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Sample records for intelligent decomposition computer

  1. Designing with computational intelligence

    CERN Document Server

    Lopes, Heitor; Mourelle, Luiza

    2017-01-01

    This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also presents a concise and efficient synthesis of different systems using computationally intelligent techniques.

  2. Intelligent distributed computing

    CERN Document Server

    Thampi, Sabu

    2015-01-01

    This book contains a selection of refereed and revised papers of the Intelligent Distributed Computing Track originally presented at the third International Symposium on Intelligent Informatics (ISI-2014), September 24-27, 2014, Delhi, India.  The papers selected for this Track cover several Distributed Computing and related topics including Peer-to-Peer Networks, Cloud Computing, Mobile Clouds, Wireless Sensor Networks, and their applications.

  3. Computational Intelligence in Intelligent Data Analysis

    CERN Document Server

    Nürnberger, Andreas

    2013-01-01

    Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intell...

  4. Affective Computing and Intelligent Interaction

    CERN Document Server

    2012-01-01

    2012 International Conference on Affective Computing and Intelligent Interaction (ICACII 2012) was the most comprehensive conference focused on the various aspects of advances in Affective Computing and Intelligent Interaction. The conference provided a rare opportunity to bring together worldwide academic researchers and practitioners for exchanging the latest developments and applications in this field such as Intelligent Computing, Affective Computing, Machine Learning, Business Intelligence and HCI.   This volume is a collection of 119 papers selected from 410 submissions from universities and industries all over the world, based on their quality and relevancy to the conference. All of the papers have been peer-reviewed by selected experts.  

  5. Computational Intelligence, Cyber Security and Computational Models

    CERN Document Server

    Anitha, R; Lekshmi, R; Kumar, M; Bonato, Anthony; Graña, Manuel

    2014-01-01

    This book contains cutting-edge research material presented by researchers, engineers, developers, and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security and Computational Models (ICC3) organized by PSG College of Technology, Coimbatore, India during December 19–21, 2013. The materials in the book include theory and applications for design, analysis, and modeling of computational intelligence and security. The book will be useful material for students, researchers, professionals, and academicians. It will help in understanding current research trends and findings and future scope of research in computational intelligence, cyber security, and computational models.

  6. Computer automation and artificial intelligence

    International Nuclear Information System (INIS)

    Hasnain, S.B.

    1992-01-01

    Rapid advances in computing, resulting from micro chip revolution has increased its application manifold particularly for computer automation. Yet the level of automation available, has limited its application to more complex and dynamic systems which require an intelligent computer control. In this paper a review of Artificial intelligence techniques used to augment automation is presented. The current sequential processing approach usually adopted in artificial intelligence has succeeded in emulating the symbolic processing part of intelligence, but the processing power required to get more elusive aspects of intelligence leads towards parallel processing. An overview of parallel processing with emphasis on transputer is also provided. A Fuzzy knowledge based controller for amination drug delivery in muscle relaxant anesthesia on transputer is described. 4 figs. (author)

  7. Computational Intelligence for Engineering Systems

    CERN Document Server

    Madureira, A; Vale, Zita

    2011-01-01

    "Computational Intelligence for Engineering Systems" provides an overview and original analysis of new developments and advances in several areas of computational intelligence. Computational Intelligence have become the road-map for engineers to develop and analyze novel techniques to solve problems in basic sciences (such as physics, chemistry and biology) and engineering, environmental, life and social sciences. The contributions are written by international experts, who provide up-to-date aspects of the topics discussed and present recent, original insights into their own experien

  8. 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.

  9. 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.

  10. Computational intelligence in biomedical imaging

    CERN Document Server

    2014-01-01

    This book provides a comprehensive overview of the state-of-the-art computational intelligence research and technologies in biomedical images with emphasis on biomedical decision making. Biomedical imaging offers useful information on patients’ medical conditions and clues to causes of their symptoms and diseases. Biomedical images, however, provide a large number of images which physicians must interpret. Therefore, computer aids are demanded and become indispensable in physicians’ decision making. This book discusses major technical advancements and research findings in the field of computational intelligence in biomedical imaging, for example, computational intelligence in computer-aided diagnosis for breast cancer, prostate cancer, and brain disease, in lung function analysis, and in radiation therapy. The book examines technologies and studies that have reached the practical level, and those technologies that are becoming available in clinical practices in hospitals rapidly such as computational inte...

  11. 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.

  12. 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 ...

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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...

  19. 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

  20. 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

  1. 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...

  2. 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 ...

  3. 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.)

  4. International Conference on Computational Intelligence 2015

    CERN Document Server

    Saha, Sujan

    2017-01-01

    This volume comprises the proceedings of the International Conference on Computational Intelligence 2015 (ICCI15). This book aims to bring together work from leading academicians, scientists, researchers and research scholars from across the globe on all aspects of computational intelligence. The work is composed mainly of original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work in all areas of computational intelligence. Specifically, the major topics covered include classical computational intelligence models and artificial intelligence, neural networks and deep learning, evolutionary swarm and particle algorithms, hybrid systems optimization, constraint programming, human-machine interaction, computational intelligence for the web analytics, robotics, computational neurosciences, neurodynamics, bioinspired and biomorphic algorithms, cross disciplinary topics and applications. The contents of this volume will be of use to researchers and professionals alike....

  5. 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...

  6. Computational Intelligence in Information Systems Conference

    CERN Document Server

    Au, Thien-Wan; Omar, Saiful

    2017-01-01

    This book constitutes the Proceedings of the Computational Intelligence in Information Systems conference (CIIS 2016), held in Brunei, November 18–20, 2016. The CIIS conference provides a platform for researchers to exchange the latest ideas and to present new research advances in general areas related to computational intelligence and its applications. The 26 revised full papers presented in this book have been carefully selected from 62 submissions. They cover a wide range of topics and application areas in computational intelligence and informatics.

  7. 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.

  8. Applications of computational intelligence in nuclear reactors

    International Nuclear Information System (INIS)

    Jayalal, M.L.; Jehadeesan, R.

    2016-01-01

    Computational intelligence techniques have been successfully employed in a wide range of applications which include the domains of medical, bioinformatics, electronics, communications and business. There has been progress in applying of computational intelligence in the nuclear reactor domain during the last two decades. The stringent nuclear safety regulations pertaining to reactor environment present challenges in the application of computational intelligence in various nuclear sub-systems. The applications of various methods of computational intelligence in the domain of nuclear reactors are discussed in this paper. (author)

  9. Intelligent computing systems emerging application areas

    CERN Document Server

    Virvou, Maria; Jain, Lakhmi

    2016-01-01

    This book at hand explores emerging scientific and technological areas in which Intelligent Computing Systems provide efficient solutions and, thus, may play a role in the years to come. It demonstrates how Intelligent Computing Systems make use of computational methodologies that mimic nature-inspired processes to address real world problems of high complexity for which exact mathematical solutions, based on physical and statistical modelling, are intractable. Common intelligent computational methodologies are presented including artificial neural networks, evolutionary computation, genetic algorithms, artificial immune systems, fuzzy logic, swarm intelligence, artificial life, virtual worlds and hybrid methodologies based on combinations of the previous. The book will be useful to researchers, practitioners and graduate students dealing with mathematically-intractable problems. It is intended for both the expert/researcher in the field of Intelligent Computing Systems, as well as for the general reader in t...

  10. New trends in computational collective intelligence

    CERN Document Server

    Kim, Sang-Wook; Trawiński, Bogdan

    2015-01-01

    This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods an...

  11. 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.

  12. 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...

  13. 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.

  14. 10th International Symposium on Intelligent Distributed Computing

    CERN Document Server

    Seghrouchni, Amal; Beynier, Aurélie; Camacho, David; Herpson, Cédric; Hindriks, Koen; Novais, Paulo

    2017-01-01

    This book presents the combined peer-reviewed proceedings of the tenth International Symposium on Intelligent Distributed Computing (IDC’2016), which was held in Paris, France from October 10th to 12th, 2016. The 23 contributions address a range of topics related to theory and application 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.

  15. Parallel computing of a climate model on the dawn 1000 by domain decomposition method

    Science.gov (United States)

    Bi, Xunqiang

    1997-12-01

    In this paper the parallel computing of a grid-point nine-level atmospheric general circulation model on the Dawn 1000 is introduced. The model was developed by the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS). The Dawn 1000 is a MIMD massive parallel computer made by National Research Center for Intelligent Computer (NCIC), CAS. A two-dimensional domain decomposition method is adopted to perform the parallel computing. The potential ways to increase the speed-up ratio and exploit more resources of future massively parallel supercomputation are also discussed.

  16. International Conference of Intelligence Computation and Evolutionary Computation ICEC 2012

    CERN Document Server

    Intelligence Computation and Evolutionary Computation

    2013-01-01

    2012 International Conference of Intelligence Computation and Evolutionary Computation (ICEC 2012) is held on July 7, 2012 in Wuhan, China. This conference is sponsored by Information Technology & Industrial Engineering Research Center.  ICEC 2012 is a forum for presentation of new research results of intelligent computation and evolutionary computation. Cross-fertilization of intelligent computation, evolutionary computation, evolvable hardware and newly emerging technologies is strongly encouraged. The forum aims to bring together researchers, developers, and users from around the world in both industry and academia for sharing state-of-art results, for exploring new areas of research and development, and to discuss emerging issues facing intelligent computation and evolutionary computation.

  17. 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.)

  18. 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

  19. 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.

  20. 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 ...

  1. 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.

  2. 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...

  3. 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 ...

  4. 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....

  5. Computational intelligence and neuromorphic computing potential for cybersecurity applications

    Science.gov (United States)

    Pino, Robinson E.; Shevenell, Michael J.; Cam, Hasan; Mouallem, Pierre; Shumaker, Justin L.; Edwards, Arthur H.

    2013-05-01

    In today's highly mobile, networked, and interconnected internet world, the flow and volume of information is overwhelming and continuously increasing. Therefore, it is believed that the next frontier in technological evolution and development will rely in our ability to develop intelligent systems that can help us process, analyze, and make-sense of information autonomously just as a well-trained and educated human expert. In computational intelligence, neuromorphic computing promises to allow for the development of computing systems able to imitate natural neurobiological processes and form the foundation for intelligent system architectures.

  6. 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...

  7. Intelligent Distributed Computing VI : Proceedings of the 6th International Symposium on Intelligent Distributed Computing

    CERN Document Server

    Badica, Costin; Malgeri, Michele; Unland, Rainer

    2013-01-01

    This book represents the combined peer-reviewed proceedings of the Sixth International Symposium on Intelligent Distributed Computing -- IDC~2012, of the International Workshop on Agents for Cloud -- A4C~2012 and of the Fourth International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS~2012. All the events were held in Calabria, Italy during September 24-26, 2012. The 37 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: adaptive and autonomous distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud computing, coalition formation, decision support systems, distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and distributed computational intelligence, parallel evolutionary computing, trus...

  8. 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

  9. 2nd International Conference on Intelligent Computing, Communication & Devices

    CERN Document Server

    Popentiu-Vladicescu, Florin

    2017-01-01

    The book presents high quality papers presented at 2nd International Conference on Intelligent Computing, Communication & Devices (ICCD 2016) organized by Interscience Institute of Management and Technology (IIMT), Bhubaneswar, Odisha, India, during 13 and 14 August, 2016. The book covers all dimensions of intelligent sciences in its three tracks, namely, intelligent computing, intelligent communication and intelligent devices. intelligent computing track covers areas such as intelligent and distributed computing, intelligent grid and cloud computing, internet of things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems. Intelligent communication covers communication and network technologies, including mobile broadband and all optical networks that are the key to groundbreaking inventions of intelligent communication technologies. This covers communication hardware, soft...

  10. 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

  11. 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.

  12. 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.

  13. 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.…

  14. 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.

  15. Computational intelligence in medical informatics

    CERN Document Server

    Gunjan, Vinit

    2015-01-01

    This Brief highlights Informatics and related techniques to Computer Science Professionals, Engineers, Medical Doctors, Bioinformatics researchers and other interdisciplinary researchers. Chapters include the Bioinformatics of Diabetes and several computational algorithms and statistical analysis approach to effectively study the disorders and possible causes along with medical applications.

  16. 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.

  17. 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

  18. Artifical Intelligence for Human Computing

    NARCIS (Netherlands)

    Huang, Th.S.; Nijholt, Antinus; Pantic, Maja; Pentland, A.; Unknown, [Unknown

    2007-01-01

    This book constitutes the thoroughly refereed post-proceedings of two events discussing AI for Human Computing: one Special Session during the Eighth International ACM Conference on Multimodal Interfaces (ICMI 2006), held in Banff, Canada, in November 2006, and a Workshop organized in conjunction

  19. 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

  20. 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)

  1. 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)

  2. 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.  

  3. 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 ...

  4. 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...

  5. 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.

  6. Cloud Computing and Business Intelligence

    Directory of Open Access Journals (Sweden)

    Alexandru Adrian TOLE

    2015-03-01

    Full Text Available The complexity of data resulting from business process is becoming overwhelming for the systems that don't use shared resources. Many aspects of the business process must be recorded and analysed in a short period of time with no errors at all. In order to obtain these results, so that management and other departments know what their next decision/job will be, there must be a continuous exchange and processing of information. "Cloud Computing" is the solution to overcome the problem of processing large amounts of data. By using this technology organizations have the benefit of using shared resources from various systems that are able to face large amount of data processing. This benefits does not only resume to a high performance system but also the costs of using such architecture are much lower.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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...

  13. 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.

  14. 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.

  15. 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

  16. 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...

  17. 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.

  18. 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. 

  19. 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 ...

  20. 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

  1. 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.  .

  2. 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.

  3. 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...

  4. 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. .

  5. 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

  6. 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.

  7. 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 ...

  8. 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...

  9. 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…

  10. 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.

  11. 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...

  12. 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.

  13. 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.  .

  14. 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.

  15. 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 ...

  16. 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.

  17. 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.

  18. 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.

  19. 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)

  20. Computational intelligence synergies of fuzzy logic, neural networks and evolutionary computing

    CERN Document Server

    Siddique, Nazmul

    2013-01-01

    Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: Covers all the aspect

  1. 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

  2. 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.)

  3. 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.

  4. 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...

  5. 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.

  6. 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. .

  7. 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 ...

  8. 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.)

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. 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...

  14. 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.

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. 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. .

  6. 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.

  7. 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

  8. 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.)

  9. 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.

  10. 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.

  11. 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.

  12. 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...

  13. 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,…

  14. 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…

  15. Computational Intelligence in a Human Brain Model

    Directory of Open Access Journals (Sweden)

    Viorel Gaftea

    2016-06-01

    Full Text Available This paper focuses on the current trends in brain research domain and the current stage of development of research for software and hardware solutions, communication capabilities between: human beings and machines, new technologies, nano-science and Internet of Things (IoT devices. The proposed model for Human Brain assumes main similitude between human intelligence and the chess game thinking process. Tactical & strategic reasoning and the need to follow the rules of the chess game, all are very similar with the activities of the human brain. The main objective for a living being and the chess game player are the same: securing a position, surviving and eliminating the adversaries. The brain resolves these goals, and more, the being movement, actions and speech are sustained by the vital five senses and equilibrium. The chess game strategy helps us understand the human brain better and easier replicate in the proposed ‘Software and Hardware’ SAH Model.

  16. 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.

  17. 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.

  18. 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.

  19. Intelligent agents in data-intensive computing

    CERN Document Server

    Correia, Luís; Molina, José

    2016-01-01

    This book presents new approaches that advance research in all aspects of agent-based models, technologies, simulations and implementations for data intensive applications. The nine chapters contain a review of recent cross-disciplinary approaches in cloud environments and multi-agent systems, and important formulations of data intensive problems in distributed computational environments together with the presentation of new agent-based tools to handle those problems and Big Data in general. This volume can serve as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary work in the areas of data intensive computing and Big Data systems using emergent large-scale distributed computing paradigms. It will also allow newcomers to grasp key concepts and potential solutions on advanced topics of theory, models, technologies, system architectures and implementation of applications in Multi-Agent systems and data intensive computing. .

  20. 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....

  1. 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...

  2. Computational neuroscience for advancing artificial intelligence

    Directory of Open Access Journals (Sweden)

    Fernando P. Ponce

    2011-07-01

    Full Text Available resumen del libro de Alonso, E. y Mondragón, E. (2011. Hershey, NY: Medical Information Science Reference. La neurociencia como disciplinapersigue el entendimiento del cerebro y su relación con el funcionamiento de la mente a través del análisis de la comprensión de la interacción de diversos procesos físicos, químicos y biológicos (Bassett & Gazzaniga, 2011. Por otra parte, numerosas disciplinasprogresivamente han realizado significativas contribuciones en esta empresa tales como la matemática, la psicología o la filosofía, entre otras. Producto de este esfuerzo, es que junto con la neurociencia tradicional han aparecido disciplinas complementarias como la neurociencia cognitiva, la neuropsicología o la neurocienciacomputacional (Bengio, 2007; Dayan & Abbott, 2005. En el contexto de la neurociencia computacional como disciplina complementaria a laneurociencia tradicional. Alonso y Mondragón (2011 editan el libroComputacional Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications.

  3. 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...

  4. 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.

  5. [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.

  6. 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

  7. Computer Vision for Artificially Intelligent Robotic Systems

    Science.gov (United States)

    Ma, Chialo; Ma, Yung-Lung

    1987-04-01

    In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main

  8. 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.

  9. 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 ...

  10. 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...

  11. 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...

  12. 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...

  13. Computational Intelligence in Highway Management: A Review

    Directory of Open Access Journals (Sweden)

    Ondrej Pribyl

    2015-10-01

    Full Text Available Highway management systems are used to improve safety and driving comfort on highways by using control strategies and providing information and warnings to drivers. They use several strategies starting from speed and lane management, through incident detection and warning systems, ramp metering, weather information up to, for example, informing drivers about alternative roads. This paper provides a review of the existing approaches to highway management systems, particularly speed harmonization and ramp metering. It is focused only on modern and advanced approaches, such as soft computing, multi-agent methods and their interconnection. Its objective is to provide guidance in the wide field of highway management and to point out the most relevant recent activities which demonstrate that development in the field of highway management is still important and that the existing research exhibits potential for further enhancement.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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...

  20. 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.

  1. 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...

  2. 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...

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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...

  14. 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...

  15. 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.

  16. 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...

  17. 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.)

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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...

  5. 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.

  6. 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.

  7. 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.

  8. 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)

  9. 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

  10. 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...

  11. 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.

  12. 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.

  13. 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 ...

  14. 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.

  15. 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.

  16. 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...

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  2. 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.  

  3. 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).

  4. 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.

  5. 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…

  6. 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

  7. Application of Computational Intelligence to Improve Education in Smart Cities

    Science.gov (United States)

    Gaffo, Fernando Henrique; de Barros, Rodolfo Miranda; Mendes, Leonardo de Souza

    2018-01-01

    According to UNESCO, education is a fundamental human right and every nation’s citizens should be granted universal access with equal quality to it. Because this goal is yet to be achieved in most countries, in particular in the developing and underdeveloped countries, it is extremely important to find more effective ways to improve education. This paper presents a model based on the application of computational intelligence (data mining and data science) that leads to the development of the student’s knowledge profile and that can help educators in their decision making for best orienting their students. This model also tries to establish key performance indicators to monitor objectives’ achievement within individual strategic planning assembled for each student. The model uses random forest for classification and prediction, graph description for data structure visualization and recommendation systems to present relevant information to stakeholders. The results presented were built based on the real dataset obtained from a Brazilian private k-9 (elementary school). The obtained results include correlations among key data, a model to predict student performance and recommendations that were generated for the stakeholders. PMID:29346288

  8. Application of Computational Intelligence to Improve Education in Smart Cities.

    Science.gov (United States)

    Gomede, Everton; Gaffo, Fernando Henrique; Briganó, Gabriel Ulian; de Barros, Rodolfo Miranda; Mendes, Leonardo de Souza

    2018-01-18

    According to UNESCO, education is a fundamental human right and every nation's citizens should be granted universal access with equal quality to it. Because this goal is yet to be achieved in most countries, in particular in the developing and underdeveloped countries, it is extremely important to find more effective ways to improve education. This paper presents a model based on the application of computational intelligence (data mining and data science) that leads to the development of the student's knowledge profile and that can help educators in their decision making for best orienting their students. This model also tries to establish key performance indicators to monitor objectives' achievement within individual strategic planning assembled for each student. The model uses random forest for classification and prediction, graph description for data structure visualization and recommendation systems to present relevant information to stakeholders. The results presented were built based on the real dataset obtained from a Brazilian private k-9 (elementary school). The obtained results include correlations among key data, a model to predict student performance and recommendations that were generated for the stakeholders.

