framework.

Smart information systems computational intelligence for real-life applications

CERN Document Server

Hopfgartner, Frank

2015-01-01

This must-read text/reference presents an overview of smart information systems for both the private and public sector, highlighting the research questions that can be studied by applying computational intelligence. The book demonstrates how to transform raw data into effective smart information services, covering the challenges and potential of this approach. Each chapter describes the algorithms, tools, measures and evaluations used to answer important questions. This is then further illustrated by a diverse selection of case studies reflecting genuine problems faced by SMEs, multinational

Algorithms in ambient intelligence

NARCIS (Netherlands)

Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Verhaegh, W.F.J.; Aarts, E.H.L.; Korst, J.H.M.

2004-01-01

In this chapter, we discuss the new paradigm for user-centered computing known as ambient intelligence and its relation with methods and techniques from the field of computational intelligence, including problem solving, machine learning, and expert systems.

MANAGEMENT OPTIMISATION OF MASS CUSTOMISATION MANUFACTURING USING COMPUTATIONAL INTELLIGENCE

Directory of Open Access Journals (Sweden)

Louwrens Butler

2018-05-01

Full Text Available Computational intelligence paradigms can be used for advanced manufacturing system optimisation. A static simulation model of an advanced manufacturing system was developed in order to simulate a manufacturing system. The purpose of this advanced manufacturing system was to mass-produce a customisable product range at a competitive cost. The aim of this study was to determine whether this new algorithm could produce a better performance than traditional optimisation methods. The algorithm produced a lower cost plan than that for a simulated annealing algorithm, and had a lower impact on the workforce.

Advanced and intelligent computations in diagnosis and control

CERN Document Server

2016-01-01

This book is devoted to the demands of research and industrial centers for diagnostics, monitoring and decision making systems that result from the increasing complexity of automation and systems, the need to ensure the highest level of reliability and safety, and continuing research and the development of innovative approaches to fault diagnosis. The contributions combine domains of engineering knowledge for diagnosis, including detection, isolation, localization, identification, reconfiguration and fault-tolerant control. The book is divided into six parts:  (I) Fault Detection and Isolation; (II) Estimation and Identification; (III) Robust and Fault Tolerant Control; (IV) Industrial and Medical Diagnostics; (V) Artificial Intelligence; (VI) Expert and Computer Systems.

Implicit upwind schemes for computational fluid dynamics. Solution by domain decomposition

International Nuclear Information System (INIS)

Clerc, S.

1998-01-01

In this work, the numerical simulation of fluid dynamics equations is addressed. Implicit upwind schemes of finite volume type are used for this purpose. The first part of the dissertation deals with the improvement of the computational precision in unfavourable situations. A non-conservative treatment of some source terms is studied in order to correct some shortcomings of the usual operator-splitting method. Besides, finite volume schemes based on Godunov's approach are unsuited to compute low Mach number flows. A modification of the up-winding by preconditioning is introduced to correct this defect. The second part deals with the solution of steady-state problems arising from an implicit discretization of the equations. A well-posed linearized boundary value problem is formulated. We prove the convergence of a domain decomposition algorithm of Schwartz type for this problem. This algorithm is implemented either directly, or in a Schur complement framework. Finally, another approach is proposed, which consists in decomposing the non-linear steady state problem. (author)

Domain decomposition parallel computing for transient two-phase flow of nuclear reactors

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae Ryong; Yoon, Han Young [KAERI, Daejeon (Korea, Republic of); Choi, Hyoung Gwon [Seoul National University, Seoul (Korea, Republic of)

2016-05-15

KAERI (Korea Atomic Energy Research Institute) has been developing a multi-dimensional two-phase flow code named CUPID for multi-physics and multi-scale thermal hydraulics analysis of Light water reactors (LWRs). The CUPID code has been validated against a set of conceptual problems and experimental data. In this work, the CUPID code has been parallelized based on the domain decomposition method with Message passing interface (MPI) library. For domain decomposition, the CUPID code provides both manual and automatic methods with METIS library. For the effective memory management, the Compressed sparse row (CSR) format is adopted, which is one of the methods to represent the sparse asymmetric matrix. CSR format saves only non-zero value and its position (row and column). By performing the verification for the fundamental problem set, the parallelization of the CUPID has been successfully confirmed. Since the scalability of a parallel simulation is generally known to be better for fine mesh system, three different scales of mesh system are considered: 40000 meshes for coarse mesh system, 320000 meshes for mid-size mesh system, and 2560000 meshes for fine mesh system. In the given geometry, both single- and two-phase calculations were conducted. In addition, two types of preconditioners for a matrix solver were compared: Diagonal and incomplete LU preconditioner. In terms of enhancement of the parallel performance, the OpenMP and MPI hybrid parallel computing for a pressure solver was examined. It is revealed that the scalability of hybrid calculation was enhanced for the multi-core parallel computation.

Intelligent interaction based on holographic personalized portal

Directory of Open Access Journals (Sweden)

Yadong Huang

2017-06-01

Full Text Available Purpose – The purpose of this paper is to study the architecture of holographic personalized portal, user modeling, commodity modeling and intelligent interaction. Design/methodology/approach – In this paper, the authors propose crowd-science industrial ecological system based on holographic personalized portal and its interaction. The holographic personality portal is based on holographic enterprises, commodities and consumers, and the personalized portal consists of accurate ontology, reliable supply, intelligent demand and smart cyberspace. Findings – The personalized portal can realize the information acquisition, characteristic analysis and holographic presentation. Then, the intelligent interaction, e.g. demand decomposition, personalized search, personalized presentation and demand prediction, will be implemented within the personalized portal. Originality/value – The authors believe that their work on intelligent interaction based on holographic personalized portal, which has been first proposed in this paper, is innovation focusing on the interaction between intelligence and convenience.

The Security Challenges in the IoT Enabled Cyber-Physical Systems and Opportunities for Evolutionary Computing & Other Computational Intelligence

OpenAIRE

He, H.; Maple, C.; Watson, T.; Tiwari, A.; Mehnen, J.; Jin, Y.; Gabrys, Bogdan

2016-01-01

Internet of Things (IoT) has given rise to the fourth industrial revolution (Industrie 4.0), and it brings great benefits by connecting people, processes and data. However, cybersecurity has become a critical challenge in the IoT enabled cyber physical systems, from connected supply chain, Big Data produced by huge amount of IoT devices, to industry control systems. Evolutionary computation combining with other computational intelligence will play an important role for cybersecurity, such as ...

A methodology for the design of experiments in computational intelligence with multiple regression models.

Science.gov (United States)

Fernandez-Lozano, Carlos; Gestal, Marcos; Munteanu, Cristian R; Dorado, Julian; Pazos, Alejandro

2016-01-01

The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.

A methodology for the design of experiments in computational intelligence with multiple regression models

Directory of Open Access Journals (Sweden)

Carlos Fernandez-Lozano

2016-12-01

Full Text Available The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.

Intelligent Computer-Assisted Instruction: A Review and Assessment of ICAI Research and Its Potential for Education.

Science.gov (United States)

Dede, Christopher J.; And Others

The first of five sections in this report places intelligent computer-assisted instruction (ICAI) in its historical context through discussions of traditional computer-assisted instruction (CAI) linear and branching programs; TICCIT and PLATO IV, two CAI demonstration projects funded by the National Science Foundation; generative programs, the…

Land Cover Classification from Multispectral Data Using Computational Intelligence Tools: A Comparative Study

Directory of Open Access Journals (Sweden)

André Mora

2017-11-01

Full Text Available This article discusses how computational intelligence techniques are applied to fuse spectral images into a higher level image of land cover distribution for remote sensing, specifically for satellite image classification. We compare a fuzzy-inference method with two other computational intelligence methods, decision trees and neural networks, using a case study of land cover classification from satellite images. Further, an unsupervised approach based on k-means clustering has been also taken into consideration for comparison. The fuzzy-inference method includes training the classifier with a fuzzy-fusion technique and then performing land cover classification using reinforcement aggregation operators. To assess the robustness of the four methods, a comparative study including three years of land cover maps for the district of Mandimba, Niassa province, Mozambique, was undertaken. Our results show that the fuzzy-fusion method performs similarly to decision trees, achieving reliable classifications; neural networks suffer from overfitting; while k-means clustering constitutes a promising technique to identify land cover types from unknown areas.

Computational Intelligence-Assisted Understanding of Nature-Inspired Superhydrophobic Behavior.

Science.gov (United States)

Zhang, Xia; Ding, Bei; Cheng, Ran; Dixon, Sebastian C; Lu, Yao

2018-01-01

In recent years, state-of-the-art computational modeling of physical and chemical systems has shown itself to be an invaluable resource in the prediction of the properties and behavior of functional materials. However, construction of a useful computational model for novel systems in both academic and industrial contexts often requires a great depth of physicochemical theory and/or a wealth of empirical data, and a shortage in the availability of either frustrates the modeling process. In this work, computational intelligence is instead used, including artificial neural networks and evolutionary computation, to enhance our understanding of nature-inspired superhydrophobic behavior. The relationships between experimental parameters (water droplet volume, weight percentage of nanoparticles used in the synthesis of the polymer composite, and distance separating the superhydrophobic surface and the pendant water droplet in adhesive force measurements) and multiple objectives (water droplet contact angle, sliding angle, and adhesive force) are built and weighted. The obtained optimal parameters are consistent with the experimental observations. This new approach to materials modeling has great potential to be applied more generally to aid design, fabrication, and optimization for myriad functional materials.

Applications of computational intelligence in biomedical technology

CERN Document Server

Majernik, Jaroslav; Pancerz, Krzysztof; Zaitseva, Elena

2016-01-01

This book presents latest results and selected applications of Computational Intelligence in Biomedical Technologies. Most of contributions deal with problems of Biomedical and Medical Informatics, ranging from theoretical considerations to practical applications. Various aspects of development methods and algorithms in Biomedical and Medical Informatics as well as Algorithms for medical image processing, modeling methods are discussed. Individual contributions also cover medical decision making support, estimation of risks of treatments, reliability of medical systems, problems of practical clinical applications and many other topics  This book is intended for scientists interested in problems of Biomedical Technologies, for researchers and academic staff, for all dealing with Biomedical and Medical Informatics, as well as PhD students. Useful information is offered also to IT companies, developers of equipment and/or software for medicine and medical professionals.  .

Research on application of intelligent computation based LUCC model in urbanization process

Science.gov (United States)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents

Randomized interpolative decomposition of separated representations

Science.gov (United States)

Biagioni, David J.; Beylkin, Daniel; Beylkin, Gregory

2015-01-01

We introduce an algorithm to compute tensor interpolative decomposition (dubbed CTD-ID) for the reduction of the separation rank of Canonical Tensor Decompositions (CTDs). Tensor ID selects, for a user-defined accuracy ɛ, a near optimal subset of terms of a CTD to represent the remaining terms via a linear combination of the selected terms. CTD-ID can be used as an alternative to or in combination with the Alternating Least Squares (ALS) algorithm. We present examples of its use within a convergent iteration to compute inverse operators in high dimensions. We also briefly discuss the spectral norm as a computational alternative to the Frobenius norm in estimating approximation errors of tensor ID. We reduce the problem of finding tensor IDs to that of constructing interpolative decompositions of certain matrices. These matrices are generated via randomized projection of the terms of the given tensor. We provide cost estimates and several examples of the new approach to the reduction of separation rank.

Hybrid-augmented intelligence:collaboration and cognition

Institute of Scientific and Technical Information of China (English)

Nan-ning ZHENG; Zi-yi LIU; Peng-ju REN; Yong-qiang MA; Shi-tao CHEN; Si-yu YU; Jian-ru XUE

2017-01-01

The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models:one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

Advances in Intelligent Modelling and Simulation Artificial Intelligence-Based Models and Techniques in Scalable Computing

CERN Document Server

Khan, Samee; Burczy´nski, Tadeusz

2012-01-01

One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under  various  types of users with evolving relationships fraught with  uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.   This book presents new ideas, theories, models...

Foreword 3rd International Conference on Affective Computing and Intelligent Interaction - ACII 2009

NARCIS (Netherlands)

Cohn, Jeffrey; Cohn, Jeffrey; Nijholt, Antinus; Pantic, Maja

2009-01-01

It is a pleasure and an honor to have organized the Third International Conference on Affective Computing and Intelligent Interaction (ACII). The conference will be held from 10th – 12th September 2009 in Amsterdam, The Netherlands. The conference series is the premier forum for presenting research

Gear fault diagnosis under variable conditions with intrinsic time-scale decomposition-singular value decomposition and support vector machine

Energy Technology Data Exchange (ETDEWEB)

Xing, Zhanqiang; Qu, Jianfeng; Chai, Yi; Tang, Qiu; Zhou, Yuming [Chongqing University, Chongqing (China)

2017-02-15

The gear vibration signal is nonlinear and non-stationary, gear fault diagnosis under variable conditions has always been unsatisfactory. To solve this problem, an intelligent fault diagnosis method based on Intrinsic time-scale decomposition (ITD)-Singular value decomposition (SVD) and Support vector machine (SVM) is proposed in this paper. The ITD method is adopted to decompose the vibration signal of gearbox into several Proper rotation components (PRCs). Subsequently, the singular value decomposition is proposed to obtain the singular value vectors of the proper rotation components and improve the robustness of feature extraction under variable conditions. Finally, the Support vector machine is applied to classify the fault type of gear. According to the experimental results, the performance of ITD-SVD exceeds those of the time-frequency analysis methods with EMD and WPT combined with SVD for feature extraction, and the classifier of SVM outperforms those for K-nearest neighbors (K-NN) and Back propagation (BP). Moreover, the proposed approach can accurately diagnose and identify different fault types of gear under variable conditions.

Human-Centric Interfaces for Ambient Intelligence

CERN Document Server

Aghajan, Hamid; Delgado, Ramon Lopez-Cozar

2009-01-01

To create truly effective human-centric ambient intelligence systems both engineering and computing methods are needed. This is the first book to bridge data processing and intelligent reasoning methods for the creation of human-centered ambient intelligence systems. Interdisciplinary in nature, the book covers topics such as multi-modal interfaces, human-computer interaction, smart environments and pervasive computing, addressing principles, paradigms, methods and applications. This book will be an ideal reference for university researchers, R&D engineers, computer engineers, and graduate s

Recent Advances on Hybrid Intelligent Systems

CERN Document Server

Melin, Patricia; Kacprzyk, Janusz

2013-01-01

This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algo...

Constructive quantum Shannon decomposition from Cartan involutions

Energy Technology Data Exchange (ETDEWEB)

Drury, Byron; Love, Peter [Department of Physics, 370 Lancaster Ave., Haverford College, Haverford, PA 19041 (United States)], E-mail: plove@haverford.edu

2008-10-03

The work presented here extends upon the best known universal quantum circuit, the quantum Shannon decomposition proposed by Shende et al (2006 IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 25 1000). We obtain the basis of the circuit's design in a pair of Cartan decompositions. This insight gives a simple constructive factoring algorithm in terms of the Cartan involutions corresponding to these decompositions.

Constructive quantum Shannon decomposition from Cartan involutions

International Nuclear Information System (INIS)

Drury, Byron; Love, Peter

2008-01-01

The work presented here extends upon the best known universal quantum circuit, the quantum Shannon decomposition proposed by Shende et al (2006 IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 25 1000). We obtain the basis of the circuit's design in a pair of Cartan decompositions. This insight gives a simple constructive factoring algorithm in terms of the Cartan involutions corresponding to these decompositions

Two-phase flow steam generator simulations on parallel computers using domain decomposition method

International Nuclear Information System (INIS)

Belliard, M.

2003-01-01

Within the framework of the Domain Decomposition Method (DDM), we present industrial steady state two-phase flow simulations of PWR Steam Generators (SG) using iteration-by-sub-domain methods: standard and Adaptive Dirichlet/Neumann methods (ADN). The averaged mixture balance equations are solved by a Fractional-Step algorithm, jointly with the Crank-Nicholson scheme and the Finite Element Method. The algorithm works with overlapping or non-overlapping sub-domains and with conforming or nonconforming meshing. Computations are run on PC networks or on massively parallel mainframe computers. A CEA code-linker and the PVM package are used (master-slave context). SG mock-up simulations, involving up to 32 sub-domains, highlight the efficiency (speed-up, scalability) and the robustness of the chosen approach. With the DDM, the computational problem size is easily increased to about 1,000,000 cells and the CPU time is significantly reduced. The difficulties related to industrial use are also discussed. (author)

Quantitative material decomposition using spectral computed tomography with an energy-resolved photon-counting detector

International Nuclear Information System (INIS)

Lee, Seungwan; Choi, Yu-Na; Kim, Hee-Joung

2014-01-01

Dual-energy computed tomography (CT) techniques have been used to decompose materials and characterize tissues according to their physical and chemical compositions. However, these techniques are hampered by the limitations of conventional x-ray detectors operated in charge integrating mode. Energy-resolved photon-counting detectors provide spectral information from polychromatic x-rays using multiple energy thresholds. These detectors allow simultaneous acquisition of data in different energy ranges without spectral overlap, resulting in more efficient material decomposition and quantification for dual-energy CT. In this study, a pre-reconstruction dual-energy CT technique based on volume conservation was proposed for three-material decomposition. The technique was combined with iterative reconstruction algorithms by using a ray-driven projector in order to improve the quality of decomposition images and reduce radiation dose. A spectral CT system equipped with a CZT-based photon-counting detector was used to implement the proposed dual-energy CT technique. We obtained dual-energy images of calibration and three-material phantoms consisting of low atomic number materials from the optimal energy bins determined by Monte Carlo simulations. The material decomposition process was accomplished by both the proposed and post-reconstruction dual-energy CT techniques. Linear regression and normalized root-mean-square error (NRMSE) analyses were performed to evaluate the quantitative accuracy of decomposition images. The calibration accuracy of the proposed dual-energy CT technique was higher than that of the post-reconstruction dual-energy CT technique, with fitted slopes of 0.97–1.01 and NRMSEs of 0.20–4.50% for all basis materials. In the three-material phantom study, the proposed dual-energy CT technique decreased the NRMSEs of measured volume fractions by factors of 0.17–0.28 compared to the post-reconstruction dual-energy CT technique. It was concluded that the

Intelligence: Real or artificial?

OpenAIRE

Schlinger, Henry D.

