WorldWideScience

Sample records for model intelligence mathias

  1. Fr. Mathias Ripensis OP and his 'Sermones de tempore'

    DEFF Research Database (Denmark)

    Jakobsen, Johnny Grandjean Gøgsig

    2014-01-01

    Indledning til netpublicering af dominikansk prædikensamling fra starten af 1300-tallet af ribemunken Mathias Ripensis. Selve kildeafskriften er foretaget af Dr. Johannes Schütz, Georg-August-Universität Göttingen, 2013, og er kun publiceret her....

  2. The reality of fiction: the ECO by Mathias Goeritz

    OpenAIRE

    Fernando Quesada

    2016-01-01

    Abstract This article covers the full biography of a building, the Experimental Museum El Eco, designed by Germanborn and Mexican émigré artist and architect Mathias Goeritz. It provides an approach intersecting the biography of the author, the history of the building, and prominent  individuals of the two cultural traditions, German and Mexican, who  participated in the creation of a very special and unique building: El Eco. On the one hand, the ethics of Expressionism, the interest in  ...

  3. The reality of fiction: the ECO by Mathias Goeritz

    Directory of Open Access Journals (Sweden)

    Fernando Quesada

    2016-05-01

    Full Text Available Abstract This article covers the full biography of a building, the Experimental Museum El Eco, designed by Germanborn and Mexican émigré artist and architect Mathias Goeritz. It provides an approach intersecting the biography of the author, the history of the building, and prominent  individuals of the two cultural traditions, German and Mexican, who  participated in the creation of a very special and unique building: El Eco. On the one hand, the ethics of Expressionism, the interest in  non-European art, the cult of primitivism and the aesthetic system of the  pair of concepts abstraction-empathy, all stemming from German culture. On the other, the pantheistic religiosity of landscape, zoomorphism and anthropomorphism, the interest in masks, and the aesthetics of  monumental scale, stemming from pre-Cortesian Mexican culture. Taking  the stance of intertwining Mathias Goeritz parcours with those of individuals and issues from his German past and his Mexican future – highlighting the figures of Wilhelm Worringer, Paul Westheim, Luis Barragán, Edmundo O'Gorman, and Ida Rodríguez Prampolini – this article proposes a return  trip from fiction to reality, following in the footsteps of the author and  comparing them with the pathway of the very building El Eco.

  4. Intelligent control based on intelligent characteristic model and its application

    Institute of Scientific and Technical Information of China (English)

    吴宏鑫; 王迎春; 邢琰

    2003-01-01

    This paper presents a new intelligent control method based on intelligent characteristic model for a kind of complicated plant with nonlinearities and uncertainties, whose controlled output variables cannot be measured on line continuously. The basic idea of this method is to utilize intelligent techniques to form the characteristic model of the controlled plant according to the principle of combining the char-acteristics of the plant with the control requirements, and then to present a new design method of intelli-gent controller based on this characteristic model. First, the modeling principles and expression of the intelligent characteristic model are presented. Then based on description of the intelligent characteristic model, the design principles and methods of the intelligent controller composed of several open-loops and closed-loops sub controllers with qualitative and quantitative information are given. Finally, the ap-plication of this method in alumina concentration control in the real aluminum electrolytic process is in-troduced. It is proved in practice that the above methods not only are easy to implement in engineering design but also avoid the trial-and-error of general intelligent controllers. It has taken better effect in the following application: achieving long-term stable control of low alumina concentration and increasing the controlled ratio of anode effect greatly from 60% to 80%.

  5. Intelligent Mobility Modeling and Simulation

    Science.gov (United States)

    2015-03-04

    cog.cs.drexel.edu/act-r/index.html) •Models sensory / motor performance of human driver or teleoperator 27UNCLASSIFIED: Distribution Statement A. Approved for...U.S. ARMY TANK AUTOMOTIVE RESEARCH, DEVELOPMENT AND ENGINEERING CENTER Intelligent Mobility Modeling and Simulation 1 Dr. P. Jayakumar, S. Arepally...Prescribed by ANSI Std Z39-18 Contents 1. Mobility - Autonomy - Latency Relationship 2. Machine - Human Partnership 3. Development of Shared Control

  6. Corpo e spazio. Una teoria compositiva nell’opera di Oswald Mathias Ungers / Matter and Space. Compositional Theory in the Work of Oswald Mathias Ungers

    Directory of Open Access Journals (Sweden)

    Gilda Giangipoli

    2016-04-01

    Full Text Available Tra i numerosi approfondimenti teorici e sperimentazioni condotti da Oswald Mathias Ungers in più di cinquant’anni della sua opera, emerge una delle prime teorie compositive applicate al tema dell’abitazione: la teoria di “corpo e spazio” che introduce una visione gerarchica degli spazi domestici anche nell’intento di ridurre il più possibile le superfici di distribuzione, per lasciare più spazio agli ambiti di vita collettiva della casa. / Between the multifarious theoretical studies and experimentations done by Oswald Mathias Ungers, in more than fifty years of his work, comes out one of the first compositional theory applied to the house-subject: the theory of “matter and space”, which introduces a hierarchic view of domestic spaces, also to reduce as much as possible distributive surfaces and to give more space to collective rooms of the house.

  7. A measurement model of multiple intelligence profiles of management graduates

    Science.gov (United States)

    Krishnan, Heamalatha; Awang, Siti Rahmah

    2017-05-01

    In this study, developing a fit measurement model and identifying the best fitting items to represent Howard Gardner's nine intelligences namely, musical intelligence, bodily-kinaesthetic intelligence, mathematical/logical intelligence, visual/spatial intelligence, verbal/linguistic intelligence, interpersonal intelligence, intrapersonal intelligence, naturalist intelligence and spiritual intelligence are the main interest in order to enhance the opportunities of the management graduates for employability. In order to develop a fit measurement model, Structural Equation Modeling (SEM) was applied. A psychometric test which is the Ability Test in Employment (ATIEm) was used as the instrument to measure the existence of nine types of intelligence of 137 University Teknikal Malaysia Melaka (UTeM) management graduates for job placement purposes. The initial measurement model contains nine unobserved variables and each unobserved variable is measured by ten observed variables. Finally, the modified measurement model deemed to improve the Normed chi-square (NC) = 1.331; Incremental Fit Index (IFI) = 0.940 and Root Mean Square of Approximation (RMSEA) = 0.049 was developed. The findings showed that the UTeM management graduates possessed all nine intelligences either high or low. Musical intelligence, mathematical/logical intelligence, naturalist intelligence and spiritual intelligence contributed highest loadings on certain items. However, most of the intelligences such as bodily kinaesthetic intelligence, visual/spatial intelligence, verbal/linguistic intelligence interpersonal intelligence and intrapersonal intelligence possessed by UTeM management graduates are just at the borderline.

  8. Economic modeling using artificial intelligence methods

    CERN Document Server

    Marwala, Tshilidzi

    2013-01-01

    This book examines the application of artificial intelligence methods to model economic data. It addresses causality and proposes new frameworks for dealing with this issue. It also applies evolutionary computing to model evolving economic environments.

  9. 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.

  10. Evolutionary model with intelligence and knowledge

    Science.gov (United States)

    Pan, Q. H.; Yu, B. L.; He, M. F.

    2005-12-01

    An evolutionary model based on Bit-String with intelligence and learning is constructed. Each individual is represented by five bit strings. Four of them relate to genes and the other denotes the knowledge from learning. The four strings relative to genes will be divided into two parts — Bit-String A and Bit-String B. Bit-String A denotes the health of an individual, at the same time Bit-String B can describe intelligence. For an individual, the cross reproduction method is used in this model. After that we explain how knowledge is represented in our model. The probability of learning is affected by intelligence. In order to study how the accumulated knowledge influences the survival process by the effect of food and space restrictions, we modify the Verhulst factor. Then, we present the results of our simulations and discuss the evolution of population, intelligence and knowledge respectively. In addition, an equation to calculate the intelligence quotient is given based on intelligence and knowledge. We discuss the distribution of intelligence quotient.

  11. Intelligent model-based OPC

    Science.gov (United States)

    Huang, W. C.; Lai, C. M.; Luo, B.; Tsai, C. K.; Chih, M. H.; Lai, C. W.; Kuo, C. C.; Liu, R. G.; Lin, H. T.

    2006-03-01

    Optical proximity correction is the technique of pre-distorting mask layouts so that the printed patterns are as close to the desired shapes as possible. For model-based optical proximity correction, a lithographic model to predict the edge position (contour) of patterns on the wafer after lithographic processing is needed. Generally, segmentation of edges is performed prior to the correction. Pattern edges are dissected into several small segments with corresponding target points. During the correction, the edges are moved back and forth from the initial drawn position, assisted by the lithographic model, to finally settle on the proper positions. When the correction converges, the intensity predicted by the model in every target points hits the model-specific threshold value. Several iterations are required to achieve the convergence and the computation time increases with the increase of the required iterations. An artificial neural network is an information-processing paradigm inspired by biological nervous systems, such as how the brain processes information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. A neural network can be a powerful data-modeling tool that is able to capture and represent complex input/output relationships. The network can accurately predict the behavior of a system via the learning procedure. A radial basis function network, a variant of artificial neural network, is an efficient function approximator. In this paper, a radial basis function network was used to build a mapping from the segment characteristics to the edge shift from the drawn position. This network can provide a good initial guess for each segment that OPC has carried out. The good initial guess reduces the required iterations. Consequently, cycle time can be shortened effectively. The optimization of the radial basis function network for this system was practiced by genetic algorithm

  12. An Intelligence Collection Management Model.

    Science.gov (United States)

    1984-06-01

    classification of inteligence collection requirements in terms of. the a-.- metnodo"c, .ev--e in Chaster Five. 116 APPgENDIX A A METHOD OF RANKING...of Artificial Intelligence Tools and Technigues to!TN’X n~l is n rs aa~emfft-.3-ufnyva: ’A TZ Ashby W. Ecss. An Introduction to Cybernetics. New York

  13. Modelling speech intelligibility in adverse conditions

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2013-01-01

    Jørgensen and Dau (J Acoust Soc Am 130:1475-1487, 2011) proposed the speech-based envelope power spectrum model (sEPSM) in an attempt to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII) in conditions with nonlinearly processed speech....... Instead of considering the reduction of the temporal modulation energy as the intelligibility metric, as assumed in the STI, the sEPSM applies the signal-to-noise ratio in the envelope domain (SNRenv). This metric was shown to be the key for predicting the intelligibility of reverberant speech as well...... subjected to phase jitter, a condition in which the spectral structure of the intelligibility of speech signal is strongly affected, while the broadband temporal envelope is kept largely intact. In contrast, the effects of this distortion can be predicted -successfully by the spectro-temporal modulation...

  14. La realidad de la ficción: el ECO de Mathias Goeritz

    OpenAIRE

    Fernando Quesada

    2016-01-01

    Resumen Este artículo recorre al completo la biografía de un edificio, el Museo  Experimental El Eco, del artista y arquitecto alemán emigrado a México Mathias Goeritz. Se entrecruzan la biografía del propio autor y la del edificio con las de personalidades de las dos tradiciones culturales, la  alemana y la mexicana, que intervinieron en la creación de una arquitectura tan particular y única como es la de El Eco. De Alemania provienen la ética del expresionismo, el interés por al arte no...