  9. Application of Computational Intelligence to Improve Education in Smart Cities

    Directory of Open Access Journals (Sweden)

    Everton Gomede

    2018-01-01

    Full Text Available According to UNESCO, education is a fundamental human right and every nation’s citizens should be granted universal access with equal quality to it. Because this goal is yet to be achieved in most countries, in particular in the developing and underdeveloped countries, it is extremely important to find more effective ways to improve education. This paper presents a model based on the application of computational intelligence (data mining and data science that leads to the development of the student’s knowledge profile and that can help educators in their decision making for best orienting their students. This model also tries to establish key performance indicators to monitor objectives’ achievement within individual strategic planning assembled for each student. The model uses random forest for classification and prediction, graph description for data structure visualization and recommendation systems to present relevant information to stakeholders. The results presented were built based on the real dataset obtained from a Brazilian private k-9 (elementary school. The obtained results include correlations among key data, a model to predict student performance and recommendations that were generated for the stakeholders.

  10. 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...

  11. 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

  12. 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.

  13. 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.

  14. 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)

  15. 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

  16. 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

  17. An Intelligent Tutor for Intrusion Detection on Computer Systems

    National Research Council Canada - National Science Library

    Rowe, Neil C; Schiavo, Sandra

    1998-01-01

    ... critical. We describe a tutor incorporating two programs. The first program uses artificial-intelligence planning methods to generate realistic audit files reporting actions of a variety of simulated users (including intruders...

  18. 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 ...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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)

  4. 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

  5. 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

  6. 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...

  7. A computational intelligence approach to the Mars Precision Landing problem

    Science.gov (United States)

    Birge, Brian Kent, III

    Various proposed Mars missions, such as the Mars Sample Return Mission (MRSR) and the Mars Smart Lander (MSL), require precise re-entry terminal position and velocity states. This is to achieve mission objectives including rendezvous with a previous landed mission, or reaching a particular geographic landmark. The current state of the art footprint is in the magnitude of kilometers. For this research a Mars Precision Landing is achieved with a landed footprint of no more than 100 meters, for a set of initial entry conditions representing worst guess dispersions. Obstacles to reducing the landed footprint include trajectory dispersions due to initial atmospheric entry conditions (entry angle, parachute deployment height, etc.), environment (wind, atmospheric density, etc.), parachute deployment dynamics, unavoidable injection error (propagated error from launch on), etc. Weather and atmospheric models have been developed. Three descent scenarios have been examined. First, terminal re-entry is achieved via a ballistic parachute with concurrent thrusting events while on the parachute, followed by a gravity turn. Second, terminal re-entry is achieved via a ballistic parachute followed by gravity turn to hover and then thrust vector to desired location. Third, a guided parafoil approach followed by vectored thrusting to reach terminal velocity is examined. The guided parafoil is determined to be the best architecture. The purpose of this study is to examine the feasibility of using a computational intelligence strategy to facilitate precision planetary re-entry, specifically to take an approach that is somewhat more intuitive and less rigid, and see where it leads. The test problems used for all research are variations on proposed Mars landing mission scenarios developed by NASA. A relatively recent method of evolutionary computation is Particle Swarm Optimization (PSO), which can be considered to be in the same general class as Genetic Algorithms. An improvement over

  8. Artificial Intelligence: Realizing the Ultimate Promises of Computing

    OpenAIRE

    Waltz, David L.

    1997-01-01

    Artificial intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. These technologies would not exist today without the sustained federal support of fundamental AI research over the past three decades.

  9. 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

  10. 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.

  11. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  12. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  13. 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…

  14. 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

  15. 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

  16. 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)

  17. Intelligent Agent Based Semantic Web in Cloud Computing Environment

    OpenAIRE

    Mukhopadhyay, Debajyoti; Sharma, Manoj; Joshi, Gajanan; Pagare, Trupti; Palwe, Adarsha

    2013-01-01

    Considering today's web scenario, there is a need of effective and meaningful search over the web which is provided by Semantic Web. Existing search engines are keyword based. They are vulnerable in answering intelligent queries from the user due to the dependence of their results on information available in web pages. While semantic search engines provides efficient and relevant results as the semantic web is an extension of the current web in which information is given well defined meaning....

  18. Artificial intelligence programming languages for computer aided manufacturing

    Science.gov (United States)

    Rieger, C.; Samet, H.; Rosenberg, J.

    1979-01-01

    Eight Artificial Intelligence programming languages (SAIL, LISP, MICROPLANNER, CONNIVER, MLISP, POP-2, AL, and QLISP) are presented and surveyed, with examples of their use in an automated shop environment. Control structures are compared, and distinctive features of each language are highlighted. A simple programming task is used to illustrate programs in SAIL, LISP, MICROPLANNER, and CONNIVER. The report assumes reader knowledge of programming concepts, but not necessarily of the languages surveyed.

  19. 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. .

  20. 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.

  1. 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…

  2. Increase in computed tomography in Australia driven mainly by practice change: A decomposition analysis.

    Science.gov (United States)

    Wright, Cameron M; Bulsara, Max K; Norman, Richard; Moorin, Rachael E

    2017-07-01

    Publicly funded computed tomography (CT) procedure descriptions in Australia often specify the body site, rather than indication for use. This study aimed to evaluate the relative contribution of demographic versus non-demographic factors in driving the increase in CT services in Australia. A decomposition analysis was conducted to assess the proportion of additional CT attributable to changing population structure, CT use on a per capita basis (CPC, a proxy for change in practice) and/or cost of CT. Aggregated Medicare usage and billing data were obtained for selected years between 1993/4 and 2012/3. The number of billed CT scans rose from 33 per annum per 1000 of population in 1993/94 (total 572,925) to 112 per 1000 by 2012/13 (total 2,540,546). The respective cost to Medicare rose from $145.7 million to $790.7 million. Change in CPC was the most important factor accounting for changes in CT services (88%) and cost (65%) over the study period. While this study cannot conclude if the increase is appropriate, it does represent a shift in how CT is used, relative to when many CT services were listed for public funding. This 'scope shift' poses questions as to need for and frequency of retrospective/ongoing review of publicly funded services, as medical advances and other demand- or supply-side factors change the way health services are used. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Material decomposition and virtual non-contrast imaging in photon counting computed tomography: an animal study

    Science.gov (United States)

    Gutjahr, R.; Polster, C.; Kappler, S.; Pietsch, H.; Jost, G.; Hahn, K.; Schöck, F.; Sedlmair, M.; Allmendinger, T.; Schmidt, B.; Krauss, B.; Flohr, T. G.

    2016-03-01

    The energy resolving capabilities of Photon Counting Detectors (PCD) in Computed Tomography (CT) facilitate energy-sensitive measurements. The provided image-information can be processed with Dual Energy and Multi Energy algorithms. A research PCD-CT firstly allows acquiring images with a close to clinical configuration of both the X-ray tube and the CT-detector. In this study, two algorithms (Material Decomposition and Virtual Non-Contrast-imaging (VNC)) are applied on a data set acquired from an anesthetized rabbit scanned using the PCD-CT system. Two contrast agents (CA) are applied: A gadolinium (Gd) based CA used to enhance contrasts for vascular imaging, and xenon (Xe) and air as a CA used to evaluate local ventilation of the animal's lung. Four different images are generated: a) A VNC image, suppressing any traces of the injected Gd imitating a native scan, b) a VNC image with a Gd-image as an overlay, where contrast enhancements in the vascular system are highlighted using colored labels, c) another VNC image with a Xe-image as an overlay, and d) a 3D rendered image of the animal's lung, filled with Xe, indicating local ventilation characteristics. All images are generated from two images based on energy bin information. It is shown that a modified version of a commercially available dual energy software framework is capable of providing images with diagnostic value obtained from the research PCD-CT system.

  4. Evolutionary Computing for Intelligent Power System Optimization and Control

    DEFF Research Database (Denmark)

    This new book focuses on how evolutionary computing techniques benefit engineering research and development tasks by converting practical problems of growing complexities into simple formulations, thus largely reducing development efforts. This book begins with an overview of the optimization the...... theory and modern evolutionary computing techniques, and goes on to cover specific applications of evolutionary computing to power system optimization and control problems....

  5. 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

  6. 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.

  7. 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

  8. 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;…

  9. 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

  10. 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

  11. Price Comparisons on the Internet Based on Computational Intelligence

    Science.gov (United States)

    Kim, Jun Woo; Ha, Sung Ho

    2014-01-01

    Information-intensive Web services such as price comparison sites have recently been gaining popularity. However, most users including novice shoppers have difficulty in browsing such sites because of the massive amount of information gathered and the uncertainty surrounding Web environments. Even conventional price comparison sites face various problems, which suggests the necessity of a new approach to address these problems. Therefore, for this study, an intelligent product search system was developed that enables price comparisons for online shoppers in a more effective manner. In particular, the developed system adopts linguistic price ratings based on fuzzy logic to accommodate user-defined price ranges, and personalizes product recommendations based on linguistic product clusters, which help online shoppers find desired items in a convenient manner. PMID:25268901

  12. Advances in Intelligent Control Systems and Computer Science

    CERN Document Server

    2013-01-01

    The conception of real-time control networks taking into account, as an integrating approach, both the specific aspects of information and knowledge processing and the dynamic and energetic particularities of physical processes and of communication networks is representing one of the newest scientific and technological challenges. The new paradigm of Cyber-Physical Systems (CPS) reflects this tendency and will certainly change the evolution of the technology, with major social and economic impact. This book presents significant results in the field of process control and advanced information and knowledge processing, with applications in the fields of robotics, biotechnology, environment, energy, transportation, et al.. It introduces intelligent control concepts and strategies as well as real-time implementation aspects for complex control approaches. One of the sections is dedicated to the complex problem of designing software systems for distributed information processing networks. Problems as complexity an...

  13. Complex system modelling and control through intelligent soft computations

    CERN Document Server

    Azar, Ahmad

    2015-01-01

    The book offers a snapshot of the theories and applications of soft computing in the area of complex systems modeling and control. It presents the most important findings discussed during the 5th International Conference on Modelling, Identification and Control, held in Cairo, from August 31-September 2, 2013. The book consists of twenty-nine selected contributions, which have been thoroughly reviewed and extended before their inclusion in the volume. The different chapters, written by active researchers in the field, report on both current theories and important applications of soft-computing. Besides providing the readers with soft-computing fundamentals, and soft-computing based inductive methodologies/algorithms, the book also discusses key industrial soft-computing applications, as well as multidisciplinary solutions developed for a variety of purposes, like windup control, waste management, security issues, biomedical applications and many others. It is a perfect reference guide for graduate students, r...

  14. 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...

  15. Editorial: Computational Creativity, Concept Invention, and General Intelligence

    Science.gov (United States)

    Besold, Tarek R.; Kühnberger, Kai-Uwe; Veale, Tony

    2015-12-01

    Over the last decade, computational creativity as a field of scientific investigation and computational systems engineering has seen growing popularity. Still, the levels of development between projects aiming at systems for artistic production or performance and endeavours addressing creative problem-solving or models of creative cognitive capacities is diverging. While the former have already seen several great successes, the latter still remain in their infancy. This volume collects reports on work trying to close the accrued gap.

  16. 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.

  17. Computer vision and imaging in intelligent transportation systems

    CERN Document Server

    Bala, Raja; Trivedi, Mohan

    2017-01-01

    Acts as a single source reference providing readers with an overview of how computer vision can contribute to the different applications in the field of road transportation. This book presents a survey of computer vision techniques related to three key broad problems in the roadway transportation domain: safety, efficiency, and law enforcement. The individual chapters present significant applications within these problem domains, each presented in a tutorial manner, describing the motivation for and benefits of the application, and a description of the state of the art.

  18. Emergence, evolution, intelligence; hydroinformatics : a study of distributed and decentralised computing using intelligent agents

    NARCIS (Netherlands)

    Babovic, V.

    1996-01-01

    The computer-controlled operating environments of such facilities as automated factories, nuclear power plants, telecommunication centres and space stations are continually becoming more complex.The situation is similar, if not even more apparent and urgent, in the case of water. Water is not only

  19. An Intelligent Computer-Based System for Sign Language Tutoring

    Science.gov (United States)

    Ritchings, Tim; Khadragi, Ahmed; Saeb, Magdy

    2012-01-01

    A computer-based system for sign language tutoring has been developed using a low-cost data glove and a software application that processes the movement signals for signs in real-time and uses Pattern Matching techniques to decide if a trainee has closely replicated a teacher's recorded movements. The data glove provides 17 movement signals from…

  20. Brain-Computer Interfacing Embedded in Intelligent and Affective Systems

    NARCIS (Netherlands)

    Nijholt, Antinus

    In this talk we survey recent research views on non-traditional brain-computer interfaces (BCI). That is, interfaces that can process brain activity input, but that are designed for the ‘general population’, rather than for clinical purposes. Control of applications can be made more robust by fusing

  1. 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.

  2. Intelligent computer systems in engineering design principles and applications

    CERN Document Server

    Sunnersjo, Staffan

    2016-01-01

    This introductory book discusses how to plan and build useful, reliable, maintainable and cost efficient computer systems for automated engineering design. The book takes a user perspective and seeks to bridge the gap between texts on principles of computer science and the user manuals for commercial design automation software. The approach taken is top-down, following the path from definition of the design task and clarification of the relevant design knowledge to the development of an operational system well adapted for its purpose. This introductory text for the practicing engineer working in industry covers most vital aspects of planning such a system. Experiences from applications of automated design systems in practice are reviewed based on a large number of real, industrial cases. The principles behind the most popular methods in design automation are presented with sufficient rigour to give the user confidence in applying them on real industrial problems. This book is also suited for a half semester c...

  3. 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.

  4. Artificial intelligence in pharmaceutical product formulation: neural computing

    Directory of Open Access Journals (Sweden)

    Svetlana Ibrić

    2009-10-01

    Full Text Available The properties of a formulation are determined not only by the ratios in which the ingredients are combined but also by the processing conditions. Although the relationships between the ingredient levels, processing conditions, and product performance may be known anecdotally, they can rarely be quantified. In the past, formulators tended to use statistical techniques to model their formulations, relying on response surfaces to provide a mechanism for optimazation. However, the optimization by such a method can be misleading, especially if the formulation is complex. More recently, advances in mathematics and computer science have led to the development of alternative modeling and data mining techniques which work with a wider range of data sources: neural networks (an attempt to mimic the processing of the human brain; genetic algorithms (an attempt to mimic the evolutionary process by which biological systems self-organize and adapt, and fuzzy logic (an attempt to mimic the ability of the human brain to draw conclusions and generate responses based on incomplete or imprecise information. In this review the current technology will be examined, as well as its application in pharmaceutical formulation and processing. The challenges, benefits and future possibilities of neural computing will be discussed.

  5. 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).

  6. 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...

  7. 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...

  8. 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...

  9. 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.

  10. 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

  11. 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...

  12. 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...

  13. 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...

  14. Computational intelligence paradigms in economic and financial decision making

    CERN Document Server

    Resta, Marina

    2016-01-01

    The book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process. In the first part the textbook presents a comprehensive and self-contained introduction to the field of self-organizing maps, elastic maps and social network analysis tools and provides necessary background material on the topic, including a discussion of more recent developments in the field. In the second part the focus is on practical applications, with particular attention paid to budgeting problems, market simulations, and decision-making processes, and on how such problems can be effectively managed by developing proper methods to automatically detect certain patterns. The book offers a valuable resource for both students and practitioners with an introductory-level college math background.

  15. 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.

  16. 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.

  17. 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.

  18. 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...

  19. 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.

  20. Computational intelligence techniques for biological data mining: An overview

    Science.gov (United States)

    Faye, Ibrahima; Iqbal, Muhammad Javed; Said, Abas Md; Samir, Brahim Belhaouari

    2014-10-01

    Computational techniques have been successfully utilized for a highly accurate analysis and modeling of multifaceted and raw biological data gathered from various genome sequencing projects. These techniques are proving much more effective to overcome the limitations of the traditional in-vitro experiments on the constantly increasing sequence data. However, most critical problems that caught the attention of the researchers may include, but not limited to these: accurate structure and function prediction of unknown proteins, protein subcellular localization prediction, finding protein-protein interactions, protein fold recognition, analysis of microarray gene expression data, etc. To solve these problems, various classification and clustering techniques using machine learning have been extensively used in the published literature. These techniques include neural network algorithms, genetic algorithms, fuzzy ARTMAP, K-Means, K-NN, SVM, Rough set classifiers, decision tree and HMM based algorithms. Major difficulties in applying the above algorithms include the limitations found in the previous feature encoding and selection methods while extracting the best features, increasing classification accuracy and decreasing the running time overheads of the learning algorithms. The application of this research would be potentially useful in the drug design and in the diagnosis of some diseases. This paper presents a concise overview of the well-known protein classification techniques.

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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)

  9. Data driven model generation based on computational intelligence

    Science.gov (United States)

    Gemmar, Peter; Gronz, Oliver; Faust, Christophe; Casper, Markus

    2010-05-01

    The simulation of discharges at a local gauge or the modeling of large scale river catchments are effectively involved in estimation and decision tasks of hydrological research and practical applications like flood prediction or water resource management. However, modeling such processes using analytical or conceptual approaches is made difficult by both complexity of process relations and heterogeneity of processes. It was shown manifold that unknown or assumed process relations can principally be described by computational methods, and that system models can automatically be derived from observed behavior or measured process data. This study describes the development of hydrological process models using computational methods including Fuzzy logic and artificial neural networks (ANN) in a comprehensive and automated manner. Methods We consider a closed concept for data driven development of hydrological models based on measured (experimental) data. The concept is centered on a Fuzzy system using rules of Takagi-Sugeno-Kang type which formulate the input-output relation in a generic structure like Ri : IFq(t) = lowAND...THENq(t+Δt) = ai0 +ai1q(t)+ai2p(t-Δti1)+ai3p(t+Δti2)+.... The rule's premise part (IF) describes process states involving available process information, e.g. actual outlet q(t) is low where low is one of several Fuzzy sets defined over variable q(t). The rule's conclusion (THEN) estimates expected outlet q(t + Δt) by a linear function over selected system variables, e.g. actual outlet q(t), previous and/or forecasted precipitation p(t ?Δtik). In case of river catchment modeling we use head gauges, tributary and upriver gauges in the conclusion part as well. In addition, we consider temperature and temporal (season) information in the premise part. By creating a set of rules R = {Ri|(i = 1,...,N)} the space of process states can be covered as concise as necessary. Model adaptation is achieved by finding on optimal set A = (aij) of conclusion

  10. 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.

  11. 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.

  12. 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.

  13. Domain Decomposition for Computing Extremely Low Frequency Induced Current in the Human Body

    OpenAIRE

    Perrussel , Ronan; Voyer , Damien; Nicolas , Laurent; Scorretti , Riccardo; Burais , Noël

    2011-01-01

    International audience; Computation of electromagnetic fields in high resolution computational phantoms requires solving large linear systems. We present an application of Schwarz preconditioners with Krylov subspace methods for computing extremely low frequency induced fields in a phantom issued from the Visible Human.

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Influence of pore size distributions on decomposition of maize leaf residue: evidence from X-ray computed micro-tomography

    Science.gov (United States)

    Negassa, Wakene; Guber, Andrey; Kravchenko, Alexandra; Rivers, Mark

    2014-05-01

    Soil's potential to sequester carbon (C) depends not only on quality and quantity of organic inputs to soil but also on the residence time of the applied organic inputs within the soil. Soil pore structure is one of the main factors that influence residence time of soil organic matter by controlling gas exchange, soil moisture and microbial activities, thereby soil C sequestration capacity. Previous attempts to investigate the fate of organic inputs added to soil did not allow examining their decomposition in situ; the drawback that can now be remediated by application of X-ray computed micro-tomography (µ-CT). The non-destructive and non-invasive nature of µ-CT gives an opportunity to investigate the effect of soil pore size distributions on decomposition of plant residues at a new quantitative level. The objective of this study is to examine the influence of pore size distributions on the decomposition of plant residue added to soil. Samples with contrasting pore size distributions were created using aggregate fractions of five different sizes (pieces of maize leaves 2.5 mg in size (equivalent to 1.71 mg C g-1 soil) were added to half of the studied samples. Samples with and without maize leaves were incubated for 120 days. CO2 emission from the samples was measured at regular time intervals. In order to ensure that the observed differences are due to differences in pore structure and not due to differences in inherent properties of the studied aggregate fractions, we repeated the whole experiment using soil from the same aggregate size fractions but ground to six replicated samples were used for intact and ground samples of all sizes with and without leaves. Two replications of the intact aggregate fractions of all sizes with leaves were subjected to µ-CT scanning before and after incubation, whereas all the remaining replications of both intact and ground aggregate fractions of <0.05, 0.05-0.1, and 1.0-2.0 mm sizes with leaves were scanned with µ-CT after

  2. 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…

  3. 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.