1992-01-01

Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

Delamination detection using methods of computational intelligence

Science.gov (United States)

Ihesiulor, Obinna K.; Shankar, Krishna; Zhang, Zhifang; Ray, Tapabrata

2012-11-01

Abstract Reliable delamination prediction scheme is indispensable in order to prevent potential risks of catastrophic failures in composite structures. The existence of delaminations changes the vibration characteristics of composite laminates and hence such indicators can be used to quantify the health characteristics of laminates. An approach for online health monitoring of in-service composite laminates is presented in this paper that relies on methods based on computational intelligence. Typical changes in the observed vibration characteristics (i.e. change in natural frequencies) are considered as inputs to identify the existence, location and magnitude of delaminations. The performance of the proposed approach is demonstrated using numerical models of composite laminates. Since this identification problem essentially involves the solution of an optimization problem, the use of finite element (FE) methods as the underlying tool for analysis turns out to be computationally expensive. A surrogate assisted optimization approach is hence introduced to contain the computational time within affordable limits. An artificial neural network (ANN) model with Bayesian regularization is used as the underlying approximation scheme while an improved rate of convergence is achieved using a memetic algorithm. However, building of ANN surrogate models usually requires large training datasets. K-means clustering is effectively employed to reduce the size of datasets. ANN is also used via inverse modeling to determine the position, size and location of delaminations using changes in measured natural frequencies. The results clearly highlight the efficiency and the robustness of the approach.

Eighth International Conference on Intelligent Systems and Knowledge Engineering

CERN Document Server

Li, Tianrui; ISKE 2013; Foundations of Intelligent Systems; Knowledge Engineering and Management; Practical Applications of Intelligent Systems

2014-01-01

"Foundations of Intelligent Systems" presents selected papers from the 2013 International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). The aim of this conference is to bring together experts from different expertise areas to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new research results and perspectives on future development. The topics in this volume include, but not limited to: Artificial Intelligence Theories, Pattern Recognition, Intelligent System Models, Speech Recognition, Computer Vision, Multi-Agent Systems, Machine Learning, Soft Computing and Fuzzy Systems, Biological Inspired Computation, Game Theory, Cognitive Systems and Information Processing, Computational Intelligence, etc. The proceedings are benefit for both researchers and practitioners who want to utilize intelligent methods in their specific research fields. Dr. Zhenkun Wen is a Professor at the College of Computer and Software Engineering, Shenzhen University...

Artificial Intelligence.

Science.gov (United States)

Wash, Darrel Patrick

1989-01-01

Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

Proceedings of the Third International Conference on Intelligent Human Computer Interaction

CERN Document Server

Pokorný, Jaroslav; Snášel, Václav; Abraham, Ajith

2013-01-01

The Third International Conference on Intelligent Human Computer Interaction 2011 (IHCI 2011) was held at Charles University, Prague, Czech Republic from August 29 - August 31, 2011. This conference was third in the series, following IHCI 2009 and IHCI 2010 held in January at IIIT Allahabad, India. Human computer interaction is a fast growing research area and an attractive subject of interest for both academia and industry. There are many interesting and challenging topics that need to be researched and discussed. This book aims to provide excellent opportunities for the dissemination of interesting new research and discussion about presented topics. It can be useful for researchers working on various aspects of human computer interaction. Topics covered in this book include user interface and interaction, theoretical background and applications of HCI and also data mining and knowledge discovery as a support of HCI applications.

Algorithms in ambient intelligence

NARCIS (Netherlands)

Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Weber, W.; Rabaey, J.M.; Aarts, E.

2005-01-01

We briefly review the concept of ambient intelligence and discuss its relation with the domain of intelligent algorithms. By means of four examples of ambient intelligent systems, we argue that new computing methods and quantification measures are needed to bridge the gap between the class of

An optimization approach for fitting canonical tensor decompositions.

Energy Technology Data Exchange (ETDEWEB)

Dunlavy, Daniel M. (Sandia National Laboratories, Albuquerque, NM); Acar, Evrim; Kolda, Tamara Gibson

2009-02-01

Tensor decompositions are higher-order analogues of matrix decompositions and have proven to be powerful tools for data analysis. In particular, we are interested in the canonical tensor decomposition, otherwise known as the CANDECOMP/PARAFAC decomposition (CPD), which expresses a tensor as the sum of component rank-one tensors and is used in a multitude of applications such as chemometrics, signal processing, neuroscience, and web analysis. The task of computing the CPD, however, can be difficult. The typical approach is based on alternating least squares (ALS) optimization, which can be remarkably fast but is not very accurate. Previously, nonlinear least squares (NLS) methods have also been recommended; existing NLS methods are accurate but slow. In this paper, we propose the use of gradient-based optimization methods. We discuss the mathematical calculation of the derivatives and further show that they can be computed efficiently, at the same cost as one iteration of ALS. Computational experiments demonstrate that the gradient-based optimization methods are much more accurate than ALS and orders of magnitude faster than NLS.

Reactive Goal Decomposition Hierarchies for On-Board Autonomy

Science.gov (United States)

Hartmann, L.

2002-01-01

to state and environment and in general can terminate the execution of a decomposition and attempt a new decomposition at any level in the hierarchy. This goal decomposition system is suitable for workstation, microprocessor and fpga implementation and thus is able to support the full range of prototyping activities, from mission design in the laboratory to development of the fpga firmware for the flight system. This approach is based on previous artificial intelligence work including (1) Brooks' subsumption architecture for robot control, (2) Firby's Reactive Action Package System (RAPS) for mediating between high level automated planning and low level execution and (3) hierarchical task networks for automated planning. Reactive goal decomposition hierarchies can be used for a wide variety of on-board autonomy applications including automating low level operation sequences (such as scheduling prerequisite operations, e.g., heaters, warm-up periods, monitoring power constraints), coordinating multiple spacecraft as in formation flying and constellations, robot manipulator operations, rendez-vous, docking, servicing, assembly, on-orbit maintenance, planetary rover operations, solar system and interstellar probes, intelligent science data gathering and disaster early warning. Goal decomposition hierarchies can support high level fault tolerance. Given models of on-board resources and goals to accomplish, the decomposition hierarchy could allocate resources to goals taking into account existing faults and in real-time reallocating resources as new faults arise. Resources to be modeled include memory (e.g., ROM, FPGA configuration memory, processor memory, payload instrument memory), processors, on-board and interspacecraft network nodes and links, sensors, actuators (e.g., attitude determination and control, guidance and navigation) and payload instruments. A goal decomposition hierarchy could be defined to map mission goals and tasks to available on-board resources. As

Challenging problems and solutions in intelligent systems

CERN Document Server

Grzegorzewski, Przemysław; Kacprzyk, Janusz; Owsiński, Jan; Penczek, Wojciech; Zadrożny, Sławomir

2016-01-01

This volume presents recent research, challenging problems and solutions in Intelligent Systems– covering the following disciplines: artificial and computational intelligence, fuzzy logic and other non-classic logics, intelligent database systems, information retrieval, information fusion, intelligent search (engines), data mining, cluster analysis, unsupervised learning, machine learning, intelligent data analysis, (group) decision support systems, intelligent agents and multi-agent systems, knowledge-based systems, imprecision and uncertainty handling, electronic commerce, distributed systems, etc. The book defines a common ground for sometimes seemingly disparate problems and addresses them by using the paradigm of broadly perceived intelligent systems. It presents a broad panorama of a multitude of theoretical and practical problems which have been successfully dealt with using the paradigm of intelligent computing.

Intelligence-Augmented Rat Cyborgs in Maze Solving.

Directory of Open Access Journals (Sweden)

Yipeng Yu

Full Text Available Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs. They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg has great potential in various applications, such as search and rescue in complex terrains.

Intelligence-Augmented Rat Cyborgs in Maze Solving.

Science.gov (United States)

Yu, Yipeng; Pan, Gang; Gong, Yongyue; Xu, Kedi; Zheng, Nenggan; Hua, Weidong; Zheng, Xiaoxiang; Wu, Zhaohui

2016-01-01

Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs). They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg) has great potential in various applications, such as search and rescue in complex terrains.

Proper generalized decompositions an introduction to computer implementation with Matlab

CERN Document Server

Cueto, Elías; Alfaro, Icíar

2016-01-01

This book is intended to help researchers overcome the entrance barrier to Proper Generalized Decomposition (PGD), by providing a valuable tool to begin the programming task. Detailed Matlab Codes are included for every chapter in the book, in which the theory previously described is translated into practice. Examples include parametric problems, non-linear model order reduction and real-time simulation, among others. Proper Generalized Decomposition (PGD) is a method for numerical simulation in many fields of applied science and engineering. As a generalization of Proper Orthogonal Decomposition or Principal Component Analysis to an arbitrary number of dimensions, PGD is able to provide the analyst with very accurate solutions for problems defined in high dimensional spaces, parametric problems and even real-time simulation. .

Intelligence of programs

Energy Technology Data Exchange (ETDEWEB)

Novak, D

1982-01-01

A general discussion about the level of artificial intelligence in computer programs is presented. The suitability of various languages for the development of complex, intelligent programs is discussed, considering fourth-generation language as well as the well established structured COBOL language. It is concluded that the success of automation in many administrative fields depends to a large extent on the development of intelligent programs.

Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods.

Science.gov (United States)

Obrzut, Bogdan; Kusy, Maciej; Semczuk, Andrzej; Obrzut, Marzanna; Kluska, Jacek

2017-12-12

Computational intelligence methods, including non-linear classification algorithms, can be used in medical research and practice as a decision making tool. This study aimed to evaluate the usefulness of artificial intelligence models for 5-year overall survival prediction in patients with cervical cancer treated by radical hysterectomy. The data set was collected from 102 patients with cervical cancer FIGO stage IA2-IIB, that underwent primary surgical treatment. Twenty-three demographic, tumor-related parameters and selected perioperative data of each patient were collected. The simulations involved six computational intelligence methods: the probabilistic neural network (PNN), multilayer perceptron network, gene expression programming classifier, support vector machines algorithm, radial basis function neural network and k-Means algorithm. The prediction ability of the models was determined based on the accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve. The results of the computational intelligence methods were compared with the results of linear regression analysis as a reference model. The best results were obtained by the PNN model. This neural network provided very high prediction ability with an accuracy of 0.892 and sensitivity of 0.975. The area under the receiver operating characteristics curve of PNN was also high, 0.818. The outcomes obtained by other classifiers were markedly worse. The PNN model is an effective tool for predicting 5-year overall survival in cervical cancer patients treated with radical hysterectomy.

Intelligent Mission Controller Node

National Research Council Canada - National Science Library

Perme, David

2002-01-01

The goal of the Intelligent Mission Controller Node (IMCN) project was to improve the process of translating mission taskings between real-world Command, Control, Communications, Computers, and Intelligence (C41...

Sentiment analysis and ontology engineering an environment of computational intelligence

CERN Document Server

Chen, Shyi-Ming

2016-01-01

This edited volume provides the reader with a fully updated, in-depth treatise on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of models of sentiment analysis and ontology –oriented engineering. The volume involves studies devoted to key issues of sentiment analysis, sentiment models, and ontology engineering. The book is structured into three main parts. The first part offers a comprehensive and prudently structured exposure to the fundamentals of sentiment analysis and natural language processing. The second part consists of studies devoted to the concepts, methodologies, and algorithmic developments elaborating on fuzzy linguistic aggregation to emotion analysis, carrying out interpretability of computational sentiment models, emotion classification, sentiment-oriented information retrieval, a methodology of adaptive dynamics in knowledge acquisition. The third part includes a plethora of applica...

Computational intelligence in wireless sensor networks recent advances and future challenges

CERN Document Server

Falcon, Rafael; Koeppen, Mario

2017-01-01

This book emphasizes the increasingly important role that Computational Intelligence (CI) methods are playing in solving a myriad of entangled Wireless Sensor Networks (WSN) related problems. The book serves as a guide for surveying several state-of-the-art WSN scenarios in which CI approaches have been employed. The reader finds in this book how CI has contributed to solve a wide range of challenging problems, ranging from balancing the cost and accuracy of heterogeneous sensor deployments to recovering from real-time sensor failures to detecting attacks launched by malicious sensor nodes and enacting CI-based security schemes. Network managers, industry experts, academicians and practitioners alike (mostly in computer engineering, computer science or applied mathematics) benefit from the spectrum of successful applications reported in this book. Senior undergraduate or graduate students may discover in this book some problems well suited for their own research endeavors. USP: Presents recent advances and fu...

Design of Intelligent Robot as A Tool for Teaching Media Based on Computer Interactive Learning and Computer Assisted Learning to Improve the Skill of University Student

Science.gov (United States)

Zuhrie, M. S.; Basuki, I.; Asto B, I. G. P.; Anifah, L.

2018-01-01

The focus of the research is the teaching module which incorporates manufacturing, planning mechanical designing, controlling system through microprocessor technology and maneuverability of the robot. Computer interactive and computer-assisted learning is strategies that emphasize the use of computers and learning aids (computer assisted learning) in teaching and learning activity. This research applied the 4-D model research and development. The model is suggested by Thiagarajan, et.al (1974). 4-D Model consists of four stages: Define Stage, Design Stage, Develop Stage, and Disseminate Stage. This research was conducted by applying the research design development with an objective to produce a tool of learning in the form of intelligent robot modules and kit based on Computer Interactive Learning and Computer Assisted Learning. From the data of the Indonesia Robot Contest during the period of 2009-2015, it can be seen that the modules that have been developed confirm the fourth stage of the research methods of development; disseminate method. The modules which have been developed for students guide students to produce Intelligent Robot Tool for Teaching Based on Computer Interactive Learning and Computer Assisted Learning. Results of students’ responses also showed a positive feedback to relate to the module of robotics and computer-based interactive learning.

Computational intelligence in multi-feature visual pattern recognition hand posture and face recognition using biologically inspired approaches

CERN Document Server

Pisharady, Pramod Kumar; Poh, Loh Ai

2014-01-01

This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...

Intelligent Systems For Aerospace Engineering: An Overview

Science.gov (United States)

KrishnaKumar, K.

2003-01-01

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

The intelligent data recorder

International Nuclear Information System (INIS)

Kojima, Mamoru; Hidekuma, Sigeru.

1985-01-01

The intelligent data recorder has been developed to data acquisition for a microwave interferometer. The 'RS-232C' which is the standard interface is used for data transmission to the host computer. Then, it's easy to connect with any computer which has general purpose serial port. In this report, the charcteristics of the intelligent data recorder and the way of developing the software are described. (author)

Fast approximate convex decomposition using relative concavity

KAUST Repository

Ghosh, Mukulika; Amato, Nancy M.; Lu, Yanyan; Lien, Jyh-Ming

2013-01-01

Approximate convex decomposition (ACD) is a technique that partitions an input object into approximately convex components. Decomposition into approximately convex pieces is both more efficient to compute than exact convex decomposition and can also generate a more manageable number of components. It can be used as a basis of divide-and-conquer algorithms for applications such as collision detection, skeleton extraction and mesh generation. In this paper, we propose a new method called Fast Approximate Convex Decomposition (FACD) that improves the quality of the decomposition and reduces the cost of computing it for both 2D and 3D models. In particular, we propose a new strategy for evaluating potential cuts that aims to reduce the relative concavity, rather than absolute concavity. As shown in our results, this leads to more natural and smaller decompositions that include components for small but important features such as toes or fingers while not decomposing larger components, such as the torso, that may have concavities due to surface texture. Second, instead of decomposing a component into two pieces at each step, as in the original ACD, we propose a new strategy that uses a dynamic programming approach to select a set of n c non-crossing (independent) cuts that can be simultaneously applied to decompose the component into n c+1 components. This reduces the depth of recursion and, together with a more efficient method for computing the concavity measure, leads to significant gains in efficiency. We provide comparative results for 2D and 3D models illustrating the improvements obtained by FACD over ACD and we compare with the segmentation methods in the Princeton Shape Benchmark by Chen et al. (2009) [31]. © 2012 Elsevier Ltd. All rights reserved.

Fast approximate convex decomposition using relative concavity

KAUST Repository

Ghosh, Mukulika

2013-02-01

Approximate convex decomposition (ACD) is a technique that partitions an input object into approximately convex components. Decomposition into approximately convex pieces is both more efficient to compute than exact convex decomposition and can also generate a more manageable number of components. It can be used as a basis of divide-and-conquer algorithms for applications such as collision detection, skeleton extraction and mesh generation. In this paper, we propose a new method called Fast Approximate Convex Decomposition (FACD) that improves the quality of the decomposition and reduces the cost of computing it for both 2D and 3D models. In particular, we propose a new strategy for evaluating potential cuts that aims to reduce the relative concavity, rather than absolute concavity. As shown in our results, this leads to more natural and smaller decompositions that include components for small but important features such as toes or fingers while not decomposing larger components, such as the torso, that may have concavities due to surface texture. Second, instead of decomposing a component into two pieces at each step, as in the original ACD, we propose a new strategy that uses a dynamic programming approach to select a set of n c non-crossing (independent) cuts that can be simultaneously applied to decompose the component into n c+1 components. This reduces the depth of recursion and, together with a more efficient method for computing the concavity measure, leads to significant gains in efficiency. We provide comparative results for 2D and 3D models illustrating the improvements obtained by FACD over ACD and we compare with the segmentation methods in the Princeton Shape Benchmark by Chen et al. (2009) [31]. © 2012 Elsevier Ltd. All rights reserved.

The fundamentals of computational intelligence system approach

CERN Document Server

Zgurovsky, Mikhail Z

2017-01-01

This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy ris...

Computer Games : 5th Workshop on Computer Games, CGW 2016, and 5th Workshop on General Intelligence in Game-Playing Agents, GIGA 2016, held in conjunction with the 25th International Conference on Artificial Intelligence, IJCAI 2016, New York, USA, July 9-10, 2016, Revised selected papers

NARCIS (Netherlands)

Cazenave, Tristan; Winands, Mark H. M; Edelkamp, Stefan; Schiffel, Stephan; Thielscher, Michael; Togelius, Julian

2017-01-01

This book constitutes the refereed proceedings of the 5th Computer Games Workshop, CGW 2016, and the 5th Workshop on General Intelligence in Game-Playing Agents, GIGA 2016, held in conjunction with the 25th International Conference on Artificial Intelligence, IJCAI 2016, in New York, USA, in July

Laser Fluence Recognition Using Computationally Intelligent Pulsed Photoacoustics Within the Trace Gases Analysis

Science.gov (United States)

Lukić, M.; Ćojbašić, Ž.; Rabasović, M. D.; Markushev, D. D.; Todorović, D. M.

2017-11-01

In this paper, the possibilities of computational intelligence applications for trace gas monitoring are discussed. For this, pulsed infrared photoacoustics is used to investigate SF6-Ar mixtures in a multiphoton regime, assisted by artificial neural networks. Feedforward multilayer perceptron networks are applied in order to recognize both the spatial characteristics of the laser beam and the values of laser fluence Φ from the given photoacoustic signal and prevent changes. Neural networks are trained in an offline batch training regime to simultaneously estimate four parameters from theoretical or experimental photoacoustic signals: the laser beam spatial profile R(r), vibrational-to-translational relaxation time τ _{V-T} , distance from the laser beam to the absorption molecules in the photoacoustic cell r* and laser fluence Φ . The results presented in this paper show that neural networks can estimate an unknown laser beam spatial profile and the parameters of photoacoustic signals in real time and with high precision. Real-time operation, high accuracy and the possibility of application for higher intensities of radiation for a wide range of laser fluencies are factors that classify the computational intelligence approach as efficient and powerful for the in situ measurement of atmospheric pollutants.