  15. INTELMOD - An Intelligent Satellite Modelling Toolkit

    Science.gov (United States)

    Aynsley, M.; Hiden, H.

    This paper describes the development of an intelligent, generic spacecraft modelling toolkit, INTELMOD (INTELligent MODeller). The system has been designed to provide an environment which can efficiently capture spacecraft engineering and operational expertise, coupled with mission or phase-related knowledge. This knowledge can then be applied to support human flight controllers at ESA (European Space Agency) in performing a number of generic monitoring, analytical and diagnostic tasks. INTELMOD has been developed using a RAD (Rapid Application Development) approach, based on the Dynamic Systems Development Methodology (DSDM) and has made extensive use of Commercial Off-The-Shelf (COTS) software products. INTELMOD also incorporates UNiT (Universal Intelligent Toolkit), to provide automatic execution of recovery procedures following fault detection and isolation. Users of INTELMOD require no formal programming experience, as models can be constructed with user-friendly editors that employ a “drag and drop” approach using pre- defined palettes of key components.

  16. On modeling and controlling intelligent systems

    Energy Technology Data Exchange (ETDEWEB)

    Dress, W.B.

    1993-11-01

    The aim of this paper is to show how certain diverse and advanced techniques of information processing and system theory might be integrated into a model of an intelligent, complex entity capable of materially enhancing an advanced information management system. To this end, we first examine the notion of intelligence and ask whether a semblance thereof can arise in a system consisting of ensembles of finite-state automata. Our goal is to find a functional model of intelligence in an information-management setting that can be used as a tool. The purpose of this tool is to allow us to create systems of increasing complexity and utility, eventually reaching the goal of an intelligent information management system that provides and anticipates needed data and information. We base our attempt on the ideas of general system theory where the four topics of system identification, modeling, optimization, and control provide the theoretical framework for constructing a complex system that will be capable of interacting with complex systems in the real world. These four key topics are discussed within the purview of cellular automata, neural networks, and evolutionary programming. This is a report of ongoing work, and not yet a success story of a synthetic intelligent system.

  17. On modeling and controlling intelligent systems

    Energy Technology Data Exchange (ETDEWEB)

    Dress, W.B.

    1993-11-01

    The aim of this paper is to show how certain diverse and advanced techniques of information processing and system theory might be integrated into a model of an intelligent, complex entity capable of materially enhancing an advanced information management system. To this end, we first examine the notion of intelligence and ask whether a semblance thereof can arise in a system consisting of ensembles of finite-state automata. Our goal is to find a functional model of intelligence in an information-management setting that can be used as a tool. The purpose of this tool is to allow us to create systems of increasing complexity and utility, eventually reaching the goal of an intelligent information management system that provides and anticipates needed data and information. We base our attempt on the ideas of general system theory where the four topics of system identification, modeling, optimization, and control provide the theoretical framework for constructing a complex system that will be capable of interacting with complex systems in the real world. These four key topics are discussed within the purview of cellular automata, neural networks, and evolutionary programming. This is a report of ongoing work, and not yet a success story of a synthetic intelligent system.

  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 la

  19. A model for Business Intelligence Systems’ Development

    Directory of Open Access Journals (Sweden)

    Manole VELICANU

    2009-01-01

    Full Text Available Often, Business Intelligence Systems (BIS require historical data or data collected from var-ious sources. The solution is found in data warehouses, which are the main technology used to extract, transform, load and store data in the organizational Business Intelligence projects. The development cycle of a data warehouse involves lots of resources, time, high costs and above all, it is built only for some specific tasks. In this paper, we’ll present some of the aspects of the BI systems’ development such as: architecture, lifecycle, modeling techniques and finally, some evaluation criteria for the system’s performance.

  20. Modeling speech intelligibility in adverse conditions

    DEFF Research Database (Denmark)

    Dau, Torsten

    2012-01-01

    by the normal as well as impaired auditory system. Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] proposed the speech-based envelope power spectrum model (sEPSM) in an attempt to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII......) in conditions with nonlinearly processed speech. Instead of considering the reduction of the temporal modulation energy as the intelligibility metric, as assumed in the STI, the sEPSM applies the signal-to-noise ratio in the envelope domain (SNRenv). This metric was shown to be the key for predicting...... the intelligibility of reverberant speech as well as noisy speech processed by spectral subtraction. However, the sEPSM cannot account for speech subjected to phase jitter, a condition in which the spectral structure of speech is destroyed, while the broadband temporal envelope is kept largely intact. In contrast...

  1. Towards a universal competitive intelligence process model

    Directory of Open Access Journals (Sweden)

    Rene Pellissier

    2013-07-01

    Full Text Available Background: Competitive intelligence (CI provides actionable intelligence, which provides a competitive edge in enterprises. However, without proper process, it is difficult to develop actionable intelligence. There are disagreements about how the CI process should be structured. For CI professionals to focus on producing actionable intelligence, and to do so with simplicity, they need a common CI process model.Objectives: The purpose of this research is to review the current literature on CI, to look at the aims of identifying and analysing CI process models, and finally to propose a universal CI process model.Method: The study was qualitative in nature and content analysis was conducted on all identified sources establishing and analysing CI process models. To identify relevant literature, academic databases and search engines were used. Moreover, a review of references in related studies led to more relevant sources, the references of which were further reviewed and analysed. To ensure reliability, only peer-reviewed articles were used.Results: The findings reveal that the majority of scholars view the CI process as a cycle of interrelated phases. The output of one phase is the input of the next phase.Conclusion: The CI process is a cycle of interrelated phases. The output of one phase is the input of the next phase. These phases are influenced by the following factors: decision makers, process and structure, organisational awareness and culture, and feedback.

  2. Towards a universal competitive intelligence process model

    Directory of Open Access Journals (Sweden)

    Rene Pellissier

    2013-08-01

    Full Text Available Background: Competitive intelligence (CI provides actionable intelligence, which provides a competitive edge in enterprises. However, without proper process, it is difficult to develop actionable intelligence. There are disagreements about how the CI process should be structured. For CI professionals to focus on producing actionable intelligence, and to do so with simplicity, they need a common CI process model.Objectives: The purpose of this research is to review the current literature on CI, to look at the aims of identifying and analysing CI process models, and finally to propose a universal CI process model.Method: The study was qualitative in nature and content analysis was conducted on all identified sources establishing and analysing CI process models. To identify relevant literature, academic databases and search engines were used. Moreover, a review of references in related studies led to more relevant sources, the references of which were further reviewed and analysed. To ensure reliability, only peer-reviewed articles were used.Results: The findings reveal that the majority of scholars view the CI process as a cycle of interrelated phases. The output of one phase is the input of the next phase.Conclusion: The CI process is a cycle of interrelated phases. The output of one phase is the input of the next phase. These phases are influenced by the following factors: decision makers, process and structure, organisational awareness and culture, and feedback.

  3. Modeling Speech Intelligibility in Hearing Impaired Listeners

    DEFF Research Database (Denmark)

    Scheidiger, Christoph; Jørgensen, Søren; Dau, Torsten

    2014-01-01

    Models of speech intelligibility (SI) have a long history, starting with the articulation index (AI, [17]), followed by the SI index (SI I, [18]) and the speech transmission index (STI, [7]), to only name a few. However, these models fail to accurately predict SI with nonlinearly processed noisy...... speech, e.g. phase jitter or spectral subtraction. Recent studies predict SI for normal-hearing (NH) listeners based on a signal-to-noise ratio measure in the envelope domain (SNRenv), in the framework of the speech-based envelope power spectrum model (sEPSM, [20, 21]). These models have shown good...... agreement with measured data under a broad range of conditions, including stationary and modulated interferers, reverberation, and spectral subtraction. Despite the advances in modeling intelligibility in NH listeners, a broadly applicable model that can predict SI in hearing-impaired (HI) listeners...

  4. Modeling of Biological Intelligence for SCM System Optimization

    OpenAIRE

    Shengyong Chen; Yujun Zheng; Carlo Cattani; Wanliang Wang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing c...

  5. A santidade da Igreja em Mathias Joseph Scheeben e nos que nele se inspiraram

    Directory of Open Access Journals (Sweden)

    Amaral, Miguel de Salis

    2006-01-01

    Full Text Available O estudo do tema da santidade da Igreja e de sua influência na história requer uma análise detalhada e circunstancial a cada período. O século XIX, por exemplo, foi pródigo em dificuldades eclesiais. O teólogo Mathias Scheeben caracteriza bem o pensamento teológico e as dificuldades da transição entre a Escola romana e o período da Neo-escolástica. Uma colaboração que merece ser aprofundada pelo deslocamento da visão jurídica da Igreja para uma visão mais sacramental e sobrenatural

  6. Intelligent Mechatronic Systems Modeling, Control and Diagnosis

    CERN Document Server

    Merzouki, Rochdi; Pathak, Pushparaj Mani; Ould Bouamama, Belkacem

    2013-01-01

    Acting as a support resource for practitioners and professionals looking to advance their understanding of complex mechatronic systems, Intelligent Mechatronic Systems explains their design and recent developments from first principles to practical applications. Detailed descriptions of the mathematical models of complex mechatronic systems, developed from fundamental physical relationships, are built on to develop innovative solutions with particular emphasis on physical model-based control strategies. Following a concurrent engineering approach, supported by industrial case studies, and drawing on the practical experience of the authors, Intelligent Mechatronic Systems covers range of topic and includes:  • An explanation of a common graphical tool for integrated design and its uses from modeling and simulation to the control synthesis • Introductions to key concepts such as different means of achieving fault tolerance, robust overwhelming control and force and impedance control • Dedicated chapters ...

  7. A review on intelligent sensory modelling

    Science.gov (United States)

    Tham, H. J.; Tang, S. Y.; Teo, K. T. K.; Loh, S. P.

    2016-06-01

    Sensory evaluation plays an important role in the quality control of food productions. Sensory data obtained through sensory evaluation are generally subjective, vague and uncertain. Classically, factorial multivariate methods such as Principle Component Analysis (PCA), Partial Least Square (PLS) method, Multiple Regression (MLR) method and Response Surface Method (RSM) are the common tools used to analyse sensory data. These methods can model some of the sensory data but may not be robust enough to analyse nonlinear data. In these situations, intelligent modelling techniques such as Fuzzy Logic and Artificial neural network (ANNs) emerged to solve the vagueness and uncertainty of sensory data. This paper outlines literature of intelligent sensory modelling on sensory data analysis.