  4. 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.

  5. 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.

  6. Application of the Decomposition Method to the Design Complexity of Computer-based Display

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hyoung Ju; Lee, Seung Woo; Seong, Poong Hyun [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Park, Jin Kyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2012-05-15

    The importance of the design of human machine interfaces (HMIs) for human performance and safety has long been recognized in process industries. In case of nuclear power plants (NPPs), HMIs have significant implications for the safety of the NPPs since poor implementation of HMIs can impair the operators' information searching ability which is considered as one of the important aspects of human behavior. To support and increase the efficiency of the operators' information searching behavior, advanced HMIs based on computer technology are provided. Operators in advanced main control room (MCR) acquire information through video display units (VDUs), and large display panel (LDP) required for the operation of NPPs. These computer-based displays contain a very large quantity of information and present them in a variety of formats than conventional MCR. For example, these displays contain more elements such as abbreviations, labels, icons, symbols, coding, and highlighting than conventional ones. As computer-based displays contain more information, complexity of the elements becomes greater due to less distinctiveness of each element. A greater understanding is emerging about the effectiveness of designs of computer-based displays, including how distinctively display elements should be designed. And according to Gestalt theory, people tend to group similar elements based on attributes such as shape, color or pattern based on the principle of similarity. Therefore, it is necessary to consider not only human operator's perception but the number of element consisting of computer-based display

  7. Application of the Decomposition Method to the Design Complexity of Computer-based Display

    International Nuclear Information System (INIS)

    Kim, Hyoung Ju; Lee, Seung Woo; Seong, Poong Hyun; Park, Jin Kyun

    2012-01-01

    The importance of the design of human machine interfaces (HMIs) for human performance and safety has long been recognized in process industries. In case of nuclear power plants (NPPs), HMIs have significant implications for the safety of the NPPs since poor implementation of HMIs can impair the operators' information searching ability which is considered as one of the important aspects of human behavior. To support and increase the efficiency of the operators' information searching behavior, advanced HMIs based on computer technology are provided. Operators in advanced main control room (MCR) acquire information through video display units (VDUs), and large display panel (LDP) required for the operation of NPPs. These computer-based displays contain a very large quantity of information and present them in a variety of formats than conventional MCR. For example, these displays contain more elements such as abbreviations, labels, icons, symbols, coding, and highlighting than conventional ones. As computer-based displays contain more information, complexity of the elements becomes greater due to less distinctiveness of each element. A greater understanding is emerging about the effectiveness of designs of computer-based displays, including how distinctively display elements should be designed. And according to Gestalt theory, people tend to group similar elements based on attributes such as shape, color or pattern based on the principle of similarity. Therefore, it is necessary to consider not only human operator's perception but the number of element consisting of computer-based display

  8. 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

  9. A full-spectral Bayesian reconstruction approach based on the material decomposition model applied in dual-energy computed tomography

    International Nuclear Information System (INIS)

    Cai, C.; Rodet, T.; Mohammad-Djafari, A.; Legoupil, S.

    2013-01-01

    Purpose: Dual-energy computed tomography (DECT) makes it possible to get two fractions of basis materials without segmentation. One is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical DECT measurements are usually obtained with polychromatic x-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam polychromaticity 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 preprocessing and the ill-conditioned water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on nonlinear forward models counting the beam polychromaticity show great potential for giving accurate fraction images.Methods: 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 nonquadratic cost function. To solve it, the use of a monotone conjugate gradient algorithm with suboptimal descent steps is proposed.Results: The performance of the proposed approach is analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also

  10. Computer simulation of the formation of tweed and modulated structures in decomposition reactions

    International Nuclear Information System (INIS)

    Chen, S.; Morris, J.W. Jr.; Khachaturyan, A.G.

    1979-03-01

    A model of coarsening in a heterogeneous cubic alloy with cubic or tetragonal precipitates is proposed. According to the model the coarsening is controlled by the relaxation of the elastic strain energy. The computer simulation of coarsening demonstrates good agreement with electron microscopic observation of the structure and diffraction pattern

  11. Computer simulation of the formation of ''tweed'' and modulated structures in decomposition reactions

    International Nuclear Information System (INIS)

    Chen, S.; Morris, J.W. Jr.; Khachaturyan, A.G.

    1979-01-01

    A model of coarsening in a heterogeneous cubic alloy with cubic or tetragonal precipitates is proposed. According to the model the coarsening is controlled by the relaxation of the elastic strain energy. The computer simulation of coarsening demonstrates good agreement with electron microscopic observation of the structure and diffraction pattern

  12. NearFar: A computer program for nearside farside decomposition of heavy-ion elastic scattering amplitude

    Science.gov (United States)

    Cha, Moon Hoe

    2007-02-01

    The NearFar program is a package for carrying out an interactive nearside-farside decomposition of heavy-ion elastic scattering amplitude. The program is implemented in Java to perform numerical operations on the nearside and farside angular distributions. It contains a graphical display interface for the numerical results. A test run has been applied to the elastic O16+Si28 scattering at E=1503 MeV. Program summaryTitle of program: NearFar Catalogue identifier: ADYP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYP_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: none Computers: designed for any machine capable of running Java, developed on PC-Pentium-4 Operating systems under which the program has been tested: Microsoft Windows XP (Home Edition) Program language used: Java Number of bits in a word: 64 Memory required to execute with typical data: case dependent No. of lines in distributed program, including test data, etc.: 3484 Number of bytes distributed program, including test data, etc.: 142 051 Distribution format: tar.gz Other software required: A Java runtime interpreter, or the Java Development Kit, version 5.0 Nature of physical problem: Interactive nearside-farside decomposition of heavy-ion elastic scattering amplitude. Method of solution: The user must supply a external data file or PPSM parameters which calculates theoretical values of the quantities to be decomposed. Typical running time: Problem dependent. In a test run, it is about 35 s on a 2.40 GHz Intel P4-processor machine.

  13. 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.

  14. 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.

  15. Tailor-made Design of Chemical Blends using Decomposition-based Computer-aided Approach

    DEFF Research Database (Denmark)

    Yunus, Nor Alafiza; Manan, Zainuddin Abd.; Gernaey, Krist

    (properties). In this way, first the systematic computer-aided technique establishes the search space, and then narrows it down in subsequent steps until a small number of feasible and promising candidates remain and then experimental work may be conducted to verify if any or all the candidates satisfy......Computer aided technique is an efficient approach to solve chemical product design problems such as 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 attributes...... is decomposed into two stages. The first stage investigates the mixture stability where all unstable mixtures are eliminated and the stable blend candidates are retained for further testing. In the second stage, the blend candidates have to satisfy a set of target properties that are ranked according...

  16. Decomposition recovery extension to the Computer Aided Prototyping System (CAPS) change-merge tool.

    OpenAIRE

    Keesling, William Ronald

    1997-01-01

    Approved for public release; distribution is unlimited A promising use of Computer Aided Prototyping System (CAPS) is to support concurrent design. Key to success in this context is the ability to automatically and reliably combine and integrate the prototypes produced in concurrent efforts. Thus, to be of practical use in this as well as most prototyping contexts, a CAPS tool must have a fast, automated, reliable prototype integration capability. The current CAPS Change Merge Tool is fast...

  17. 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.

  18. 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.

  19. 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)

  20. Evaluation of trade influence on economic growth rate by computational intelligence approach

    Science.gov (United States)

    Sokolov-Mladenović, Svetlana; Milovančević, Milos; Mladenović, Igor

    2017-01-01

    In this study was analyzed the influence of trade parameters on the economic growth forecasting accuracy. Computational intelligence method was used for the analyzing since the method can handle highly nonlinear data. It is known that the economic growth could be modeled based on the different trade parameters. In this study five input parameters were considered. These input parameters were: trade in services, exports of goods and services, imports of goods and services, trade and merchandise trade. All these parameters were calculated as added percentages in gross domestic product (GDP). The main goal was to select which parameters are the most impactful on the economic growth percentage. GDP was used as economic growth indicator. Results show that the imports of goods and services has the highest influence on the economic growth forecasting accuracy.

  1. 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.

  2. 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.

  3. ECG Signal Processing, Classification and Interpretation A Comprehensive Framework of Computational Intelligence

    CERN Document Server

    Pedrycz, Witold

    2012-01-01

    Electrocardiogram (ECG) signals are among the most important sources of diagnostic information in healthcare so improvements in their analysis may also have telling consequences. Both the underlying signal technology and a burgeoning variety of algorithms and systems developments have proved successful targets for recent rapid advances in research. ECG Signal Processing, Classification and Interpretation shows how the various paradigms of Computational Intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. Neural networks do well at capturing the nonlinear nature of the signals, information granules realized as fuzzy sets help to confer interpretability on the data and evolutionary optimization may be critical in supporting the structural development of ECG classifiers and models of ECG signals. The contributors address concepts, methodology, algorithms, and case studies and applications exploiting the paradigm of Comp...

  4. 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.

  5. 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

  6. DE-BLURRING SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY IMAGES USING WAVELET DECOMPOSITION

    Directory of Open Access Journals (Sweden)

    Neethu M. Sasi

    2016-02-01

    Full Text Available Single photon emission computed tomography imaging is a popular nuclear medicine imaging technique which generates images by detecting radiations emitted by radioactive isotopes injected in the human body. Scattering of these emitted radiations introduces blur in this type of images. This paper proposes an image processing technique to enhance cardiac single photon emission computed tomography images by reducing the blur in the image. The algorithm works in two main stages. In the first stage a maximum likelihood estimate of the point spread function and the true image is obtained. In the second stage Lucy Richardson algorithm is applied on the selected wavelet coefficients of the true image estimate. The significant contribution of this paper is that processing of images is done in the wavelet domain. Pre-filtering is also done as a sub stage to avoid unwanted ringing effects. Real cardiac images are used for the quantitative and qualitative evaluations of the algorithm. Blur metric, peak signal to noise ratio and Tenengrad criterion are used as quantitative measures. Comparison against other existing de-blurring algorithms is also done. The simulation results indicate that the proposed method effectively reduces blur present in the image.

  7. Computer-assisted bladder cancer grading: α-shapes for color space decomposition

    Science.gov (United States)

    Niazi, M. K. K.; Parwani, Anil V.; Gurcan, Metin N.

    2016-03-01

    According to American Cancer Society, around 74,000 new cases of bladder cancer are expected during 2015 in the US. To facilitate the bladder cancer diagnosis, we present an automatic method to differentiate carcinoma in situ (CIS) from normal/reactive cases that will work on hematoxylin and eosin (H and E) stained images of bladder. The method automatically determines the color deconvolution matrix by utilizing the α-shapes of the color distribution in the RGB color space. Then, variations in the boundary of transitional epithelium are quantified, and sizes of nuclei in the transitional epithelium are measured. We also approximate the "nuclear to cytoplasmic ratio" by computing the ratio of the average shortest distance between transitional epithelium and nuclei to average nuclei size. Nuclei homogeneity is measured by computing the kurtosis of the nuclei size histogram. The results show that 30 out of 34 (88.2%) images were correctly classified by the proposed method, indicating that these novel features are viable markers to differentiate CIS from normal/reactive bladder.

  8. 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…

  9. Computational intelligence approach for NOx emissions minimization in a coal-fired utility boiler

    International Nuclear Information System (INIS)

    Zhou Hao; Zheng Ligang; Cen Kefa

    2010-01-01

    The current work presented a computational intelligence approach used for minimizing NO x emissions in a 300 MW dual-furnaces coal-fired utility boiler. The fundamental idea behind this work included NO x emissions characteristics modeling and NO x emissions optimization. First, an objective function aiming at estimating NO x emissions characteristics from nineteen operating parameters of the studied boiler was represented by a support vector regression (SVR) model. Second, four levels of primary air velocities (PA) and six levels of secondary air velocities (SA) were regulated by using particle swarm optimization (PSO) so as to achieve low NO x emissions combustion. To reduce the time demanding, a more flexible stopping condition was used to improve the computational efficiency without the loss of the quality of the optimization results. The results showed that the proposed approach provided an effective way to reduce NO x emissions from 399.7 ppm to 269.3 ppm, which was much better than a genetic algorithm (GA) based method and was slightly better than an ant colony optimization (ACO) based approach reported in the earlier work. The main advantage of PSO was that the computational cost, typical of less than 25 s under a PC system, is much less than those required for ACO. This meant the proposed approach would be more applicable to online and real-time applications for NO x emissions minimization in actual power plant boilers.

  10. Domain decomposition for the computation of radiosity in lighting simulation; Decomposition de domaines pour le calcul de la radiosite en simulation d'eclairage

    Energy Technology Data Exchange (ETDEWEB)

    Salque, B

    1998-07-01

    This work deals with the equation of radiosity, this equation describes the transport of light energy through a diffuse medium, its resolution enables us to simulate the presence of light sources. The equation of radiosity is an integral equation who admits a unique solution in realistic cases. The different methods of solving are reviewed. The equation of radiosity can not be formulated as the integral form of a classical partial differential equation, but this work shows that the technique of domain decomposition can be successfully applied to the equation of radiosity if this approach is framed by considerations of physics. This method provides a system of independent equations valid for each sub-domain and whose main parameter is luminance. Some numerical examples give an idea of the convergence of the algorithm. This method is applied to the optimization of the shape of a light reflector.

  11. 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

  12. Symbolic computation on integrable decompositions for the cylindrical Kadomtsev-Petviashvili equation from dusty plasmas and Bose-Einstein condensates

    International Nuclear Information System (INIS)

    Li Juan; Xu Tao; Zhang Haiqiang; Gao Yitian; Tian Bo

    2008-01-01

    In this paper, the cylindrical Kadomtsev-Petviashvili (KP) equation arising from dusty plasmas and Bose-Einstein condensates is investigated by the decomposition method. Through the nonlinearization of a single Lax pair, this equation is decomposed into a generalized variable-coefficient Burgers equation and its third-order extension, and then a series of analytic soliton-like solutions are obtained. Furthermore, with the aid of symbolic computation, a symmetry potential constraint in terms of the squared eigenfunctions is proposed to nonlinearize two symmetry Lax pairs into the first two variable-coefficient 2N-coupled soliton systems in the same hierarchy. Based on the Lax representation for these two decomposed soliton systems, a Darboux transformation is constructed to iteratively generate the multi-soliton-like solutions. Via the obtained analytic soliton-like solutions, the graphical analysis is devoted to the one-parabola soliton structure, compressive and rarefactive soliton resonance phenomena occurring in dusty plasmas and Bose-Einstein condensates

  13. Computational study of the combustion and atmospheric decomposition of 2-methylfuran

    KAUST Repository

    Davis, Alexander C.

    2013-08-22

    There is a growing interest in alkylfurans as potential biofuels. Recent work has highlighted the need for further study of the atmospheric oxidation mechanism of 2-methylfuran (2MF). This study utilizes the high level composite computational methods, G4 and CBS-QB3, to determine the bond dissociation energies for the C-H bond in 2MF and the reaction enthalpies and barrier heights of several of the known possible initiation reaction pathways. This study also investigates the possible subsequent low temperature reaction pathways following the addition of OH and then O2 onto the 2MF ring. The placement of the OH and O2 on the ring, either cis or trans to each other, dictates the viability of subsequent reactions. Of particular interest is the observation that 1,4 H-migrations that abstract the hydrogen bound to the same carbon as the OH have abnormally low barrier height. This dramatic decrease puts the reaction barrier lower than concerted eliminations and 6-membered ring Waddington-type reactions. In addition, a novel reaction type, described as a Waddington concerted elimination, is reported herein. This reaction, when viable, is generally more favorable than other reactions. The results presented here are of interest to combustion modelers and atmospheric chemists, particularly those working on aromatic hydrocarbons and systems with conjugated double bonds. © 2013 American Chemical Society.

  14. 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 ...

  15. 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.

  16. A comparative analysis among computational intelligence techniques for dissolved oxygen prediction in Delaware River

    Directory of Open Access Journals (Sweden)

    Ehsan Olyaie

    2017-05-01

    Full Text Available Most of the water quality models previously developed and used in dissolved oxygen (DO prediction are complex. Moreover, reliable data available to develop/calibrate new DO models is scarce. Therefore, there is a need to study and develop models that can handle easily measurable parameters of a particular site, even with short length. In recent decades, computational intelligence techniques, as effective approaches for predicting complicated and significant indicator of the state of aquatic ecosystems such as DO, have created a great change in predictions. In this study, three different AI methods comprising: (1 two types of artificial neural networks (ANN namely multi linear perceptron (MLP and radial based function (RBF; (2 an advancement of genetic programming namely linear genetic programming (LGP; and (3 a support vector machine (SVM technique were used for DO prediction in Delaware River located at Trenton, USA. For evaluating the performance of the proposed models, root mean square error (RMSE, Nash–Sutcliffe efficiency coefficient (NS, mean absolute relative error (MARE and, correlation coefficient statistics (R were used to choose the best predictive model. The comparison of estimation accuracies of various intelligence models illustrated that the SVM was able to develop the most accurate model in DO estimation in comparison to other models. Also, it was found that the LGP model performs better than the both ANNs models. For example, the determination coefficient was 0.99 for the best SVM model, while it was 0.96, 0.91 and 0.81 for the best LGP, MLP and RBF models, respectively. In general, the results indicated that an SVM model could be employed satisfactorily in DO estimation.

  17. Computational intelligence in gait research: a perspective on current applications and future challenges.

    Science.gov (United States)

    Lai, Daniel T H; Begg, Rezaul K; Palaniswami, Marimuthu

    2009-09-01

    Our mobility is an important daily requirement so much so that any disruption to it severely degrades our perceived quality of life. Studies in gait and human movement sciences, therefore, play a significant role in maintaining the well-being of our mobility. Current gait analysis involves numerous interdependent gait parameters that are difficult to adequately interpret due to the large volume of recorded data and lengthy assessment times in gait laboratories. A proposed solution to these problems is computational intelligence (CI), which is an emerging paradigm in biomedical engineering most notably in pathology detection and prosthesis design. The integration of CI technology in gait systems facilitates studies in disorders caused by lower limb defects, cerebral disorders, and aging effects by learning data relationships through a combination of signal processing and machine learning techniques. Learning paradigms, such as supervised learning, unsupervised learning, and fuzzy and evolutionary algorithms, provide advanced modeling capabilities for biomechanical systems that in the past have relied heavily on statistical analysis. CI offers the ability to investigate nonlinear data relationships, enhance data interpretation, design more efficient diagnostic methods, and extrapolate model functionality. These are envisioned to result in more cost-effective, efficient, and easy-to-use systems, which would address global shortages in medical personnel and rising medical costs. This paper surveys current signal processing and CI methodologies followed by gait applications ranging from normal gait studies and disorder detection to artificial gait simulation. We review recent systems focusing on the existing challenges and issues involved in making them successful. We also examine new research in sensor technologies for gait that could be combined with these intelligent systems to develop more effective healthcare solutions.

  18. 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.

  19. 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.

  20. Soft Computing Optimizer For Intelligent Control Systems Design: The Structure And Applications

    Directory of Open Access Journals (Sweden)

    Sergey A. Panfilov

    2003-10-01

    Full Text Available Soft Computing Optimizer (SCO as a new software tool for design of robust intelligent control systems is described. It is based on the hybrid methodology of soft computing and stochastic simulation. It uses as an input the measured or simulated data about the modeled system. SCO is used to design an optimal fuzzy inference system, which approximates a random behavior of control object with the certain accuracy. The task of the fuzzy inference system construction is reduced to the subtasks such as forming of the linguistic variables for each input and output variable, creation of rule data base, optimization of rule data base and refinement of the parameters of the membership functions. Each task by the corresponding genetic algorithm (with an appropriate fitness function is solved. The result of SCO application is the design of Knowledge Base of a Fuzzy Controller, which contains the value information about developed fuzzy inference system. Such value information can be downloaded into the actual fuzzy controller to perform online fuzzy control. Simulations results of robust fuzzy control of nonlinear dynamic systems and experimental results of application on automotive semi-active suspension control are demonstrated.