Artificial intelligence. Application of the Statistical Neural Networks computer program in nuclear medicine

International Nuclear Information System (INIS)

Stefaniak, B.; Cholewinski, W.; Tarkowska, A.

2005-01-01

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer application of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. In this paper practical aspects of scientific application of ANN in medicine using the Statistical Neural Networks Computer program, were presented. Several steps of data analysis with the above ANN software package were discussed shortly, from material selection and its dividing into groups to the types of obtained results. The typical problems connected with assessing scintigrams by ANN were also described. (author)

Can Designing Self-Representations through Creative Computing Promote an Incremental View of Intelligence and Enhance Creativity among At-Risk Youth?

Directory of Open Access Journals (Sweden)

Ina Blau

2016-12-01

Full Text Available Creative computing is one of the rapidly growing educational trends around the world. Previous studies have shown that creative computing can empower disadvantaged children and youth. At-risk youth tend to hold a negative view of self and perceive their abilities as inferior compared to “normative” pupils. The Implicit Theories of Intelligence approach (ITI; Dweck, 1999, 2008 suggests a way of changing beliefs regarding one’s abilities. This paper reports findings from an experiment that explores the impact of a short intervention among at-risk youth and “normative” high-school students on (1 changing ITI from being perceived as fixed (entity view of intelligence to more flexible (incremental view of intelligence and (2 the quality of digital self-representations programmed though a creative computing app. The participants were 117 Israeli youth aged 14-17, half of whom were at-risk youth. The participants were randomly assigned to the experimental and control conditions. The experimental group watched a video of a lecture regarding brain plasticity that emphasized flexibility and the potential of human intelligence to be cultivated. The control group watched a neutral lecture about brain-functioning and creativity. Following the intervention, all of the participants watched screencasts of basic training for the Scratch programming app, designed artifacts that digitally represented themselves five years later and reported their ITI. The results showed more incremental ITI in the experimental group compared to the control group and among normative students compared to at-risk youth. In contrast to the research hypothesis, the Scratch projects of the at-risk youth, especially in the experimental condition, were rated by neutral judges as being more creative, more aesthetically designed, and more clearly conveying their message. The results suggest that creative computing combined with the ITI intervention is a way of developing

Canonical Polyadic Decomposition With Auxiliary Information for Brain-Computer Interface.

Science.gov (United States)

Li, Junhua; Li, Chao; Cichocki, Andrzej

2017-01-01

Physiological signals are often organized in the form of multiple dimensions (e.g., channel, time, task, and 3-D voxel), so it is better to preserve original organization structure when processing. Unlike vector-based methods that destroy data structure, canonical polyadic decomposition (CPD) aims to process physiological signals in the form of multiway array, which considers relationships between dimensions and preserves structure information contained by the physiological signal. Nowadays, CPD is utilized as an unsupervised method for feature extraction in a classification problem. After that, a classifier, such as support vector machine, is required to classify those features. In this manner, classification task is achieved in two isolated steps. We proposed supervised CPD by directly incorporating auxiliary label information during decomposition, by which a classification task can be achieved without an extra step of classifier training. The proposed method merges the decomposition and classifier learning together, so it reduces procedure of classification task compared with that of respective decomposition and classification. In order to evaluate the performance of the proposed method, three different kinds of signals, synthetic signal, EEG signal, and MEG signal, were used. The results based on evaluations of synthetic and real signals demonstrated that the proposed method is effective and efficient.

From curve fitting to machine learning an illustrative guide to scientific data analysis and computational intelligence

CERN Document Server

Zielesny, Achim

2016-01-01

This successful book provides in its second edition an interactive and illustrative guide from two-dimensional curve fitting to multidimensional clustering and machine learning with neural networks or support vector machines. Along the way topics like mathematical optimization or evolutionary algorithms are touched. All concepts and ideas are outlined in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics. The major topics are extensively outlined with exploratory examples and applications. The primary goal is to be as illustrative as possible without hiding problems and pitfalls but to address them. The character of an illustrative cookbook is complemented with specific sections that address more fundamental questions like the relation between machine learning and human intelligence. All topics are completely demonstrated with the computing platform Mathematica and the Computational Intelligence Packages (CIP), a high-level function library developed with M...

Computational intelligence in time series forecasting theory and engineering applications

CERN Document Server

Palit, Ajoy K

2005-01-01

Foresight in an engineering enterprise can make the difference between success and failure, and can be vital to the effective control of industrial systems. Applying time series analysis in the on-line milieu of most industrial plants has been problematic owing to the time and computational effort required. The advent of soft computing tools offers a solution. The authors harness the power of intelligent technologies individually and in combination. Examples of the particular systems and processes susceptible to each technique are investigated, cultivating a comprehensive exposition of the improvements on offer in quality, model building and predictive control and the selection of appropriate tools from the plethora available. Application-oriented engineers in process control, manufacturing, production industry and research centres will find much to interest them in this book. It is suitable for industrial training purposes, as well as serving as valuable reference material for experimental researchers.

Artificial Intelligence--Applications in Education.

Science.gov (United States)

Poirot, James L.; Norris, Cathleen A.

1987-01-01

This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…

Making Friends in Dark Shadows: An Examination of the Use of Social Computing Strategy Within the United States Intelligence Community Since 9/11

Directory of Open Access Journals (Sweden)

Andrew Chomik

2011-01-01

Full Text Available The tragic events of 9/11/2001 in the United States highlighted failures in communication and cooperation in the U.S. intelligence community. Agencies within the community failed to “connect the dots” by not collaborating in intelligence gathering efforts, which resulted in severe gaps in data sharing that eventually contributed to the terrorist attack on American soil. Since then, and under the recommendation made by the 9/11 Commission Report, the United States intelligence community has made organizational and operational changes to intelligence gathering and sharing, primarily with the creation of the Office of the Director of National Intelligence (ODNI. The ODNI has since introduced a series of web-based social computing tools to be used by all members of the intelligence community, primarily with its closed-access wiki entitled “Intellipedia” and their social networking service called “A-Space”. This paper argues that, while the introduction of these and other social computing tools have been adopted successfully into the intelligence workplace, they have reached a plateau in their use and serve only as complementary tools to otherwise pre-existing information sharing processes. Agencies continue to ‘stove-pipe’ their respective data, a chronic challenge that plagues the community due to bureaucratic policy, technology use and workplace culture. This paper identifies and analyzes these challenges, and recommends improvements in the use of these tools, both in the business processes behind them and the technology itself. These recommendations aim to provide possible solutions for using these social computing tools as part of a more trusted, collaborative information sharing process.

Artificial intelligence in medicine.

OpenAIRE

Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

2004-01-01

INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of ...

Automated design of analog and high-frequency circuits a computational intelligence approach

CERN Document Server

Liu, Bo; Fernández, Francisco V

2014-01-01

Computational intelligence techniques are becoming more and more important for automated problem solving nowadays. Due to the growing complexity of industrial applications and the increasingly tight time-to-market requirements, the time available for thorough problem analysis and development of tailored solution methods is decreasing. There is no doubt that this trend will continue in the foreseeable future. Hence, it is not surprising that robust and general automated problem solving methods with satisfactory performance are needed.

On Using Intelligent Computer-Assisted Language Learning in Real-Life Foreign Language Teaching and Learning

Science.gov (United States)

Amaral, Luiz A.; Meurers, Detmar

2011-01-01

This paper explores the motivation and prerequisites for successful integration of Intelligent Computer-Assisted Language Learning (ICALL) tools into current foreign language teaching and learning (FLTL) practice. We focus on two aspects, which we argue to be important for effective ICALL system development and use: (i) the relationship between…

ANALISIS PERANCANGAN BUSINESS INTELLIGENCE BERBASIS SAAS CLOUD COMPUTING

Directory of Open Access Journals (Sweden)

I Gede Adnyana

2014-05-01

Full Text Available Persaingan bisnis yang ketat, mendorong setiap perusahaan menyusun strategi bisnis agar dapat bertahan dari para pesaing. Penyusunan strategi bisnis mutlak memerlukan informasi yang tepat dan akurat, pengolahan hingga analisis data yang menghasilkan informasi yang tepat dan akurat menjadi proses yang sangat penting. Business Intelligence (BI menawarkan solusi bisnis untuk menganalisis data dan memungkinkan suatu perusahaan untuk mengambil keputusan untuk meningkatkan keuntungan dan kinerja bisnis. Namun, BI mahal untuk diimplementasikan, memerlukan biaya pemeliharaan yang tidak sedikit dan infrastruktur yang kuat. Hal ini mendorong perusahaan mengurangi biaya tetapi masih memiliki teknologi yang tepat untuk memungkinkan mereka untuk membuat keputusan, mengidentifikasi peluang dan proaktif mengidentifikasi risiko yang dapat mempengaruhi bisnis. Konsep Software as a Service (SaaS Cloud Computing dapat menjawab tantangan yang dihadapi BI. Sebelum merancang BI berbasis SaaS perlu diketahui parameter-parameter evaluasi hingga kelebihan dan kekurangannya.

A review on economic emission dispatch problems using quantum computational intelligence

Science.gov (United States)

Mahdi, Fahad Parvez; Vasant, Pandian; Kallimani, Vish; Abdullah-Al-Wadud, M.

2016-11-01

Economic emission dispatch (EED) problems are one of the most crucial problems in power systems. Growing energy demand, limitation of natural resources and global warming make this topic into the center of discussion and research. This paper reviews the use of Quantum Computational Intelligence (QCI) in solving Economic Emission Dispatch problems. QCI techniques like Quantum Genetic Algorithm (QGA) and Quantum Particle Swarm Optimization (QPSO) algorithm are discussed here. This paper will encourage the researcher to use more QCI based algorithm to get better optimal result for solving EED problems.

The Slice Algorithm For Irreducible Decomposition of Monomial Ideals

DEFF Research Database (Denmark)

Roune, Bjarke Hammersholt

2009-01-01

Irreducible decomposition of monomial ideals has an increasing number of applications from biology to pure math. This paper presents the Slice Algorithm for computing irreducible decompositions, Alexander duals and socles of monomial ideals. The paper includes experiments showing good performance...

Intelligent mechatronics; Intelligent mechatronics

Energy Technology Data Exchange (ETDEWEB)

Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

1995-10-01

Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

Quo vadis, Intelligent Machine?

Directory of Open Access Journals (Sweden)

Rosemarie Velik

2010-09-01

Full Text Available Artificial Intelligence (AI is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this is no task easy to be solved. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in future. The goal is to mediate an understanding for the developments and changes in thinking in course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

Science.gov (United States)

Wei, Yawei; Venayagamoorthy, Ganesh Kumar

2017-09-01

To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

Energy Technology Data Exchange (ETDEWEB)

Jha, Sumit Kumar [University of Central Florida, Orlando; Pullum, Laura L [ORNL; Ramanathan, Arvind [ORNL

2016-01-01

Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.

Recent advances in computational intelligence in defense and security

CERN Document Server

Falcon, Rafael; Zincir-Heywood, Nur; Abbass, Hussein

2016-01-01

This volume is an initiative undertaken by the IEEE Computational Intelligence Society’s Task Force on Security, Surveillance and Defense to consolidate and disseminate the role of CI techniques in the design, development and deployment of security and defense solutions. Applications range from the detection of buried explosive hazards in a battlefield to the control of unmanned underwater vehicles, the delivery of superior video analytics for protecting critical infrastructures or the development of stronger intrusion detection systems and the design of military surveillance networks. Defense scientists, industry experts, academicians and practitioners alike will all benefit from the wide spectrum of successful applications compiled in this volume. Senior undergraduate or graduate students may also discover uncharted territory for their own research endeavors.

A cyber kill chain based taxonomy of banking Trojans for evolutionary computational intelligence

OpenAIRE

Kiwia, D; Dehghantanha, A; Choo, K-KR; Slaughter, J

2017-01-01

Malware such as banking Trojans are popular with financially-motivated cybercriminals. Detection of banking Trojans remains a challenging task, due to the constant evolution of techniques used to obfuscate and circumvent existing detection and security solutions. Having a malware taxonomy can facilitate the design of mitigation strategies such as those based on evolutionary computational intelligence. Specifically, in this paper, we propose a cyber kill chain based taxonomy of banking Trojans...

ARTIFICIAL INTELLIGENCE IN DETERMINATION OF MARKETING CUSTOMER STRATEGY

OpenAIRE

Markić, Brano; Bijakšić, Sanja; Šantić, Marko

2015-01-01

Artificial intelligence is a computer-based analytical process that tends to create computational systems which we would incline to be called intelligent. Expert systems are the most important part of the artificial intelligence from economic perspective. Expert systems attempt to mimic the human thought process including reasoning and optimization. “Knowledge” is represented by a set of “if-then” rules in a form of knowledge base. The results of artificial intelligence system implementation ...

ARTIFICIAL INTELLIGENCE IN DETERMINATION OF MARKETING CUSTOMER STRATEGY

OpenAIRE

Markić, Brano; Bijakšić, Sanja; Šantić, Marko

2016-01-01

Artificial intelligence is a computer-based analytical process that tends to create computational systems which we would incline to be called intelligent. Expert systems are the most important part of the artificial intelligence from economic perspective. Expert systems attempt to mimic the human thought process including reasoning and optimization. “Knowledge” is represented by a set of “if-then” rules in a form of knowledge base. The results of artificial intelligence system implementation ...

15th International conference on Hybrid Intelligent Systems

CERN Document Server

Han, Sang; Al-Sharhan, Salah; Liu, Hongbo

2016-01-01

This book is devoted to the hybridization of intelligent systems which is a promising research field of modern computational intelligence concerned with the development of the next generation of intelligent systems. This Volume contains the papers presented in the Fifteenth International conference on Hybrid Intelligent Systems (HIS 2015) held in Seoul, South Korea during November 16-18, 2015. The 26 papers presented in this Volume were carefully reviewed and selected from 90 paper submissions. The Volume will be a valuable reference to researchers, students and practitioners in the computational intelligence field.

Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

Science.gov (United States)

Yaratan, Huseyin

2003-01-01

An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

Air quality estimation by computational intelligence methodologies

Directory of Open Access Journals (Sweden)

Ćirić Ivan T.

2012-01-01

Full Text Available The subject of this study is to compare different computational intelligence methodologies based on artificial neural networks used for forecasting an air quality parameter - the emission of CO2, in the city of Niš. Firstly, inputs of the CO2 emission estimator are analyzed and their measurement is explained. It is known that the traffic is the single largest emitter of CO2 in Europe. Therefore, a proper treatment of this component of pollution is very important for precise estimation of emission levels. With this in mind, measurements of traffic frequency and CO2 concentration were carried out at critical intersections in the city, as well as the monitoring of a vehicle direction at the crossroad. Finally, based on experimental data, different soft computing estimators were developed, such as feed forward neural network, recurrent neural network, and hybrid neuro-fuzzy estimator of CO2 emission levels. Test data for some characteristic cases presented at the end of the paper shows good agreement of developed estimator outputs with experimental data. Presented results are a true indicator of the implemented method usability. [Projekat Ministarstva nauke Republike Srbije, br. III42008-2/2011: Evaluation of Energy Performances and br. TR35016/2011: Indoor Environment Quality of Educational Buildings in Serbia with Impact to Health and Research of MHD Flows around the Bodies, in the Tip Clearances and Channels and Application in the MHD Pumps Development

A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

Science.gov (United States)

Becker, Lee A.

1987-01-01

Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

The Birth of Artificial Intelligence: First Conference on Artificial Intelligence in Paris in 1951?

OpenAIRE

Bruderer , Herbert

2016-01-01

International audience; The 1956 Dartmouth conference is often considered as the cradle of artificial intelligence. There is a controversy on its origin. Some historians of computing believe that Turing or Zuse were the fathers of machine intelligence. However, the first working chess-playing automaton was developed by Torres Quevedo by 1912. Moreover, there was a large and important (but forgotten) European conference on computing and human thinking in Paris in 1951.

8th International Symposium on Intelligent Distributed Computing & Workshop on Cyber Security and Resilience of Large-Scale Systems & 6th International Workshop on Multi-Agent Systems Technology and Semantics

CERN Document Server

Braubach, Lars; Venticinque, Salvatore; Badica, Costin

2015-01-01

This book represents the combined peer-reviewed proceedings of the Eight International Symposium on Intelligent Distributed Computing - IDC'2014, of the Workshop on Cyber Security and Resilience of Large-Scale Systems - WSRL-2014, and of the Sixth International Workshop on Multi-Agent Systems Technology and Semantics- MASTS-2014. All the events were held in Madrid, Spain, during September 3-5, 2014. The 47 contributions published in this book address several topics related to theory and applications of the intelligent distributed computing and multi-agent systems, including: agent-based data processing, ambient intelligence, collaborative systems, cryptography and security, distributed algorithms, grid and cloud computing, information extraction, knowledge management, big data and ontologies, social networks, swarm intelligence or videogames amongst others.

Intelligent Computer Vision System for Automated Classification

International Nuclear Information System (INIS)

Jordanov, Ivan; Georgieva, Antoniya

2010-01-01

In this paper we investigate an Intelligent Computer Vision System applied for recognition and classification of commercially available cork tiles. The system is capable of acquiring and processing gray images using several feature generation and analysis techniques. Its functionality includes image acquisition, feature extraction and preprocessing, and feature classification with neural networks (NN). We also discuss system test and validation results from the recognition and classification tasks. The system investigation also includes statistical feature processing (features number and dimensionality reduction techniques) and classifier design (NN architecture, target coding, learning complexity and performance, and training with our own metaheuristic optimization method). The NNs trained with our genetic low-discrepancy search method (GLPτS) for global optimisation demonstrated very good generalisation abilities. In our view, the reported testing success rate of up to 95% is due to several factors: combination of feature generation techniques; application of Analysis of Variance (ANOVA) and Principal Component Analysis (PCA), which appeared to be very efficient for preprocessing the data; and use of suitable NN design and learning method.

Artificial Intelligence and Economic Theories

OpenAIRE

Marwala, Tshilidzi; Hurwitz, Evan

2017-01-01

The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence such as the swarming of birds, the working of the brain and the pathfinding of the ants. These techniques have impact on economic theories. This book studies the impact of artificial intelligence on economic theories, a subject that has not been extensively studied. The theories that...

New approaches in intelligent image analysis techniques, methodologies and applications

CERN Document Server

Nakamatsu, Kazumi

2016-01-01

This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the...