  8. La realidad de la ficción: el ECO de Mathias Goeritz

    Directory of Open Access Journals (Sweden)

    Fernando Quesada

    2016-05-01

    Full Text Available Resumen Este artículo recorre al completo la biografía de un edificio, el Museo  Experimental El Eco, del artista y arquitecto alemán emigrado a México Mathias Goeritz. Se entrecruzan la biografía del propio autor y la del edificio con las de personalidades de las dos tradiciones culturales, la  alemana y la mexicana, que intervinieron en la creación de una arquitectura tan particular y única como es la de El Eco. De Alemania provienen la ética del expresionismo, el interés por al arte no europeo, el culto al primitivismo y el sistema estético del par abstracción-empatía. De México la religiosidad panteísta del paisaje, el zoomorfismo y antropomorfismo, el interés por las máscaras y la estética monumental. A partir del cruce de Mathias Goeritz con personas y temas provenientes de su pasado alemán y de su futuro mexicano, en las que cabe resaltar las figuras de Wilhelm Worringer, Paul Westheim, Luis Barragán, Edmundo O’Gorman e Ida Rodríguez Prampolini, es posible en este artículo proponer un viaje de ida y vuelta de la ficción a la realidad, siguiendo los pasos de su autor y comparándolos con los que siguió el propio edificio.

  9. TOWARD COLLECTIVE INTELLIGENCE OF ONLINE COMMUNITIES: A PRIMITIVE CONCEPTUAL MODEL

    Institute of Scientific and Technical Information of China (English)

    Shuangling LUO; Haoxiang XIA; Taketoshi YOSHIDA; Zhongtuo WANG

    2009-01-01

    Inspired by the ideas of Swarm Intelligence and the "global brain", a concept of "community intelligence" is suggested in the present paper, reflecting that some "intelligent" features may emerge in a Web-mediated online community from interactions and knowledge-transmissions between the community members. This possible research field of community intelligence is then examined under the backgrounds of "community" and "intelligence" researches. Furthermore, a conceptual model of community intelligence is developed from two views. From the structural view, the community intelligent system is modeled as a knowledge supernetwork that is comprised of triple interwoven networks of the media network, the human network, and the knowledge network. Furthermore, based on a dyad of knowledge in two forms of "knowing" and "knoware", the dynamic view describes the basic mechanics of the formation and evolution of "community intelligence". A few relevant research issues are shortly discussed on the basis of the proposed conceptual model.

  10. Artificial Intelligence Software Engineering (AISE) model

    Science.gov (United States)

    Kiss, Peter A.

    1990-01-01

    The American Institute of Aeronautics and Astronautics has initiated a committee on standards for Artificial Intelligence. Presented are the initial efforts of one of the working groups of that committee. A candidate model is presented for the development life cycle of knowledge based systems (KBSs). The intent is for the model to be used by the aerospace community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are shown and detailed as are the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

  11. Artificial Intelligence Software Engineering (AISE) model

    Science.gov (United States)

    Kiss, Peter A.

    1990-01-01

    The American Institute of Aeronautics and Astronautics has initiated a committee on standards for Artificial Intelligence. Presented are the initial efforts of one of the working groups of that committee. A candidate model is presented for the development life cycle of knowledge based systems (KBSs). The intent is for the model to be used by the aerospace community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are shown and detailed as are the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

  12. Modelling speech intelligibility in adverse conditions.

    Science.gov (United States)

    Jørgensen, Søren; Dau, Torsten

    2013-01-01

    Jørgensen and Dau (J Acoust Soc Am 130:1475-1487, 2011) proposed the speech-based envelope power spectrum model (sEPSM) in an attempt to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII) in conditions with nonlinearly processed speech. Instead of considering the reduction of the temporal modulation energy as the intelligibility metric, as assumed in the STI, the sEPSM applies the signal-to-noise ratio in the envelope domain (SNRenv). This metric was shown to be the key for predicting the intelligibility of reverberant speech as well as noisy speech processed by spectral subtraction. The key role of the SNRenv metric is further supported here by the ability of a short-term version of the sEPSM to predict speech masking release for different speech materials and modulated interferers. However, the sEPSM cannot account for speech subjected to phase jitter, a condition in which the spectral structure of the intelligibility of speech signal is strongly affected, while the broadband temporal envelope is kept largely intact. In contrast, the effects of this distortion can be predicted -successfully by the spectro-temporal modulation index (STMI) (Elhilali et al., Speech Commun 41:331-348, 2003), which assumes an explicit analysis of the spectral "ripple" structure of the speech signal. However, since the STMI applies the same decision metric as the STI, it fails to account for spectral subtraction. The results from this study suggest that the SNRenv might reflect a powerful decision metric, while some explicit across-frequency analysis seems crucial in some conditions. How such across-frequency analysis is "realized" in the auditory system remains unresolved.

  13. Business Intelligence Modeling in Launch Operations

    Science.gov (United States)

    Bardina, Jorge E.; Thirumalainambi, Rajkumar; Davis, Rodney D.

    2005-01-01

    This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation .based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations. process models, systems and environment models, and cost models as a comprehensive disciplined enterprise analysis environment. Significant emphasis is being placed on adapting root cause from existing Shuttle operations to exploration. Technical challenges include cost model validation, integration of parametric models with discrete event process and systems simulations. and large-scale simulation integration. The enterprise architecture is required for coherent integration of systems models. It will also require a plan for evolution over the life of the program. The proposed technology will produce

  14. Business intelligence modeling in launch operations

    Science.gov (United States)

    Bardina, Jorge E.; Thirumalainambi, Rajkumar; Davis, Rodney D.

    2005-05-01

    The future of business intelligence in space exploration will focus on the intelligent system-of-systems real-time enterprise. In present business intelligence, a number of technologies that are most relevant to space exploration are experiencing the greatest change. Emerging patterns of set of processes rather than organizational units leading to end-to-end automation is becoming a major objective of enterprise information technology. The cost element is a leading factor of future exploration systems. This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations, process models, systems and environment models, and cost models as a comprehensive disciplined

  15. Intelligent Model for Traffic Safety Applications

    Directory of Open Access Journals (Sweden)

    C. Chellappan

    2012-01-01

    Full Text Available Problem statement: This study presents an analysis on road traffic system focused on the use of communications to detect dangerous vehicles on roads and highways and how it could be used to enhance driver safety. Approach: The intelligent traffic safety application model is based on all traffic flow theories developed in the last years, leading to reliable representations of road traffic, which is of major importance in achieving the attenuation of traffic problems. The model also includes the decision making process from the driver in accelerating, decelerating and changing lanes. Results: The individuality of each of these processes appears from the model parameters that are randomly generated from statistical distributions introduced as input parameters. Conclusion: This allows the integration of the individuality factor of the population elements yielding knowledge on various driving modes at wide variety of situations.

  16. 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.

  17. 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.

  18. Intelligence and Personal Influence in Groups: Four Nonlinear Models.

    Science.gov (United States)

    Simonton, Dean Keith

    1985-01-01

    Four models are developed to provide a conceptual basis for a curvilinear relation between intelligence and an individual's influence over group members. The models deal with influence and percentile placement in intelligence, comprehension by potential followers, vulnerability to rival intellects, and correlation between mean group IQ and the…

  19. Intelligent Model for Video Survillance Security System

    Directory of Open Access Journals (Sweden)

    J. Vidhya

    2013-12-01

    Full Text Available Video surveillance system senses and trails out all the threatening issues in the real time environment. It prevents from security threats with the help of visual devices which gather the information related to videos like CCTV’S and IP (Internet Protocol cameras. Video surveillance system has become a key for addressing problems in the public security. They are mostly deployed on the IP based network. So, all the possible security threats exist in the IP based application might also be the threats available for the reliable application which is available for video surveillance. In result, it may increase cybercrime, illegal video access, mishandling videos and so on. Hence, in this paper an intelligent model is used to propose security for video surveillance system which ensures safety and it provides secured access on video.

  20. Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

    Science.gov (United States)

    MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

    2014-04-01

    This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

  1. ID Model Construction and Validation: A Multiple Intelligences Case

    Science.gov (United States)

    Tracey, Monica W.; Richey, Rita C.

    2007-01-01

    This is a report of a developmental research study that aimed to construct and validate an instructional design (ID) model that incorporates the theory and practice of multiple intelligences (MI). The study consisted of three phases. In phase one, the theoretical foundations of multiple Intelligences and ID were examined to guide the development…

  2. Credit Scoring Model Hybridizing Artificial Intelligence with Logistic Regression

    Directory of Open Access Journals (Sweden)

    Han Lu

    2013-01-01

    Full Text Available Today the most commonly used techniques for credit scoring are artificial intelligence and statistics. In this paper, we started a new way to use these two kinds of models. Through logistic regression filters the variables with a high degree of correlation, artificial intelligence models reduce complexity and accelerate convergence, while these models hybridizing logistic regression have better explanations in statistically significance, thus improve the effect of artificial intelligence models. With experiments on German data set, we find an interesting phenomenon defined as ‘Dimensional interference’ with support vector machine and from cross validation it can be seen that the new method gives a lot of help with credit scoring.

  3. Multidimensional Learner Model In Intelligent Learning System

    Science.gov (United States)

    Deliyska, B.; Rozeva, A.

    2009-11-01

    The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

  4. World modeling for cooperative intelligent vehicles

    NARCIS (Netherlands)

    Papp, Z.; Brown, C.; Bartels, C.

    2008-01-01

    Cooperative intelligent vehicle systems constitute a promising way to improving traffic throughput, safety and comfort. The state-of-the-art intelligent-vehicle applications usually can be described as a collection of interacting, highly autonomous, complex dynamical systems (the individual vehicles

  5. Model of key success factors for Business Intelligence implementation

    Directory of Open Access Journals (Sweden)

    Peter Mesaros

    2016-07-01

    Full Text Available New progressive technologies recorded growth in every area. Information-communication technologies facilitate the exchange of information and it facilitates management of everyday activities in enterprises. Specific modules (such as Business Intelligence facilitate decision-making. Several studies have demonstrated the positive impact of Business Intelligence to decision-making. The first step is to put in place the enterprise. The implementation process is influenced by many factors. This article discusses the issue of key success factors affecting to successful implementation of Business Intelligence. The article describes the key success factors for successful implementation and use of Business Intelligence based on multiple studies. The main objective of this study is to verify the effects and dependence of selected factors and proposes a model of key success factors for successful implementation of Business Intelligence. Key success factors and the proposed model are studied in Slovak enterprises.

  6. 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 ...

  7. 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.

  8. EMOTIONAL INTELLIGENCE AND ORGANIZATIONAL COMPETITIVENESS: MANAGEMENT MODEL APPROACH

    Directory of Open Access Journals (Sweden)

    John N. N. Ugoani

    2016-09-01

    Full Text Available Modern organization theory considers emotional intelligence as the index of competencies that help organizations to develop a vision for competitiveness. It also allows organizational leaders to enthusiastically commit to the vision, and energize organizational members to achieve the vision. To maximize competiveness organizations use models to simplify and clarify thinking, to identify important aspects, to suggest explanations and to predict consequences, and explore other performance areas that would otherwise be hidden in an excess of words. The survey research design was used to explore the relationship between emotional intelligence and organizational competitiveness. The study found that emotional intelligence has strong positive relationship with organizational competitiveness

  9. Modeling of biological intelligence for SCM system optimization.

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  10. Modeling of Biological Intelligence for SCM System Optimization

    Directory of Open Access Journals (Sweden)

    Shengyong Chen

    2012-01-01

    Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  11. Intelligent predictive model of ventilating capacity of imperial smelt furnace

    Institute of Scientific and Technical Information of China (English)

    唐朝晖; 胡燕瑜; 桂卫华; 吴敏

    2003-01-01

    In order to know the ventilating capacity of imperial smelt furnace (ISF), and increase the output of plumbum, an intelligent modeling method based on gray theory and artificial neural networks(ANN) is proposed, in which the weight values in the integrated model can be adjusted automatically. An intelligent predictive model of the ventilating capacity of the ISF is established and analyzed by the method. The simulation results and industrial applications demonstrate that the predictive model is close to the real plant, the relative predictive error is 0.72%, which is 50% less than the single model, leading to a notable increase of the output of plumbum.