  1. 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...

  2. 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.

  3. 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)

  4. 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.

  5. 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.

  6. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    Science.gov (United States)

    Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

    2006-12-01

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

  7. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    International Nuclear Information System (INIS)

    Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

    2006-01-01

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis

  8. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Stoitsis, John [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece)]. E-mail: stoitsis@biosim.ntua.gr; Valavanis, Ioannis [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece); Mougiakakou, Stavroula G. [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece); Golemati, Spyretta [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece); Nikita, Alexandra [University of Athens, Medical School 152 28 Athens (Greece); Nikita, Konstantina S. [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece)

    2006-12-20

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

  9. Computational Intelligence and Game Design for Effective At-Home Stroke Rehabilitation.

    Science.gov (United States)

    Borghese, Nunzio Alberto; Pirovano, Michele; Lanzi, Pier Luca; Wüest, Seline; de Bruin, Eling D

    2013-04-01

    The aim of this article is to describe a game engine that has all the characteristics needed to support rehabilitation at home. The low-cost tracking devices recently introduced in the entertainment market allow measuring reliably at home, in real time, players' motion with a hands-free approach. Such systems have also become a source of inspiration for researchers working in rehabilitation. Computer games appear suited to guide rehabilitation because of their ability to engage the users. However, commercial videogames and game engines lack the peculiar functionalities required in rehabilitation: Games should be adapted to each patient's functional status, and monitoring the patient's motion is mandatory to avoid maladaptation. Feedback on performance and progression of the exercises should be provided. Lastly, several tracking devices should be considered, according to the patient's pathology and rehabilitation aims. We have analyzed the needs of the clinicians and of the patients associated in performing rehabilitation at home, identifying the characteristics that the game engine should have. The result of this analysis has led us to develop the Intelligent Game Engine for Rehabilitation (IGER) system, which combines the principles upon which commercial games are designed with the needs of rehabilitation. IGER is heavily based on computational intelligence: Adaptation of the difficulty level of the exercise is carried out through a Bayesian framework from the observation of the patient's success rate. Monitoring is implemented in fuzzy systems and based on rules defined for the exercises by clinicians. Several devices can be attached to IGER through an input abstraction layer, like the Nintendo ® (Kyoto, Japan) Wii™ Balance Board™, the Microsoft ® (Redmond, WA) Kinect, the Falcon from Novint Technologies (Albuquerque, NM), or the Tyromotion (Graz, Austria) Timo ® plate balance board. IGER is complemented with videogames embedded in a specific taxonomy

  10. Computational intelligence models to predict porosity of tablets using minimum features

    Directory of Open Access Journals (Sweden)

    Khalid MH

    2017-01-01

    Full Text Available Mohammad Hassan Khalid,1 Pezhman Kazemi,1 Lucia Perez-Gandarillas,2 Abderrahim Michrafy,2 Jakub Szlęk,1 Renata Jachowicz,1 Aleksander Mendyk1 1Department of Pharmaceutical Technology and Biopharmaceutics, Faculty of Pharmacy, Jagiellonian University Medical College, Krakow, Poland; 2Centre National de la Recherche Scientifique, Centre RAPSODEE, Mines Albi, Université de Toulouse, Albi, France Abstract: The effects of different formulations and manufacturing process conditions on the physical properties of a solid dosage form are of importance to the pharmaceutical industry. It is vital to have in-depth understanding of the material properties and governing parameters of its processes in response to different formulations. Understanding the mentioned aspects will allow tighter control of the process, leading to implementation of quality-by-design (QbD practices. Computational intelligence (CI offers an opportunity to create empirical models that can be used to describe the system and predict future outcomes in silico. CI models can help explore the behavior of input parameters, unlocking deeper understanding of the system. This research endeavor presents CI models to predict the porosity of tablets created by roll-compacted binary mixtures, which were milled and compacted under systematically varying conditions. CI models were created using tree-based methods, artificial neural networks (ANNs, and symbolic regression trained on an experimental data set and screened using root-mean-square error (RMSE scores. The experimental data were composed of proportion of microcrystalline cellulose (MCC (in percentage, granule size fraction (in micrometers, and die compaction force (in kilonewtons as inputs and porosity as an output. The resulting models show impressive generalization ability, with ANNs (normalized root-mean-square error [NRMSE] =1% and symbolic regression (NRMSE =4% as the best-performing methods, also exhibiting reliable predictive

  11. 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.  

  12. 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

  13. 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.

  14. Computational Intelligence and Wavelet Transform Based Metamodel for Efficient Generation of Not-Yet Simulated Waveforms.

    Directory of Open Access Journals (Sweden)

    Gabriel Oltean

    Full Text Available The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system. The necessary data are obtained by early-stage simulation of an electronic control system from the automotive industry. The metamodel development is based on three key elements: a wavelet transform for waveform characterization, a genetic algorithm optimization to detect the optimal wavelet transform and to identify the most relevant decomposition coefficients, and an artificial neuronal network to derive the relevant coefficients of the wavelet transform for any new parameters combination. The resulted metamodels for three different waveform families are fully reliable. They satisfy the required key points: high accuracy (a maximum mean squared error of 7.1x10-5 for the unity-based normalized waveforms, efficiency (fully affordable computational effort for metamodel build-up: maximum 18 minutes on a general purpose computer, and simplicity (less than 1 second for running the metamodel, the user only provides the parameters combination. The metamodels can be used for very efficient generation of new waveforms, for any possible combination of dependent parameters, offering the possibility to explore the entire design space. A wide range of possibilities becomes achievable for the user, such as: all design corners can be analyzed, possible worst-case situations can be investigated, extreme values of waveforms can be discovered, sensitivity analyses can be performed (the influence of each

  15. Computational Intelligence and Wavelet Transform Based Metamodel for Efficient Generation of Not-Yet Simulated Waveforms.

    Science.gov (United States)

    Oltean, Gabriel; Ivanciu, Laura-Nicoleta

    2016-01-01

    The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system. The necessary data are obtained by early-stage simulation of an electronic control system from the automotive industry. The metamodel development is based on three key elements: a wavelet transform for waveform characterization, a genetic algorithm optimization to detect the optimal wavelet transform and to identify the most relevant decomposition coefficients, and an artificial neuronal network to derive the relevant coefficients of the wavelet transform for any new parameters combination. The resulted metamodels for three different waveform families are fully reliable. They satisfy the required key points: high accuracy (a maximum mean squared error of 7.1x10-5 for the unity-based normalized waveforms), efficiency (fully affordable computational effort for metamodel build-up: maximum 18 minutes on a general purpose computer), and simplicity (less than 1 second for running the metamodel, the user only provides the parameters combination). The metamodels can be used for very efficient generation of new waveforms, for any possible combination of dependent parameters, offering the possibility to explore the entire design space. A wide range of possibilities becomes achievable for the user, such as: all design corners can be analyzed, possible worst-case situations can be investigated, extreme values of waveforms can be discovered, sensitivity analyses can be performed (the influence of each parameter on the

  16. Computational Intelligence and Wavelet Transform Based Metamodel for Efficient Generation of Not-Yet Simulated Waveforms

    Science.gov (United States)

    Oltean, Gabriel; Ivanciu, Laura-Nicoleta

    2016-01-01

    The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system. The necessary data are obtained by early-stage simulation of an electronic control system from the automotive industry. The metamodel development is based on three key elements: a wavelet transform for waveform characterization, a genetic algorithm optimization to detect the optimal wavelet transform and to identify the most relevant decomposition coefficients, and an artificial neuronal network to derive the relevant coefficients of the wavelet transform for any new parameters combination. The resulted metamodels for three different waveform families are fully reliable. They satisfy the required key points: high accuracy (a maximum mean squared error of 7.1x10-5 for the unity-based normalized waveforms), efficiency (fully affordable computational effort for metamodel build-up: maximum 18 minutes on a general purpose computer), and simplicity (less than 1 second for running the metamodel, the user only provides the parameters combination). The metamodels can be used for very efficient generation of new waveforms, for any possible combination of dependent parameters, offering the possibility to explore the entire design space. A wide range of possibilities becomes achievable for the user, such as: all design corners can be analyzed, possible worst-case situations can be investigated, extreme values of waveforms can be discovered, sensitivity analyses can be performed (the influence of each parameter on the

  17. Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions

    Science.gov (United States)

    Jha, Abhinav K.; Barrett, Harrison H.; Frey, Eric C.; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A.

    2015-09-01

    Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and

  18. Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions.

    Science.gov (United States)

    Jha, Abhinav K; Barrett, Harrison H; Frey, Eric C; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A

    2015-09-21

    Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and

  19. 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.

  20. An Intelligent and Secure Health Monitoring Scheme Using IoT Sensor Based on Cloud Computing

    Directory of Open Access Journals (Sweden)

    Jin-Xin Hu

    2017-01-01

    Full Text Available Internet of Things (IoT is the network of physical objects where information and communication technology connect multiple embedded devices to the Internet for collecting and exchanging data. An important advancement is the ability to connect such devices to large resource pools such as cloud. The integration of embedded devices and cloud servers offers wide applicability of IoT to many areas of our life. With the aging population increasing every day, embedded devices with cloud server can provide the elderly with more flexible service without the need to visit hospitals. Despite the advantages of the sensor-cloud model, it still has various security threats. Therefore, the design and integration of security issues, like authentication and data confidentiality for ensuring the elderly’s privacy, need to be taken into consideration. In this paper, an intelligent and secure health monitoring scheme using IoT sensor based on cloud computing and cryptography is proposed. The proposed scheme achieves authentication and provides essential security requirements.

  1. Performance of multiobjective computational intelligence algorithms for the routing and wavelength assignment problem

    Directory of Open Access Journals (Sweden)

    Jorge Patiño

    2016-01-01

    Full Text Available This paper presents an evaluation performance of computational intelligence algorithms based on the multiobjective theory for the solution of the Routing and Wavelength Assignment problem (RWA in optical networks. The study evaluates the Firefly Algorithm, the Differential Evolutionary Algorithm, the Simulated Annealing Algorithm and two versions of the Particle Swarm Optimization algorithm. The paper provides a description of the multiobjective algorithms; then, an evaluation based on the performance provided by the multiobjective algorithms versus mono-objective approaches when dealing with different traffic loads, different numberof wavelengths and wavelength conversion process over the NSFNet topology is presented. Simulation results show that monoobjective algorithms properly solve the RWA problem for low values of data traffic and low number of wavelengths. However, the multiobjective approaches adapt better to online traffic when the number of wavelengths available in the network increases as well as when wavelength conversion is implemented in the nodes.

  2. Epileptic seizure predictors based on computational intelligence techniques: a comparative study with 278 patients.

    Science.gov (United States)

    Alexandre Teixeira, César; Direito, Bruno; Bandarabadi, Mojtaba; Le Van Quyen, Michel; Valderrama, Mario; Schelter, Bjoern; Schulze-Bonhage, Andreas; Navarro, Vincent; Sales, Francisco; Dourado, António

    2014-05-01

    The ability of computational intelligence methods to predict epileptic seizures is evaluated in long-term EEG recordings of 278 patients suffering from pharmaco-resistant partial epilepsy, also known as refractory epilepsy. This extensive study in seizure prediction considers the 278 patients from the European Epilepsy Database, collected in three epilepsy centres: Hôpital Pitié-là-Salpêtrière, Paris, France; Universitätsklinikum Freiburg, Germany; Centro Hospitalar e Universitário de Coimbra, Portugal. For a considerable number of patients it was possible to find a patient specific predictor with an acceptable performance, as for example predictors that anticipate at least half of the seizures with a rate of false alarms of no more than 1 in 6 h (0.15 h⁻¹). We observed that the epileptic focus localization, data sampling frequency, testing duration, number of seizures in testing, type of machine learning, and preictal time influence significantly the prediction performance. The results allow to face optimistically the feasibility of a patient specific prospective alarming system, based on machine learning techniques by considering the combination of several univariate (single-channel) electroencephalogram features. We envisage that this work will serve as benchmark data that will be of valuable importance for future studies based on the European Epilepsy Database. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  3. Computational Intelligence Method for Early Diagnosis Dengue Haemorrhagic Fever Using Fuzzy on Mobile Device

    Directory of Open Access Journals (Sweden)

    Salman Afan

    2014-03-01

    Full Text Available Mortality from Dengue Haemorrhagic Fever (DHF is still increasing in Indonesia particularly in Jakarta. Diagnosis of the dengue shall be made as early as possible so that first aid can be given in expectation of decreasing death risk. The Study will be conducted by developing expert system based on Computational Intelligence Method. On the first year, study will use the Fuzzy Inference System (FIS Method to diagnose Dengue Haemorrhagic Fever particularly in Mobile Device consist of smart phone. Expert system application which particularly using fuzzy system can be applied in mobile device and it is useful to make early diagnosis of Dengue Haemorrhagic Fever that produce outcome faster than laboratory test. The evaluation of this application is conducted by performing accuracy test before and after validation using data of patient who has the Dengue Haemorrhagic Fever. This expert system application is easy, convenient, and practical to use, also capable of making the early diagnosis of Dengue Haemorraghic to avoid mortality in the first stage.

  4. New evaluation methods for conceptual design selection using computational intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai [University of Electronic Science and Technology of China, Chengdu (China); Xue, Lihua [Higher Education Press, Beijing (China)

    2013-03-15

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  5. New evaluation methods for conceptual design selection using computational intelligence techniques

    International Nuclear Information System (INIS)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai; Xue, Lihua

    2013-01-01

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  6. Computational intelligence-based optimization of maximally stable extremal region segmentation for object detection

    Science.gov (United States)

    Davis, Jeremy E.; Bednar, Amy E.; Goodin, Christopher T.; Durst, Phillip J.; Anderson, Derek T.; Bethel, Cindy L.

    2017-05-01

    Particle swarm optimization (PSO) and genetic algorithms (GAs) are two optimization techniques from the field of computational intelligence (CI) for search problems where a direct solution can not easily be obtained. One such problem is finding an optimal set of parameters for the maximally stable extremal region (MSER) algorithm to detect areas of interest in imagery. Specifically, this paper describes the design of a GA and PSO for optimizing MSER parameters to detect stop signs in imagery produced via simulation for use in an autonomous vehicle navigation system. Several additions to the GA and PSO are required to successfully detect stop signs in simulated images. These additions are a primary focus of this paper and include: the identification of an appropriate fitness function, the creation of a variable mutation operator for the GA, an anytime algorithm modification to allow the GA to compute a solution quickly, the addition of an exponential velocity decay function to the PSO, the addition of an "execution best" omnipresent particle to the PSO, and the addition of an attractive force component to the PSO velocity update equation. Experimentation was performed with the GA using various combinations of selection, crossover, and mutation operators and experimentation was also performed with the PSO using various combinations of neighborhood topologies, swarm sizes, cognitive influence scalars, and social influence scalars. The results of both the GA and PSO optimized parameter sets are presented. This paper details the benefits and drawbacks of each algorithm in terms of detection accuracy, execution speed, and additions required to generate successful problem specific parameter sets.

  7. 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.

  8. A Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Mohammad Nurul Afsar Shaon

    2017-05-01

    Full Text Available A wormhole attack is one of the most critical and challenging security threats for wireless sensor networks because of its nature and ability to perform concealed malicious activities. This paper proposes an innovative wormhole detection scheme to detect wormhole attacks using computational intelligence and an artificial neural network (ANN. Most wormhole detection schemes reported in the literature assume the sensors are uniformly distributed in a network, and, furthermore, they use statistical and topological information and special hardware for their detection. However, these schemes may perform poorly in non-uniformly distributed networks, and, moreover, they may fail to defend against “out of band” and “in band” wormhole attacks. The aim of the proposed research is to develop a detection scheme that is able to detect all kinds of wormhole attacks in both uniformly and non-uniformly distributed sensor networks. Furthermore, the proposed research does not require any special hardware and causes no significant network overhead throughout the network. Most importantly, the probable location of the malicious nodes can be identified by the proposed ANN based detection scheme. We evaluate the efficacy of the proposed detection scheme in terms of detection accuracy, false positive rate, and false negative rate. The performance of the proposed algorithm is also compared with other machine learning techniques (i.e. SVM and regularized nonlinear logistic regression (LR based detection models. The simulation results show that proposed ANN based algorithm outperforms the SVM or LR based detection schemes in terms of detection accuracy, false positive rate, and false negative rates.

  9. INTELLIGENT COMPUTING SYSTEM FOR RESERVOIR ANALYSIS AND RISK ASSESSMENT OF THE RED RIVER FORMATION

    Energy Technology Data Exchange (ETDEWEB)

    Mark A. Sippel; William C. Carrigan; Kenneth D. Luff; Lyn Canter

    2003-11-12

    Integrated software has been written that comprises the tool kit for the Intelligent Computing System (ICS). The software tools in ICS have been developed for characterization of reservoir properties and evaluation of hydrocarbon potential using a combination of inter-disciplinary data sources such as geophysical, geologic and engineering variables. The ICS tools provide a means for logical and consistent reservoir characterization and oil reserve estimates. The tools can be broadly characterized as (1) clustering tools, (2) neural solvers, (3) multiple-linear regression, (4) entrapment-potential calculator and (5) file utility tools. ICS tools are extremely flexible in their approach and use, and applicable to most geologic settings. The tools are primarily designed to correlate relationships between seismic information and engineering and geologic data obtained from wells, and to convert or translate seismic information into engineering and geologic terms or units. It is also possible to apply ICS in a simple framework that may include reservoir characterization using only engineering, seismic, or geologic data in the analysis. ICS tools were developed and tested using geophysical, geologic and engineering data obtained from an exploitation and development project involving the Red River Formation in Bowman County, North Dakota and Harding County, South Dakota. Data obtained from 3D seismic surveys, and 2D seismic lines encompassing nine prospective field areas were used in the analysis. The geologic setting of the Red River Formation in Bowman and Harding counties is that of a shallow-shelf, carbonate system. Present-day depth of the Red River formation is approximately 8000 to 10,000 ft below ground surface. This report summarizes production results from well demonstration activity, results of reservoir characterization of the Red River Formation at demonstration sites, descriptions of ICS tools and strategies for their application.

  10. Making Computers Smarter: A Look At the Controversial Field of Artificial Intelligence.

    Science.gov (United States)

    Green, John O.

    1984-01-01

    Defines artificial intelligence (AI) and discusses its history; the current state of the art, research, experimentation, and practical applications; and probable future developments. Key dates in the history of AI and eight references are provided. (MBR)

  11. Army Intelligence Analysis and Interpretation: Assessing the Utility and Limitations of Computational Diagnostic Reasoning

    National Research Council Canada - National Science Library

    Powell, Gerald M

    2004-01-01

    .... For fusion in the Army, little has been published reflecting an elaboration of functionality on levels 2 and 3 of this model, both of which are viewed as critical elements of intelligence analysis and interpretation. Walsh (2002...

  12. Computer-aided N. M. R. spectra interpretation. I. An artificial intelligence system

    Energy Technology Data Exchange (ETDEWEB)

    Vida, M [Central N.M.R. Laboratory, Slovak Technical University, Bratislava (Czechoslovakia)

    1980-03-01

    Some desirable hardware and software features of an artificial intelligence system tailored to the needs of a modern computerized n.m.r. laboratory are discussed. A system corresponding to this idea is described.

  13. 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.

  14. 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.

  15. Application of Computational Intelligence Methods to In-Core Fuel Management

    International Nuclear Information System (INIS)

    Erdogan, A.