Cognitive logical systems with artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Liss, E

1983-09-01

The simulation of cognitive processes for the purpose of the technical development of learning systems with intelligent behavior is a basic object of the young interdisciplinary cognition science which is based upon artificial intelligence, cognitive psychology, computer science, linguistics and pedagogics. Cognitive systems may be described as knowledge-based logical systems. Based on structural and functional principles of intelligent automata and elementary information processing systems with structural learning capability the future process, machine and robot controls, advising units and fifth generation computers may be developed.

A study on optimal task decomposition of networked parallel computing using PVM

International Nuclear Information System (INIS)

Seong, Kwan Jae; Kim, Han Gyoo

1998-01-01

A numerical study is performed to investigate the effect of task decomposition on networked parallel processes using Parallel Virtual Machine (PVM). In our study, a PVM program distributed over a network of workstations is used in solving a finite difference version of a one dimensional heat equation, where natural choice of PVM programming structure would be the master-slave paradigm, with the aim of finding an optimal configuration resulting in least computing time including communication overhead among machines. Given a set of PVM tasks comprised of one master and five slave programs, it is found that there exists a pseudo-optimal number of machines, which does not necessarily coincide with the number of tasks, that yields the best performance when the network is under a light usage. Increasing the number of machines beyond this optimal one does not improve computing performance since increase in communication overhead among the excess number of machines offsets the decrease in CPU time obtained by distributing the PVM tasks among these machines. However, when the network traffic is heavy, the results exhibit a more random characteristic that is explained by the random nature of data transfer time

Narrative theories as computational models: reader-oriented theory and artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Galloway, P.

1983-12-01

In view of the rapid development of reader-oriented theory and its interest in dynamic models of narrative, the author speculates in a serious way about what such models might look like in computational terms. Researchers in artificial intelligence (AI) have already begun to develop models of story understanding as the emphasis in ai research has shifted toward natural language understanding and as ai has allied itself with cognitive psychology and linguistics to become cognitive science. Research in ai and in narrative theory share many common interests and problems and both studies might benefit from an exchange of ideas. 11 references.

Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm

Directory of Open Access Journals (Sweden)

Moteaal Asadi Shirzi

2007-03-01

Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.

A general-purpose development environment for intelligent computer-aided training systems

Science.gov (United States)

Savely, Robert T.

1990-01-01

Space station training will be a major task, requiring the creation of large numbers of simulation-based training systems for crew, flight controllers, and ground-based support personnel. Given the long duration of space station missions and the large number of activities supported by the space station, the extension of space shuttle training methods to space station training may prove to be impractical. The application of artificial intelligence technology to simulation training can provide the ability to deliver individualized training to large numbers of personnel in a distributed workstation environment. The principal objective of this project is the creation of a software development environment which can be used to build intelligent training systems for procedural tasks associated with the operation of the space station. Current NASA Johnson Space Center projects and joint projects with other NASA operational centers will result in specific training systems for existing space shuttle crew, ground support personnel, and flight controller tasks. Concurrently with the creation of these systems, a general-purpose development environment for intelligent computer-aided training systems will be built. Such an environment would permit the rapid production, delivery, and evolution of training systems for space station crew, flight controllers, and other support personnel. The widespread use of such systems will serve to preserve task and training expertise, support the training of many personnel in a distributed manner, and ensure the uniformity and verifiability of training experiences. As a result, significant reductions in training costs can be realized while safety and the probability of mission success can be enhanced.

A practical material decomposition method for x-ray dual spectral computed tomography.

Science.gov (United States)

Hu, Jingjing; Zhao, Xing

2016-03-17

X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today's clinical dual energy CT scanners usually measure different rays for different energy spectra and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.

7th International Conference on Intelligent Systems and Knowledge Engineering

CERN Document Server

Li, Tianrui; Li, Hongbo

2014-01-01

These proceedings present technical papers selected from the 2012 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2012), held on December 15-17 in Beijing. The aim of this conference is to bring together experts from different fields of expertise to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new findings and perspectives on future developments. The proceedings introduce current scientific and technical advances in the fields of artificial intelligence, machine learning, pattern recognition, data mining, knowledge engineering, information retrieval, information theory, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, and natural-language processing, etc. Furthermore they include papers on new intelligent computing paradigms, which combine new computing methodologies, e.g., cloud computing, service computing and pervasive computing with traditional intelligent methods. By presenting new method...

15th IEEE International Conference on Intelligent Engineering Systems

CERN Document Server

Živčák, Jozef; Aspects of Computational Intelligence Theory and Applications

2013-01-01

This volume covers the state-of-the art of the research and development in various aspects of computational intelligence and gives some perspective directions of development. Except the traditional engineering areas that contain theoretical knowledge, applications, designs and projects, the book includes the area of use of computational intelligence in biomedical engineering. „Aspects of Computational Intelligence: Theory and Applications” is a compilation of carefully selected extended papers written on the basis of original contributions presented at the 15th IEEE International Conference on Intelligent Engineering Systems 2011, INES 2011 held at June 23.-26. 2011 in AquaCity Poprad, Slovakia.    

APPROACH ON INTELLIGENT OPTIMIZATION DESIGN BASED ON COMPOUND KNOWLEDGE

Institute of Scientific and Technical Information of China (English)

Yao Jianchu; Zhou Ji; Yu Jun

2003-01-01

A concept of an intelligent optimal design approach is proposed, which is organized by a kind of compound knowledge model. The compound knowledge consists of modularized quantitative knowledge, inclusive experience knowledge and case-based sample knowledge. By using this compound knowledge model, the abundant quantity information of mathematical programming and the symbolic knowledge of artificial intelligence can be united together in this model. The intelligent optimal design model based on such a compound knowledge and the automatically generated decomposition principles based on it are also presented. Practically, it is applied to the production planning, process schedule and optimization of production process of a refining & chemical work and a great profit is achieved. Specially, the methods and principles are adaptable not only to continuous process industry, but also to discrete manufacturing one.

Effects of calibration methods on quantitative material decomposition in photon-counting spectral computed tomography using a maximum a posteriori estimator.

Science.gov (United States)

Curtis, Tyler E; Roeder, Ryan K

2017-10-01

Advances in photon-counting detectors have enabled quantitative material decomposition using multi-energy or spectral computed tomography (CT). Supervised methods for material decomposition utilize an estimated attenuation for each material of interest at each photon energy level, which must be calibrated based upon calculated or measured values for known compositions. Measurements using a calibration phantom can advantageously account for system-specific noise, but the effect of calibration methods on the material basis matrix and subsequent quantitative material decomposition has not been experimentally investigated. Therefore, the objective of this study was to investigate the influence of the range and number of contrast agent concentrations within a modular calibration phantom on the accuracy of quantitative material decomposition in the image domain. Gadolinium was chosen as a model contrast agent in imaging phantoms, which also contained bone tissue and water as negative controls. The maximum gadolinium concentration (30, 60, and 90 mM) and total number of concentrations (2, 4, and 7) were independently varied to systematically investigate effects of the material basis matrix and scaling factor calibration on the quantitative (root mean squared error, RMSE) and spatial (sensitivity and specificity) accuracy of material decomposition. Images of calibration and sample phantoms were acquired using a commercially available photon-counting spectral micro-CT system with five energy bins selected to normalize photon counts and leverage the contrast agent k-edge. Material decomposition of gadolinium, calcium, and water was performed for each calibration method using a maximum a posteriori estimator. Both the quantitative and spatial accuracy of material decomposition were most improved by using an increased maximum gadolinium concentration (range) in the basis matrix calibration; the effects of using a greater number of concentrations were relatively small in

Bayesian Multi-Energy Computed Tomography reconstruction approaches based on decomposition models

International Nuclear Information System (INIS)

Cai, Caifang

2013-01-01

Multi-Energy Computed Tomography (MECT) makes it possible to get multiple fractions of basis materials without segmentation. In medical application, one is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical MECT measurements are usually obtained with polychromatic X-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam poly-chromaticity fail to estimate the correct decomposition fractions and result in Beam-Hardening Artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log pre-processing and the water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on non-linear forward models counting the beam poly-chromaticity show great potential for giving accurate fraction images.This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint Maximum A Posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a non-quadratic cost function. To solve it, the use of a monotone Conjugate Gradient (CG) algorithm with suboptimal descent steps is proposed.The performances of the proposed approach are analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also

International Conference on Computer, Communication and Computational Sciences

CERN Document Server

Mishra, Krishn; Tiwari, Shailesh; Singh, Vivek

2017-01-01

Exchange of information and innovative ideas are necessary to accelerate the development of technology. With advent of technology, intelligent and soft computing techniques came into existence with a wide scope of implementation in engineering sciences. Keeping this ideology in preference, this book includes the insights that reflect the ‘Advances in Computer and Computational Sciences’ from upcoming researchers and leading academicians across the globe. It contains high-quality peer-reviewed papers of ‘International Conference on Computer, Communication and Computational Sciences (ICCCCS 2016), held during 12-13 August, 2016 in Ajmer, India. These papers are arranged in the form of chapters. The content of the book is divided into two volumes that cover variety of topics such as intelligent hardware and software design, advanced communications, power and energy optimization, intelligent techniques used in internet of things, intelligent image processing, advanced software engineering, evolutionary and ...

Artificial intelligence and information-control systems of robots - 87

International Nuclear Information System (INIS)

Plander, I.

1987-01-01

Independent research areas of artificial intelligence represent the following problems: automatic problem solving and new knowledge discovering, automatic program synthesis, natural language, picture and scene recognition and understanding, intelligent control systems of robots equipped with sensoric subsystems, dialogue of two knowledge systems, as well as studying and modelling higher artificial intelligence attributes, such as emotionality and personality. The 4th Conference draws on the problems treated at the preceding Conferences, and presents the most recent knowledge on the following topics: theoretical problems of artificial intelligence, knowledge-based systems, expert systems, perception and pattern recognition, robotics, intelligent computer-aided design, special-purpose computer systems for artificial intelligence and robotics

Bregmanized Domain Decomposition for Image Restoration

KAUST Repository

Langer, Andreas

2012-05-22

Computational problems of large-scale data are gaining attention recently due to better hardware and hence, higher dimensionality of images and data sets acquired in applications. In the last couple of years non-smooth minimization problems such as total variation minimization became increasingly important for the solution of these tasks. While being favorable due to the improved enhancement of images compared to smooth imaging approaches, non-smooth minimization problems typically scale badly with the dimension of the data. Hence, for large imaging problems solved by total variation minimization domain decomposition algorithms have been proposed, aiming to split one large problem into N > 1 smaller problems which can be solved on parallel CPUs. The N subproblems constitute constrained minimization problems, where the constraint enforces the support of the minimizer to be the respective subdomain. In this paper we discuss a fast computational algorithm to solve domain decomposition for total variation minimization. In particular, we accelerate the computation of the subproblems by nested Bregman iterations. We propose a Bregmanized Operator Splitting-Split Bregman (BOS-SB) algorithm, which enforces the restriction onto the respective subdomain by a Bregman iteration that is subsequently solved by a Split Bregman strategy. The computational performance of this new approach is discussed for its application to image inpainting and image deblurring. It turns out that the proposed new solution technique is up to three times faster than the iterative algorithm currently used in domain decomposition methods for total variation minimization. © Springer Science+Business Media, LLC 2012.

A new multivariate empirical mode decomposition method for improving the performance of SSVEP-based brain-computer interface

Science.gov (United States)

Chen, Yi-Feng; Atal, Kiran; Xie, Sheng-Quan; Liu, Quan

2017-08-01

Objective. Accurate and efficient detection of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG) is essential for the related brain-computer interface (BCI) applications. Approach. Although the canonical correlation analysis (CCA) has been applied extensively and successfully to SSVEP recognition, the spontaneous EEG activities and artifacts that often occur during data recording can deteriorate the recognition performance. Therefore, it is meaningful to extract a few frequency sub-bands of interest to avoid or reduce the influence of unrelated brain activity and artifacts. This paper presents an improved method to detect the frequency component associated with SSVEP using multivariate empirical mode decomposition (MEMD) and CCA (MEMD-CCA). EEG signals from nine healthy volunteers were recorded to evaluate the performance of the proposed method for SSVEP recognition. Main results. We compared our method with CCA and temporally local multivariate synchronization index (TMSI). The results suggest that the MEMD-CCA achieved significantly higher accuracy in contrast to standard CCA and TMSI. It gave the improvements of 1.34%, 3.11%, 3.33%, 10.45%, 15.78%, 18.45%, 15.00% and 14.22% on average over CCA at time windows from 0.5 s to 5 s and 0.55%, 1.56%, 7.78%, 14.67%, 13.67%, 7.33% and 7.78% over TMSI from 0.75 s to 5 s. The method outperformed the filter-based decomposition (FB), empirical mode decomposition (EMD) and wavelet decomposition (WT) based CCA for SSVEP recognition. Significance. The results demonstrate the ability of our proposed MEMD-CCA to improve the performance of SSVEP-based BCI.

6th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

CERN Document Server

2016-01-01

This edited book presents scientific results of the 16th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2015) which was held on June 1 – 3, 2015 in Takamatsu, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

CERN Document Server

SNPD 2016

2016-01-01

This edited book presents scientific results of the 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2016) which was held on May 30 - June 1, 2016 in Shanghai, China. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

Man and computer

International Nuclear Information System (INIS)

Fischbach, K.F.

1981-01-01

The discussion of cultural and sociological consequences of computer evolution is hindered by human prejudice. For example the sentence 'a computer is at best as intelligent as its programmer' veils actual developments. Theoretical limits of computer intelligence are the limits of intelligence in general. Modern computer systems replace not only human labour, but also human decision making and thereby human responsibility. The historical situation is unique. Human head-work is being automated and man is loosing function. (orig.) [de

Artificial Intelligence and Its Importance in Education.

Science.gov (United States)

Tilmann, Martha J.

Artificial intelligence, or the study of ideas that enable computers to be intelligent, is discussed in terms of what it is, what it has done, what it can do, and how it may affect the teaching of tomorrow. An extensive overview of artificial intelligence examines its goals and applications and types of artificial intelligence including (1) expert…

A COMPARISON BETWEEN THREE PREDICTIVE MODELS OF COMPUTATIONAL INTELLIGENCE

Directory of Open Access Journals (Sweden)

DUMITRU CIOBANU

2013-12-01

Full Text Available Time series prediction is an open problem and many researchers are trying to find new predictive methods and improvements for the existing ones. Lately methods based on neural networks are used extensively for time series prediction. Also, support vector machines have solved some of the problems faced by neural networks and they began to be widely used for time series prediction. The main drawback of those two methods is that they are global models and in the case of a chaotic time series it is unlikely to find such model. In this paper it is presented a comparison between three predictive from computational intelligence field one based on neural networks one based on support vector machine and another based on chaos theory. We show that the model based on chaos theory is an alternative to the other two methods.

CIMS: A Context-Based Intelligent Multimedia System for Ubiquitous Cloud Computing

Directory of Open Access Journals (Sweden)

Abhilash Sreeramaneni

2015-06-01

Full Text Available Mobile users spend a tremendous amount of time surfing multimedia contents over the Internet to pursue their interests. A resource-constrained smart device demands more intensive computing tasks and lessens the battery life. To address the resource limitations (i.e., memory, lower maintenance cost, easier access, computing tasks in mobile devices, mobile cloud computing is needed. Several approaches have been proposed to confront the challenges of mobile cloud computing, but difficulties still remain. However, in the coming years, context collecting, processing, and interchanging the results on a heavy network will cause vast computations and reduce the battery life in mobiles. In this paper, we propose a “context-based intelligent multimedia system” (CIMS for ubiquitous cloud computing. The main goal of this research is to lessen the computing percentage, storage complexities, and battery life for mobile users by using pervasive cloud computing. Moreover, to reduce the computing and storage concerns in mobiles, the cloud server collects several groups of user profiles with similarities by executing K-means clustering on users’ data (context and multimedia contents. The distribution process conveys real-time notifications to smartphone users, according to what is stated in his/her profile. We considered a mobile cloud offloading system, which decides the offloading actions to/from cloud servers. Context-aware decision-making (CAD customizes the mobile device performance with different specifications such as short response time and lesser energy consumption. The analysis says that our CIMS takes advantage of cost-effective features to produce high-quality information for mobile (or smart device users in real time. Moreover, our CIMS lessens the computation and storage complexities for mobile users, as well as cloud servers. Simulation analysis suggests that our approach is more efficient than existing domains.

A Decomposition Theorem for Finite Automata.

Science.gov (United States)

Santa Coloma, Teresa L.; Tucci, Ralph P.

1990-01-01

Described is automata theory which is a branch of theoretical computer science. A decomposition theorem is presented that is easier than the Krohn-Rhodes theorem. Included are the definitions, the theorem, and a proof. (KR)

Inter-cooperative collective intelligence techniques and applications

CERN Document Server

Bessis, Nik

2014-01-01

This book covers the latest advances in the rapid growing field of inter-cooperative collective intelligence aiming the integration and cooperation of various computational resources, networks and intelligent processing paradigms to collectively build intelligence and advanced decision support and interfaces for end-users. The book brings a comprehensive view of the state-of-the-art in the field of integration of sensor networks, IoT and Cloud computing, massive and intelligent querying and processing of data. As a result, the book presents lessons learned so far and identifies new research issues, challenges and opportunities for further research and development agendas. Emerging areas of applications are also identified and usefulness of inter-cooperative collective intelligence is envisaged.   Researchers, software developers, practitioners and students interested in the field of inter-cooperative collective intelligence will find the comprehensive coverage of this book useful for their research, academic...

Solution of Fractional Order System of Bagley-Torvik Equation Using Evolutionary Computational Intelligence

Directory of Open Access Journals (Sweden)

Muhammad Asif Zahoor Raja

2011-01-01

Full Text Available A stochastic technique has been developed for the solution of fractional order system represented by Bagley-Torvik equation. The mathematical model of the equation was developed with the help of feed-forward artificial neural networks. The training of the networks was made with evolutionary computational intelligence based on genetic algorithm hybrid with pattern search technique. Designed scheme was successfully applied to different forms of the equation. Results are compared with standard approximate analytic, stochastic numerical solvers and exact solutions.

Snap-drift neural computing for intelligent diagnostic feedback

OpenAIRE

Habte, Samson

2017-01-01

Information and communication technologies have been playing a crucial role in improving the efficiency and effectiveness of learning and teaching in higher education. Two decades ago, research studies were focused on how to use artificial intelligence techniques to imitate teachers or tutors in delivering learning sessions. Machine learning techniques have been applied in several research studies to construct a student model in the context of intelligent tutoring systems. However, the usage ...

Modelling intelligent behavior

Science.gov (United States)

Green, H. S.; Triffet, T.

1993-01-01

An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

Principles of artificial intelligence

CERN Document Server

Nilsson, Nils J

1980-01-01

A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

Artificial Intelligence Applications to High-Technology Training.