  12. Intelligent Cost Modeling Based on Soft Computing for Avionics Systems

    Institute of Scientific and Technical Information of China (English)

    ZHU Li-li; LI Zhuang-sheng; XU Zong-ze

    2006-01-01

    In parametric cost estimating, objections to using statistical Cost Estimating Relationships (CERs) and parametric models include problems of low statistical significance due to limited data points, biases in the underlying data, and lack of robustness. Soft Computing (SC) technologies are used for building intelligent cost models. The SC models are systemically evaluated based on their training and prediction of the historical cost data of airborne avionics systems. Results indicating the strengths and weakness of each model are presented. In general, the intelligent cost models have higher prediction precision, better data adaptability, and stronger self-learning capability than the regression CERs.

  13. Building information modeling based on intelligent parametric technology

    Institute of Scientific and Technical Information of China (English)

    ZENG Xudong; TAN Jie

    2007-01-01

    In order to push the information organization process of the building industry,promote sustainable architectural design and enhance the competitiveness of China's building industry,the author studies building information modeling (BIM) based on intelligent parametric modeling technology.Building information modeling is a new technology in the field of computer aided architectural design,which contains not only geometric data,but also the great amount of engineering data throughout the lifecycle of a building.The author also compares BIM technology with two-dimensional CAD technology,and demonstrates the advantages and characteristics of intelligent parametric modeling technology.Building information modeling,which is based on intelligent parametric modeling technology,will certainly replace traditional computer aided architectural design and become the new driving force to push forward China's building industry in this information age.

  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. Intelligence Fusion Modeling. A Proposed Approach.

    Science.gov (United States)

    1983-09-16

    Maintenance and performance histories of sensor systems are maintained by the Technical Control and Analysis Center ( TCAE ). Process. Reported data...SIGINT Signals Intelligence SNR Signal to Noise Ratio SYSMSG System Message TCAE Technical Control and Analysis Element TRADOC Training and Doctrine

  16. Prediction of speech intelligibility based on an auditory preprocessing model

    DEFF Research Database (Denmark)

    Christiansen, Claus Forup Corlin; Pedersen, Michael Syskind; Dau, Torsten

    2010-01-01

    Classical speech intelligibility models, such as the speech transmission index (STI) and the speech intelligibility index (SII) are based on calculations on the physical acoustic signals. The present study predicts speech intelligibility by combining a psychoacoustically validated model of auditory...... preprocessing [Dau et al., 1997. J. Acoust. Soc. Am. 102, 2892-2905] with a simple central stage that describes the similarity of the test signal with the corresponding reference signal at a level of the internal representation of the signals. The model was compared with previous approaches, whereby a speech...... in noise experiment was used for training and an ideal binary mask experiment was used for evaluation. All three models were able to capture the trends in the speech in noise training data well, but the proposed model provides a better prediction of the binary mask test data, particularly when the binary...

  17. Towards an Intelligent Project Based Organization Business Model

    Directory of Open Access Journals (Sweden)

    Alami Marrouni Oussama

    2013-01-01

    Full Text Available Global economy is undergoing a recession phase that had made competition tougher and imposed new business framework. Businesses have to shift from the classical management approaches to an Intelligent Project Based Organization (IPBO model that provides flexibility and agility. IPBO model is intended to reinforce the proven advantages of Project Based Organization (PBO by the use of suitable Enterprise Intelligence (EI Systems. The goal of this paper is to propose an IPBO model that combines benefits of PBO and EI and helps overcoming their pitfalls

  18. VEHICLE SIMULATION MODEL FOR DEVELOPING AN INTELLIGENT SLOPE SHIFT STRATEGY

    Institute of Scientific and Technical Information of China (English)

    Jin Hui; Ge Anlin

    2004-01-01

    With the rapid development of electronics and the growing demand for higher vehicle performance,intelligent shift technology is becoming increasingly important,and it promises to be a developing trend in vehicle automatic transmissions.A new simulation model is presented,which includes engine,powertrain,tire and vehicle dynamics models.Based on the model,simulation experiments are conducted to investigate the slope shift strategy.The data and conclusions obtained from the simulations are valuable contributions to the development of an intelligent slope shift strategy.

  19. 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.

  20. An Intelligence Process Model Based on a Collaborative Approach

    Science.gov (United States)

    2011-06-01

    including Open Source ( OSINT ), in the production of intelligence. All-source intelligence is both a separate intelligence discipline and the name of the...and signature intelligence (MASINT), Technical intelligence (TECHINT), Open source intelligence ( OSINT ), and Biometric intelligence (BIOINT)) to...characterizing the processes for each discipline (HUMINT, SIGINT, OSINT , IMINT, GEOINT, etc.). Then, we analyzed the All-Source activities and processes

  1. Technical intelligence in animals: the kea model.

    Science.gov (United States)

    Huber, Ludwig; Gajdon, Gyula K

    2006-10-01

    The ability to act on information flexibly is one of the cornerstones of intelligent behavior. As particularly informative example, tool-oriented behavior has been investigated to determine to which extent nonhuman animals understand means-end relations, object affordances, and have specific motor skills. Even planning with foresight, goal-directed problem solving and immediate causal inference have been a focus of research. However, these cognitive abilities may not be restricted to tool-using animals but may be found also in animals that show high levels of curiosity, object exploration and manipulation, and extractive foraging behavior. The kea, a New Zealand parrot, is a particularly good example. We here review findings from laboratory experiments and field observations of keas revealing surprising cognitive capacities in the physical domain. In an experiment with captive keas, the success rate of individuals that were allowed to observe a trained conspecific was significantly higher than that of naive control subjects due to their acquisition of some functional understanding of the task through observation. In a further experiment using the string-pulling task, a well-probed test for means-end comprehension, we found the keas finding an immediate solution that could not be improved upon in nine further trials. We interpreted their performance as insightful in the sense of being sensitive of the relevant functional properties of the task and thereby producing a new adaptive response without trial-and-error learning. Together, these findings contribute to the ongoing debate on the distribution of higher cognitive skills in the animal kingdom by showing high levels of sensorimotor intelligence in animals that do not use tools. In conclusion, we suggest that the 'Technical intelligence hypothesis' (Byrne, Machiavellian intelligence II: extensions and evaluations, pp 289-211, 1997), which has been proposed to explain the origin of the ape/monkey grade-shift in

  2. Intelligent negotiation model for ubiquitous group decision scenarios

    Institute of Scientific and Technical Information of China (English)

    Joo CARNEIRO; Diogo MARTINHO; Goreti MARREIROS; Paulo NOVAIS

    2016-01-01

    Supporting group decision-making in ubiquitous contexts is a complex task that must deal with a large amount of factors to succeed. Here we propose an approach for an intelligent negotiation model to support the group decision-making process specifically designed for ubiquitous contexts. Our approach can be used by researchers that intend to include arguments, complex algorithms, and agents’ modeling in a negotiation model. It uses a social networking logic due to the type of communication employed by the agents and it intends to support the ubiquitous group decision-making process in a similar way to the real process, which simultaneously preserves the amount and quality of intelligence generated in face-to-face meetings. We propose a new look into this problem by considering and defining strategies to deal with important points such as the type of attributes in the multi- criterion problems, agents’ reasoning, and intelligent dialogues.

  3. 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.

  4. Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System

    Institute of Scientific and Technical Information of China (English)

    Zhong-Qi Sheng; Chang-Ping Tang; Ci-Xing Lv

    2010-01-01

    Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.

  5. Improved Modeling of Intelligent Tutoring Systems Using Ant Colony Optimization

    Science.gov (United States)

    Rastegarmoghadam, Mahin; Ziarati, Koorush

    2017-01-01

    Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…

  6. COMPUTATIONALLY INTELLIGENT MODELLING AND CONTROL OF FLUIDIZED BED COMBUSTION PROCESS

    Directory of Open Access Journals (Sweden)

    Ivan T Ćirić

    2011-01-01

    Full Text Available In this paper modelling and control approaches for fluidized bed combustion process have been considered, that are based on the use of computational intelligence. Proposed adaptive neuro-fuzzy-genetic modelling and intelligent control strategies provide for efficient combining of available expert knowledge with experimental data. Firstly, based on the qualitative information on the desulphurization process, models of the SO2 emission in fluidized bed combustion have been developed, which provides for economical and efficient reduction of SO2 in FBC by estimation of optimal process parameters and by design of intelligent control systems based on defined emission models. Also, efficient fuzzy nonlinear FBC process modelling strategy by combining several linearized combustion models has been presented. Finally, fuzzy and conventional process control systems for fuel flow and primary air flow regulation based on developed models and optimized by genetic algorithms have also been developed. Obtained results indicate that computationally intelligent approach can be successfully applied for modelling and control of complex fluidized bed combustion process.

  7. Forecasting rain events - Meteorological models or collective intelligence?

    Science.gov (United States)

    Arazy, Ofer; Halfon, Noam; Malkinson, Dan

    2015-04-01

    Collective intelligence is shared (or group) intelligence that emerges from the collective efforts of many individuals. Collective intelligence is the aggregate of individual contributions: from simple collective decision making to more sophisticated aggregations such as in crowdsourcing and peer-production systems. In particular, collective intelligence could be used in making predictions about future events, for example by using prediction markets to forecast election results, stock prices, or the outcomes of sport events. To date, there is little research regarding the use of collective intelligence for prediction of weather forecasting. The objective of this study is to investigate the extent to which collective intelligence could be utilized to accurately predict weather events, and in particular rainfall. Our analyses employ metrics of group intelligence, as well as compare the accuracy of groups' predictions against the predictions of the standard model used by the National Meteorological Services. We report on preliminary results from a study conducted over the 2013-2014 and 2014-2015 winters. We have built a web site that allows people to make predictions on precipitation levels on certain locations. During each competition participants were allowed to enter their precipitation forecasts (i.e. 'bets') at three locations and these locations changed between competitions. A precipitation competition was defined as a 48-96 hour period (depending on the expected weather conditions), bets were open 24-48 hours prior to the competition, and during betting period participants were allowed to change their bets with no limitation. In order to explore the effect of transparency, betting mechanisms varied across study's sites: full transparency (participants able to see each other's bets); partial transparency (participants see the group's average bet); and no transparency (no information of others' bets is made available). Several interesting findings emerged from

  8. Evaluation of Artificial Intelligence Based Models for Chemical Biodegradability Prediction

    Directory of Open Access Journals (Sweden)

    Aleksandar Sabljic

    2004-12-01

    Full Text Available This study presents a review of biodegradability modeling efforts including a detailed assessment of two models developed using an artificial intelligence based methodology. Validation results for these models using an independent, quality reviewed database, demonstrate that the models perform well when compared to another commonly used biodegradability model, against the same data. The ability of models induced by an artificial intelligence methodology to accommodate complex interactions in detailed systems, and the demonstrated reliability of the approach evaluated by this study, indicate that the methodology may have application in broadening the scope of biodegradability models. Given adequate data for biodegradability of chemicals under environmental conditions, this may allow for the development of future models that include such things as surface interface impacts on biodegradability for example.