    2001-01-01

    In this study, a computer program package has been developed which supports the in-core fuel management activities for pressurized water reactors, generates and recommends an optimum loading pattern to ensure safe and efficient reactor operation. A search for an optimum fuel loading pattern must be conducted in the space of several core parameters such as power distribution, which is an excessively time consuming computational process. Global core calculation codes take a relatively long time to do the task. The time interval necessary for the iterative process was reduced by using an artificial neural network estimator for the calculations. In this way, it was possible to analyze more loading patterns in the same time interval and the probability of finding a desired optimum was increased. As a case study, the core of the Almaraz Nuclear Plant of Spain, a pressurized water reactor, was modeled for the core calculation code system. The 2-group cross sections for the fuel assembly types were calculated and stored for later usage with the diffusion code. 2000 loading patterns were generated by placing fuel assemblies to random positions in the core, and for each pattern the power distribution and effective multiplication factor (k e ff) were calculated with the diffusion code. At the next stage, 500 of the loading patterns were introduced to the neural network as input data for the training process. The remaining 1500 patterns were used to validate the neural network implementation. It was shown that the neural network estimates the power distribution and the K effective within acceptable error limits. To complete the system, a loading pattern generator was developed. This module consists of a set of rules and an algorithm that places the fuel assemblies to core positions. The neural network estimated the power distribution and k e ff for the loading patterns that were generated by this module. The patterns that have a maximum power fraction lower than, and a minimum

  16. Computational intelligence for the Balanced Scorecard: studying performance trends of hemodialysis clinics.

    Science.gov (United States)

    Cattinelli, Isabella; Bolzoni, Elena; Chermisi, Milena; Bellocchio, Francesco; Barbieri, Carlo; Mari, Flavio; Amato, Claudia; Menzer, Marcus; Stopper, Andrea; Gatti, Emanuele

    2013-07-01

    The Balanced Scorecard (BSC) is a general, widely employed instrument for enterprise performance monitoring based on the periodic assessment of strategic Key Performance Indicators that are scored against preset targets. The BSC is currently employed as an effective management support tool within Fresenius Medical Care (FME) and is routinely analyzed via standard statistical methods. More recently, the application of computational intelligence techniques (namely, self-organizing maps) to BSC data has been proposed as a way to enhance the quantity and quality of information that can be extracted from it. In this work, additional methods are presented to analyze the evolution of clinic performance over time. Performance evolution is studied at the single-clinic level by computing two complementary indexes that measure the proportion of time spent within performance clusters and improving/worsening trends. Self-organizing maps are used in conjunction with these indexes to identify the specific drivers of the observed performance. The performance evolution for groups of clinics is modeled under a probabilistic framework by resorting to Markov chain properties. These allow a study of the probability of transitioning between performance clusters as time progresses for the identification of the performance level that is expected to become dominant over time. We show the potential of the proposed methods through illustrative results derived from the analysis of BSC data of 109 FME clinics in three countries. We were able to identify the performance drivers for specific groups of clinics and to distinguish between countries whose performances are likely to improve from those where a decline in performance might be expected. According to the stationary distribution of the Markov chain, the expected trend is best in Turkey (where the highest performance cluster has the highest probability, P=0.46), followed by Portugal (where the second best performance cluster dominates

  17. Domain decomposition with local refinement for flow simulation around a nuclear waste disposal site: direct computation versus simulation using code coupling with OCamlP3L

    Energy Technology Data Exchange (ETDEWEB)

    Clement, F.; Vodicka, A.; Weis, P. [Institut National de Recherches Agronomiques (INRA), 78 - Le Chesnay (France); Martin, V. [Institut National de Recherches Agronomiques (INRA), 92 - Chetenay Malabry (France); Di Cosmo, R. [Institut National de Recherches Agronomiques (INRA), 78 - Le Chesnay (France); Paris-7 Univ., 75 (France)

    2003-07-01

    We consider the application of a non-overlapping domain decomposition method with non-matching grids based on Robin interface conditions to the problem of flow surrounding an underground nuclear waste disposal. We show with a simple example how one can refine the mesh locally around the storage with this technique. A second aspect is studied in this paper. The coupling between the sub-domains can be achieved by computing in two ways: either directly (i.e. the domain decomposition algorithm is included in the code that solves the problems on the sub-domains) or using code coupling. In the latter case, each sub-domain problem is solved separately and the coupling is performed by another program. We wrote a coupling program in the functional language Ocaml, using the OcamIP31 environment devoted to ease the parallelism. This at the same time we test the code coupling and we use the natural parallel property of domain decomposition methods. Some simple 2D numerical tests show promising results, and further studies are under way. (authors)

  18. Domain decomposition with local refinement for flow simulation around a nuclear waste disposal site: direct computation versus simulation using code coupling with OCamlP3L

    International Nuclear Information System (INIS)

    Clement, F.; Vodicka, A.; Weis, P.; Martin, V.; Di Cosmo, R.

    2003-01-01

    We consider the application of a non-overlapping domain decomposition method with non-matching grids based on Robin interface conditions to the problem of flow surrounding an underground nuclear waste disposal. We show with a simple example how one can refine the mesh locally around the storage with this technique. A second aspect is studied in this paper. The coupling between the sub-domains can be achieved by computing in two ways: either directly (i.e. the domain decomposition algorithm is included in the code that solves the problems on the sub-domains) or using code coupling. In the latter case, each sub-domain problem is solved separately and the coupling is performed by another program. We wrote a coupling program in the functional language Ocaml, using the OcamIP31 environment devoted to ease the parallelism. This at the same time we test the code coupling and we use the natural parallel property of domain decomposition methods. Some simple 2D numerical tests show promising results, and further studies are under way. (authors)

  19. 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...

  20. ARGUMENTS ON USING COMPUTER-ASSISTED AUDIT TECHNIQUES (CAAT AND BUSINESS INTELLIGENCE TO IMPROVE THE WORK OF THE FINANCIAL AUDITOR

    Directory of Open Access Journals (Sweden)

    Ciprian-Costel, MUNTEANU

    2014-11-01

    Full Text Available In the 21st century, one of the most efficient ways to achieve an independent audit and quality opinion is by using information from the organization database, mainly documents in electronic format. With the help of Computer-Assisted Audit Techniques (CAAT, the financial auditor analyzes part or even all the data about a company in reference to other information within or outside the entity. The main purpose of this paper is to show the benefits of evolving from traditional audit techniques and tools to modern and , why not, visionary CAAT, which are supported by business intelligence systems. Given the opportunity to perform their work in IT environments, the auditors would start using the tools of business intelligence, a key factor which contributes to making successful business decisions . CAAT enable auditors to test large amount of data quickly and accurately and therefore increase the confidence they have in their opinion.

  1. 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...

  2. 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....

  3. 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

  4. 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

  5. Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology, Volume 1

    Science.gov (United States)

    Hyde, Patricia R.; Loftin, R. Bowen

    1993-01-01

    These proceedings are organized in the same manner as the conference's contributed sessions, with the papers grouped by topic area. These areas are as follows: VE (virtual environment) training for Space Flight, Virtual Environment Hardware, Knowledge Aquisition for ICAT (Intelligent Computer-Aided Training) & VE, Multimedia in ICAT Systems, VE in Training & Education (1 & 2), Virtual Environment Software (1 & 2), Models in ICAT systems, ICAT Commercial Applications, ICAT Architectures & Authoring Systems, ICAT Education & Medical Applications, Assessing VE for Training, VE & Human Systems (1 & 2), ICAT Theory & Natural Language, ICAT Applications in the Military, VE Applications in Engineering, Knowledge Acquisition for ICAT, and ICAT Applications in Aerospace.

  6. Improved scFv Anti-HIV-1 p17 Binding Affinity Guided from the Theoretical Calculation of Pairwise Decomposition Energies and Computational Alanine Scanning

    Directory of Open Access Journals (Sweden)

    Panthip Tue-ngeun

    2013-01-01

    Full Text Available Computational approaches have been used to evaluate and define important residues for protein-protein interactions, especially antigen-antibody complexes. In our previous study, pairwise decomposition of residue interaction energies of single chain Fv with HIV-1 p17 epitope variants has indicated the key specific residues in the complementary determining regions (CDRs of scFv anti-p17. In this present investigation in order to determine whether a specific side chain group of residue in CDRs plays an important role in bioactivity, computational alanine scanning has been applied. Molecular dynamics simulations were done with several complexes of original scFv anti-p17 and scFv anti-p17mutants with HIV-1 p17 epitope variants with a production run up to 10 ns. With the combination of pairwise decomposition residue interaction and alanine scanning calculations, the point mutation has been initially selected at the position MET100 to improve the residue binding affinity. The calculated docking interaction energy between a single mutation from methionine to either arginine or glycine has shown the improved binding affinity, contributed from the electrostatic interaction with the negative favorably interaction energy, compared to the wild type. Theoretical calculations agreed well with the results from the peptide ELISA results.

  7. A Game Based e-Learning System to Teach Artificial Intelligence in the Computer Sciences Degree

    Science.gov (United States)

    de Castro-Santos, Amable; Fajardo, Waldo; Molina-Solana, Miguel

    2017-01-01

    Our students taking the Artificial Intelligence and Knowledge Engineering courses often encounter a large number of problems to solve which are not directly related to the subject to be learned. To solve this problem, we have developed a game based e-learning system. The elected game, that has been implemented as an e-learning system, allows to…

  8. Using Computer-Based Artificial Intelligence Technology to Help ESL Students.

    Science.gov (United States)

    Adams, Dennis M.

    This paper discusses ways in which artificial intelligence (AI) technologies may be used to aid students for whom English is a second language in the development of language and reading skills, and asserts that the coupling of technology with close adult-teacher contacts within a context of cultural precedents and social rewards is an important…

  9. Decomposition techniques

    Science.gov (United States)

    Chao, T.T.; Sanzolone, R.F.

    1992-01-01

    Sample decomposition is a fundamental and integral step in the procedure of geochemical analysis. It is often the limiting factor to sample throughput, especially with the recent application of the fast and modern multi-element measurement instrumentation. The complexity of geological materials makes it necessary to choose the sample decomposition technique that is compatible with the specific objective of the analysis. When selecting a decomposition technique, consideration should be given to the chemical and mineralogical characteristics of the sample, elements to be determined, precision and accuracy requirements, sample throughput, technical capability of personnel, and time constraints. This paper addresses these concerns and discusses the attributes and limitations of many techniques of sample decomposition along with examples of their application to geochemical analysis. The chemical properties of reagents as to their function as decomposition agents are also reviewed. The section on acid dissolution techniques addresses the various inorganic acids that are used individually or in combination in both open and closed systems. Fluxes used in sample fusion are discussed. The promising microwave-oven technology and the emerging field of automation are also examined. A section on applications highlights the use of decomposition techniques for the determination of Au, platinum group elements (PGEs), Hg, U, hydride-forming elements, rare earth elements (REEs), and multi-elements in geological materials. Partial dissolution techniques used for geochemical exploration which have been treated in detail elsewhere are not discussed here; nor are fire-assaying for noble metals and decomposition techniques for X-ray fluorescence or nuclear methods be discussed. ?? 1992.

  10. Application of the SP theory of intelligence to the understanding of natural vision and the development of computer vision.

    Science.gov (United States)

    Wolff, J Gerard

    2014-01-01

    The SP theory of intelligence aims to simplify and integrate concepts in computing and cognition, with information compression as a unifying theme. This article is about how the SP theory may, with advantage, be applied to the understanding of natural vision and the development of computer vision. Potential benefits include an overall simplification of concepts in a universal framework for knowledge and seamless integration of vision with other sensory modalities and other aspects of intelligence. Low level perceptual features such as edges or corners may be identified by the extraction of redundancy in uniform areas in the manner of the run-length encoding technique for information compression. The concept of multiple alignment in the SP theory may be applied to the recognition of objects, and to scene analysis, with a hierarchy of parts and sub-parts, at multiple levels of abstraction, and with family-resemblance or polythetic categories. The theory has potential for the unsupervised learning of visual objects and classes of objects, and suggests how coherent concepts may be derived from fragments. As in natural vision, both recognition and learning in the SP system are robust in the face of errors of omission, commission and substitution. The theory suggests how, via vision, we may piece together a knowledge of the three-dimensional structure of objects and of our environment, it provides an account of how we may see things that are not objectively present in an image, how we may recognise something despite variations in the size of its retinal image, and how raster graphics and vector graphics may be unified. And it has things to say about the phenomena of lightness constancy and colour constancy, the role of context in recognition, ambiguities in visual perception, and the integration of vision with other senses and other aspects of intelligence.

  11. An Intelligent Computer-aided Training System (CAT) for Diagnosing Adult Illiterates: Integrating NASA Technology into Workplace Literacy

    Science.gov (United States)

    Yaden, David B., Jr.

    1991-01-01

    An important part of NASA's mission involves the secondary application of its technologies in the public and private sectors. One current application being developed is The Adult Literacy Evaluator, a simulation-based diagnostic tool designed to assess the operant literacy abilities of adults having difficulties in learning to read and write. Using Intelligent Computer-Aided Training (ICAT) system technology in addition to speech recognition, closed-captioned television (CCTV), live video and other state-of-the-art graphics and storage capabilities, this project attempts to overcome the negative effects of adult literacy assessment by allowing the client to interact with an intelligent computer system which simulates real-life literacy activities and materials and which measures literacy performance in the actual context of its use. The specific objectives of the project are as follows: (1) to develop a simulation-based diagnostic tool to assess adults' prior knowledge about reading and writing processes in actual contexts of application; (2) to provide a profile of readers' strengths and weaknesses; and (3) to suggest instructional strategies and materials which can be used as a beginning point for remediation. In the first and development phase of the project, descriptions of literacy events and environments are being written and functional literacy documents analyzed for their components. From these descriptions, scripts are being generated which define the interaction between the student, an on-screen guide and the simulated literacy environment.

  12. Potential applications of artificial intelligence in computer-based management systems for mixed waste incinerator facility operation

    International Nuclear Information System (INIS)

    Rivera, A.L.; Singh, S.P.N.; Ferrada, J.J.

    1991-01-01

    The Department of Energy/Oak Ridge Field Office (DOE/OR) operates a mixed waste incinerator facility at the Oak Ridge K-25 Site, designed for the thermal treatment of incinerable liquid, sludge, and solid waste regulated under the Toxic Substances Control Act (TSCA) and the Resource Conversion and Recovery Act (RCRA). Operation of the TSCA Incinerator is highly constrained as a result of the regulatory, institutional, technical, and resource availability requirements. This presents an opportunity for applying computer technology as a technical resource for mixed waste incinerator operation to facilitate promoting and sustaining a continuous performance improvement process while demonstrating compliance. This paper describes mixed waste incinerator facility performance-oriented tasks that could be assisted by Artificial Intelligence (AI) and the requirements for AI tools that would implement these algorithms in a computer-based system. 4 figs., 1 tab

  13. Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning

    CERN Document Server

    Demetriadis, Stavros; Xhafa, Fatos

    2012-01-01

    Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligen...

  14. Residential Consumer-Centric Demand-Side Management Based on Energy Disaggregation-Piloting Constrained Swarm Intelligence: Towards Edge Computing

    Science.gov (United States)

    Hu, Yu-Chen

    2018-01-01

    The emergence of smart Internet of Things (IoT) devices has highly favored the realization of smart homes in a down-stream sector of a smart grid. The underlying objective of Demand Response (DR) schemes is to actively engage customers to modify their energy consumption on domestic appliances in response to pricing signals. Domestic appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption intelligently. Besides, to residential customers for DR implementation, maintaining a balance between energy consumption cost and users’ comfort satisfaction is a challenge. Hence, in this paper, a constrained Particle Swarm Optimization (PSO)-based residential consumer-centric load-scheduling method is proposed. The method can be further featured with edge computing. In contrast with cloud computing, edge computing—a method of optimizing cloud computing technologies by driving computing capabilities at the IoT edge of the Internet as one of the emerging trends in engineering technology—addresses bandwidth-intensive contents and latency-sensitive applications required among sensors and central data centers through data analytics at or near the source of data. A non-intrusive load-monitoring technique proposed previously is utilized to automatic determination of physical characteristics of power-intensive home appliances from users’ life patterns. The swarm intelligence, constrained PSO, is used to minimize the energy consumption cost while considering users’ comfort satisfaction for DR implementation. The residential consumer-centric load-scheduling method proposed in this paper is evaluated under real-time pricing with inclining block rates and is demonstrated in a case study. The experimentation reported in this paper shows the proposed residential consumer-centric load-scheduling method can re-shape loads by home appliances in response to DR signals. Moreover, a phenomenal reduction in peak power consumption is achieved

  15. Residential Consumer-Centric Demand-Side Management Based on Energy Disaggregation-Piloting Constrained Swarm Intelligence: Towards Edge Computing

    Directory of Open Access Journals (Sweden)

    Yu-Hsiu Lin

    2018-04-01

    Full Text Available The emergence of smart Internet of Things (IoT devices has highly favored the realization of smart homes in a down-stream sector of a smart grid. The underlying objective of Demand Response (DR schemes is to actively engage customers to modify their energy consumption on domestic appliances in response to pricing signals. Domestic appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption intelligently. Besides, to residential customers for DR implementation, maintaining a balance between energy consumption cost and users’ comfort satisfaction is a challenge. Hence, in this paper, a constrained Particle Swarm Optimization (PSO-based residential consumer-centric load-scheduling method is proposed. The method can be further featured with edge computing. In contrast with cloud computing, edge computing—a method of optimizing cloud computing technologies by driving computing capabilities at the IoT edge of the Internet as one of the emerging trends in engineering technology—addresses bandwidth-intensive contents and latency-sensitive applications required among sensors and central data centers through data analytics at or near the source of data. A non-intrusive load-monitoring technique proposed previously is utilized to automatic determination of physical characteristics of power-intensive home appliances from users’ life patterns. The swarm intelligence, constrained PSO, is used to minimize the energy consumption cost while considering users’ comfort satisfaction for DR implementation. The residential consumer-centric load-scheduling method proposed in this paper is evaluated under real-time pricing with inclining block rates and is demonstrated in a case study. The experimentation reported in this paper shows the proposed residential consumer-centric load-scheduling method can re-shape loads by home appliances in response to DR signals. Moreover, a phenomenal reduction in peak power

  16. Residential Consumer-Centric Demand-Side Management Based on Energy Disaggregation-Piloting Constrained Swarm Intelligence: Towards Edge Computing.

    Science.gov (United States)

    Lin, Yu-Hsiu; Hu, Yu-Chen

    2018-04-27

    The emergence of smart Internet of Things (IoT) devices has highly favored the realization of smart homes in a down-stream sector of a smart grid. The underlying objective of Demand Response (DR) schemes is to actively engage customers to modify their energy consumption on domestic appliances in response to pricing signals. Domestic appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption intelligently. Besides, to residential customers for DR implementation, maintaining a balance between energy consumption cost and users’ comfort satisfaction is a challenge. Hence, in this paper, a constrained Particle Swarm Optimization (PSO)-based residential consumer-centric load-scheduling method is proposed. The method can be further featured with edge computing. In contrast with cloud computing, edge computing—a method of optimizing cloud computing technologies by driving computing capabilities at the IoT edge of the Internet as one of the emerging trends in engineering technology—addresses bandwidth-intensive contents and latency-sensitive applications required among sensors and central data centers through data analytics at or near the source of data. A non-intrusive load-monitoring technique proposed previously is utilized to automatic determination of physical characteristics of power-intensive home appliances from users’ life patterns. The swarm intelligence, constrained PSO, is used to minimize the energy consumption cost while considering users’ comfort satisfaction for DR implementation. The residential consumer-centric load-scheduling method proposed in this paper is evaluated under real-time pricing with inclining block rates and is demonstrated in a case study. The experimentation reported in this paper shows the proposed residential consumer-centric load-scheduling method can re-shape loads by home appliances in response to DR signals. Moreover, a phenomenal reduction in peak power consumption is achieved

  17. Neural computing thermal comfort index PMV for the indoor environment intelligent control system

    Science.gov (United States)

    Liu, Chang; Chen, Yifei

    2013-03-01

    Providing indoor thermal comfort and saving energy are two main goals of indoor environmental control system. An intelligent comfort control system by combining the intelligent control and minimum power control strategies for the indoor environment is presented in this paper. In the system, for realizing the comfort control, the predicted mean vote (PMV) is designed as the control goal, and with chastening formulas of PMV, it is controlled to optimize for improving indoor comfort lever by considering six comfort related variables. On the other hand, a RBF neural network based on genetic algorithm is designed to calculate PMV for better performance and overcoming the nonlinear feature of the PMV calculation better. The formulas given in the paper are presented for calculating the expected output values basing on the input samples, and the RBF network model is trained depending on input samples and the expected output values. The simulation result is proved that the design of the intelligent calculation method is valid. Moreover, this method has a lot of advancements such as high precision, fast dynamic response and good system performance are reached, it can be used in practice with requested calculating error.