Science.gov (United States)

Dede, Christopher

1987-01-01

Discusses the use of artificial intelligence to improve occupational instruction in complex subjects with high performance goals, such as those required for high-technology jobs. Highlights include intelligent computer assisted instruction, examples in space technology training, intelligent simulation environments, and the need for adult training…

Asynchronous Task-Based Polar Decomposition on Manycore Architectures

KAUST Repository

Sukkari, Dalal

2016-10-25

This paper introduces the first asynchronous, task-based implementation of the polar decomposition on manycore architectures. Based on a new formulation of the iterative QR dynamically-weighted Halley algorithm (QDWH) for the calculation of the polar decomposition, the proposed implementation replaces the original and hostile LU factorization for the condition number estimator by the more adequate QR factorization to enable software portability across various architectures. Relying on fine-grained computations, the novel task-based implementation is also capable of taking advantage of the identity structure of the matrix involved during the QDWH iterations, which decreases the overall algorithmic complexity. Furthermore, the artifactual synchronization points have been severely weakened compared to previous implementations, unveiling look-ahead opportunities for better hardware occupancy. The overall QDWH-based polar decomposition can then be represented as a directed acyclic graph (DAG), where nodes represent computational tasks and edges define the inter-task data dependencies. The StarPU dynamic runtime system is employed to traverse the DAG, to track the various data dependencies and to asynchronously schedule the computational tasks on the underlying hardware resources, resulting in an out-of-order task scheduling. Benchmarking experiments show significant improvements against existing state-of-the-art high performance implementations (i.e., Intel MKL and Elemental) for the polar decomposition on latest shared-memory vendors\\' systems (i.e., Intel Haswell/Broadwell/Knights Landing, NVIDIA K80/P100 GPUs and IBM Power8), while maintaining high numerical accuracy.

14th ACIS/IEEE International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

CERN Document Server

Studies in Computational Intelligence : Volume 492

2013-01-01

This edited book presents scientific results of the 14th ACIS/IEEE International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2013), held in Honolulu, Hawaii, USA on July 1-3, 2013. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 17 outstanding papers from those papers accepted for presentation at the conference.  

15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

CERN Document Server

2015-01-01

This edited book presents scientific results of 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014) held on June 30 – July 2, 2014 in Las Vegas Nevada, USA. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 13 outstanding papers from those papers accepted for presentation at the conference.

2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research

Science.gov (United States)

2010-01-01

Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT

Quantum-mechanical computers and uncomputability

International Nuclear Information System (INIS)

Lloyd, S.

1993-01-01

The time evolution operator for any quantum-mechanical computer is diagonalizable, but to obtain the diagonal decomposition of a program state of the computer is as hard as actually performing the computation corresponding to the program. In particular, if a quantum-mechanical system is capable of universal computation, then the diagonal decomposition of program states is uncomputable. As a result, in a universe in which local variables support universal computation, a quantum-mechanical theory for that universe that supplies its spectrum cannot supply the spectral decomposition of the computational variables. A ''theory of everything'' can be simultaneously correct and fundamentally incomplete

Artificial intelligence and tutoring systems computational and cognitive approaches to the communication of knowledge

CERN Document Server

Wenger, Etienne

2014-01-01

Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge focuses on the cognitive approaches, methodologies, principles, and concepts involved in the communication of knowledge. The publication first elaborates on knowledge communication systems, basic issues, and tutorial dialogues. Concerns cover natural reasoning and tutorial dialogues, shift from local strategies to multiple mental models, domain knowledge, pedagogical knowledge, implicit versus explicit encoding of knowledge, knowledge communication, and practical and theoretic

Linear, Constant-rounds Bit-decomposition

DEFF Research Database (Denmark)

Reistad, Tord; Toft, Tomas

2010-01-01

When performing secure multiparty computation, tasks may often be simple or difficult depending on the representation chosen. Hence, being able to switch representation efficiently may allow more efficient protocols. We present a new protocol for bit-decomposition: converting a ring element x ∈ ℤ M...

Effect of water depth on the performance of intelligent computing models in predicting wave transmission of floating pipe breakwater.

Digital Repository Service at National Institute of Oceanography (India)

Patil, S.G.; Mandal, S.; Hegde, A.V.

Understanding the physics of complex system plays an important role in selection of data for training intelligent computing models. Based on the physics of the wave transmission of Horizontally Interlaced Multilayer Moored Floating Pipe Breakwater...

Advanced Applications of Neural Networks and Artificial Intelligence: A Review

OpenAIRE

Koushal Kumar; Gour Sundar Mitra Thakur

2012-01-01

Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is c...

International Conference on Intelligent and Interactive Systems and Applications

CERN Document Server

Patnaik, Srikanta; Yu, Zhengtao

2017-01-01

This book provides the latest research findings and developments in the field of interactive intelligent systems, addressing diverse areas such as autonomous systems, Internet and cloud computing, pattern recognition and vision systems, mobile computing and intelligent networking, and e-enabled systems. It gathers selected papers from the International Conference on Intelligent and Interactive Systems and Applications (IISA2016) held on June 25–26, 2016 in Shanghai, China. Interactive intelligent systems are among the most important multi-disciplinary research and development domains of artificial intelligence, human–computer interaction, machine learning and new Internet-based technologies. Accordingly, these systems embrace a considerable number of application areas such as autonomous systems, expert systems, mobile systems, recommender systems, knowledge-based and semantic web-based systems, virtual communication environments, and decision support systems, to name a few. To date, research on interactiv...

Primal Recovery from Consensus-Based Dual Decomposition for Distributed Convex Optimization

NARCIS (Netherlands)

Simonetto, A.; Jamali-Rad, H.

2015-01-01

Dual decomposition has been successfully employed in a variety of distributed convex optimization problems solved by a network of computing and communicating nodes. Often, when the cost function is separable but the constraints are coupled, the dual decomposition scheme involves local parallel

A Systolic Architecture for Singular Value Decomposition,

Science.gov (United States)

1983-01-01

Presented at the 1 st International Colloquium on Vector and Parallel Computing in Scientific Applications, Paris, March 191J Contract N00014-82-K.0703...Gene Golub. Private comunication . given inputs x and n 2 , compute 2 2 2 2 /6/ G. H. Golub and F. T. Luk : "Singular Value I + X1 Decomposition

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

KAUST Repository

Sukkari, Dalal E.; Ltaief, Hatem; Faverge, Mathieu; Keyes, David E.

2017-01-01

This paper introduces the first asynchronous, task-based formulation of the polar decomposition and its corresponding implementation on manycore architectures. Based on a formulation of the iterative QR dynamically-weighted Halley algorithm (QDWH) for the calculation of the polar decomposition, the proposed implementation replaces the original LU factorization for the condition number estimator by the more adequate QR factorization to enable software portability across various architectures. Relying on fine-grained computations, the novel task-based implementation is capable of taking advantage of the identity structure of the matrix involved during the QDWH iterations, which decreases the overall algorithmic complexity. Furthermore, the artifactual synchronization points have been weakened compared to previous implementations, unveiling look-ahead opportunities for better hardware occupancy. The overall QDWH-based polar decomposition can then be represented as a directed acyclic graph (DAG), where nodes represent computational tasks and edges define the inter-task data dependencies. The StarPU dynamic runtime system is employed to traverse the DAG, to track the various data dependencies and to asynchronously schedule the computational tasks on the underlying hardware resources, resulting in an out-of-order task scheduling. Benchmarking experiments show significant improvements against existing state-of-the-art high performance implementations for the polar decomposition on latest shared-memory vendors' systems, while maintaining numerical accuracy.

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

KAUST Repository

Sukkari, Dalal E.

2017-09-29

This paper introduces the first asynchronous, task-based formulation of the polar decomposition and its corresponding implementation on manycore architectures. Based on a formulation of the iterative QR dynamically-weighted Halley algorithm (QDWH) for the calculation of the polar decomposition, the proposed implementation replaces the original LU factorization for the condition number estimator by the more adequate QR factorization to enable software portability across various architectures. Relying on fine-grained computations, the novel task-based implementation is capable of taking advantage of the identity structure of the matrix involved during the QDWH iterations, which decreases the overall algorithmic complexity. Furthermore, the artifactual synchronization points have been weakened compared to previous implementations, unveiling look-ahead opportunities for better hardware occupancy. The overall QDWH-based polar decomposition can then be represented as a directed acyclic graph (DAG), where nodes represent computational tasks and edges define the inter-task data dependencies. The StarPU dynamic runtime system is employed to traverse the DAG, to track the various data dependencies and to asynchronously schedule the computational tasks on the underlying hardware resources, resulting in an out-of-order task scheduling. Benchmarking experiments show significant improvements against existing state-of-the-art high performance implementations for the polar decomposition on latest shared-memory vendors\\' systems, while maintaining numerical accuracy.

Embedding Topical Elements of Parallel Programming, Computer Graphics, and Artificial Intelligence across the Undergraduate CS Required Courses

Directory of Open Access Journals (Sweden)

James Wolfer

2015-02-01

Full Text Available Traditionally, topics such as parallel computing, computer graphics, and artificial intelligence have been taught as stand-alone courses in the computing curriculum. Often these are elective courses, limiting the material to the subset of students choosing to take the course. Recently there has been movement to distribute topics across the curriculum in order to ensure that all graduates have been exposed to concepts such as parallel computing. Previous work described an attempt to systematically weave a tapestry of topics into the undergraduate computing curriculum. This paper reviews that work and expands it with representative examples of assignments, demonstrations, and results as well as describing how the tools and examples deployed for these classes have a residual effect on classes such as Comptuer Literacy.

Introducing artificial intelligence into structural optimization programs

International Nuclear Information System (INIS)

Jozwiak, S.F.

1987-01-01

Artificial Intelligence /AI/ is defined as the branch of the computer science concerned with the study of the ideas that enable computers to be intelligent. The main purpose of the application of AI in engineering is to develop computer programs which function better as tools for engineers and designers. Many computer programs today have properties which make them inconvenient to their final users and the research carried within the field of AI provides tools and techniques so that these restriction can be removed. The continuous progress in computer technology has lead to developing efficient computer systems which can be applied to more than simple solving sets of equations. (orig.)

NET-COMPUTER: Internet Computer Architecture and its Application in E-Commerce

Directory of Open Access Journals (Sweden)

P. O. Umenne

2012-12-01

Full Text Available Research in Intelligent Agents has yielded interesting results, some of which have been translated into commer­cial ventures. Intelligent Agents are executable software components that represent the user, perform tasks on behalf of the user and when the task terminates, the Agents send the result to the user. Intelligent Agents are best suited for the Internet: a collection of computers connected together in a world-wide computer network. Swarm and HYDRA computer architectures for Agents’ execution were developed at the University of Surrey, UK in the 90s. The objective of the research was to develop a software-based computer architecture on which Agents execution could be explored. The combination of Intelligent Agents and HYDRA computer architecture gave rise to a new computer concept: the NET-Computer in which the comput­ing resources reside on the Internet. The Internet computers form the hardware and software resources, and the user is provided with a simple interface to access the Internet and run user tasks. The Agents autonomously roam the Internet (NET-Computer executing the tasks. A growing segment of the Internet is E-Commerce for online shopping for products and services. The Internet computing resources provide a marketplace for product suppliers and consumers alike. Consumers are looking for suppliers selling products and services, while suppliers are looking for buyers. Searching the vast amount of information available on the Internet causes a great deal of problems for both consumers and suppliers. Intelligent Agents executing on the NET-Computer can surf through the Internet and select specific information of interest to the user. The simulation results show that Intelligent Agents executing HYDRA computer architecture could be applied in E-Commerce.

Machine listening intelligence

Science.gov (United States)

Cella, C. E.

2017-05-01

This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

Business Intelligence v prostředí Cloudu

OpenAIRE

Náhlovský, Tomáš

2015-01-01

This master thesis deals with Business Intelligence in Cloud computing environment and comparing some of available solutions, that are currently offered on the market. The theoretical part focuses on definition of Business Intelligence and Cloud computing terms and combination thereof, including a description of the components, functionalities and technologies that use. The theoretical part describes, among other, the current trends from the world of Business Intelligence. The practical part ...

Recent Advances in Intelligent Engineering Systems

CERN Document Server

Klempous, Ryszard; Araujo, Carmen

2012-01-01

This volume is a collection of 19 chapters on intelligent engineering systems written by respectable experts of the fields. The book consists of three parts. The first part is devoted to the foundational aspects of computational intelligence. It consists of 8 chapters that include studies in genetic algorithms, fuzzy logic connectives, enhanced intelligence in product models, nature-inspired optimization technologies, particle swarm optimization, evolution algorithms, model complexity of neural networks, and fitness landscape analysis. The second part contains contributions to intelligent computation in networks, presented in 5 chapters. The covered subjects include the application of self-organizing maps for early detection of denial of service attacks, combating security threats via immunity and adaptability in cognitive radio networks, novel modifications in WSN network design for improved SNR and reliability, a conceptual framework for the design of audio based cognitive infocommunication channels, and a ...

Prospective Algorithms for Quantum Evolutionary Computation

OpenAIRE

Sofge, Donald A.

2008-01-01

This effort examines the intersection of the emerging field of quantum computing and the more established field of evolutionary computation. The goal is to understand what benefits quantum computing might offer to computational intelligence and how computational intelligence paradigms might be implemented as quantum programs to be run on a future quantum computer. We critically examine proposed algorithms and methods for implementing computational intelligence paradigms, primarily focused on ...

Parallel finite elements with domain decomposition and its pre-processing

International Nuclear Information System (INIS)

Yoshida, A.; Yagawa, G.; Hamada, S.

1993-01-01

This paper describes a parallel finite element analysis using a domain decomposition method, and the pre-processing for the parallel calculation. Computer simulations are about to replace experiments in various fields, and the scale of model to be simulated tends to be extremely large. On the other hand, computational environment has drastically changed in these years. Especially, parallel processing on massively parallel computers or computer networks is considered to be promising techniques. In order to achieve high efficiency on such parallel computation environment, large granularity of tasks, a well-balanced workload distribution are key issues. It is also important to reduce the cost of pre-processing in such parallel FEM. From the point of view, the authors developed the domain decomposition FEM with the automatic and dynamic task-allocation mechanism and the automatic mesh generation/domain subdivision system for it. (author)

Natural Inspired Intelligent Visual Computing and Its Application to Viticulture.

Science.gov (United States)

Ang, Li Minn; Seng, Kah Phooi; Ge, Feng Lu

2017-05-23

This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia. The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model. The arcs detected are then extended to perform the multiple arcs and ring detectors information processing for the berry detection application. The performance of the developed algorithms were compared with traditional image processing algorithms like the circular Hough transform (CHT) and other well-known circle detection methods. The proposed AIS approach gave a Fscore of 0.71 compared with Fscores of 0.28 and 0.30 for the CHT and a parameter-free circle detection technique (RPCD) respectively.

NET-COMPUTER: Internet Computer Architecture and its Application in E-Commerce

OpenAIRE

P. O. Umenne; M. O. Odhiambo

2012-01-01

Research in Intelligent Agents has yielded interesting results, some of which have been translated into commer­cial ventures. Intelligent Agents are executable software components that represent the user, perform tasks on behalf of the user and when the task terminates, the Agents send the result to the user. Intelligent Agents are best suited for the Internet: a collection of computers connected together in a world-wide computer network. Swarm and HYDRA computer architectures for Agents’ ex...

Prediction of pork loin quality using online computer vision system and artificial intelligence model.

Science.gov (United States)

Sun, Xin; Young, Jennifer; Liu, Jeng-Hung; Newman, David

2018-06-01

The objective of this project was to develop a computer vision system (CVS) for objective measurement of pork loin under industry speed requirement. Color images of pork loin samples were acquired using a CVS. Subjective color and marbling scores were determined according to the National Pork Board standards by a trained evaluator. Instrument color measurement and crude fat percentage were used as control measurements. Image features (18 color features; 1 marbling feature; 88 texture features) were extracted from whole pork loin color images. Artificial intelligence prediction model (support vector machine) was established for pork color and marbling quality grades. The results showed that CVS with support vector machine modeling reached the highest prediction accuracy of 92.5% for measured pork color score and 75.0% for measured pork marbling score. This research shows that the proposed artificial intelligence prediction model with CVS can provide an effective tool for predicting color and marbling in the pork industry at online speeds. Copyright © 2018 Elsevier Ltd. All rights reserved.

Early detection and identification of anomalies in chemical regime based on computational intelligence techniques

International Nuclear Information System (INIS)

Figedy, Stefan; Smiesko, Ivan

2012-01-01

This article provides brief information about the fundamental features of a newly-developed diagnostic system for early detection and identification of anomalies being generated in water chemistry regime of the primary and secondary circuit of the VVER-440 reactor. This system, which is called SACHER (System of Analysis of CHEmical Regime), was installed within the major modernization project at the NPP-V2 Bohunice in the Slovak Republic. The SACHER system has been fully developed on MATLAB environment. It is based on computational intelligence techniques and inserts various elements of intelligent data processing modules for clustering, diagnosing, future prediction, signal validation, etc, into the overall chemical information system. The application of SACHER would essentially assist chemists to identify the current situation regarding anomalies being generated in the primary and secondary circuit water chemistry. This system is to be used for diagnostics and data handling, however it is not intended to fully replace the presence of experienced chemists to decide upon corrective actions. (author)

Artificial Intelligence and Science Education.

Science.gov (United States)

Good, Ron

1987-01-01

Defines artificial intelligence (AI) in relation to intelligent computer-assisted instruction (ICAI) and science education. Provides a brief background of AI work, examples of expert systems, examples of ICAI work, and addresses problems facing AI workers that have implications for science education. Proposes a revised model of the Karplus/Renner…

Intelligent Multi-Media Integrated Interface Project

Science.gov (United States)

1990-06-01

been devoted to the application of aritificial intelligence technology to the development of human -computer interface technology that integrates speech...RADC-TR-90-128 Final Technical Report June 1090 AD-A225 973 INTELLIGENT MULTI-MEDIA INTEGRATED INTERFACE PROJECT Calspan-University of Buffalo...contractual obligations or notices on a specific document require that it be returned. INTELLIGENT MULTI-MEDIA INTEGRATED INTERFACE PROJECT J. G. Neal J. M

Multiresolution signal decomposition transforms, subbands, and wavelets

CERN Document Server

Akansu, Ali N; Haddad, Paul R

2001-01-01

The uniqueness of this book is that it covers such important aspects of modern signal processing as block transforms from subband filter banks and wavelet transforms from a common unifying standpoint, thus demonstrating the commonality among these decomposition techniques. In addition, it covers such ""hot"" areas as signal compression and coding, including particular decomposition techniques and tables listing coefficients of subband and wavelet filters and other important properties.The field of this book (Electrical Engineering/Computer Science) is currently booming, which is, of course

Artificial Intelligence and Moral intelligence

Directory of Open Access Journals (Sweden)

Laura Pana

2008-07-01

Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

Primary decomposition of zero-dimensional ideals over finite fields

Science.gov (United States)

Gao, Shuhong; Wan, Daqing; Wang, Mingsheng

2009-03-01

A new algorithm is presented for computing primary decomposition of zero-dimensional ideals over finite fields. Like Berlekamp's algorithm for univariate polynomials, the new method is based on the invariant subspace of the Frobenius map acting on the quotient algebra. The dimension of the invariant subspace equals the number of primary components, and a basis of the invariant subspace yields a complete decomposition. Unlike previous approaches for decomposing multivariate polynomial systems, the new method does not need primality testing nor any generic projection, instead it reduces the general decomposition problem directly to root finding of univariate polynomials over the ground field. Also, it is shown how Groebner basis structure can be used to get partial primary decomposition without any root finding.