  9. Artificial intelligence support for scientific model-building

    Science.gov (United States)

    Keller, Richard M.

    1992-01-01

    Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

  10. [Epidemiological intelligence as a model of organization in health].

    Science.gov (United States)

    Rodrigues-Júnior, Antonio Luiz

    2012-03-01

    The concept of epidemiological intelligence, as a construction of information societies, goes beyond monitoring a list of diseases and the ability to elicit rapid responses. The concept should consider the complexity of the definition of epidemiology in the identification of this object of study without being limited to a set of actions in a single government sector. The activities of epidemiological intelligence include risk assessment, strategies for prevention and protection, subsystems of information, crisis management rooms, geographical analysis, etc. This concept contributes to the understanding of policies in health, in multisectorial and geopolitical dimensions, as regards the organization of services around public health emergencies, primary healthcare, as well as disasters. The activities of epidemiological intelligence should not be restricted to scientific research, but the researchers must beware of threats to public health. Lalonde's model enabled consideration of epidemiological intelligence as a way to restructure policies and share resources by creating communities of intelligence, whose purpose is primarily to deal with public health emergencies and disasters.

  11. Technologies for conceptual modelling and intelligent query formulation

    CSIR Research Space (South Africa)

    Alberts, R

    2008-11-01

    Full Text Available modelling and intelligent query formulation R ALBERTS1, K BRITZ1, A GERBER1, K HALLAND1,2, T MEYER1, L PRETORIUS1,2 (1) Knowledge Systems Group, Meraka Institute, CSIR, Pretoria, Gauteng, South Africa (2) School of Computing, University of South... this problem still more pressing: in this case an excess of information can be equivalent to an absence of information It is therefore necessary to use tools that organise data into intelligible and easily-accessible structures and return answers...

  12. Intelligent control of HVAC systems. Part I: Modeling and synthesis

    Directory of Open Access Journals (Sweden)

    Adrian TOADER

    2013-03-01

    Full Text Available This is the first part of a work on intelligent type control of Heating, Ventilating and Air-Conditioning (HVAC systems. The study is performed from the perspective of giving a unitary control method to ensure high energy efficiency and air quality improving. To illustrate the proposed HVAC control technique, in this first part it is considered as benchmark problem a single thermal space HVAC system. The construction of the mathematical model is performed only with a view to obtain a framework of HVAC intelligent control validation by numerical simulations. The latter will be reported in a second part of the study.

  13. The highly intelligent virtual agents for modeling financial markets

    Science.gov (United States)

    Yang, G.; Chen, Y.; Huang, J. P.

    2016-02-01

    Researchers have borrowed many theories from statistical physics, like ensemble, Ising model, etc., to study complex adaptive systems through agent-based modeling. However, one fundamental difference between entities (such as spins) in physics and micro-units in complex adaptive systems is that the latter are usually with high intelligence, such as investors in financial markets. Although highly intelligent virtual agents are essential for agent-based modeling to play a full role in the study of complex adaptive systems, how to create such agents is still an open question. Hence, we propose three principles for designing high artificial intelligence in financial markets and then build a specific class of agents called iAgents based on these three principles. Finally, we evaluate the intelligence of iAgents through virtual index trading in two different stock markets. For comparison, we also include three other types of agents in this contest, namely, random traders, agents from the wealth game (modified on the famous minority game), and agents from an upgraded wealth game. As a result, iAgents perform the best, which gives a well support for the three principles. This work offers a general framework for the further development of agent-based modeling for various kinds of complex adaptive systems.

  14. Intelligent Transportation and Evacuation Planning A Modeling-Based Approach

    CERN Document Server

    Naser, Arab

    2012-01-01

    Intelligent Transportation and Evacuation Planning: A Modeling-Based Approach provides a new paradigm for evacuation planning strategies and techniques. Recently, evacuation planning and modeling have increasingly attracted interest among researchers as well as government officials. This interest stems from the recent catastrophic hurricanes and weather-related events that occurred in the southeastern United States (Hurricane Katrina and Rita). The evacuation methods that were in place before and during the hurricanes did not work well and resulted in thousands of deaths. This book offers insights into the methods and techniques that allow for implementing mathematical-based, simulation-based, and integrated optimization and simulation-based engineering approaches for evacuation planning. This book also: Comprehensively discusses the application of mathematical models for evacuation and intelligent transportation modeling Covers advanced methodologies in evacuation modeling and planning Discusses principles a...

  15. A Conversation Model Enabling Intelligent Agents to Give Emotional Support

    OpenAIRE

    Van der Zwaan, J.M.; Dignum, V; Jonker, C.M.

    2012-01-01

    In everyday life, people frequently talk to others to help them deal with negative emotions. To some extent, everybody is capable of comforting other people, but so far conversational agents are unable to deal with this type of situation. To provide intelligent agents with the capability to give emotional support, we propose a domain-independent conversational model that is based on topics suggested by cognitive appraisal theories of emotion and the 5-phase model that is used to structure onl...

  16. PERFORMANCE-BASED INTELLIGENT RESOURCE DESCRIPTION MODEL FOR INTERNET-BASED PRODUCT DESIGN

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Issues on intelligent resource description and multiple intelligent resources integration for Internet-based collaborative design are analyzed. A performance-based intelligent resource description model for Internet-based product design is proposed, which can help to create, store,manipulate and exchange intelligent resource description information for applications, tools and systems in Internet-based product design. A method to integrate multiple intelligent resources to fulfill a complex product design and analysis via Internet is also proposed. A real project for improving the bearing system design of a turbo-expander with many intelligent resources in prominent universities is presented as a case study.

  17. Modeling and simulating human teamwork behaviors using intelligent agents

    Science.gov (United States)

    Fan, Xiaocong; Yen, John

    2004-12-01

    Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is important for training humans in gaining collaborative skills, for supporting humans in making critical decisions by proactively gathering, fusing, and sharing information, and for building coherent teams with both humans and agents working effectively on intelligence-intensive problems. Teamwork modeling is also challenging because the research has spanned diverse disciplines from business management to cognitive science, human discourse, and distributed artificial intelligence. This article presents an extensive, but not exhaustive, list of work in the field, where the taxonomy is organized along two main dimensions: team social structure and social behaviors. Along the dimension of social structure, we consider agent-only teams and mixed human-agent teams. Along the dimension of social behaviors, we consider collaborative behaviors, communicative behaviors, helping behaviors, and the underpinning of effective teamwork-shared mental models. The contribution of this article is that it presents an organizational framework for analyzing a variety of teamwork simulation systems and for further studying simulated teamwork behaviors.

  18. An Intelligent Model for Pairs Trading Using Genetic Algorithms.

    Science.gov (United States)

    Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

    2015-01-01

    Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

  19. An Intelligent Model for Pairs Trading Using Genetic Algorithms

    Science.gov (United States)

    Hsu, Chi-Jen; Chen, Chi-Chung; Li, Chen-An

    2015-01-01

    Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice. PMID:26339236

  20. THE FUZZY OVERLAY STUDENT MODEL IN AN INTELLIGENT TUTORING SYSTEM

    Directory of Open Access Journals (Sweden)

    D. I. Popov

    2015-01-01

    Full Text Available The article is devoted to the development of the student model for use in an intelligent tutoring system (ITS designed for the evaluation of students’ competencies in different Higher Education Facilities. There are classification and examples of the various student models, the most suitable for the evaluation of competencies is selected and finalized. The dynamic overlay fuzzy student model builded on the domain model based on the concept of didactic units is described in this work. The formulas, chart and diagrams are provided.

  1. Intelligent CAD Methodology Research of Adaptive Modeling

    Institute of Scientific and Technical Information of China (English)

    ZHANG Weibo; LI Jun; YAN Jianrong

    2006-01-01

    The key to carry out ICAD technology is to establish the knowledge-based and wide rang of domains-covered product model. This paper put out a knowledge-based methodology of adaptive modeling. It is under the Ontology mind, using the Object-Oriented technology and being a knowledge-based model framework. It involves the diverse domains in product design and realizes the multi-domain modeling, embedding the relative information including standards, regulars and expert experience. To test the feasibility of the methodology, the research bonds of the automotive diaphragm spring clutch design and an adaptive clutch design model is established, using the knowledge-based modeling language-AML.

  2. Intelligent Intrusion Detection System Model Using Rough Neural Network

    Institute of Scientific and Technical Information of China (English)

    YAN Huai-zhi; HU Chang-zhen; TAN Hui-min

    2005-01-01

    A model of intelligent intrusion detection based on rough neural network (RNN), which combines the neural network and rough set, is presented. It works by capturing network packets to identify network intrusions or malicious attacks using RNN with sub-nets. The sub-net is constructed by detection-oriented signatures extracted using rough set theory to detect different intrusions. It is proved that RNN detection method has the merits of adaptive, high universality,high convergence speed, easy upgrading and management.

  3. Interoperation Modeling for Intelligent Domotic Environments

    Science.gov (United States)

    Bonino, Dario; Corno, Fulvio

    This paper introduces an ontology-based model for domotic device inter-operation. Starting from a previously published ontology (DogOnt) a refactoring and extension is described allowing to explicitly represent device capabilities, states and commands, and supporting abstract modeling of device inter-operation.

  4. Self-assessed intelligence, personality, and psychometric intelligence: preliminary validation of a model with a selected student population

    Directory of Open Access Journals (Sweden)

    Maria A. Novikova

    2012-01-01

    Full Text Available In the current study, self-assessed intelligence (SAI is presented as a multidimensionalconstruct related both to personality and to psychometric intelligence. Onthe basis of data obtained from a Russian student sample (N = 496, the authorsvalidate a structural model in which SAI acts as a mediating variable between latentvariables of measured IQ and the trait of acceptance of uncertainty. Evidencefor signifi cant gender diff erences in SAI in favor of men is also given.

  5. Network Models for Cognitive Development and Intelligence

    National Research Council Canada - National Science Library

    Han L J VanDer; Kees-Jan Kan; Maarten Marsman; Claire E Stevenson

    2017-01-01

    ... (dimensionality of individual differences). The welcome integration of the two fields requires the construction of mechanistic models of cognition and cognitive development that explain key phenomena in individual differences research...