  18. 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

  19. Phantom-less bone mineral density (BMD) measurement using dual energy computed tomography-based 3-material decomposition

    Science.gov (United States)

    Hofmann, Philipp; Sedlmair, Martin; Krauss, Bernhard; Wichmann, Julian L.; Bauer, Ralf W.; Flohr, Thomas G.; Mahnken, Andreas H.

    2016-03-01

    Osteoporosis is a degenerative bone disease usually diagnosed at the manifestation of fragility fractures, which severely endanger the health of especially the elderly. To ensure timely therapeutic countermeasures, noninvasive and widely applicable diagnostic methods are required. Currently the primary quantifiable indicator for bone stability, bone mineral density (BMD), is obtained either by DEXA (Dual-energy X-ray absorptiometry) or qCT (quantitative CT). Both have respective advantages and disadvantages, with DEXA being considered as gold standard. For timely diagnosis of osteoporosis, another CT-based method is presented. A Dual Energy CT reconstruction workflow is being developed to evaluate BMD by evaluating lumbar spine (L1-L4) DE-CT images. The workflow is ROI-based and automated for practical use. A dual energy 3-material decomposition algorithm is used to differentiate bone from soft tissue and fat attenuation. The algorithm uses material attenuation coefficients on different beam energy levels. The bone fraction of the three different tissues is used to calculate the amount of hydroxylapatite in the trabecular bone of the corpus vertebrae inside a predefined ROI. Calibrations have been performed to obtain volumetric bone mineral density (vBMD) without having to add a calibration phantom or to use special scan protocols or hardware. Accuracy and precision are dependent on image noise and comparable to qCT images. Clinical indications are in accordance with the DEXA gold standard. The decomposition-based workflow shows bone degradation effects normally not visible on standard CT images which would induce errors in normal qCT results.

  20. Application of multi-thread computing and domain decomposition to the 3-D neutronics Fem code Cronos

    International Nuclear Information System (INIS)

    Ragusa, J.C.

    2003-01-01

    The purpose of this paper is to present the parallelization of the flux solver and the isotopic depletion module of the code, either using Message Passing Interface (MPI) or OpenMP. Thread parallelism using OpenMP was used to parallelize the mixed dual FEM (finite element method) flux solver MINOS. Investigations regarding the opportunity of mixing parallelism paradigms will be discussed. The isotopic depletion module was parallelized using domain decomposition and MPI. An attempt at using OpenMP was unsuccessful and will be explained. This paper is organized as follows: the first section recalls the different types of parallelism. The mixed dual flux solver and its parallelization are then presented. In the third section, we describe the isotopic depletion solver and its parallelization; and finally conclude with some future perspectives. Parallel applications are mandatory for fine mesh 3-dimensional transport and simplified transport multigroup calculations. The MINOS solver of the FEM neutronics code CRONOS2 was parallelized using the directive based standard OpenMP. An efficiency of 80% (resp. 60%) was achieved with 2 (resp. 4) threads. Parallelization of the isotopic depletion solver was obtained using domain decomposition principles and MPI. Efficiencies greater than 90% were reached. These parallel implementations were tested on a shared memory symmetric multiprocessor (SMP) cluster machine. The OpenMP implementation in the solver MINOS is only the first step towards fully using the SMPs cluster potential with a mixed mode parallelism. Mixed mode parallelism can be achieved by combining message passing interface between clusters with OpenMP implicit parallelism within a cluster

  1. Application of multi-thread computing and domain decomposition to the 3-D neutronics Fem code Cronos

    Energy Technology Data Exchange (ETDEWEB)

    Ragusa, J.C. [CEA Saclay, Direction de l' Energie Nucleaire, Service d' Etudes des Reacteurs et de Modelisations Avancees (DEN/SERMA), 91 - Gif sur Yvette (France)

    2003-07-01

    The purpose of this paper is to present the parallelization of the flux solver and the isotopic depletion module of the code, either using Message Passing Interface (MPI) or OpenMP. Thread parallelism using OpenMP was used to parallelize the mixed dual FEM (finite element method) flux solver MINOS. Investigations regarding the opportunity of mixing parallelism paradigms will be discussed. The isotopic depletion module was parallelized using domain decomposition and MPI. An attempt at using OpenMP was unsuccessful and will be explained. This paper is organized as follows: the first section recalls the different types of parallelism. The mixed dual flux solver and its parallelization are then presented. In the third section, we describe the isotopic depletion solver and its parallelization; and finally conclude with some future perspectives. Parallel applications are mandatory for fine mesh 3-dimensional transport and simplified transport multigroup calculations. The MINOS solver of the FEM neutronics code CRONOS2 was parallelized using the directive based standard OpenMP. An efficiency of 80% (resp. 60%) was achieved with 2 (resp. 4) threads. Parallelization of the isotopic depletion solver was obtained using domain decomposition principles and MPI. Efficiencies greater than 90% were reached. These parallel implementations were tested on a shared memory symmetric multiprocessor (SMP) cluster machine. The OpenMP implementation in the solver MINOS is only the first step towards fully using the SMPs cluster potential with a mixed mode parallelism. Mixed mode parallelism can be achieved by combining message passing interface between clusters with OpenMP implicit parallelism within a cluster.

  2. Separation of hepatic iron and fat by dual-source dual-energy computed tomography based on material decomposition: an animal study.

    Science.gov (United States)

    Ma, Jing; Song, Zhi-Qiang; Yan, Fu-Hua

    2014-01-01

    To explore the feasibility of dual-source dual-energy computed tomography (DSDECT) for hepatic iron and fat separation in vivo. All of the procedures in this study were approved by the Research Animal Resource Center of Shanghai Ruijin Hospital. Sixty rats that underwent DECT scanning were divided into the normal group, fatty liver group, liver iron group, and coexisting liver iron and fat group, according to Prussian blue and HE staining. The data for each group were reconstructed and post-processed by an iron-specific, three-material decomposition algorithm. The iron enhancement value and the virtual non-iron contrast value, which indicated overloaded liver iron and residual liver tissue, respectively, were measured. Spearman's correlation and one-way analysis of variance (ANOVA) were performed, respectively, to analyze statistically the correlations with the histopathological results and differences among groups. The iron enhancement values were positively correlated with the iron pathology grading (r = 0.729, pVNC) values were negatively correlated with the fat pathology grading (r = -0.642,pVNC values (F = 25.308,pVNC values were only observed between the fat-present and fat-absent groups. Separation of hepatic iron and fat by dual energy material decomposition in vivo was feasible, even when they coexisted.

  3. Project APhiD: A Lorenz-gauged A-Φ decomposition for parallelized computation of ultra-broadband electromagnetic induction in a fully heterogeneous Earth

    Science.gov (United States)

    Weiss, Chester J.

    2013-08-01

    An essential element for computational hypothesis testing, data inversion and experiment design for electromagnetic geophysics is a robust forward solver, capable of easily and quickly evaluating the electromagnetic response of arbitrary geologic structure. The usefulness of such a solver hinges on the balance among competing desires like ease of use, speed of forward calculation, scalability to large problems or compute clusters, parsimonious use of memory access, accuracy and by necessity, the ability to faithfully accommodate a broad range of geologic scenarios over extremes in length scale and frequency content. This is indeed a tall order. The present study addresses recent progress toward the development of a forward solver with these properties. Based on the Lorenz-gauged Helmholtz decomposition, a new finite volume solution over Cartesian model domains endowed with complex-valued electrical properties is shown to be stable over the frequency range 10-2-1010 Hz and range 10-3-105 m in length scale. Benchmark examples are drawn from magnetotellurics, exploration geophysics, geotechnical mapping and laboratory-scale analysis, showing excellent agreement with reference analytic solutions. Computational efficiency is achieved through use of a matrix-free implementation of the quasi-minimum-residual (QMR) iterative solver, which eliminates explicit storage of finite volume matrix elements in favor of "on the fly" computation as needed by the iterative Krylov sequence. Further efficiency is achieved through sparse coupling matrices between the vector and scalar potentials whose non-zero elements arise only in those parts of the model domain where the conductivity gradient is non-zero. Multi-thread parallelization in the QMR solver through OpenMP pragmas is used to reduce the computational cost of its most expensive step: the single matrix-vector product at each iteration. High-level MPI communicators farm independent processes to available compute nodes for

  4. 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.

  5. Generative Computer Assisted Instruction: An Application of Artificial Intelligence to CAI.

    Science.gov (United States)

    Koffman, Elliot B.

    Frame-oriented computer-assisted instruction (CAI) systems dominate the field, but these mechanized programed texts utilize the computational power of the computer to a minimal degree and are difficult to modify. Newer, generative CAI systems which are supplied with a knowledge of subject matter can generate their own problems and solutions, can…

  6. Effect of roll compaction on granule size distribution of microcrystalline cellulose–mannitol mixtures: computational intelligence modeling and parametric analysis

    Directory of Open Access Journals (Sweden)

    Kazemi P

    2017-01-01

    Full Text Available Pezhman Kazemi,1 Mohammad Hassan Khalid,1 Ana Pérez Gago,2 Peter Kleinebudde,2 Renata Jachowicz,1 Jakub Szlęk,1 Aleksander Mendyk1 1Department of Pharmaceutical Technology and Biopharmaceutics, Faculty of Pharmacy, Jagiellonian University Medical College, Krakow, Poland; 2Institute of Pharmaceutics and Biopharmaceutics, Heinrich-Heine-University, Düsseldorf, Germany Abstract: Dry granulation using roll compaction is a typical unit operation for producing solid dosage forms in the pharmaceutical industry. Dry granulation is commonly used if the powder mixture is sensitive to heat and moisture and has poor flow properties. The output of roll compaction is compacted ribbons that exhibit different properties based on the adjusted process parameters. These ribbons are then milled into granules and finally compressed into tablets. The properties of the ribbons directly affect the granule size distribution (GSD and the quality of final products; thus, it is imperative to study the effect of roll compaction process parameters on GSD. The understanding of how the roll compactor process parameters and material properties interact with each other will allow accurate control of the process, leading to the implementation of quality by design practices. Computational intelligence (CI methods have a great potential for being used within the scope of quality by design approach. The main objective of this study was to show how the computational intelligence techniques can be useful to predict the GSD by using different process conditions of roll compaction and material properties. Different techniques such as multiple linear regression, artificial neural networks, random forest, Cubist and k-nearest neighbors algorithm assisted by sevenfold cross-validation were used to present generalized models for the prediction of GSD based on roll compaction process setting and material properties. The normalized root-mean-squared error and the coefficient of

  7. 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.

  8. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  9. Doing Very Big Calculations on Modest Size Computers: Reducing the Cost of Exact Diagonalization Using Singular Value Decomposition

    International Nuclear Information System (INIS)

    Weinstein, M.

    2012-01-01

    I will talk about a new way of implementing Lanczos and contraction algorithms to diagonalize lattice Hamiltonians that dramatically reduces the memory required to do the computation, without restricting to variational ansatzes. (author)

  10. SIMON [Semi-Intelligent Mobile Observing Navigator] combines radiation hardness with computer power

    International Nuclear Information System (INIS)

    Weber, P.J.; Vanecek, C.W.

    1990-01-01

    SIMON - the Semi-Intelligent Mobile Observing Navigator - has been under development at the US Department of Energy's (DoE's) Savannah River Laboratory for four years. The robot's on-board intelligence units are designed to be radiation-resistant, making it able to function for extended periods within a remotely operated facility. In its current form, SIMON is being developed by the laboratory's Robotics Group for use in the site's production reactors, but it can be adapted for use in any nuclear facility, including commercial reactors. The challenge for Savannah River Laboratory engineers was to eliminate the need for human inspection of certain components. To do this, they designed a robot that could do three things for reactor operators: measure radiation; measure temperature; and provide televised views inside the reactor facility. To be useful, the robot has to be extremely mobile, and its components had to be able to survive months without maintenance in the radiation, temperature and humidity encountered in nuclear facilities. The robot also had to be cost-effective. (author)

  11. Intelligent computer aided training systems in the real world: Making the technology accessible to the educational mainstream

    Science.gov (United States)

    Kovarik, Madeline

    1993-01-01

    Intelligent computer aided training systems hold great promise for the application of this technology to mainstream education and training. Yet, this technology, which holds such a vast potential impact for the future of education and training, has had little impact beyond the enclaves of government research labs. This is largely due to the inaccessibility of the technology to those individuals in whose hands it can have the greatest impact, teachers and educators. Simply throwing technology at an educator and expecting them to use it as an effective tool is not the answer. This paper provides a background into the use of technology as a training tool. MindLink, developed by HyperTech Systems, provides trainers with a powerful rule-based tool that can be integrated directly into a Windows application. By embedding expert systems technology it becomes more accessible and easier to master.

  12. The Effects of Self-Regulatory Learning through Computer-Assisted Intelligent Tutoring System on the Improvement of EFL Learners' Speaking Ability

    Science.gov (United States)

    Mohammadzadeh, Ahmad; Sarkhosh, Mehdi

    2018-01-01

    The current study attempted to investigate the effects of self-regulatory learning through computer-assisted intelligent tutoring system on the improvement of speaking ability. The participants of the study, who spoke Azeri Turkish as their mother tongue, were students of Applied Linguistics at BA level at Pars Abad's Azad University, Ardebil,…

  13. Student Science Training Program in Mathematics, Physics and Computer Science. Final Report to the National Science Foundation. Artificial Intelligence Memo No. 393.

    Science.gov (United States)

    Abelson, Harold; diSessa, Andy

    During the summer of 1976, the MIT Artificial Intelligence Laboratory sponsored a Student Science Training Program in Mathematics, Physics, and Computer Science for high ability secondary school students. This report describes, in some detail, the style of the program, the curriculum and the projects the students under-took. It is hoped that this…

  14. An Intelligent and Fast Chaotic Encryption Using Digital Logic Circuits for Ad-Hoc and Ubiquitous Computing

    Directory of Open Access Journals (Sweden)

    Ankur Khare

    2016-05-01

    Full Text Available Delays added by the encryption process represent an overhead for smart computing devices in ad-hoc and ubiquitous computing intelligent systems. Digital Logic Circuits are faster than other computing techniques, so these can be used for fast encryption to minimize processing delays. Chaotic Encryption is more attack-resilient than other encryption techniques. One of the most attractive properties of cryptography is known as an avalanche effect, in which two different keys produce distinct cipher text for the same information. Important properties of chaotic systems are sensitivity to initial conditions and nonlinearity, which makes two similar keys that generate different cipher text a source of confusion. In this paper a novel fast and secure Chaotic Map-based encryption technique using 2’s Compliment (CET-2C has been proposed, which uses a logistic map which implies that a negligible difference in parameters of the map generates different cipher text. Cryptanalysis of the proposed algorithm shows the strength and security of algorithm and keys. Performance of the proposed algorithm has been analyzed in terms of running time, throughput and power consumption. It is to be shown in comparison graphs that the proposed algorithm gave better results compare to different algorithms like AES and some others.

  15. Artificial intelligence-based computer modeling tools for controlling slag foaming in electric arc furnaces

    Science.gov (United States)

    Wilson, Eric Lee

    Due to increased competition in a world economy, steel companies are currently interested in developing techniques that will allow for the improvement of the steelmaking process, either by increasing output efficiency or by improving the quality of their product, or both. Slag foaming is one practice that has been shown to contribute to both these goals. However, slag foaming is highly dynamic and difficult to model or control. This dissertation describes an effort to use artificial intelligence-based tools (genetic algorithms, fuzzy logic, and neural networks) to both model and control the slag foaming process. Specifically, a neural network is trained and tested on slag foaming data provided by a steel plant. This neural network model is then controlled by a fuzzy logic controller, which in turn is optimized by a genetic algorithm. This tuned controller is then installed at a steel plant and given control be a more efficient slag foaming controller than what was previously used by the steel plant.

  16. Separation of hepatic iron and fat by dual-source dual-energy computed tomography based on material decomposition: an animal study.

    Directory of Open Access Journals (Sweden)

    Jing Ma

    Full Text Available OBJECTIVE: To explore the feasibility of dual-source dual-energy computed tomography (DSDECT for hepatic iron and fat separation in vivo. MATERIALS AND METHODS: All of the procedures in this study were approved by the Research Animal Resource Center of Shanghai Ruijin Hospital. Sixty rats that underwent DECT scanning were divided into the normal group, fatty liver group, liver iron group, and coexisting liver iron and fat group, according to Prussian blue and HE staining. The data for each group were reconstructed and post-processed by an iron-specific, three-material decomposition algorithm. The iron enhancement value and the virtual non-iron contrast value, which indicated overloaded liver iron and residual liver tissue, respectively, were measured. Spearman's correlation and one-way analysis of variance (ANOVA were performed, respectively, to analyze statistically the correlations with the histopathological results and differences among groups. RESULTS: The iron enhancement values were positively correlated with the iron pathology grading (r = 0.729, p<0.001. Virtual non-iron contrast (VNC values were negatively correlated with the fat pathology grading (r = -0.642,p<0.0001. Different groups showed significantly different iron enhancement values and VNC values (F = 25.308,p<0.001; F = 10.911, p<0.001, respectively. Among the groups, significant differences in iron enhancement values were only observed between the iron-present and iron-absent groups, and differences in VNC values were only observed between the fat-present and fat-absent groups. CONCLUSION: Separation of hepatic iron and fat by dual energy material decomposition in vivo was feasible, even when they coexisted.

  17. A new decomposition-based computer-aided molecular/mixture design methodology for the design of optimal solvents and solvent mixtures

    DEFF Research Database (Denmark)

    Karunanithi, A.T.; Achenie, L.E.K.; Gani, Rafiqul

    2005-01-01

    This paper presents a novel computer-aided molecular/mixture design (CAMD) methodology for the design of optimal solvents and solvent mixtures. The molecular/mixture design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a performance objective is to be optim......This paper presents a novel computer-aided molecular/mixture design (CAMD) methodology for the design of optimal solvents and solvent mixtures. The molecular/mixture design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a performance objective...... is to be optimized subject to structural, property, and process constraints. The general molecular/mixture design problem is divided into two parts. For optimal single-compound design, the first part is solved. For mixture design, the single-compound design is first carried out to identify candidates...... and then the second part is solved to determine the optimal mixture. The decomposition of the CAMD MINLP model into relatively easy to solve subproblems is essentially a partitioning of the constraints from the original set. This approach is illustrated through two case studies. The first case study involves...

  18. Non-binary decomposition trees - a method of reliability computation for systems with known minimal paths/cuts

    Energy Technology Data Exchange (ETDEWEB)

    Malinowski, Jacek

    2004-05-01

    A coherent system with independent components and known minimal paths (cuts) is considered. In order to compute its reliability, a tree structure T is constructed whose nodes contain the modified minimal paths (cuts) and numerical values. The value of a non-leaf node is a function of its child nodes' values. The values of leaf nodes are calculated from a simple formula. The value of the root node is the system's failure probability (reliability). Subsequently, an algorithm computing the system's failure probability (reliability) is constructed. The algorithm scans all nodes of T using a stack structure for this purpose. The nodes of T are alternately put on and removed from the stack, their data being modified in the process. Once the algorithm has terminated, the stack contains only the final modification of the root node of T, and its value is equal to the system's failure probability (reliability)

  19. Non-binary decomposition trees - a method of reliability computation for systems with known minimal paths/cuts

    International Nuclear Information System (INIS)

    Malinowski, Jacek

    2004-01-01

    A coherent system with independent components and known minimal paths (cuts) is considered. In order to compute its reliability, a tree structure T is constructed whose nodes contain the modified minimal paths (cuts) and numerical values. The value of a non-leaf node is a function of its child nodes' values. The values of leaf nodes are calculated from a simple formula. The value of the root node is the system's failure probability (reliability). Subsequently, an algorithm computing the system's failure probability (reliability) is constructed. The algorithm scans all nodes of T using a stack structure for this purpose. The nodes of T are alternately put on and removed from the stack, their data being modified in the process. Once the algorithm has terminated, the stack contains only the final modification of the root node of T, and its value is equal to the system's failure probability (reliability)

  20. Granular computing and intelligent systems design with information granules of higher order and higher type

    CERN Document Server

    Pedrycz, Witold; Chen, Shyi-Ming

    2011-01-01

    Information granules are conceptual entities that aid the perception of complex phenomena. This book looks at granular computing techniques such as algorithmic pursuits and includes diverse applications and case studies from fields such as power engineering.