Towards Brain-inspired Web Intelligence

Science.gov (United States)

Zhong, Ning

Artificial Intelligence (AI) has been mainly studied within the realm of computer based technologies. Various computational models and knowledge based systems have been developed for automated reasoning, learning, and problem-solving. However, there still exist several grand challenges. The AI research has not produced major breakthrough recently due to a lack of understanding of human brains and natural intelligence. In addition, most of the AI models and systems will not work well when dealing with large-scale, dynamically changing, open and distributed information sources at a Web scale.

Soft computing in computer and information science

CERN Document Server

Fray, Imed; Pejaś, Jerzy

2015-01-01

This book presents a carefully selected and reviewed collection of papers presented during the 19th Advanced Computer Systems conference ACS-2014. The Advanced Computer Systems conference concentrated from its beginning on methods and algorithms of artificial intelligence. Further future brought new areas of interest concerning technical informatics related to soft computing and some more technological aspects of computer science such as multimedia and computer graphics, software engineering, web systems, information security and safety or project management. These topics are represented in the present book under the categories Artificial Intelligence, Design of Information and Multimedia Systems, Information Technology Security and Software Technologies.

Integrating Hypermedia Objects In An Intelligent Tutoring System

Directory of Open Access Journals (Sweden)

Emilia PECHEANU

2001-12-01

Full Text Available The paper describes the internal architecture of an Intelligent Tutoring System, CS-Tutor. The architectural design of the tutorial system was developed in a collaborative work at the Department of Computer Science of the University of Galati and the Department of Applied Informatics of the Faculty of Computer Science of Iasi. Intelligent Tutoring Systems (ITS are software packages which use the Artificial Intelligence techniques to aid in learning of some subject or skill. In recent years, Hypermedia has been gained the interest of many researchers working in the teaching field of study. The CS-Tutor internal architecture is based upon integrating Hypermedia Objects in an Intelligent Knowledge-Based frame.

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation.

Science.gov (United States)

Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

2015-01-01

Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency.

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

Science.gov (United States)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

Solving Multi-Pollutant Emission Dispatch Problem Using Computational Intelligence Technique

Directory of Open Access Journals (Sweden)

Nur Azzammudin Rahmat

2016-06-01

Full Text Available Economic dispatch is a crucial process conducted by the utilities to correctly determine the satisfying amount of power to be generated and distributed to the consumers. During the process, the utilities also consider pollutant emission as the consequences of fossil-fuel consumption. Fossil-fuel includes petroleum, coal, and natural gas; each has its unique chemical composition of pollutants i.e. sulphur oxides (SOX, nitrogen oxides (NOX and carbon oxides (COX. This paper presents multi-pollutant emission dispatch problem using computational intelligence technique. In this study, a novel emission dispatch technique is formulated to determine the amount of the pollutant level. It utilizes a pre-developed optimization technique termed as differential evolution immunized ant colony optimization (DEIANT for the emission dispatch problem. The optimization results indicated high level of COX level, regardless of any type of fossil fuel consumed.

Computational intelligence for qualitative coaching diagnostics: Automated assessment of tennis swings to improve performance and safety

OpenAIRE

Bačić, Boris; Hume, Patria

2017-01-01

Coaching technology, wearables and exergames can provide quantitative feedback based on measured activity, but there is little evidence of qualitative feedback to aid technique improvement. To achieve personalised qualitative feedback, we demonstrated a proof-of-concept prototype combining kinesiology and computational intelligence that could help improving tennis swing technique. Three-dimensional tennis motion data were acquired from multi-camera video (22 backhands and 21 forehands, includ...

Multilevel domain decomposition for electronic structure calculations

International Nuclear Information System (INIS)

Barrault, M.; Cances, E.; Hager, W.W.; Le Bris, C.

2007-01-01

We introduce a new multilevel domain decomposition method (MDD) for electronic structure calculations within semi-empirical and density functional theory (DFT) frameworks. This method iterates between local fine solvers and global coarse solvers, in the spirit of domain decomposition methods. Using this approach, calculations have been successfully performed on several linear polymer chains containing up to 40,000 atoms and 200,000 atomic orbitals. Both the computational cost and the memory requirement scale linearly with the number of atoms. Additional speed-up can easily be obtained by parallelization. We show that this domain decomposition method outperforms the density matrix minimization (DMM) method for poor initial guesses. Our method provides an efficient preconditioner for DMM and other linear scaling methods, variational in nature, such as the orbital minimization (OM) procedure

Solving and Interpreting Large-scale Harvest Scheduling Problems by Duality and Decomposition

OpenAIRE

Berck, Peter; Bible, Thomas

1982-01-01

This paper presents a solution to the forest planning problem that takes advantage of both the duality of linear programming formulations currently being used for harvest scheduling and the characteristics of decomposition inherent in the forest land class-relationship. The subproblems of decomposition, defined as the dual, can be solved in a simple, recursive fashion. In effect, such a technique reduces the computational burden in terms of time and computer storage as compared to the traditi...

Power System Decomposition for Practical Implementation of Bulk-Grid Voltage Control Methods

Energy Technology Data Exchange (ETDEWEB)

Vallem, Mallikarjuna R.; Vyakaranam, Bharat GNVSR; Holzer, Jesse T.; Elizondo, Marcelo A.; Samaan, Nader A.

2017-10-19

Power system algorithms such as AC optimal power flow and coordinated volt/var control of the bulk power system are computationally intensive and become difficult to solve in operational time frames. The computational time required to run these algorithms increases exponentially as the size of the power system increases. The solution time for multiple subsystems is less than that for solving the entire system simultaneously, and the local nature of the voltage problem lends itself to such decomposition. This paper describes an algorithm that can be used to perform power system decomposition from the point of view of the voltage control problem. Our approach takes advantage of the dominant localized effect of voltage control and is based on clustering buses according to the electrical distances between them. One of the contributions of the paper is to use multidimensional scaling to compute n-dimensional Euclidean coordinates for each bus based on electrical distance to perform algorithms like K-means clustering. A simple coordinated reactive power control of photovoltaic inverters for voltage regulation is used to demonstrate the effectiveness of the proposed decomposition algorithm and its components. The proposed decomposition method is demonstrated on the IEEE 118-bus system.

The essential Turing Seminal writings in computing, logic, philosophy, artificial intelligence, and artificial life plus the secrets of enigma

CERN Document Server

2004-01-01

The ideas that gave birth to the computer age. Alan Turing, pioneer of computing and WWII codebreaker, was one of the most important and influential thinkers of the twentieth century. In this volume for the first time his key writings are made available to a broad, non-specialist readership. They make fascinating reading both in their own right and for their historic significance: contemporary computational theory, cognitive science, artificial intelligence, and artificial life all spring from this ground-breaking work, which is also rich. in philosophical and logical insight. An introduction

Computer Assisted Instructional Design for Computer-Based Instruction. Final Report. Working Papers.

Science.gov (United States)

Russell, Daniel M.; Pirolli, Peter

Recent advances in artificial intelligence and the cognitive sciences have made it possible to develop successful intelligent computer-aided instructional systems for technical and scientific training. In addition, computer-aided design (CAD) environments that support the rapid development of such computer-based instruction have also been recently…

Intelligence for embedded systems a methodological approach

CERN Document Server

Alippi, Cesare

2014-01-01

Addressing current issues of which any engineer or computer scientist should be aware, this monograph is a response to the need to adopt a new computational paradigm as the methodological basis for designing pervasive embedded systems with sensor capabilities. The requirements of this paradigm are to control complexity, to limit cost and energy consumption, and to provide adaptation and cognition abilities allowing the embedded system to interact proactively with the real world. The quest for such intelligence requires the formalization of a new generation of intelligent systems able to exploit advances in digital architectures and in sensing technologies. The book sheds light on the theory behind intelligence for embedded systems with specific focus on: ·        robustness (the robustness of a computational flow and its evaluation); ·        intelligence (how to mimic the adaptation and cognition abilities of the human brain), ·        the capacity to learn in non-stationary and evolv...

Computer simulations of austenite decomposition of microalloyed 700 MPa steel during cooling

Science.gov (United States)

Pohjonen, Aarne; Paananen, Joni; Mourujärvi, Juho; Manninen, Timo; Larkiola, Jari; Porter, David

2018-05-01

We present computer simulations of austenite decomposition to ferrite and bainite during cooling. The phase transformation model is based on Johnson-Mehl-Avrami-Kolmogorov type equations. The model is parameterized by numerical fitting to continuous cooling data obtained with Gleeble thermo-mechanical simulator and it can be used for calculation of the transformation behavior occurring during cooling along any cooling path. The phase transformation model has been coupled with heat conduction simulations. The model includes separate parameters to account for the incubation stage and for the kinetics after the transformation has started. The incubation time is calculated with inversion of the CCT transformation start time. For heat conduction simulations we employed our own parallelized 2-dimensional finite difference code. In addition, the transformation model was also implemented as a subroutine in commercial finite-element software Abaqus which allows for the use of the model in various engineering applications.

Applications of tensor (multiway array) factorizations and decompositions in data mining

DEFF Research Database (Denmark)

Mørup, Morten

2011-01-01

Tensor (multiway array) factorization and decomposition has become an important tool for data mining. Fueled by the computational power of modern computer researchers can now analyze large-scale tensorial structured data that only a few years ago would have been impossible. Tensor factorizations...... have several advantages over two-way matrix factorizations including uniqueness of the optimal solution and component identification even when most of the data is missing. Furthermore, multiway decomposition techniques explicitly exploit the multiway structure that is lost when collapsing some...... of the modes of the tensor in order to analyze the data by regular matrix factorization approaches. Multiway decomposition is being applied to new fields every year and there is no doubt that the future will bring many exciting new applications. The aim of this overview is to introduce the basic concepts...

2nd International Conference on INformation Systems Design and Intelligent Applications

CERN Document Server

Satapathy, Suresh; Sanyal, Manas; Sarkar, Partha; Mukhopadhyay, Anirban

2015-01-01

The second international conference on INformation Systems Design and Intelligent Applications (INDIA – 2015) held in Kalyani, India during January 8-9, 2015. The book covers all aspects of information system design, computer science and technology, general sciences, and educational research. Upon a double blind review process, a number of high quality papers are selected and collected in the book, which is composed of two different volumes, and covers a variety of topics, including natural language processing, artificial intelligence, security and privacy, communications, wireless and sensor networks, microelectronics, circuit and systems, machine learning, soft computing, mobile computing and applications, cloud computing, software engineering, graphics and image processing, rural engineering, e-commerce, e-governance, business computing, molecular computing, nano computing, chemical computing, intelligent computing for GIS and remote sensing, bio-informatics and bio-computing. These fields are not only ...

3rd International Conference on INformation Systems Design and Intelligent Applications

CERN Document Server

Mandal, Jyotsna; Udgata, Siba; Bhateja, Vikrant

2016-01-01

The third international conference on INformation Systems Design and Intelligent Applications (INDIA – 2016) held in Visakhapatnam, India during January 8-9, 2016. The book covers all aspects of information system design, computer science and technology, general sciences, and educational research. Upon a double blind review process, a number of high quality papers are selected and collected in the book, which is composed of three different volumes, and covers a variety of topics, including natural language processing, artificial intelligence, security and privacy, communications, wireless and sensor networks, microelectronics, circuit and systems, machine learning, soft computing, mobile computing and applications, cloud computing, software engineering, graphics and image processing, rural engineering, e-commerce, e-governance, business computing, molecular computing, nano-computing, chemical computing, intelligent computing for GIS and remote sensing, bio-informatics and bio-computing. These fields are not...

An extended Intelligent Water Drops algorithm for workflow scheduling in cloud computing environment

Directory of Open Access Journals (Sweden)

Shaymaa Elsherbiny

2018-03-01

Full Text Available Cloud computing is emerging as a high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. Many resource management methods may enhance the efficiency of the whole cloud computing system. The key part of cloud computing resource management is resource scheduling. Optimized scheduling of tasks on the cloud virtual machines is an NP-hard problem and many algorithms have been presented to solve it. The variations among these schedulers are due to the fact that the scheduling strategies of the schedulers are adapted to the changing environment and the types of tasks. The focus of this paper is on workflows scheduling in cloud computing, which is gaining a lot of attention recently because workflows have emerged as a paradigm to represent complex computing problems. We proposed a novel algorithm extending the natural-based Intelligent Water Drops (IWD algorithm that optimizes the scheduling of workflows on the cloud. The proposed algorithm is implemented and embedded within the workflows simulation toolkit and tested in different simulated cloud environments with different cost models. Our algorithm showed noticeable enhancements over the classical workflow scheduling algorithms. We made a comparison between the proposed IWD-based algorithm with other well-known scheduling algorithms, including MIN-MIN, MAX-MIN, Round Robin, FCFS, and MCT, PSO and C-PSO, where the proposed algorithm presented noticeable enhancements in the performance and cost in most situations.

Freedom and privacy in ambient intelligence

NARCIS (Netherlands)

Brey, Philip A.E.

2006-01-01

This paper analyzes ethical aspects of the new paradigm of Ambient Intelligence, which is a combination of Ubiquitous Computing and Intelligent User Interfaces (IUI’s). After an introduction to the approach, two key ethical dimensions will be analyzed: freedom and privacy. It is argued that Ambient

Identification of liquid-phase decomposition species and reactions for guanidinium azotetrazolate

International Nuclear Information System (INIS)

Kumbhakarna, Neeraj R.; Shah, Kaushal J.; Chowdhury, Arindrajit; Thynell, Stefan T.

2014-01-01

Highlights: • Guanidinium azotetrazolate (GzT) is a high-nitrogen energetic material. • FTIR spectroscopy and ToFMS spectrometry were used for species identification. • Quantum mechanics was used to identify transition states and decomposition pathways. • Important reactions in the GzT liquid-phase decomposition process were identified. • Initiation of decomposition occurs via ring opening, releasing N 2 . - Abstract: The objective of this work is to analyze the decomposition of guanidinium azotetrazolate (GzT) in the liquid phase by using a combined experimental and computational approach. The experimental part involves the use of Fourier transform infrared (FTIR) spectroscopy to acquire the spectral transmittance of the evolved gas-phase species from rapid thermolysis, as well as to acquire spectral transmittance of the condensate and residue formed from the decomposition. Time-of-flight mass spectrometry (ToFMS) is also used to acquire mass spectra of the evolved gas-phase species. Sub-milligram samples of GzT were heated at rates of about 2000 K/s to a set temperature (553–573 K) where decomposition occurred under isothermal conditions. N 2 , NH 3 , HCN, guanidine and melamine were identified as products of decomposition. The computational approach is based on using quantum mechanics for confirming the identity of the species observed in experiments and for identifying elementary chemical reactions that formed these species. In these ab initio techniques, various levels of theory and basis sets were used. Based on the calculated enthalpy and free energy values of various molecular structures, important reaction pathways were identified. Initiation of decomposition of GzT occurs via ring opening to release N 2

What makes you clever the puzzle of intelligence

CERN Document Server

Partridge, Derek

2014-01-01

From Black Holes and Big Bangs to the Higgs boson and the infinitesimal building blocks of all matter, modern science has been spectacularly successful, with one glaring exception - intelligence. Intelligence still remains as one of the greatest mysteries in science. How do you chat so effortlessly? How do you remember, and why do you forget? From a basis of ten maxims What Makes You Clever explains the difficulties as well as the persuasive and persistent over-estimations of progress in Artificial Intelligence. Computers have transformed our lives, and will continue to do so for many years to come. But ever since the Turing Test proposed in 1950 up to IBM's Deep Blue computer that won the second six-game match against world champion Garry Kasparov, the science of artificial intelligence has struggled to make progress. The reader's expertise is engaged to probe human language, machine learning, neural computing, holistic systems and emergent phenomenon. What Makes You Clever reveals the difficulties that s...

Reconstruction method for fluorescent X-ray computed tomography by least-squares method using singular value decomposition

Science.gov (United States)

Yuasa, T.; Akiba, M.; Takeda, T.; Kazama, M.; Hoshino, A.; Watanabe, Y.; Hyodo, K.; Dilmanian, F. A.; Akatsuka, T.; Itai, Y.

1997-02-01

We describe a new attenuation correction method for fluorescent X-ray computed tomography (FXCT) applied to image nonradioactive contrast materials in vivo. The principle of the FXCT imaging is that of computed tomography of the first generation. Using monochromatized synchrotron radiation from the BLNE-5A bending-magnet beam line of Tristan Accumulation Ring in KEK, Japan, we studied phantoms with the FXCT method, and we succeeded in delineating a 4-mm-diameter channel filled with a 500 /spl mu/g I/ml iodine solution in a 20-mm-diameter acrylic cylindrical phantom. However, to detect smaller iodine concentrations, attenuation correction is needed. We present a correction method based on the equation representing the measurement process. The discretized equation system is solved by the least-squares method using the singular value decomposition. The attenuation correction method is applied to the projections by the Monte Carlo simulation and the experiment to confirm its effectiveness.

Limited-memory adaptive snapshot selection for proper orthogonal decomposition

Energy Technology Data Exchange (ETDEWEB)

Oxberry, Geoffrey M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kostova-Vassilevska, Tanya [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Arrighi, Bill [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Chand, Kyle [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-04-02

Reduced order models are useful for accelerating simulations in many-query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models can have prohibitively expensive memory and floating-point operation costs in high-performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time-stepping ordinary differential equation solvers. The error estimator used in this work is related to theory bounding the approximation error in time of proper orthogonal decomposition-based reduced order models, and memory usage is minimized by computing the singular value decomposition using a single-pass incremental algorithm. Results for a viscous Burgers’ test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full order model is recovered to within discretization error. The resulting method can be used on supercomputers to generate proper orthogonal decomposition-based reduced order models, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space.

Intelligent bioinformatics : the application of artificial intelligence techniques to bioinformatics problems

National Research Council Canada - National Science Library

Keedwell, Edward

2005-01-01

... Intelligence and Computer Science 3.1 Introduction to search 3.2 Search algorithms 3.3 Heuristic search methods 3.4 Optimal search strategies 3.5 Problems with search techniques 3.6 Complexity of...