  6. The Intelligent Decision Support System Model of SARS

    Institute of Scientific and Technical Information of China (English)

    ZhouXingyu; ZhangJiang; LiuYang; XieYanqing; ZhangRan; ZhaoYang; HeZhongxiong

    2004-01-01

    Based on the intelligent decision support system, a new method was presented to defense the catastrophic infectious disease such as SARS, Bird Flu, etc.. By using All Set theory, the decision support system (DSS) model can be built to analyze the noise information and forecast the trend of the catastrophe then to give the method or policy to defend the disease. The model system is composed of four subsystems: the noise analysis subsystem, forecast and simulation subsystem, diagnosis subsystem and second recovery subsystem. They are discussed briefly in this paper. This model can be used not only for SARS but also for other paroxysmal accidences.

  7. The role of business intelligence in decision process modeling

    Directory of Open Access Journals (Sweden)

    Višnja Istrat

    2015-10-01

    Full Text Available Decision making is a very significant and complex function of management that requires methods and techniques that simplify the process of choosing the best alternative. In modern business, the challenge for managers is to find the alternatives for improving the decision-making process. Decisions directly affect profit generation and positioning of the company in the market. It is well-known that people dealt with the phenomenon of decision making in each phase of the development of society, which has triggered the need to learn more about this process. The main contribution of this paper is to show the significance of business intelligence tools and techniques as support to the decision making process of managers. Research results have shown that business intelligence plays an enormous role in modern decision process modeling.

  8. Electricity load modelling using computational intelligence

    NARCIS (Netherlands)

    Ter Borg, R.W.

    2005-01-01

    As a consequence of the liberalisation of the electricity markets in Europe, market players have to continuously adapt their future supply to match their customers' demands. This poses the challenge of obtaining a predictive model that accurately describes electricity loads, current in this thesis.

  9. Intelligent diagnosis of jaundice with dynamic uncertain causality graph model.

    Science.gov (United States)

    Hao, Shao-Rui; Geng, Shi-Chao; Fan, Lin-Xiao; Chen, Jia-Jia; Zhang, Qin; Li, Lan-Juan

    2017-05-01

    Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A "chaining" inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure.

  10. Intelligent diagnosis of jaundice with dynamic uncertain causality graph model*

    Science.gov (United States)

    Hao, Shao-rui; Geng, Shi-chao; Fan, Lin-xiao; Chen, Jia-jia; Zhang, Qin; Li, Lan-juan

    2017-01-01

    Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A “chaining” inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure. PMID:28471111

  11. An Intelligent Analysis Model for Multisource Volatile Memory

    Directory of Open Access Journals (Sweden)

    Xiaolu Zhang

    2013-09-01

    Full Text Available For the rapidly development of network and distributed computing environment, it make researchers harder to do analysis examines only from one or few pieces of data source in persistent data-oriented approaches, so as the volatile memory analysis either. Therefore, mass data automatically analysis and action modeling needs to be considered for reporting entire network attack process. To model multiple volatile data sources situation can help understand and describe both thinking process of investigator and possible action step for attacker. This paper presents a Game model for multisource volatile data and applies it to main memory images analysis with the definition of space-time feature for volatile element information. Abstract modeling allows the lessons gleaned in performing intelligent analysis, evidence filing and automating presentation. Finally, a test demo based on the model is also present to illustrate the whole procedure

  12. Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

    Science.gov (United States)

    Abbasi, Maryam; El Hanandeh, Ali

    2016-10-01

    Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg.

  13. Emotional intelligence: an integrative meta-analysis and cascading model.

    Science.gov (United States)

    Joseph, Dana L; Newman, Daniel A

    2010-01-01

    Research and valid practice in emotional intelligence (EI) have been impeded by lack of theoretical clarity regarding (a) the relative roles of emotion perception, emotion understanding, and emotion regulation facets in explaining job performance; (b) conceptual redundancy of EI with cognitive intelligence and Big Five personality; and (c) application of the EI label to 2 distinct sets of constructs (i.e., ability-based EI and mixed-based EI). In the current article, the authors propose and then test a theoretical model that integrates these factors. They specify a progressive (cascading) pattern among ability-based EI facets, in which emotion perception must causally precede emotion understanding, which in turn precedes conscious emotion regulation and job performance. The sequential elements in this progressive model are believed to selectively reflect Conscientiousness, cognitive ability, and Neuroticism, respectively. "Mixed-based" measures of EI are expected to explain variance in job performance beyond cognitive ability and personality. The cascading model of EI is empirically confirmed via meta-analytic data, although relationships between ability-based EI and job performance are shown to be inconsistent (i.e., EI positively predicts performance for high emotional labor jobs and negatively predicts performance for low emotional labor jobs). Gender and race differences in EI are also meta-analyzed. Implications for linking the EI fad in personnel selection to established psychological theory are discussed.

  14. Modeling the prediction of business intelligence system effectiveness.

    Science.gov (United States)

    Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I

    2016-01-01

    Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.

  15. Application of Artificial Intelligence for Bridge Deterioration Model

    Directory of Open Access Journals (Sweden)

    Zhang Chen

    2015-01-01

    Full Text Available The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention. An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper. When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters. This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention.

  16. Advances in Intelligent Modelling and Simulation Simulation Tools and Applications

    CERN Document Server

    Oplatková, Zuzana; Carvalho, Marco; Kisiel-Dorohinicki, Marek

    2012-01-01

    The human capacity to abstract complex systems and phenomena into simplified models has played a critical role in the rapid evolution of our modern industrial processes and scientific research. As a science and an art, Modelling and Simulation have been one of the core enablers of this remarkable human trace, and have become a topic of great importance for researchers and practitioners. This book was created to compile some of the most recent concepts, advances, challenges and ideas associated with Intelligent Modelling and Simulation frameworks, tools and applications. The first chapter discusses the important aspects of a human interaction and the correct interpretation of results during simulations. The second chapter gets to the heart of the analysis of entrepreneurship by means of agent-based modelling and simulations. The following three chapters bring together the central theme of simulation frameworks, first describing an agent-based simulation framework, then a simulator for electrical machines, and...

  17. Application of Artificial Intelligence for Bridge Deterioration Model.

    Science.gov (United States)

    Chen, Zhang; Wu, Yangyang; Li, Li; Sun, Lijun

    2015-01-01

    The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention. An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper. When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters. This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention.

  18. Neuro-Based Artificial Intelligence Model for Loan Decisions

    Directory of Open Access Journals (Sweden)

    Shorouq F. Eletter

    2010-01-01

    Full Text Available Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian Commercial banks. A multi-layer feed-forward neural network with backpropagation learning algorithm was used to build up the proposed model. Results: Different representative cases of loan applications were considered based on the guidelines of different banks in Jordan, to validate the neural network model. Conclusion: The results indicated that artificial neural networks are a successful technology that can be used in loan application evaluation in the Jordanian commercial banks.

  19. A Swarm Intelligence Based Model for Mobile Cloud Computing

    Directory of Open Access Journals (Sweden)

    Ahmed S. Salama

    2015-01-01

    Full Text Available Mobile Computing (MC provides multi services and a lot of advantages for millions of users across the world over the internet. Millions of business customers have leveraged cloud computing services through mobile devices to get what is called Mobile Cloud Computing (MCC. MCC aims at using cloud computing techniques for storage and processing of data on mobile devices, thereby reducing their limitations. This paper proposes architecture for a Swarm Intelligence Based Mobile Cloud Computing Model (SIBMCCM. A model that uses a proposed Parallel Particle Swarm Optimization (PPSO algorithm to enhance the access time for the mobile cloud computing services which support different E Commerce models and to better secure the communication through the mobile cloud and the mobile commerce transactions.

  20. 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.

  1. Mobile intelligent agent entity model towards QoS guarantee

    Institute of Scientific and Technical Information of China (English)

    LI Jie; WANG Ru-chuan; BIAN Zhen-gai

    2006-01-01

    Implementing a flexible configuration of the QoS parameter in a distributed computing network has become a problem due to the weak scalability of current approaches.In an effort to solve this problem,an inner basic model of an intelligent agent (IA) is presented.The IA functionality was extended by introducing a primarily mobile agent.A QoS guarantee scheme was subsequently designed and implemented based on the model as well.By utilizing the proposed scheme,the IA can sense,predict and configure the data flow traffic.Since the communicating ability was considered and provided,the competition among different devices could be eliminated effectively and the global traffic can be optimized.The results of the simulations have shown that the proposed model can provide a QoS guarantee.

  2. 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...

  3. Intelligent Model for Measuring Organization Maturity in E-Business

    Directory of Open Access Journals (Sweden)

    Sadra Ahmadi

    2009-07-01

    Full Text Available E-Business is one of the most fascinating areas of information Technology. Managers should seek out means for making decision towards optimizing resource development in this area in order to control their expense and capital allocations at a higher, strategic level. To do this, manager must first identify their level of e-business development and plan to improve the status quo by identifying factors contributing to the growth in this approach. The present paper aims to construct and develop intelligent models for determining the organization status quo and management decision-making towards improving the situation using fuzzy [logic] tools. Thus for modeling these factors and their impact, the contributing factors in development of e-business approaches were identified by literature survey. These were later categorized using Delphi Method. Furthermore the FCM model was used to graphically illustrate the causal relationships among factors, including the mode and means of their mutual impact.

  4. A Soft Intelligent Risk Evaluation Model for Credit Scoring Classification

    Directory of Open Access Journals (Sweden)

    Mehdi Khashei

    2015-09-01

    Full Text Available Risk management is one of the most important branches of business and finance. Classification models are the most popular and widely used analytical group of data mining approaches that can greatly help financial decision makers and managers to tackle credit risk problems. However, the literature clearly indicates that, despite proposing numerous classification models, credit scoring is often a difficult task. On the other hand, there is no universal credit-scoring model in the literature that can be accurately and explanatorily used in all circumstances. Therefore, the research for improving the efficiency of credit-scoring models has never stopped. In this paper, a hybrid soft intelligent classification model is proposed for credit-scoring problems. In the proposed model, the unique advantages of the soft computing techniques are used in order to modify the performance of the traditional artificial neural networks in credit scoring. Empirical results of Australian credit card data classifications indicate that the proposed hybrid model outperforms its components, and also other classification models presented for credit scoring. Therefore, the proposed model can be considered as an appropriate alternative tool for binary decision making in business and finance, especially in high uncertainty conditions.

  5. Synthetic vision and emotion calculation in intelligent virtual human modeling.

    Science.gov (United States)

    Zhao, Y; Kang, J; Wright, D K

    2007-01-01

    The virtual human technique can already provide vivid and believable human behaviour in more and more scenarios. Virtual humans are expected to replace real humans in hazardous situations to undertake tests and feed back valuable information. This paper will introduce a virtual human with a novel collision-based synthetic vision, short-term memory model and a capability to implement emotion calculation and decision making. The virtual character based on this model can 'see' what is in its field of view (FOV) and remember those objects. After that, a group of affective computing equations have been introduced. These equations have been implemented into a proposed emotion calculation process to enlighten emotion for virtual intelligent humans.