  1. The Convergence of the telematic, computing and information services as a basis for using artificial intelligence to manage complex techno-organizational systems

    Directory of Open Access Journals (Sweden)

    Raikov Alexander

    2018-01-01

    Full Text Available The authors analyses the problems of using artificial intelligence to manage complex techno-organizational systems on the basis of the convergence of the telematic, computing and information services in order to manage complex techno-organizational systems in the aerospace industry. This means getting the space objects a higher level of management based on the self-organizing integration principle. Using the artificial intelligence elements allows us to get more optimal and limit values parameters of the ordinal and critical situations in real time. Thus, it helps us to come closer to the limit values parameters of the managed objects due to rising managing and observant possibilities.

  2. Intelligent Decisional Assistant that Facilitate the Choice of a Proper Computer System Applied in Busines

    OpenAIRE

    Nicolae MARGINEAN

    2009-01-01

    The choice of a proper computer system is not an easy task for a decider. One reason could be the present market development of computer systems applied in business. The big number of the Romanian market players determines a big number of computerized products, with a multitude of various properties. Our proposal tries to optimize and facilitate this decisional process within an e-shop where are sold IT packets applied in business, building an online decisional assistant, a special component ...

  3. A SURVEY ON LOAD BALANCING IN CLOUD COMPUTING USING ARTIFICIAL INTELLIGENCE TECHNIQUES

    OpenAIRE

    Amandeep Kaur; Pooja Nagpal

    2016-01-01

    Since its inception, the cloud computing paradigm has gained the widespread popularity in the industry and academia. The economical, scalable, expedient, ubiquitous, and on-demand access to shared resources are some of the characteristics of the cloud that have resulted in shifting the business processes to the cloud. The cloud computing attracts the attention of research community due to its potential to provide tremendous benefits to the industry and the community. But with the increasing d...

  4. 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.

  5. Supporting Multi-agent Coordination and Computational Collective Intelligence in Enterprise 2.0 Platform

    Directory of Open Access Journals (Sweden)

    Seddik Reguieg

    2017-12-01

    Full Text Available In this paper, we propose a novel approach utilizing a professional Social network (Pro Social Network and a new coordination protocol (CordiNet. Our motivation behind this article is to convince Small and Medium Enterprises managers that current organizations have chosen to use Enterprise 2.0 tools because these latter have demonstrated remarkable innovation as well as successful collaboration and collective intelligence. The particularity of our work is that is allows employer to share diagnosis and fault repair procedures on the basis of some modeling agents. In fact, each enterprise is represented by a container of agents to ensure a secured and confidential information exchange between intra employers, and a central main container to connect all enterprises’ containers for a social information exchange. Enterprise’s container consists of a Checker Enterprise Agent (ChEA, a Coordinator Enterprise Agent (CoEA and a Search Enterprise Agent (SeEA. Whereas the central main container comprises its proper agents such as Selection Agent (SA, and a Supervisor Agent (SuA. JADE platform is used to allow agents to communicate and collaborate. The FIPA-ACL performatives have been extended for this purpose. We conduct some experiments to demonstrate the feasibility of our approach.

  6. Decision Support System Based on Computational Collective Intelligence in Campus Information Systems

    Science.gov (United States)

    Saito, Yoshihito; Matsuo, Tokuro

    Education institutions such as universities have a lot of information including book information, equipment administrative information, student information, and several others. The institutions also have multiple information in time series. As collective intelligence in campus, integrating and reusing these preserved information regarding career and taking a class, university can effectively support students' decision making of their getting jobs and subjects choice. Our purpose of support is to increase student's motivation. In this paper, we focus on course record and job information included in students' information, and propose the method to analyze correlation between a pattern of taking class and job lined up. Afterwards, we propose a support system regarding getting a job and taking class by using our proposed method. For a student who has his/her favorite job to get, the system supports his/her decision making of lecture choice by recommending a set of appropriate lecture groups. On another hand, for a student who does not have favorite job to get, the system supports his/her decision making of getting job by presenting appropriate job families related with lecture group in which he/she has ever taken. The contribution of this paper is showing a concrete method to reuse the campus collective information, implementing a system, and user perspectives.

  7. 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

  8. Computational red teaming risk analytics of big-data-to-decisions intelligent systems

    CERN Document Server

    Abbass, Hussein A

    2015-01-01

    Written to bridge the information needs of management and computational scientists, this book presents the first comprehensive treatment of Computational Red Teaming (CRT).  The author describes an analytics environment that blends human reasoning and computational modeling to design risk-aware and evidence-based smart decision making systems. He presents the Shadow CRT Machine, which shadows the operations of an actual system to think with decision makers, challenge threats, and design remedies. This is the first book to generalize red teaming (RT) outside the military and security domains and it offers coverage of RT principles, practical and ethical guidelines. The author utilizes Gilbert’s principles for introducing a science. Simplicity: where the book follows a special style to make it accessible to a wide range of  readers. Coherence:  where only necessary elements from experimentation, optimization, simulation, data mining, big data, cognitive information processing, and system thinking are blend...

  9. Ubiquitous Computing Services Discovery and Execution Using a Novel Intelligent Web Services Algorithm

    Science.gov (United States)

    Choi, Okkyung; Han, SangYong

    2007-01-01

    Ubiquitous Computing makes it possible to determine in real time the location and situations of service requesters in a web service environment as it enables access to computers at any time and in any place. Though research on various aspects of ubiquitous commerce is progressing at enterprises and research centers, both domestically and overseas, analysis of a customer's personal preferences based on semantic web and rule based services using semantics is not currently being conducted. This paper proposes a Ubiquitous Computing Services System that enables a rule based search as well as semantics based search to support the fact that the electronic space and the physical space can be combined into one and the real time search for web services and the construction of efficient web services thus become possible.

  10. An Initial Look at Alternative Computing Technologies for the Intelligence Community

    Science.gov (United States)

    2014-01-01

    et al., “Overview of the SpiNNaker System Architecture,” IEEE Transactions on Computers, Vol. 62, pp. 2454–2467, 2013 [49] Gardner, T. S., Cantor , C...of dynamical evolution,” Physica D: Nonlinear Phenomena, Vol. 120, pp. 188–195, 1998 [82] Marr, B., George , J., Degnan, B., Anderson, D. V., & Hasler

  11. Intelligent Computer-Aided Instruction and Musical Performance Skills. CITE Report No. 18.

    Science.gov (United States)

    Baker, Michael

    This paper is a transcription from memory of a short talk that used overhead projector slides, with musical examples played on an Apple Macintosh computer and a Yamaha CX5 synthesizer. The slides appear in the text as reduced "icons" at the point where they would have been used in the talk. The paper concerns ways in which artificial intelligence…

  12. A review of Computational Intelligence techniques in coral reef-related applications

    NARCIS (Netherlands)

    Salcedo-Sanz, S.; Cuadra, L.; Vermeij, M.J.A.

    Studies on coral reefs increasingly combine aspects of science and technology to understand the complex dynamics and processes that shape these benthic ecosystems. Recently, the use of advanced computational algorithms has entered coral reef science as new powerful tools that help solve complex

  13. Artificial intelligence applied to natural products; computer study of pimarane diterpene

    International Nuclear Information System (INIS)

    Lopes, M.N.; Borges, J.H.G.; Furlan, M.; Gastmans, J.P.; Emerenciano, V. de

    1989-01-01

    This paper describes the study of the sup(13)C NMR characteristic signals of naturally occurring pimarane. The analysis is performed by computer, starting from a data base which encloses about 400 diterpenes and using the PICKUPS programm. BNy this way it is possible to analyse substructure from one to five atoms as well as the effects of substituents on them. (author)

  14. Artificial intelligence in medicine and cardiac imaging: harnessing big data and advanced computing to provide personalized medical diagnosis and treatment.

    Science.gov (United States)

    Dilsizian, Steven E; Siegel, Eliot L

    2014-01-01

    Although advances in information technology in the past decade have come in quantum leaps in nearly every aspect of our lives, they seem to be coming at a slower pace in the field of medicine. However, the implementation of electronic health records (EHR) in hospitals is increasing rapidly, accelerated by the meaningful use initiatives associated with the Center for Medicare & Medicaid Services EHR Incentive Programs. The transition to electronic medical records and availability of patient data has been associated with increases in the volume and complexity of patient information, as well as an increase in medical alerts, with resulting "alert fatigue" and increased expectations for rapid and accurate diagnosis and treatment. Unfortunately, these increased demands on health care providers create greater risk for diagnostic and therapeutic errors. In the near future, artificial intelligence (AI)/machine learning will likely assist physicians with differential diagnosis of disease, treatment options suggestions, and recommendations, and, in the case of medical imaging, with cues in image interpretation. Mining and advanced analysis of "big data" in health care provide the potential not only to perform "in silico" research but also to provide "real time" diagnostic and (potentially) therapeutic recommendations based on empirical data. "On demand" access to high-performance computing and large health care databases will support and sustain our ability to achieve personalized medicine. The IBM Jeopardy! Challenge, which pitted the best all-time human players against the Watson computer, captured the imagination of millions of people across the world and demonstrated the potential to apply AI approaches to a wide variety of subject matter, including medicine. The combination of AI, big data, and massively parallel computing offers the potential to create a revolutionary way of practicing evidence-based, personalized medicine.

  15. Data-Driven Approaches for Computation in Intelligent Biomedical Devices: A Case Study of EEG Monitoring for Chronic Seizure Detection

    Directory of Open Access Journals (Sweden)

    Naveen Verma

    2011-04-01

    Full Text Available Intelligent biomedical devices implies systems that are able to detect specific physiological processes in patients so that particular responses can be generated. This closed-loop capability can have enormous clinical value when we consider the unprecedented modalities that are beginning to emerge for sensing and stimulating patient physiology. Both delivering therapy (e.g., deep-brain stimulation, vagus nerve stimulation, etc. and treating impairments (e.g., neural prosthesis requires computational devices that can make clinically relevant inferences, especially using minimally-intrusive patient signals. The key to such devices is algorithms that are based on data-driven signal modeling as well as hardware structures that are specialized to these. This paper discusses the primary application-domain challenges that must be overcome and analyzes the most promising methods for this that are emerging. We then look at how these methods are being incorporated in ultra-low-energy computational platforms and systems. The case study for this is a seizure-detection SoC that includes instrumentation and computation blocks in support of a system that exploits patient-specific modeling to achieve accurate performance for chronic detection. The SoC samples each EEG channel at a rate of 600 Hz and performs processing to derive signal features on every two second epoch, consuming 9 μJ/epoch/channel. Signal feature extraction reduces the data rate by a factor of over 40×, permitting wireless communication from the patient’s head while reducing the total power on the head by 14×.

  16. 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

  17. Intelligent Decisional Assistant that Facilitate the Choice of a Proper Computer System Applied in Busines

    Directory of Open Access Journals (Sweden)

    Nicolae MARGINEAN

    2009-01-01

    Full Text Available The choice of a proper computer system is not an easy task for a decider. One reason could be the present market development of computer systems applied in business. The big number of the Romanian market players determines a big number of computerized products, with a multitude of various properties. Our proposal tries to optimize and facilitate this decisional process within an e-shop where are sold IT packets applied in business, building an online decisional assistant, a special component conceived to facilitate the decision making needed for the selection of the pertinent IT package that fits the requirements of one certain business, described by the decider. The user interacts with the system as an online buyer that visit an e-shop where are sold IT package applied in economy.

  18. Internet of Things and Inter-cooperative Computational Technologies for Collective Intelligence

    CERN Document Server

    Xhafa, Fatos; Varvarigou, Dora; Hill, Richard; Li, Maozhen

    2013-01-01

    Over the past two decades, we have witnessed unprecedented innovations in the development of miniaturized electromechanical devices and low-power wireless communication making practical the embedding of networked computational devices into a rapidly widening range of material entities. This trend has enabled the coupling of physical objects and digital information into cyber-physical systems and it is widely expected to revolutionize the way resource computational consumption and provision will occur. Specifically, one of the core ingredients of this vision, the so-called Internet of Things (IoT), demands the provision of networked services to support interaction between conventional IT systems with both physical and artificial objects. In this way, IoT is seen as a combination of several emerging technologies, which enables the transformation of everyday objects into smart objects. It is also perceived as a paradigm that connects real world with digital world. The focus of this book is on the novel collecti...

  19. Reexamining Computational Support for Intelligence Analysis: A Functional Design for a Future Capability

    Science.gov (United States)

    2016-07-14

    Approaches to Computational Support 6.1 Paradigms and Methods In today’s open-world environment, historical paradigms and methods that rely on deep ...focused on methods of this type, with a deep basis on argumentation-based principles. One clear example of these remarks is shown in the writing of...Proceedings of the 5th 2013 Forum on Information Retrieval Evaluation [33] Dan Roth and Wen -tau Yih. Integer linear programming inference for

  20. An intelligent and secure system for predicting and preventing Zika virus outbreak using Fog computing

    Science.gov (United States)

    Sareen, Sanjay; Gupta, Sunil Kumar; Sood, Sandeep K.

    2017-10-01

    Zika virus is a mosquito-borne disease that spreads very quickly in different parts of the world. In this article, we proposed a system to prevent and control the spread of Zika virus disease using integration of Fog computing, cloud computing, mobile phones and the Internet of things (IoT)-based sensor devices. Fog computing is used as an intermediary layer between the cloud and end users to reduce the latency time and extra communication cost that is usually found high in cloud-based systems. A fuzzy k-nearest neighbour is used to diagnose the possibly infected users, and Google map web service is used to provide the geographic positioning system (GPS)-based risk assessment to prevent the outbreak. It is used to represent each Zika virus (ZikaV)-infected user, mosquito-dense sites and breeding sites on the Google map that help the government healthcare authorities to control such risk-prone areas effectively and efficiently. The proposed system is deployed on Amazon EC2 cloud to evaluate its performance and accuracy using data set for 2 million users. Our system provides high accuracy of 94.5% for initial diagnosis of different users according to their symptoms and appropriate GPS-based risk assessment.

  1. How Computers Are Used in the Teaching of Music and Speculations about How Artificial Intelligence Could Be Applied to Radically Improve the Learning of Compositional Skills. CITE Report No. 6.

    Science.gov (United States)

    Holland, Simon

    This paper forms part of a preliminary survey for work on the application of artificial intelligence theories and techniques to the learning of music composition skills. The paper deals with present day applications of computers to the teaching of music and speculations about how artificial intelligence might be used to foster music composition in…

  2. 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...

  3. 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

  4. 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.

  5. Collective-Intelligence Recommender Systems: Advancing Computer Tailoring for Health Behavior Change Into the 21st Century.

    Science.gov (United States)

    Sadasivam, Rajani Shankar; Cutrona, Sarah L; Kinney, Rebecca L; Marlin, Benjamin M; Mazor, Kathleen M; Lemon, Stephenie C; Houston, Thomas K

    2016-03-07

    What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior theories. In collective-intelligence recommender systems (hereafter recommender systems) used by Web 2.0 companies (eg, Netflix and Amazon), machine learning algorithms combine user profiles and continuous feedback ratings of content (from themselves and other users) to empirically tailor content. Augmenting current theory-based CTHC with empirical recommender systems could be evaluated as the next frontier for CTHC. The objective of our study was to uncover barriers and challenges to using recommender systems in health promotion. We conducted a focused literature review, interviewed subject experts (n=8), and synthesized the results. We describe (1) limitations of current CTHC systems, (2) advantages of incorporating recommender systems to move CTHC forward, and (3) challenges to incorporating recommender systems into CTHC. Based on the evidence presented, we propose a future research agenda for CTHC systems. We promote discussion of ways to move CTHC into the 21st century by incorporation of recommender systems.

  6. Computational intelligence-based polymerase chain reaction primer selection based on a novel teaching-learning-based optimisation.

    Science.gov (United States)

    Cheng, Yu-Huei

    2014-12-01

    Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.

  7. Humanitarian health computing using artificial intelligence and social media: A narrative literature review.

    Science.gov (United States)

    Fernandez-Luque, Luis; Imran, Muhammad

    2018-06-01

    According to the World Health Organization (WHO), over 130 million people are in constant need of humanitarian assistance due to natural disasters, disease outbreaks, and conflicts, among other factors. These health crises can compromise the resilience of healthcare systems, which are essential for achieving the health objectives of the sustainable development goals (SDGs) of the United Nations (UN). During a humanitarian health crisis, rapid and informed decision making is required. This is often challenging due to information scarcity, limited resources, and strict time constraints. Moreover, the traditional approach to digital health development, which involves a substantial requirement analysis, a feasibility study, and deployment of technology, is ill-suited for many crisis contexts. The emergence of Web 2.0 technologies and social media platforms in the past decade, such as Twitter, has created a new paradigm of massive information and misinformation, in which new technologies need to be developed to aid rapid decision making during humanitarian health crises. Humanitarian health crises increasingly require the analysis of massive amounts of information produced by different sources, such as social media content, and, hence, they are a prime case for the use of artificial intelligence (AI) techniques to help identify relevant information and make it actionable. To identify challenges and opportunities for using AI in humanitarian health crises, we reviewed the literature on the use of AI techniques to process social media. We performed a narrative literature review aimed at identifying examples of the use of AI in humanitarian health crises. Our search strategy was designed to get a broad overview of the different applications of AI in a humanitarian health crisis and their challenges. A total of 1459 articles were screened, and 24 articles were included in the final analysis. Successful case studies of AI applications in a humanitarian health crisis have

  8. 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

  9. 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.

  10. Opportunities for artificial intelligence application in computer- aided management of mixed waste incinerator facilities

    International Nuclear Information System (INIS)

    Rivera, A.L.; Ferrada, J.J.; Singh, S.P.N.

    1992-01-01

    The Department of Energy/Oak Ridge Field Office (DOE/OR) operates a mixed waste incinerator facility at the Oak Ridge K-25 Site. It is designed for the thermal treatment of incinerable liquid, sludge, and solid waste regulated under the Toxic Substances Control Act (TSCA) and the Resource Conservation and Recovery Act (RCRA). This facility, known as the TSCA Incinerator, services seven DOE/OR installations. This incinerator was recently authorized for production operation in the United States for the processing of mixed (radioactively contaminated-chemically hazardous) wastes as regulated under TSCA and RCRA. Operation of the TSCA Incinerator is highly constrained as a result of the regulatory, institutional, technical, and resource availability requirements. These requirements impact the characteristics and disposition of incinerator residues, limits the quality of liquid and gaseous effluents, limit the characteristics and rates of waste feeds and operating conditions, and restrict the handling of the waste feed inventories. This incinerator facility presents an opportunity for applying computer technology as a technical resource for mixed waste incinerator operation to facilitate promoting and sustaining a continuous performance improvement process while demonstrating compliance. Demonstrated computer-aided management systems could be transferred to future mixed waste incinerator facilities

  11. Do more intelligent brains retain heightened plasticity for longer in development? A computational investigation.

    Science.gov (United States)

    Thomas, Michael S C

    2016-06-01

    Twin studies indicate that the heritability of general cognitive ability - the genetic contribution to individual differences - increases with age. Brant et al. (2013) reported that this increase in heritability occurs earlier in development for low ability children than high ability children. Allied with structural brain imaging results that indicate faster thickening and thinning of cortex for high ability children (Shaw et al., 2006), Brant and colleagues argued higher cognitive ability represents an extended sensitive period for brain development. However, they admitted no coherent mechanistic account can currently reconcile the key empirical data. Here, computational methods are employed to demonstrate the empirical data can be reconciled without recourse to variations in sensitive periods. These methods utilized population-based artificial neural network models of cognitive development. In the model, ability-related variations stemmed from the timing of the increases in the non-linearity of computational processes, causing dizygotic twins to diverge in their behavior. These occurred in a population where: (a) ability was determined by the combined small contributions of many neurocomputational factors, and (b) individual differences in ability were largely genetically constrained. The model's explanation of developmental increases in heritability contrasts with proposals that these increases represent emerging gene-environment correlations (Haworth et al., 2010). The article advocates simulating inherited individual differences within an explicitly developmental framework. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

  12. Development of a Computer-Aided System for Competitive Intelligence%竞争情报计算机辅助系统的开发

    Institute of Scientific and Technical Information of China (English)

    刘玉照; 曹君祥

    2000-01-01

    Competitive Information System (CIS) is a computer-aided system for competitive intelligence, and is designed for the information requirements of the corporate strategic management. The development of CIS is an important part of corporate Strategic Information Planning (SIP), and CIS directly supports the strategic objects of the corporate. The life cycle of CIS includes traditional life cycle, prototyping life cycle, object-oriented life cycle and so on.