Novel approach for dam break flow modeling using computational intelligence

Science.gov (United States)

Seyedashraf, Omid; Mehrabi, Mohammad; Akhtari, Ali Akbar

2018-04-01

A new methodology based on the computational intelligence (CI) system is proposed and tested for modeling the classic 1D dam-break flow problem. The reason to seek for a new solution lies in the shortcomings of the existing analytical and numerical models. This includes the difficulty of using the exact solutions and the unwanted fluctuations, which arise in the numerical results. In this research, the application of the radial-basis-function (RBF) and multi-layer-perceptron (MLP) systems is detailed for the solution of twenty-nine dam-break scenarios. The models are developed using seven variables, i.e. the length of the channel, the depths of the up-and downstream sections, time, and distance as the inputs. Moreover, the depths and velocities of each computational node in the flow domain are considered as the model outputs. The models are validated against the analytical, and Lax-Wendroff and MacCormack FDM schemes. The findings indicate that the employed CI models are able to replicate the overall shape of the shock- and rarefaction-waves. Furthermore, the MLP system outperforms RBF and the tested numerical schemes. A new monolithic equation is proposed based on the best fitting model, which can be used as an efficient alternative to the existing piecewise analytic equations.

A posteriori error analysis of multiscale operator decomposition methods for multiphysics models

International Nuclear Information System (INIS)

Estep, D; Carey, V; Tavener, S; Ginting, V; Wildey, T

2008-01-01

Multiphysics, multiscale models present significant challenges in computing accurate solutions and for estimating the error in information computed from numerical solutions. In this paper, we describe recent advances in extending the techniques of a posteriori error analysis to multiscale operator decomposition solution methods. While the particulars of the analysis vary considerably with the problem, several key ideas underlie a general approach being developed to treat operator decomposition multiscale methods. We explain these ideas in the context of three specific examples

Intelligent control and automation technology for nuclear applications

International Nuclear Information System (INIS)

Kim, Jae Hee; Kim, Ko Ryeo; Lee, Jae Cheol; Eom, Heung Seop; Lee, Jang Soo

1994-01-01

Using recently established intelligent mobile robot theory and high technologies in computer science, we have designed an inspection automation system for welded parts of the reactor vessel, and we intend to establish basic technologies. The recent status of those technologies is surveyed for various application areas, and the characteristics and availability of those techniques such as intelligent mobile robot, digital computer control, intelligent user interface, realtime data processing, ultrasonic signal processing, intelligent user interface, intelligent defect recognition, are studied and examined at first. The high performance and compact size inspection system is designed, and if implemented, it is expected to be very efficient in economic point of view. In addition, the use of integrated SW system leads to the reduction of human errors. Through the analysis results and experiences, we investigated the further feasibility of basic technology applications to the various similar operation systems in NPP. (Author)

Efficient morse decompositions of vector fields.

Science.gov (United States)

Chen, Guoning; Mischaikow, Konstantin; Laramee, Robert S; Zhang, Eugene

2008-01-01

Existing topology-based vector field analysis techniques rely on the ability to extract the individual trajectories such as fixed points, periodic orbits, and separatrices that are sensitive to noise and errors introduced by simulation and interpolation. This can make such vector field analysis unsuitable for rigorous interpretations. We advocate the use of Morse decompositions, which are robust with respect to perturbations, to encode the topological structures of a vector field in the form of a directed graph, called a Morse connection graph (MCG). While an MCG exists for every vector field, it need not be unique. Previous techniques for computing MCG's, while fast, are overly conservative and usually results in MCG's that are too coarse to be useful for the applications. To address this issue, we present a new technique for performing Morse decomposition based on the concept of tau-maps, which typically provides finer MCG's than existing techniques. Furthermore, the choice of tau provides a natural tradeoff between the fineness of the MCG's and the computational costs. We provide efficient implementations of Morse decomposition based on tau-maps, which include the use of forward and backward mapping techniques and an adaptive approach in constructing better approximations of the images of the triangles in the meshes used for simulation.. Furthermore, we propose the use of spatial tau-maps in addition to the original temporal tau-maps. These techniques provide additional trade-offs between the quality of the MCGs and the speed of computation. We demonstrate the utility of our technique with various examples in the plane and on surfaces including engine simulation data sets.

Introduction to the SP theory of intelligence

OpenAIRE

Wolff, J Gerard

2018-01-01

This article provides a brief introduction to the "Theory of Intelligence" and its realisation in the "SP Computer Model". The overall goal of the SP programme of research, in accordance with long-established principles in science, has been the simplification and integration of observations and concepts across artificial intelligence, mainstream computing, mathematics, and human learning, perception, and cognition. In broad terms, the SP system is a brain-like system that takes in "New" infor...

Computer-aided diagnosis and artificial intelligence in clinical imaging.

Science.gov (United States)

Shiraishi, Junji; Li, Qiang; Appelbaum, Daniel; Doi, Kunio

2011-11-01

Computer-aided diagnosis (CAD) is rapidly entering the radiology mainstream. It has already become a part of the routine clinical work for the detection of breast cancer with mammograms. The computer output is used as a "second opinion" in assisting radiologists' image interpretations. The computer algorithm generally consists of several steps that may include image processing, image feature analysis, and data classification via the use of tools such as artificial neural networks (ANN). In this article, we will explore these and other current processes that have come to be referred to as "artificial intelligence." One element of CAD, temporal subtraction, has been applied for enhancing interval changes and for suppressing unchanged structures (eg, normal structures) between 2 successive radiologic images. To reduce misregistration artifacts on the temporal subtraction images, a nonlinear image warping technique for matching the previous image to the current one has been developed. Development of the temporal subtraction method originated with chest radiographs, with the method subsequently being applied to chest computed tomography (CT) and nuclear medicine bone scans. The usefulness of the temporal subtraction method for bone scans was demonstrated by an observer study in which reading times and diagnostic accuracy improved significantly. An additional prospective clinical study verified that the temporal subtraction image could be used as a "second opinion" by radiologists with negligible detrimental effects. ANN was first used in 1990 for computerized differential diagnosis of interstitial lung diseases in CAD. Since then, ANN has been widely used in CAD schemes for the detection and diagnosis of various diseases in different imaging modalities, including the differential diagnosis of lung nodules and interstitial lung diseases in chest radiography, CT, and position emission tomography/CT. It is likely that CAD will be integrated into picture archiving and

Methods of Computational Intelligence in the Context of Quality Assurance in Foundry Products

Directory of Open Access Journals (Sweden)

Rojek G.

2016-06-01

Full Text Available One way to ensure the required technical characteristics of castings is the strict control of production parameters affecting the quality of the finished products. If the production process is improperly configured, the resulting defects in castings lead to huge losses. Therefore, from the point of view of economics, it is advisable to use the methods of computational intelligence in the field of quality assurance and adjustment of parameters of future production. At the same time, the development of knowledge in the field of metallurgy, aimed to raise the technical level and efficiency of the manufacture of foundry products, should be followed by the development of information systems to support production processes in order to improve their effectiveness and compliance with the increasingly more stringent requirements of ergonomics, occupational safety, environmental protection and quality. This article is a presentation of artificial intelligence methods used in practical applications related to quality assurance. The problem of control of the production process involves the use of tools such as the induction of decision trees, fuzzy logic, rough set theory, artificial neural networks or case-based reasoning.

Recent developments in spatial analysis spatial statistics, behavioural modelling, and computational intelligence

CERN Document Server

Getis, Arthur

1997-01-01

In recent years, spatial analysis has become an increasingly active field, as evidenced by the establishment of educational and research programs at many universities. Its popularity is due mainly to new technologies and the development of spatial data infrastructures. This book illustrates some recent developments in spatial analysis, behavioural modelling, and computational intelligence. World renown spatial analysts explain and demonstrate their new and insightful models and methods. The applications are in areas of societal interest such as the spread of infectious diseases, migration behaviour, and retail and agricultural location strategies. In addition, there is emphasis on the uses of new technologoies for the analysis of spatial data through the application of neural network concepts.

1st International Scientific Conference on Intelligent Information Technologies for Industry

CERN Document Server

Kovalev, Sergey; Tarassov, Valery; Snášel, Václav

2016-01-01

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.

13th International Conference on Distributed Computing and Artificial Intelligence

CERN Document Server

Silvestri, Marcello; González, Sara

2016-01-01

The special session Decision Economics (DECON) 2016 is a scientific forum by which to share ideas, projects, researches results, models and experiences associated with the complexity of behavioral decision processes aiming at explaining socio-economic phenomena. DECON 2016 held in the University of Seville, Spain, as part of the 13th International Conference on Distributed Computing and Artificial Intelligence (DCAI) 2016. In the tradition of Herbert A. Simon’s interdisciplinary legacy, this book dedicates itself to the interdisciplinary study of decision-making in the recognition that relevant decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, small and international business, management, operations, and production. Decision-making issues are of crucial importance in economics. Not surprisingly, the study of decision-making has received a growing empirical research efforts in the applied economic literature over the last ...

Time Series Analysis, Modeling and Applications A Computational Intelligence Perspective

CERN Document Server

Chen, Shyi-Ming

2013-01-01

Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological a...

8th Asian Conference on Intelligent Information and Database Systems

CERN Document Server

Madeyski, Lech; Nguyen, Ngoc

2016-01-01

The objective of this book is to contribute to the development of the intelligent information and database systems with the essentials of current knowledge, experience and know-how. The book contains a selection of 40 chapters based on original research presented as posters during the 8th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2016) held on 14–16 March 2016 in Da Nang, Vietnam. The papers to some extent reflect the achievements of scientific teams from 17 countries in five continents. The volume is divided into six parts: (a) Computational Intelligence in Data Mining and Machine Learning, (b) Ontologies, Social Networks and Recommendation Systems, (c) Web Services, Cloud Computing, Security and Intelligent Internet Systems, (d) Knowledge Management and Language Processing, (e) Image, Video, Motion Analysis and Recognition, and (f) Advanced Computing Applications and Technologies. The book is an excellent resource for researchers, those working in artificial intelligence, mu...

On the de Rham–Wu decomposition for Riemannian and Lorentzian manifolds

International Nuclear Information System (INIS)

Galaev, Anton S

2014-01-01

It is explained how to find the de Rham decomposition of a Riemannian manifold and the Wu decomposition of a Lorentzian manifold. For that it is enough to find parallel symmetric bilinear forms on the manifold, and do some linear algebra. This result will allow to compute the connected holonomy group of an arbitrary Riemannian or Lorentzian manifold. (paper)

Intelligent Continuous Double Auction method For Service Allocation in Cloud Computing

Directory of Open Access Journals (Sweden)

Nima Farajian

2013-10-01

Full Text Available Market-oriented approach is an effective method for resource management because of its regulation of supply and demand and is suitable for cloud environment where the computing resources, either software or hardware, are virtualized and allocated as services from providers to users. In this paper a continuous double auction method for efficient cloud service allocation is presented in which i enables consumers to order various resources (services for workflows and coallocation, ii consumers and providers make bid and request prices based on deadline and workload time and in addition providers can tradeoff between utilization time and price of bids, iii auctioneers can intelligently find optimum matching by sharing and merging resources which result more trades. Experimental results show that proposed method is efficient in terms of successful allocation rate and resource utilization.

Nonconformity problem in 3D Grid decomposition

Czech Academy of Sciences Publication Activity Database

Kolcun, Alexej

2002-01-01

Roč. 10, č. 1 (2002), s. 249-253 ISSN 1213-6972. [International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2002/10./. Plzeň, 04.02.2002-08.02.2002] R&D Projects: GA ČR GA105/99/1229; GA ČR GA105/01/1242 Institutional research plan: CEZ:AV0Z3086906 Keywords : structured mesh * decomposition * nonconformity Subject RIV: BA - General Mathematics

Individual Differences in Learning from an Intelligent Discovery World: Smithtown.

Science.gov (United States)

Shute, Valerie J.

"Smithtown" is an intelligent computer program designed to enhance an individual's scientific inquiry skills as well as to provide an environment for learning principles of basic microeconomics. It was hypothesized that intelligent computer instruction on applying effective interrogative skills (e.g., changing one variable at a time…

Applications of artificial intelligence to scientific research

Science.gov (United States)

Prince, Mary Ellen

1986-01-01

Artificial intelligence (AI) is a growing field which is just beginning to make an impact on disciplines other than computer science. While a number of military and commercial applications were undertaken in recent years, few attempts were made to apply AI techniques to basic scientific research. There is no inherent reason for the discrepancy. The characteristics of the problem, rather than its domain, determines whether or not it is suitable for an AI approach. Expert system, intelligent tutoring systems, and learning programs are examples of theoretical topics which can be applied to certain areas of scientific research. Further research and experimentation should eventurally make it possible for computers to act as intelligent assistants to scientists.

11th International Conference on Computer and Information Science

CERN Document Server

Computer and Information 2012

2012-01-01

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence – quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results.   The purpose of the 11th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2012...

DREAMS and IMAGE: A Model and Computer Implementation for Concurrent, Life-Cycle Design of Complex Systems

Science.gov (United States)

Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.

1995-01-01

Computing architectures are being assembled that extend concurrent engineering practices by providing more efficient execution and collaboration on distributed, heterogeneous computing networks. Built on the successes of initial architectures, requirements for a next-generation design computing infrastructure can be developed. These requirements concentrate on those needed by a designer in decision-making processes from product conception to recycling and can be categorized in two areas: design process and design information management. A designer both designs and executes design processes throughout design time to achieve better product and process capabilities while expanding fewer resources. In order to accomplish this, information, or more appropriately design knowledge, needs to be adequately managed during product and process decomposition as well as recomposition. A foundation has been laid that captures these requirements in a design architecture called DREAMS (Developing Robust Engineering Analysis Models and Specifications). In addition, a computing infrastructure, called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment), is being developed that satisfies design requirements defined in DREAMS and incorporates enabling computational technologies.

Employing Artificial Intelligence To Minimise Internet Fraud

Directory of Open Access Journals (Sweden)

Edward Wong Sek Khin

2009-12-01

Full Text Available Internet fraud is increasing on a daily basis with new methods for extracting funds from government, corporations, businesses in general, and persons appearing almost hourly. The increases in on-line purchasing and the constant vigilance of both seller and buyer have meant that the criminal seems to be one-step ahead at all times. To pre-empt or to stop fraud before it can happen occurs in the non-computer based daily transactions of today because of the natural intelligence of the players, both seller and buyer. Currently, even with advances in computing techniques, intelligence is not the current strength of any computing system of today, yet techniques are available which may reduce the occurrences of fraud, and are usually referred to as artificial intelligence systems.This paper provides an overview of the use of current artificial intelligence (AI techniques as a means of combating fraud.Initially the paper describes how artificial intelligence techniques are employed in systems for detecting credit card fraud (online and offline fraud and insider trading.Following this, an attempt is made to propose the using of MonITARS (Monitoring Insider Trading and Regulatory Surveillance Systems framework which use a combination of genetic algorithms, neural nets and statistical analysis in detecting insider dealing. Finally, the paper discusses future research agenda to the role of using MonITARS system.

FPGA Based Intelligent Co-operative Processor in Memory Architecture

DEFF Research Database (Denmark)

Ahmed, Zaki; Sotudeh, Reza; Hussain, Dil Muhammad Akbar

2011-01-01

benefits of PIM, a concept of Co-operative Intelligent Memory (CIM) was developed by the intelligent system group of University of Hertfordshire, based on the previously developed Co-operative Pseudo Intelligent Memory (CPIM). This paper provides an overview on previous works (CPIM, CIM) and realization......In a continuing effort to improve computer system performance, Processor-In-Memory (PIM) architecture has emerged as an alternative solution. PIM architecture incorporates computational units and control logic directly on the memory to provide immediate access to the data. To exploit the potential...

Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data.

Science.gov (United States)

Liu, Yuanyuan; Shang, Fanhua; Jiao, Licheng; Cheng, James; Cheng, Hong

2015-11-01

In recent years, low-rank tensor completion (LRTC) problems have received a significant amount of attention in computer vision, data mining, and signal processing. The existing trace norm minimization algorithms for iteratively solving LRTC problems involve multiple singular value decompositions of very large matrices at each iteration. Therefore, they suffer from high computational cost. In this paper, we propose a novel trace norm regularized CANDECOMP/PARAFAC decomposition (TNCP) method for simultaneous tensor decomposition and completion. We first formulate a factor matrix rank minimization model by deducing the relation between the rank of each factor matrix and the mode- n rank of a tensor. Then, we introduce a tractable relaxation of our rank function, and then achieve a convex combination problem of much smaller-scale matrix trace norm minimization. Finally, we develop an efficient algorithm based on alternating direction method of multipliers to solve our problem. The promising experimental results on synthetic and real-world data validate the effectiveness of our TNCP method. Moreover, TNCP is significantly faster than the state-of-the-art methods and scales to larger problems.

Thermal unimolecular decomposition of methanol. Zum thermischen unimolekularen Zerfall von Methanol

Energy Technology Data Exchange (ETDEWEB)

Spindler, K

1979-01-01

The thermal unimolecular decomposition of methanol and that of acetone (1B) were investigated experimentally after reflected shockwaves, by following up the OH and CH/sub 3/ absorption or the CH/sub 3/ and acetone absorption respectively. A computer simulation of the decomposition of methanol and the subsequent reactions was done. This gave velocity constants for some reactions, which are different from those that are found in the literature. The experimental investigation of the decomposition of acetone, from comparison of the results with the data in the literature, shows that the observations of CH/sub 3/ absorption are very suitable for obtaining velocity constants for decomposition reactions, where CH/sub 3/ radicals are formed in the first stage.

Intelligent Information Systems Institute

National Research Council Canada - National Science Library

Gomes, Carla

2004-01-01

...) at Cornell during the first three years of operation. IISI's mandate is threefold: To perform and stimulate research in computational and data-intensive methods for intelligent decision making systems...

Artificial Intelligence (AI) Studies in Water Resources

OpenAIRE

Ay, Murat; Özyıldırım, Serhat

2018-01-01

Artificial intelligence has been extensively used in many areas such as computer science,robotics, engineering, medicine, translation, economics, business, and psychology. Variousstudies in the literature show that the artificial intelligence in modeling approaches give closeresults to the real data for solution of linear, non-linear, and other systems. In this study, wereviewed the current state-of-the-art and progress on the modelling of artificial intelligence forwater variables: rainfall-...