  6. A vector relational data modeling approach to Insider threat intelligence

    Science.gov (United States)

    Kelly, Ryan F.; Anderson, Thomas S.

    2016-05-01

    We address the problem of detecting insider threats before they can do harm. In many cases, co-workers notice indications of suspicious activity prior to insider threat attacks. A partial solution to this problem requires an understanding of how information can better traverse the communication network between human intelligence and insider threat analysts. Our approach employs modern mobile communications technology and scale free network architecture to reduce the network distance between human sensors and analysts. In order to solve this problem, we propose a Vector Relational Data Modeling approach to integrate human "sensors," geo-location, and existing visual analytics tools. This integration problem is known to be difficult due to quadratic increases in cost associated with complex integration solutions. A scale free network integration approach using vector relational data modeling is proposed as a method for reducing network distance without increasing cost.

  7. Promising synergies of simulation model management, software engineering, artificial intelligence, and general system theories

    Energy Technology Data Exchange (ETDEWEB)

    Oren, T.I.

    1982-01-01

    Simulation is viewed within the model management paradigm. Major components of simulation systems as well as elements of model management are outlined. Possible synergies of simulation model management, software engineering, artificial intelligence, and general system theories are systematized. 21 references.

  8. Corticonic models of brain mechanisms underlying cognition and intelligence

    Science.gov (United States)

    Farhat, Nabil H.

    The concern of this review is brain theory or more specifically, in its first part, a model of the cerebral cortex and the way it: (a) interacts with subcortical regions like the thalamus and the hippocampus to provide higher-level-brain functions that underlie cognition and intelligence, (b) handles and represents dynamical sensory patterns imposed by a constantly changing environment, (c) copes with the enormous number of such patterns encountered in a lifetime by means of dynamic memory that offers an immense number of stimulus-specific attractors for input patterns (stimuli) to select from, (d) selects an attractor through a process of “conjugation” of the input pattern with the dynamics of the thalamo-cortical loop, (e) distinguishes between redundant (structured) and non-redundant (random) inputs that are void of information, (f) can do categorical perception when there is access to vast associative memory laid out in the association cortex with the help of the hippocampus, and (g) makes use of “computation” at the edge of chaos and information driven annealing to achieve all this. Other features and implications of the concepts presented for the design of computational algorithms and machines with brain-like intelligence are also discussed. The material and results presented suggest, that a Parametrically Coupled Logistic Map network (PCLMN) is a minimal model of the thalamo-cortical complex and that marrying such a network to a suitable associative memory with re-entry or feedback forms a useful, albeit, abstract model of a cortical module of the brain that could facilitate building a simple artificial brain. In the second part of the review, the results of numerical simulations and drawn conclusions in the first part are linked to the most directly relevant works and views of other workers. What emerges is a picture of brain dynamics on the mesoscopic and macroscopic scales that gives a glimpse of the nature of the long sought after brain code

  9. The ability model of emotional intelligence: Searching for valid measures

    OpenAIRE

    Fiori, M.; Antonakis, J.

    2011-01-01

    Current measures of ability emotional intelligence (EI)--including the well-known Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)--suffer from several limitations, including low discriminant validity and questionable construct and incremental validity. We show that the MSCEIT is largely predicted by personality dimensions, general intelligence, and demographics having multiple R's with the MSCEIT branches up to .66; for the general EI factor this relation was even stronger (Multiple...

  10. Analysis of Intelligent Transportation Systems Using Model-Driven Simulations

    Directory of Open Access Journals (Sweden)

    Alberto Fernández-Isabel

    2015-06-01

    Full Text Available Intelligent Transportation Systems (ITSs integrate information, sensor, control, and communication technologies to provide transport related services. Their users range from everyday commuters to policy makers and urban planners. Given the complexity of these systems and their environment, their study in real settings is frequently unfeasible. Simulations help to address this problem, but present their own issues: there can be unintended mistakes in the transition from models to code; their platforms frequently bias modeling; and it is difficult to compare works that use different models and tools. In order to overcome these problems, this paper proposes a framework for a model-driven development of these simulations. It is based on a specific modeling language that supports the integrated specification of the multiple facets of an ITS: people, their vehicles, and the external environment; and a network of sensors and actuators conveniently arranged and distributed that operates over them. The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications. There are also guidelines to help researchers in the application of this infrastructure. A case study on advanced management of traffic lights with cameras illustrates its use.

  11. Analysis of Intelligent Transportation Systems Using Model-Driven Simulations

    Science.gov (United States)

    Fernández-Isabel, Alberto; Fuentes-Fernández, Rubén

    2015-01-01

    Intelligent Transportation Systems (ITSs) integrate information, sensor, control, and communication technologies to provide transport related services. Their users range from everyday commuters to policy makers and urban planners. Given the complexity of these systems and their environment, their study in real settings is frequently unfeasible. Simulations help to address this problem, but present their own issues: there can be unintended mistakes in the transition from models to code; their platforms frequently bias modeling; and it is difficult to compare works that use different models and tools. In order to overcome these problems, this paper proposes a framework for a model-driven development of these simulations. It is based on a specific modeling language that supports the integrated specification of the multiple facets of an ITS: people, their vehicles, and the external environment; and a network of sensors and actuators conveniently arranged and distributed that operates over them. The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications. There are also guidelines to help researchers in the application of this infrastructure. A case study on advanced management of traffic lights with cameras illustrates its use. PMID:26083232

  12. Modeling Common-Sense Decisions in Artificial Intelligence

    Science.gov (United States)

    Zak, Michail

    2010-01-01

    A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation

  13. Integrated Modeling and Intelligent Control Methods of Grinding Process

    Directory of Open Access Journals (Sweden)

    Jie-sheng Wang

    2013-01-01

    Full Text Available The grinding process is a typical complex nonlinear multivariable process with strongly coupling and large time delays. Based on the data-driven modeling theory, the integrated modeling and intelligent control method of grinding process is carried out in the paper, which includes the soft-sensor model of economic and technique indexes, the optimized set-point model utilizing case-based reasoning, and the self-tuning PID decoupling controller. For forecasting the key technology indicators (grinding granularity and mill discharge rate of grinding process, an adaptive soft-sensor modeling method based on wavelet neural network optimized by the improved shuffled frog leaping algorithm (ISFLA is proposed. Then, a set point optimization control strategy of grinding process based on case-based reasoning (CBR method is adopted to obtain the optimized velocity set-point of ore feed and pump water feed in the grinding process controlled loops. Finally, a self-tuning PID decoupling controller optimized is used to control the grinding process. Simulation results and industrial application experiments clearly show the feasibility and effectiveness of control methods and satisfy the real-time control requirements of the grinding process.

  14. Advances in simulated modeling of vibration systems based on computational intelligence

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Computational intelligence is the computational simulation of the bio-intelligence, which includes artificial neural networks, fuzzy systems and evolutionary computations. This article summarizes the state of the art in the field of simulated modeling of vibration systems using methods of computational intelligence, based on some relevant subjects and the authors' own research work. First, contributions to the applications of computational intelligence to the identification of nonlinear characteristics of packaging are reviewed. Subsequently, applications of the newly developed training algorithms for feedforward neural networks to the identification of restoring forces in multi-degree-of-freedom nonlinear systems are discussed. Finally, the neural-network-based method of model reduction for the dynamic simulation of microelectromechanical systems (MEMS) using generalized Hebbian algorithm (GHA) and robust GHA is outlined. The prospects of the simulated modeling of vibration systems using techniques of computational intelligence are also indicated.

  15. An application of artificial intelligence for rainfall–runoff modeling

    Indian Academy of Sciences (India)

    Ali Aytek; M Asce; Murat Alp

    2008-04-01

    This study proposes an application of two techniques of artificial intelligence (AI) for rainfall–runoff modeling: the artificial neural networks (ANN) and the evolutionary computation (EC). Two different ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods are compared with one EC method, Gene Expression Programming (GEP) which is a new evolutionary algorithm that evolves computer programs. The daily hydrometeorological data of three rainfall stations and one streamflow station for Juniata River Basin in Pennsylvania state of USA are taken into consideration in the model development. Statistical parameters such as average, standard deviation, coefficient of variation, skewness, minimum and maximum values, as well as criteria such as mean square error (MSE) and determination coefficient (2) are used to measure the performance of the models. The results indicate that the proposed genetic programming (GP) formulation performs quite well compared to results obtained by ANNs and is quite practical for use. It is concluded from the results that GEP can be proposed as an alternative to ANN models.

  16. A dynamical model of general intelligence: The positive manifold of intelligence by mutualism

    NARCIS (Netherlands)

    van der Maas, H.L.J.; Dolan, C.V.; Grasman, R.P.P.P.; Wicherts, J.M.; Huizenga, H.M.; Raijmakers, M.E.J.

    2006-01-01

    Scores on cognitive tasks used in intelligence tests correlate positively with each other, that is, they display a positive manifold of correlations. The positive manifold is often explained by positing a dominant latent variable, the g factor, associated with a single quantitative cognitive or biol

  17. Developmental Process Model for the Java Intelligent Tutoring System

    Science.gov (United States)

    Sykes, Edward

    2007-01-01

    The Java Intelligent Tutoring System (JITS) was designed and developed to support the growing trend of Java programming around the world. JITS is an advanced web-based personalized tutoring system that is unique in several ways. Most programming Intelligent Tutoring Systems require the teacher to author problems with corresponding solutions. JITS,…

  18. Modelling intelligence-led policing to identify its potential

    NARCIS (Netherlands)

    Hengst-Bruggeling, M. den; Graaf, H.A.L.M. de; Scheepstal, P.G.M. van

    2014-01-01

    lntelligence-led policing is a concept of policing that has been applied throughout the world. Despite some encouraging reports, the effect of intelligence-led policing is largely unknown. This paper presents a method with which it is possible to identify intelligence-led policing's potential to

  19. Modelling intelligence-led policing to identify its potential

    NARCIS (Netherlands)

    Hengst-Bruggeling, M. den; Graaf, H.A.L.M. de; Scheepstal, P.G.M. van

    2014-01-01

    lntelligence-led policing is a concept of policing that has been applied throughout the world. Despite some encouraging reports, the effect of intelligence-led policing is largely unknown. This paper presents a method with which it is possible to identify intelligence-led policing's potential to inc

  20. AN INTELLIGENT CLASSIFICATION MODEL FOR PHISHING EMAIL DETECTION

    Directory of Open Access Journals (Sweden)

    Adwan Yasin

    2016-07-01

    Full Text Available Phishing attacks are one of the trending cyber-attacks that apply socially engineered messages that are communicated to people from professional hackers aiming at fooling users to reveal their sensitive information, the most popular communication channel to those messages is through users’ emails. This paper presents an intelligent classification model for detecting phishing emails using knowledge discovery, data mining and text processing techniques. This paper introduces the concept of phishing terms weighting which evaluates the weight of phishing terms in each email. The pre-processing phase is enhanced by applying text stemming and WordNet ontology to enrich the model with word synonyms. The model applied the knowledge discovery procedures using five popular classification algorithms and achieved a notable enhancement in classification accuracy; 99.1% accuracy was achieved using the Random Forest algorithm and 98.4% using J48, which is –to our knowledge- the highest accuracy rate for an accredited data set. This paper also presents a comparative study with similar proposed classification techniques.