  13. Application of the Fuzzy Computational Intelligence in Power Quality Data Management

    Directory of Open Access Journals (Sweden)

    Hoda Farag

    2017-03-01

    Full Text Available In Electrical Power Distribution System the sustained availability and quality of electric power are the main challenge they need to satisfy so overcoming the power quality (PQ degradation became an asset. This Paper addresses the perfect load management using the computational techniques by analyzing the data of the system taking into account the density of the  feeding nodes and its distribution  also the classification of major Power quality degradations such as power factor and harmonics in the System and The methodology will be illustrated, simulated and evaluated using the fuzzy technique clustering the data and on an Artificial Neural Network (ANN to achieve the optimum utilization of the energy loads and perfect load management and optimization. Simulation results demonstrate the effectiveness of the proposed algorithm in reducing the power and energy losses, improving the quality of the electric power system.

  14. Artificial Intelligence - A New Field of Computer Science Which Any Business Should Consider

    Directory of Open Access Journals (Sweden)

    Oprișan Oana

    2017-01-01

    Full Text Available Anyone can remember what it meant for business IT solutions a few years ago. On themarket there is a clear segmentation between ERP, CRM, Document Management, BI, and so on. Asegmentation that has gradually added other elements, such as Analytics, and, more recently, BigData, with its leading corollary, Cognitive Computing. Technological developments, and especiallybusiness developments, marked by the growing need for real-time, real-world information fromgrowing data volumes, have made such a segmentation on the business solutions market start tofade Clear boundaries. Obviously, we can not speak at present about an integrative solution thatincludes all the sub-segments of this market. Such a fully integrated solution would be extremelyexpensive and perhaps too rigid to meet the needs of all market players.

  15. Artificial intelligence in peer review: How can evolutionary computation support journal editors?

    Science.gov (United States)

    Mrowinski, Maciej J; Fronczak, Piotr; Fronczak, Agata; Ausloos, Marcel; Nedic, Olgica

    2017-01-01

    With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors' workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy). Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems.

  16. Artificial intelligence in peer review: How can evolutionary computation support journal editors?

    Directory of Open Access Journals (Sweden)

    Maciej J Mrowinski

    Full Text Available With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors' workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy. Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems.

  17. Comparative study of computational intelligence approaches for NOx reduction of coal-fired boiler

    International Nuclear Information System (INIS)

    Wei, Zhongbao; Li, Xiaolu; Xu, Lijun; Cheng, Yanting

    2013-01-01

    This paper focuses on NO x emission prediction and operating parameters optimization for coal-fired boilers. Support Vector Regression (SVR) model based on CGA (Conventional Genetic Algorithm) was proposed to model the relationship between the operating parameters and the concentration of NO x emission. Then CGA and two modified algorithms, the Quantum Genetic Algorithm (QGA) and SAGA (Simulated Annealing Genetic Algorithm), were employed to optimize the operating parameters of the coal-fired boiler to reduce NO x emission. The results showed that the proposed SVR model was more accurate than the widely used Artificial Neural Network (ANN) model when employed to predict the concentration of NO x emission. The mean relative error and correlation coefficient calculated by the proposed SVR model were 2.08% and 0.95, respectively. Among the three optimization algorithms implemented in this paper, the SAGA showed superiority to the other two algorithms considering the quality of solution within a given computing time. The SVR plus SAGA method was preferable to predict the concentration of NO x emission and further to optimize the operating parameters to achieve low NO x emission for coal-fired boilers. - Highlights: • The CGA based SVR model is proposed to predict the concentration of NO x emission. • The CGA based SVR model performs better than the widely used ANN model. • CGA and two modified algorithms are compared to optimize the parameters. • The SAGA is preferable for its high quality of solution and low computing time. • The SVR plus SAGA is successfully employed to optimize the operating parameters

  18. Demonstration of Intelligent Control and Fan Improvements in Computer Room Air Handlers

    Energy Technology Data Exchange (ETDEWEB)

    Coles, Henry [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Greenberg, Steve [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Vita, Corinne [Vigilent, Oakland, CA (United States)

    2012-11-30

    This report documents a demonstration of the energy-efficiency improvement provided by a new control system for computer room air handling devices. It also analyzes measured and reported air handling device fan power associated with changing the fan type. A 135,000 square foot commercial data center was used for the demonstration. All air handling units were upgraded with improved efficiency fans, and a control system that automatically adjusts the fan speed for the air handling units was added. Power measurements were collected for a baseline and for a period with the fan speed control system active. Changing the fan type resulted in a savings of 47 percent of energy used by the air handling equipment and associated chiller plant energy needed to cool the air handlers themselves. The addition of the fan speed control resulted in an additional 37 percent savings in the same two categories. The combined savings for the two improvements for the same categories was 66 percent compared to the data center fitted with the original fans without a control system. The energy use reduction provided by the complete air handling device improvement program for the whole data center site is estimated to be 2.9 million kilowatt hours per year—an overall data center site savings of 8.0 percent. The reduced electrical energy use at the site provides a 1.9 million pound yearly reduction of carbon dioxide emissions. This demonstration showed that fan upgrades and a control system addition provide cost-effective improvements for data centers, with a payback reported to be under two years without utility incentives. In addition to the control system providing energy savings, the data collection and visual analysis capabilities provided immediate and long-term benefits. It is recommended that data center operators consider investing in fan upgrades and/or adding fan speed control for computer room air handlers.

  19. Intelligent and interactive computer image of a nuclear power plant: The ImagIn project

    International Nuclear Information System (INIS)

    Haubensack, D.; Malvache, P.; Valleix, P.

    1998-01-01

    The ImagIn project consists in a method and a set of computer tools apt to bring perceptible and assessable improvements in the operational safety of a nuclear plant. Its aim is to design an information system that would maintain a highly detailed computerized representation of a nuclear plant in its initial state and throughout its in-service life. It is not a tool to drive or help driving the nuclear plant, but a tool that manages concurrent operations that modify the plant configuration in a very general was (maintenance for example). The configuration of the plant, as well as rules and constraints about it, are described in a object-oriented knowledge database, which is built using a generic ImagIn meta-model based on the semantical network theory. An inference engine works on this database and is connected to reality through interfaces to operators and captors on the installation; it verifies constantly in real-time the consistency of the database according to its inner rules, and reports eventual problems to concerned operators. A special effort is made on interfaces to provide natural and intuitive tools (using virtual reality, natural language, voice recognition and synthesis). A laboratory application on a fictive but realistic installation already exists and is used to simulate various tests and scenarii. A real application is being constructed on Siloe, an experimental reactor of the CEA. (author)

  20. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  1. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

    Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  2. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Science.gov (United States)

    Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

  3. Development of Semi-Automatic Lathe by using Intelligent Soft Computing Technique

    Science.gov (United States)

    Sakthi, S.; Niresh, J.; Vignesh, K.; Anand Raj, G.

    2018-03-01

    This paper discusses the enhancement of conventional lathe machine to semi-automated lathe machine by implementing a soft computing method. In the present scenario, lathe machine plays a vital role in the engineering division of manufacturing industry. While the manual lathe machines are economical, the accuracy and efficiency are not up to the mark. On the other hand, CNC machine provide the desired accuracy and efficiency, but requires a huge capital. In order to over come this situation, a semi-automated approach towards the conventional lathe machine is developed by employing stepper motors to the horizontal and vertical drive, that can be controlled by Arduino UNO -microcontroller. Based on the input parameters of the lathe operation the arduino coding is been generated and transferred to the UNO board. Thus upgrading from manual to semi-automatic lathe machines can significantly increase the accuracy and efficiency while, at the same time, keeping a check on investment cost and consequently provide a much needed escalation to the manufacturing industry.

  4. Computational benefits using artificial intelligent methodologies for the solution of an environmental design problem: saltwater intrusion.

    Science.gov (United States)

    Papadopoulou, Maria P; Nikolos, Ioannis K; Karatzas, George P

    2010-01-01

    Artificial Neural Networks (ANNs) comprise a powerful tool to approximate the complicated behavior and response of physical systems allowing considerable reduction in computation time during time-consuming optimization runs. In this work, a Radial Basis Function Artificial Neural Network (RBFN) is combined with a Differential Evolution (DE) algorithm to solve a water resources management problem, using an optimization procedure. The objective of the optimization scheme is to cover the daily water demand on the coastal aquifer east of the city of Heraklion, Crete, without reducing the subsurface water quality due to seawater intrusion. The RBFN is utilized as an on-line surrogate model to approximate the behavior of the aquifer and to replace some of the costly evaluations of an accurate numerical simulation model which solves the subsurface water flow differential equations. The RBFN is used as a local approximation model in such a way as to maintain the robustness of the DE algorithm. The results of this procedure are compared to the corresponding results obtained by using the Simplex method and by using the DE procedure without the surrogate model. As it is demonstrated, the use of the surrogate model accelerates the convergence of the DE optimization procedure and additionally provides a better solution at the same number of exact evaluations, compared to the original DE algorithm.

  5. The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility.

    Science.gov (United States)

    Bentsen, Thomas; May, Tobias; Kressner, Abigail A; Dau, Torsten

    2018-01-01

    Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech intelligibility in normal-hearing listeners. A substantial improvement of 25.4 percentage points in speech intelligibility scores was found going from a subband-based architecture, in which a Gaussian Mixture Model-based classifier predicts the distributions of speech and noise for each frequency channel, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where the units are assigned a continuous value between zero and one. Therefore, both components play significant roles and by combining them, speech intelligibility improvements were obtained in a six-talker condition at a low signal-to-noise ratio.

  6. Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis.

    Science.gov (United States)

    Lee, Hyunkwang; Troschel, Fabian M; Tajmir, Shahein; Fuchs, Georg; Mario, Julia; Fintelmann, Florian J; Do, Synho

    2017-08-01

    Pretreatment risk stratification is key for personalized medicine. While many physicians rely on an "eyeball test" to assess whether patients will tolerate major surgery or chemotherapy, "eyeballing" is inherently subjective and difficult to quantify. The concept of morphometric age derived from cross-sectional imaging has been found to correlate well with outcomes such as length of stay, morbidity, and mortality. However, the determination of the morphometric age is time intensive and requires highly trained experts. In this study, we propose a fully automated deep learning system for the segmentation of skeletal muscle cross-sectional area (CSA) on an axial computed tomography image taken at the third lumbar vertebra. We utilized a fully automated deep segmentation model derived from an extended implementation of a fully convolutional network with weight initialization of an ImageNet pre-trained model, followed by post processing to eliminate intramuscular fat for a more accurate analysis. This experiment was conducted by varying window level (WL), window width (WW), and bit resolutions in order to better understand the effects of the parameters on the model performance. Our best model, fine-tuned on 250 training images and ground truth labels, achieves 0.93 ± 0.02 Dice similarity coefficient (DSC) and 3.68 ± 2.29% difference between predicted and ground truth muscle CSA on 150 held-out test cases. Ultimately, the fully automated segmentation system can be embedded into the clinical environment to accelerate the quantification of muscle and expanded to volume analysis of 3D datasets.

  7. An infrastructure with a unified control plane to integrate IP into optical metro networks to provide flexible and intelligent bandwidth on demand for cloud computing

    Science.gov (United States)

    Yang, Wei; Hall, Trevor

    2012-12-01

    The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users and the nature of the Internet traffic will undertake a fundamental transformation. Consequently, the current Internet will no longer suffice for serving cloud traffic in metro areas. This work proposes an infrastructure with a unified control plane that integrates simple packet aggregation technology with optical express through the interoperation between IP routers and electrical traffic controllers in optical metro networks. The proposed infrastructure provides flexible, intelligent, and eco-friendly bandwidth on demand for cloud computing in metro areas.

  8. 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...

  9. 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

  10. 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

  11. Introducing AI into MEMS can lead us to brain-computer interfaces and super-human intelligence

    OpenAIRE

    Sanders, David

    2009-01-01

    Last year, I spoke about the progress being made in machine intelligence (Sanders, 2008c) and with sensors and networks of sensors (Sanders, 2008b). Earlier this year (in this journal) I spoke about ambient-intelligence, rapid-prototyping and the role of humans in the factories of the future (Sanders, 2009a). I addressed new applications and technologies such as merging machines with human beings, micro-electromechanics, electro-mechanical systems that can be personalized, smarter than human ...

  12. 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.

  13. 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...

  14. 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...

  15. 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.

  16. 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)

  17. 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 ...

  18. 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)

  19. 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.

  20. 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…

  1. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  2. Two-stage approach for risk estimation of fetal trisomy 21 and other aneuploidies using computational intelligence systems.

    Science.gov (United States)

    Neocleous, A C; Syngelaki, A; Nicolaides, K H; Schizas, C N

    2018-04-01

    To estimate the risk of fetal trisomy 21 (T21) and other chromosomal abnormalities (OCA) at 11-13 weeks' gestation using computational intelligence classification methods. As a first step, a training dataset consisting of 72 054 euploid pregnancies, 295 cases of T21 and 305 cases of OCA was used to train an artificial neural network. Then, a two-stage approach was used for stratification of risk and diagnosis of cases of aneuploidy in the blind set. In Stage 1, using four markers, pregnancies in the blind set were classified into no risk and risk. No-risk pregnancies were not examined further, whereas the risk pregnancies were forwarded to Stage 2 for further examination. In Stage 2, using seven markers, pregnancies were classified into three types of risk, namely no risk, moderate risk and high risk. Of 36 328 unknown to the system pregnancies (blind set), 17 512 euploid, two T21 and 18 OCA were classified as no risk in Stage 1. The remaining 18 796 cases were forwarded to Stage 2, of which 7895 euploid, two T21 and two OCA cases were classified as no risk, 10 464 euploid, 83 T21 and 61 OCA as moderate risk and 187 euploid, 50 T21 and 52 OCA as high risk. The sensitivity and the specificity for T21 in Stage 2 were 97.1% and 99.5%, respectively, and the false-positive rate from Stage 1 to Stage 2 was reduced from 51.4% to ∼1%, assuming that the cell-free DNA test could identify all euploid and aneuploid cases. We propose a method for early diagnosis of chromosomal abnormalities that ensures that most T21 cases are classified as high risk at any stage. At the same time, the number of euploid cases subjected to invasive or cell-free DNA examinations was minimized through a routine procedure offered in two stages. Our method is minimally invasive and of relatively low cost, highly effective at T21 identification and it performs better than do other existing statistical methods. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd. Copyright

  3. Creating Intelligent Computer Workstation of a Freight Officer in a Single Information Space of Railway Transport: Synergetic Approach

    Science.gov (United States)

    Malybaev, Saken K.; Malaybaev, Nurlan S.; Isina, Botakoz M.; Kenzhekeeva, Akbope R.; Khuangan, Nurbol

    2016-01-01

    The article presents the results of researches aimed at the creation of automated workplaces for railway transport specialists with the help of intelligent information systems. The analysis of tendencies of information technologies development in the transport network was conducted. It was determined that the most effective approach is to create…

  4. Application of Computational Methods Mm2 and Gussian for Studing Unimolecular Decomposition of Vinil Ethers based on the Mechanism of Hydrogen Bonding

    OpenAIRE

    Behnaz Shahrokh; Garnik N. Sargsyan; Arkadi B. Harutyunyan

    2012-01-01

    Investigations of the unimolecular decomposition of vinyl ethyl ether (VEE), vinyl propyl ether (VPE) and vinyl butyl ether (VBE) have shown that activation of the molecule of a ether results in formation of a cyclic construction - the transition state (TS), which may lead to the displacement of the thermodynamic equilibrium towards the reaction products. The TS is obtained by applying energy minimization relative to the ground state of an ether under the program MM2 when...

  5. 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.

  6. A hybrid optical switch architecture to integrate IP into optical networks to provide flexible and intelligent bandwidth on demand for cloud computing

    Science.gov (United States)

    Yang, Wei; Hall, Trevor J.

    2013-12-01

    The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.

  7. Artificial Intelligence and Moral intelligence

    OpenAIRE

    Laura Pana

    2008-01-01

    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,...

  8. 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.

  9. 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.

  10. P ≠NP Millenium-Problem(MP) TRIVIAL Physics Proof Via NATURAL TRUMPS Artificial-``Intelligence'' Via: Euclid Geometry, Plato Forms, Aristotle Square-of-Opposition, Menger Dimension-Theory Connections!!! NO Computational-Complexity(CC)/ANYthing!!!: Geometry!!!

    Science.gov (United States)

    Clay, London; Menger, Karl; Rota, Gian-Carlo; Euclid, Alexandria; Siegel, Edward

    P ≠NP MP proof is by computer-''science''/SEANCE(!!!)(CS) computational-''intelligence'' lingo jargonial-obfuscation(JO) NATURAL-Intelligence(NI) DISambiguation! CS P =(?) =NP MEANS (Deterministic)(PC) = (?) =(Non-D)(PC) i.e. D(P) =(?) = N(P). For inclusion(equality) vs. exclusion (inequality) irrelevant (P) simply cancels!!! (Equally any/all other CCs IF both sides identical). Crucial question left: (D) =(?) =(ND), i.e. D =(?) = N. Algorithmics[Sipser[Intro. Thy.Comp.(`97)-p.49Fig.1.15!!!

  11. Intelligent Routines

    CERN Document Server

    Anastassiou, George A

    Intelligent Routines II: Solving Linear Algebra and Differential Geometry with Sage” contains numerous of examples and problems as well as many unsolved problems. This book extensively applies the successful software Sage, which can be found free online http://www.sagemath.org/. Sage is a recent and popular software for mathematical computation, available freely and simple to use. This book is useful to all applied scientists in mathematics, statistics and engineering, as well for late undergraduate and graduate students of above subjects. It is the first such book in solving symbolically with Sage problems in Linear Algebra and Differential Geometry. Plenty of SAGE applications are given at each step of the exposition.

  12. 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

  13. Spectral Decomposition Algorithm (SDA)

    Data.gov (United States)

    National Aeronautics and Space Administration — Spectral Decomposition Algorithm (SDA) is an unsupervised feature extraction technique similar to PCA that was developed to better distinguish spectral features in...

  14. Thermal decomposition of pyrite

    International Nuclear Information System (INIS)

    Music, S.; Ristic, M.; Popovic, S.

    1992-01-01

    Thermal decomposition of natural pyrite (cubic, FeS 2 ) has been investigated using X-ray diffraction and 57 Fe Moessbauer spectroscopy. X-ray diffraction analysis of pyrite ore from different sources showed the presence of associated minerals, such as quartz, szomolnokite, stilbite or stellerite, micas and hematite. Hematite, maghemite and pyrrhotite were detected as thermal decomposition products of natural pyrite. The phase composition of the thermal decomposition products depends on the terature, time of heating and starting size of pyrite chrystals. Hematite is the end product of the thermal decomposition of natural pyrite. (author) 24 refs.; 6 figs.; 2 tabs

  15. Intelligent Decision-Making System with Green Pervasive Computing for Renewable Energy Business in Electricity Markets on Smart Grid

    Directory of Open Access Journals (Sweden)

    Park JongHyuk

    2009-01-01

    Full Text Available This paper is about the intelligent decision-making system for the smart grid based electricity market which requires distributed decision making on the competitive environments composed of many players and components. It is very important to consider the renewable energy and emission problem which are expected to be monitored by wireless communication networks. It is very difficult to predict renewable energy outputs and emission prices over time horizon, so it could be helpful to catch up those data on real time basis using many different kinds of communication infrastructures. On this backgrounds this paper provides an algorithm to make an optimal decision considering above factors.

  16. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  17. Competitive Intelligence.

    Science.gov (United States)

    Bergeron, Pierrette; Hiller, Christine A.

    2002-01-01

    Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

  18. Variance decomposition in stochastic simulators.

    Science.gov (United States)

    Le Maître, O P; Knio, O M; Moraes, A

    2015-06-28

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  19. Variance decomposition in stochastic simulators

    Science.gov (United States)

    Le Maître, O. P.; Knio, O. M.; Moraes, A.

    2015-06-01

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  20. Variance decomposition in stochastic simulators

    Energy Technology Data Exchange (ETDEWEB)

    Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

    2015-06-28

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.