THRESHOLD LOGIC IN ARTIFICIAL INTELLIGENCE

Science.gov (United States)

COMPUTER LOGIC, ARTIFICIAL INTELLIGENCE , BIONICS, GEOMETRY, INPUT OUTPUT DEVICES, LINEAR PROGRAMMING, MATHEMATICAL LOGIC, MATHEMATICAL PREDICTION, NETWORKS, PATTERN RECOGNITION, PROBABILITY, SWITCHING CIRCUITS, SYNTHESIS

A comprehensive review of the use of computational intelligence methods in mineral exploration

Directory of Open Access Journals (Sweden)

Habibollah Bazdar

2017-11-01

Full Text Available Introduction Mineral exploration is a process by which it is decided whether or not continuing explorations at the end of each stage t will be cost-effective or not. This decision is dependent upon many factors including technical factors, economic, social and other related factors. All new methods used in mineral exploration are meant to make this decision making more simplified. In recent years, advanced computational intelligence methods for modeling along with many other disciplines of science, including the science of mineral exploration have been used. Although the results of the application of these methods show a good performance, it is essential to determine the mineral potential in terms of geology, mineralogy, petrology and other factors for a final decision. The purpose of this paper is to provide a comprehensive set of mineral exploration research and different applications of computational intelligence techniques in this respect during the last decades. Materials and methods Artificial neural network and its application in mineral exploration Artificial neural network (ANN is a series of communications between the units or nodes that try to function like neurons of the human brain (Jorjani et al., 2008. The network processing capability of communication between the units and the weights connection originates or comes from learning or are predetermined (Monjezi and Dehghani, 2008. The ANN method has been applied in different branches of mining exploration in the last decades (Brown et al., 2000; Leite and de Souza Filho, 2009; Porwal et al., 2003. Support vector machines (SVM and its application in mineral exploration SVM uses a set of examples with known class of information to build a linear hyperplane separating samples of different classes. This initial dataset is known as a training set and every sample within it is characterized by features upon which the classification is based (Smirnoff et al., 2008. The SVM classifier is a

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation

Directory of Open Access Journals (Sweden)

Hongzhi Hu

2015-01-01

Full Text Available Due to the extensive social influence, public health emergency has attracted great attention in today’s society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event’s social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback based on ACP simulation system which was successfully applied to the analysis of A (H1N1 Flu emergency.

A Python Engine for Teaching Artificial Intelligence in Games

OpenAIRE

Riedl, Mark O.

2015-01-01

Computer games play an important role in our society and motivate people to learn computer science. Since artificial intelligence is integral to most games, they can also be used to teach artificial intelligence. We introduce the Game AI Game Engine (GAIGE), a Python game engine specifically designed to teach about how AI is used in computer games. A progression of seven assignments builds toward a complete, working Multi-User Battle Arena (MOBA) game. We describe the engine, the assignments,...

Using dynamic mode decomposition for real-time background/foreground separation in video

Science.gov (United States)

Kutz, Jose Nathan; Grosek, Jacob; Brunton, Steven; Fu, Xing; Pendergrass, Seth

2017-06-06

The technique of dynamic mode decomposition (DMD) is disclosed herein for the purpose of robustly separating video frames into background (low-rank) and foreground (sparse) components in real-time. Foreground/background separation is achieved at the computational cost of just one singular value decomposition (SVD) and one linear equation solve, thus producing results orders of magnitude faster than robust principal component analysis (RPCA). Additional techniques, including techniques for analyzing the video for multi-resolution time-scale components, and techniques for reusing computations to allow processing of streaming video in real time, are also described herein.

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation.   Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation. Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

Brain computer interfaces as intelligent sensors for enhancing human-computer interaction

NARCIS (Netherlands)

Poel, M.; Nijboer, F.; Broek, E.L. van den; Fairclough, S.; Nijholt, A.

2012-01-01

BCIs are traditionally conceived as a way to control apparatus, an interface that allows you to act on" external devices as a form of input control. We propose an alternative use of BCIs, that of monitoring users as an additional intelligent sensor to enrich traditional means of interaction. This

Brain computer interfaces as intelligent sensors for enhancing human-computer interaction

NARCIS (Netherlands)

Poel, Mannes; Nijboer, Femke; van den Broek, Egon; Fairclough, Stephen; Morency, Louis-Philippe; Bohus, Dan; Aghajan, Hamid; Nijholt, Antinus; Cassell, Justine; Epps, Julien

2012-01-01

BCIs are traditionally conceived as a way to control apparatus, an interface that allows you to "act on" external devices as a form of input control. We propose an alternative use of BCIs, that of monitoring users as an additional intelligent sensor to enrich traditional means of interaction. This

USE OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN QUALITY IMPROVING PROCESS

OpenAIRE

KALİTE İYİLEŞTİRME SÜRECİNDE YAPAY ZEKÃ KAYA; Orhan ENGİN

2005-01-01

Today, changing of competition conditions and customer preferences caused to happen many differences in the viewpoint of firms' quality studies. At the same time, improvements in computer technologies accelerated use of artificial intelligence. Artificial intelligence technologies are being used to solve many industry problems. In this paper, we investigated the use of artificial intelligence techniques to solve quality problems. The artificial intelligence techniques, which are used in quali...

6th International Symposium on Ambient Intelligence

CERN Document Server

Novais, Paulo; Pereira, António; González, Gabriel; Fernández-Caballero, Antonio

2015-01-01

This volume contains the proceedings of the 6th International Symposium on Ambient Intelligence (ISAmI 2015), held in Salamanca, Spain on June 3th-5th at the University of Salamanca. After a careful review, 27 papers from 10 different countries were selected to be presented in ISAmI 2015 at the conference and published in the proceedings.  ISAmI has been running annually and aiming to bring together researchers from various disciplines that constitute the scientific field of Ambient Intelligence to present and discuss the latest results, new ideas, projects and lessons learned, namely in terms of software and applications, and aims to bring together researchers from various disciplines that are interested in all aspects of this area. Ambient Intelligence is a recent paradigm emerging from Artificial Intelligence, where computers are used as proactive tools assisting people with their day-to-day activities, making everyone’s life more comfortable. Another main concern of AmI originates from the human comput...

Domain decomposition method for solving the neutron diffusion equation

International Nuclear Information System (INIS)

Coulomb, F.

1989-03-01

The aim of this work is to study methods for solving the neutron diffusion equation; we are interested in methods based on a classical finite element discretization and well suited for use on parallel computers. Domain decomposition methods seem to answer this preoccupation. This study deals with a decomposition of the domain. A theoretical study is carried out for Lagrange finite elements and some examples are given; in the case of mixed dual finite elements, the study is based on examples [fr

Decomposition of toluene in a steady-state atmospheric-pressure glow discharge

International Nuclear Information System (INIS)

Trushkin, A. N.; Grushin, M. E.; Kochetov, I. V.; Trushkin, N. I.; Akishev, Yu. S.

2013-01-01

Results are presented from experimental studies of decomposition of toluene (C 6 H 5 CH 3 ) in a polluted air flow by means of a steady-state atmospheric pressure glow discharge at different water vapor contents in the working gas. The experimental results on the degree of C 6 H 5 CH 3 removal are compared with the results of computer simulations conducted in the framework of the developed kinetic model of plasma chemical decomposition of toluene in the N 2 : O 2 : H 2 O gas mixture. A substantial influence of the gas flow humidity on toluene decomposition in the atmospheric pressure glow discharge is demonstrated. The main mechanisms of the influence of humidity on C 6 H 5 CH 3 decomposition are determined. The existence of two stages in the process of toluene removal, which differ in their duration and the intensity of plasma chemical decomposition of C 6 H 5 CH 3 is established. Based on the results of computer simulations, the composition of the products of plasma chemical reactions at the output of the reactor is analyzed as a function of the specific energy deposition and gas flow humidity. The existence of a catalytic cycle in which hydroxyl radical OH acts a catalyst and which substantially accelerates the recombination of oxygen atoms and suppression of ozone generation when the plasma-forming gas contains water vapor is established.

Decomposition of toluene in a steady-state atmospheric-pressure glow discharge

Science.gov (United States)

Trushkin, A. N.; Grushin, M. E.; Kochetov, I. V.; Trushkin, N. I.; Akishev, Yu. S.

2013-02-01

Results are presented from experimental studies of decomposition of toluene (C6H5CH3) in a polluted air flow by means of a steady-state atmospheric pressure glow discharge at different water vapor contents in the working gas. The experimental results on the degree of C6H5CH3 removal are compared with the results of computer simulations conducted in the framework of the developed kinetic model of plasma chemical decomposition of toluene in the N2: O2: H2O gas mixture. A substantial influence of the gas flow humidity on toluene decomposition in the atmospheric pressure glow discharge is demonstrated. The main mechanisms of the influence of humidity on C6H5CH3 decomposition are determined. The existence of two stages in the process of toluene removal, which differ in their duration and the intensity of plasma chemical decomposition of C6H5CH3 is established. Based on the results of computer simulations, the composition of the products of plasma chemical reactions at the output of the reactor is analyzed as a function of the specific energy deposition and gas flow humidity. The existence of a catalytic cycle in which hydroxyl radical OH acts a catalyst and which substantially accelerates the recombination of oxygen atoms and suppression of ozone generation when the plasma-forming gas contains water vapor is established.

Radical decomposition of 2,4-dinitrotoluene (DNT at conditions of advanced oxidation. Computational study

Directory of Open Access Journals (Sweden)

Liudmyla K. Sviatenko

2016-12-01

Full Text Available At the present time one of the main remediation technologies for such environmental pollutant as 2,4-dinitrotoluene (DNT is advanced oxidation processes (AOPs. Since hydroxyl radical is the most common active species for AOPs, in particular for Fenton oxidation, the study modeled mechanism of interaction between DNT and hydroxyl radical at SMD(Pauling/M06-2X/6-31+G(d,p level. Computed results allow to suggest the most energetically favourable pathway for the process. DNT decomposition consists of sequential hydrogen abstractions and hydroxyl attachments passing through 2,4-dinitrobenzyl alcohol, 2,4-dinitrobenzaldehyde, and 2,4-dinitrobenzoic acid. Further replacement of nitro- and carboxyl groups by hydroxyl leads to 2,4-dihydroxybenzoic acid and 2,4-dinitrophenol, respectively. Reaction intermediates and products are experimentally confirmed. Mostly of reaction steps have low energy barriers, some steps are diffusion controlled. The whole process is highly exothermic.

Detailed Chemical Kinetic Modeling of Hydrazine Decomposition

Science.gov (United States)

Meagher, Nancy E.; Bates, Kami R.

2000-01-01

The purpose of this research project is to develop and validate a detailed chemical kinetic mechanism for gas-phase hydrazine decomposition. Hydrazine is used extensively in aerospace propulsion, and although liquid hydrazine is not considered detonable, many fuel handling systems create multiphase mixtures of fuels and fuel vapors during their operation. Therefore, a thorough knowledge of the decomposition chemistry of hydrazine under a variety of conditions can be of value in assessing potential operational hazards in hydrazine fuel systems. To gain such knowledge, a reasonable starting point is the development and validation of a detailed chemical kinetic mechanism for gas-phase hydrazine decomposition. A reasonably complete mechanism was published in 1996, however, many of the elementary steps included had outdated rate expressions and a thorough investigation of the behavior of the mechanism under a variety of conditions was not presented. The current work has included substantial revision of the previously published mechanism, along with a more extensive examination of the decomposition behavior of hydrazine. An attempt to validate the mechanism against the limited experimental data available has been made and was moderately successful. Further computational and experimental research into the chemistry of this fuel needs to be completed.

A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

Science.gov (United States)

Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

2016-06-01

To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

Experiments with microcomputer-based artificial intelligence environments

Science.gov (United States)

Summers, E.G.; MacDonald, R.A.

1988-01-01

The U.S. Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the "artificial intelligence computer," and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently, inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Gold Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming. ?? 1988 International Association for Mathematical Geology.

Artificial Intelligence Techniques and Methodology

OpenAIRE

Carbonell, Jaime G.; Sleeman, Derek

1982-01-01

Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

High Performance Polar Decomposition on Distributed Memory Systems

KAUST Repository

Sukkari, Dalal E.

2016-08-08

The polar decomposition of a dense matrix is an important operation in linear algebra. It can be directly calculated through the singular value decomposition (SVD) or iteratively using the QR dynamically-weighted Halley algorithm (QDWH). The former is difficult to parallelize due to the preponderant number of memory-bound operations during the bidiagonal reduction. We investigate the latter scenario, which performs more floating-point operations but exposes at the same time more parallelism, and therefore, runs closer to the theoretical peak performance of the system, thanks to more compute-bound matrix operations. Profiling results show the performance scalability of QDWH for calculating the polar decomposition using around 9200 MPI processes on well and ill-conditioned matrices of 100K×100K problem size. We study then the performance impact of the QDWH-based polar decomposition as a pre-processing step toward calculating the SVD itself. The new distributed-memory implementation of the QDWH-SVD solver achieves up to five-fold speedup against current state-of-the-art vendor SVD implementations. © Springer International Publishing Switzerland 2016.

Intelligent structural optimization: Concept, Model and Methods

International Nuclear Information System (INIS)

Lu, Dagang; Wang, Guangyuan; Peng, Zhang

2002-01-01

Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented

Proceedings of the International Conference on Information Systems Design and Intelligent Applications 2012

CERN Document Server

Avadhani, P; Abraham, Ajith

2012-01-01

This volume contains the papers presented at INDIA-2012: International conference on  Information system Design and Intelligent Applications held on January 5-7, 2012 in Vishakhapatnam, India. This conference was organized by Computer Society of India (CSI), Vishakhapatnam chapter well supported by Vishakhapatnam Steel, RINL, Govt of India. It contains 108 papers contributed by authors from six different countries across four continents. These research papers mainly focused on intelligent applications and various system design issues. The papers cover a wide range of topics of computer science and information technology discipline ranging from image processing, data base application, data mining, grid and cloud computing, bioinformatics among many others. The various intelligent tools like swarm intelligence, artificial intelligence, evolutionary algorithms, bio-inspired algorithms have been applied in different papers for solving various challenging IT related problems.

Multi-material decomposition of spectral CT images

Science.gov (United States)

Mendonça, Paulo R. S.; Bhotika, Rahul; Maddah, Mahnaz; Thomsen, Brian; Dutta, Sandeep; Licato, Paul E.; Joshi, Mukta C.

2010-04-01

Spectral Computed Tomography (Spectral CT), and in particular fast kVp switching dual-energy computed tomography, is an imaging modality that extends the capabilities of conventional computed tomography (CT). Spectral CT enables the estimation of the full linear attenuation curve of the imaged subject at each voxel in the CT volume, instead of a scalar image in Hounsfield units. Because the space of linear attenuation curves in the energy ranges of medical applications can be accurately described through a two-dimensional manifold, this decomposition procedure would be, in principle, limited to two materials. This paper describes an algorithm that overcomes this limitation, allowing for the estimation of N-tuples of material-decomposed images. The algorithm works by assuming that the mixing of substances and tissue types in the human body has the physicochemical properties of an ideal solution, which yields a model for the density of the imaged material mix. Under this model the mass attenuation curve of each voxel in the image can be estimated, immediately resulting in a material-decomposed image triplet. Decomposition into an arbitrary number of pre-selected materials can be achieved by automatically selecting adequate triplets from an application-specific material library. The decomposition is expressed in terms of the volume fractions of each constituent material in the mix; this provides for a straightforward, physically meaningful interpretation of the data. One important application of this technique is in the digital removal of contrast agent from a dual-energy exam, producing a virtual nonenhanced image, as well as in the quantification of the concentration of contrast observed in a targeted region, thus providing an accurate measure of tissue perfusion.

Correct use of the Gordon decomposition in the calculation of nucleon magnetic dipole moments

International Nuclear Information System (INIS)

Mekhfi, Mustapha

2008-01-01

We perform the calculation of the nucleon dipole magnetic moment in full detail using the Gordon decomposition of the free quark current. This calculation has become necessary because of frequent misuse of the Gordon decomposition by some authors in computing the nucleon dipole magnetic moment

Intelligent Cloud Learning Model for Online Overseas Chinese Education

Directory of Open Access Journals (Sweden)

Yidong Chen

2015-02-01

Full Text Available With the development of Chinese economy, oversea Chinese education has been paid more and more attention. However, the overseas Chinese education resource is relatively lack because of historical reasons, which hindered further development . How to better share the Chinese education resources and provide intelligent personalized information service for overseas student is a key problem to be solved. In recent years, the rise of cloud computing provides us an opportunity to realize intelligent learning mode. Cloud computing offers some advantages by allowing users to use infrastructure, platforms and software . In this paper we proposed an intelligent cloud learning model based on cloud computing. The learning model can utilize network resources sufficiently to implement resource sharing according to the personal needs of students, and provide a good practicability for online overseas Chinese education.

Ozone decomposition

Directory of Open Access Journals (Sweden)

Batakliev Todor

2014-06-01

Full Text Available Catalytic ozone decomposition is of great significance because ozone is a toxic substance commonly found or generated in human environments (aircraft cabins, offices with photocopiers, laser printers, sterilizers. Considerable work has been done on ozone decomposition reported in the literature. This review provides a comprehensive summary of the literature, concentrating on analysis of the physico-chemical properties, synthesis and catalytic decomposition of ozone. This is supplemented by a review on kinetics and catalyst characterization which ties together the previously reported results. Noble metals and oxides of transition metals have been found to be the most active substances for ozone decomposition. The high price of precious metals stimulated the use of metal oxide catalysts and particularly the catalysts based on manganese oxide. It has been determined that the kinetics of ozone decomposition is of first order importance. A mechanism of the reaction of catalytic ozone decomposition is discussed, based on detailed spectroscopic investigations of the catalytic surface, showing the existence of peroxide and superoxide surface intermediates

Tensor renormalization group with randomized singular value decomposition

Science.gov (United States)

Morita, Satoshi; Igarashi, Ryo; Zhao, Hui-Hai; Kawashima, Naoki

2018-03-01

An algorithm of the tensor renormalization group is proposed based on a randomized algorithm for singular value decomposition. Our algorithm is applicable to a broad range of two-dimensional classical models. In the case of a square lattice, its computational complexity and memory usage are proportional to the fifth and the third power of the bond dimension, respectively, whereas those of the conventional implementation are of the sixth and the fourth power. The oversampling parameter larger than the bond dimension is sufficient to reproduce the same result as full singular value decomposition even at the critical point of the two-dimensional Ising model.

Analysis of Changes in Market Shares of Commercial Banks Operating in Turkey Using Computational Intelligence Algorithms

OpenAIRE

Amasyali, M. Fatih; Demırhan, Ayse; Bal, Mert

2014-01-01

This paper aims to model the change in market share of 30 domestic and foreign banks, which have been operating between the years 1990 and 2009 in Turkey by taking into consideration 20 financial ratios of those banks. Due to the fragile structure of the banking sector in Turkey, this study plays an important role for determining the changes in market share of banks and taking the necessary measures promptly. For this reason, computational intelligence methods have been used in the study. Acc...