  1. Predicting chick body mass by artificial intelligence-based models

    Directory of Open Access Journals (Sweden)

    Patricia Ferreira Ponciano Ferraz

    2014-07-01

    Full Text Available The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks - with the variables dry-bulb air temperature, duration of thermal stress (days, chick age (days, and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs and neuro-fuzzy networks (NFNs. The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

  2. The effect of learning models and emotional intelligence toward students learning outcomes on reaction rate

    Science.gov (United States)

    Sutiani, Ani; Silitonga, Mei Y.

    2017-08-01

    This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.

  3. Does Reading Cause Later Intelligence? Accounting for Stability in Models of Change.

    Science.gov (United States)

    Bailey, Drew H; Littlefield, Andrew K

    2016-11-08

    This study reanalyzes data presented by Ritchie, Bates, and Plomin (2015) who used a cross-lagged monozygotic twin differences design to test whether reading ability caused changes in intelligence. The authors used data from a sample of 1,890 monozygotic twin pairs tested on reading ability and intelligence at five occasions between the ages of 7 and 16, regressing twin differences in intelligence on twin differences in prior intelligence and twin differences in prior reading ability. Results from a state-trait model suggest that reported effects of reading ability on later intelligence may be artifacts of previously uncontrolled factors, both environmental in origin and stable during this developmental period, influencing both constructs throughout development. Implications for cognitive developmental theory and methods are discussed. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

  4. Structural equation model of intellectual change and continuity and predictors of intelligence in older men.

    Science.gov (United States)

    Gold, D P; Andres, D; Etezadi, J; Arbuckle, T; Schwartzman, A; Chaikelson, J

    1995-06-01

    This study examined the effects of abilities as a young adult, an engaged lifestyle, personality, age, and health on continuity and change in intellectual abilities from early to late adulthood. A battery of measures, including a verbal and nonverbal intelligence test, was given to 326 Canadian army veterans. Archival data provided World War Two enlistment scores on the same intelligence test for this sample: Results indicated relative stability of intellectual scores across 40 years, with increases in vocabulary and decreases in arithmetic, verbal analogies, and nonverbal skills. Young adult intelligence was the most important determinant of older adult performance. Predictors for verbal intelligence were consistent with an engagement model of intellectual maintenance but also indicated the importance of introversion-extraversion and age. Nonverbal intelligence in late life was predicted by young adult nonverbal scores, age, health, and introversion-extraversion.

  5. Emotional intelligence model for directors of research centers in mexico

    Directory of Open Access Journals (Sweden)

    Mara Maricela Trujillo Flores

    2008-01-01

    H5 Social skills exhibited by directors, that are also part of interpersonal intelligence, allow a director to exert a greater influence on the working group, facilitating communication, conflict management, leadership, collaboration, cooperation and development of team skills.

  6. Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model

    National Research Council Canada - National Science Library

    Chen, Hui; Xiong, Shenghua; Ren, Xuan

    2014-01-01

    ... rate of return to simplify the complexity of this detection. In this paper, an artificial intelligence model was developed to identify adults at risk of metabolic syndrome based on physical signs...

  7. Design, modelling, implementation, and intelligent fuzzy control of a hovercraft

    Science.gov (United States)

    El-khatib, M. M.; Hussein, W. M.

    2011-05-01

    A Hovercraft is an amphibious vehicle that hovers just above the ground or water by air cushion. The concept of air cushion vehicle can be traced back to 1719. However, the practical form of hovercraft nowadays is traced back to 1955. The objective of the paper is to design, simulate and implement an autonomous model of a small hovercraft equipped with a mine detector that can travel over any terrains. A real time layered fuzzy navigator for a hovercraft in a dynamic environment is proposed. The system consists of a Takagi-Sugenotype fuzzy motion planner and a modified proportional navigation based fuzzy controller. The system philosophy is inspired by human routing when moving between obstacles based on visual information including the right and left views from which he makes his next step towards the goal in the free space. It intelligently combines two behaviours to cope with obstacle avoidance as well as approaching a goal using a proportional navigation path accounting for hovercraft kinematics. MATLAB/Simulink software tool is used to design and verify the proposed algorithm.

  8. Gray matter correlates of Trait and Ability models of emotional intelligence.

    Science.gov (United States)

    Killgore, William D S; Weber, Mareen; Schwab, Zachary J; Deldonno, Sophie R; Kipman, Maia; Weiner, Melissa R; Rauch, Scott L

    2012-06-20

    Research suggests that emotional intelligence capacities may be related to the functional integrity of the corticolimbic regions including the ventromedial prefrontal cortex, insula, and amygdala. No study has yet examined regional brain volumes in relation to the two dominant models of emotional intelligence: the Ability model, which posits a set of specific demonstrable capabilities for solving emotional problems, and the Trait model, which proposes a set of stable emotional competencies that can be assessed through subjectively rated self-report scales. In 36 healthy participants, we correlated scores on the Mayer-Salovey-Caruso Emotional Intelligence Test (an Ability measure) and the Bar-On Emotional Quotient Inventory (a Trait measure) with regional brain volumes using voxel-based morphometry. Total Mayer-Salovey-Caruso Emotional Intelligence Test scores were positively correlated with the left insula grey matter volume. The Strategic emotional intelligence subscale correlated positively with the left ventromedial prefrontal cortex and insular volume. In contrast, for the Bar-On Emotional Quotient Inventory, Stress Management scores correlated positively with the bilateral ventromedial prefrontal cortex volume. Amygdala volumes were unrelated to emotional intelligence measures. Findings support the role of the ventromedial prefrontal cortex and insula as key nodes in the emotional intelligence circuitry.

  9. Evolvable mathematical models: A new artificial Intelligence paradigm

    Science.gov (United States)

    Grouchy, Paul

    We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

  10. Bayesian Model Averaging of Artificial Intelligence Models for Hydraulic Conductivity Estimation

    Science.gov (United States)

    Nadiri, A.; Chitsazan, N.; Tsai, F. T.; Asghari Moghaddam, A.

    2012-12-01

    This research presents a Bayesian artificial intelligence model averaging (BAIMA) method that incorporates multiple artificial intelligence (AI) models to estimate hydraulic conductivity and evaluate estimation uncertainties. Uncertainty in the AI model outputs stems from error in model input as well as non-uniqueness in selecting different AI methods. Using one single AI model tends to bias the estimation and underestimate uncertainty. BAIMA employs Bayesian model averaging (BMA) technique to address the issue of using one single AI model for estimation. BAIMA estimates hydraulic conductivity by averaging the outputs of AI models according to their model weights. In this study, the model weights were determined using the Bayesian information criterion (BIC) that follows the parsimony principle. BAIMA calculates the within-model variances to account for uncertainty propagation from input data to AI model output. Between-model variances are evaluated to account for uncertainty due to model non-uniqueness. We employed Takagi-Sugeno fuzzy logic (TS-FL), artificial neural network (ANN) and neurofuzzy (NF) to estimate hydraulic conductivity for the Tasuj plain aquifer, Iran. BAIMA combined three AI models and produced better fitting than individual models. While NF was expected to be the best AI model owing to its utilization of both TS-FL and ANN models, the NF model is nearly discarded by the parsimony principle. The TS-FL model and the ANN model showed equal importance although their hydraulic conductivity estimates were quite different. This resulted in significant between-model variances that are normally ignored by using one AI model.

  11. Intelligent decision-making models for production and retail operations

    CERN Document Server

    Guo, Zhaoxia

    2016-01-01

    This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting.

  12. Intelligent open learning systems concepts, models and algorithms

    CERN Document Server

    Rózewski, Przemyslaw; Tadeusiewicz, Ryszard; Zaikin, Oleg

    2011-01-01

    In presented book the Intelligent Open Learning Systems (IOLS) are proposed, described, discussed, and evaluated. The IOLS is a system in which traditional methods of online teaching are enhanced through the use of artificial intelligence and cognitive science. This is the main topic of the book. It consists of ten chapters and is divided into three parts. The first part concentrates on the Open Learning System (OLS) analysis, in particular: the social and educational meanings of the OLS, the new role of the teacher and the new requirements regarding the structure of didactic material. Moreove

  13. System dynamics modeling of the impact of Internet-of-Things on intelligent urban transportation

    OpenAIRE

    Marshall, Phil

    2015-01-01

    Urban transportation systems are at the cusp of a major transformation that capitalizes on the proliferation of the Internet-of-Things (IoT), autonomous and cooperative vehicular and intelligent roadway technologies, advanced traffic management systems, and big data analytics. The benefits of these smart-transportation technologies were investigated using System Dynamics modeling, with particular emphasis towards vehicle sharing, intelligent highway systems, and smart-parking solutions. The m...

  14. Intelligent Model Management in a Forest Ecosystem Management Decision Support System

    Science.gov (United States)

    Donald Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mark Twery; H. Michael Rauscher; Peter Knopp; Scott Thomasma; Mayukh Dass; Hajime Uchiyama

    2002-01-01

    Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard...

  15. A Conversation Model Enabling Intelligent Agents to Give Emotional Support

    NARCIS (Netherlands)

    Van der Zwaan, J.M.; Dignum, V.; Jonker, C.M.

    2012-01-01

    In everyday life, people frequently talk to others to help them deal with negative emotions. To some extent, everybody is capable of comforting other people, but so far conversational agents are unable to deal with this type of situation. To provide intelligent agents with the capability to give emo

  16. A Conversation Model Enabling Intelligent Agents to Give Emotional Support

    NARCIS (Netherlands)

    Van der Zwaan, J.M.; Dignum, V.; Jonker, C.M.

    2012-01-01

    In everyday life, people frequently talk to others to help them deal with negative emotions. To some extent, everybody is capable of comforting other people, but so far conversational agents are unable to deal with this type of situation. To provide intelligent agents with the capability to give emo

  17. Emotional Intelligence Competencies and the Army Leadership Requirements Model

    Science.gov (United States)

    2015-06-12

    cultural stereotype in the military that suggests the display of emotions is less than desirable, however the ability for military leaders to regulate...2004) found that older participants rated higher in emotional intelligence competencies than younger participants. Additionally, women scored...behaviors, and actions make sound ethical decisions, avoid stereotypes , refrain from verbally lashing out, and never compromise their values. An

  18. The Cylindrical Structure of the Wechsler Intelligence Scale for Children--IV: A Retest of the Guttman Model of Intelligence

    Science.gov (United States)

    Cohen, Arie; Fiorello, Catherine A.; Farley, Frank H.

    2006-01-01

    A previous study on the underlying structure of the Wechsler intelligence test (WISC-R; [Wechsler, D. (1974). Manual WISC-R: Wechsler intelligence scale for children-Revised. New York: Psychological Corporation]), using smallest space analysis (SSA) [Guttman, L., and Levy, S. (1991). Two structural laws for intelligence tests.…

  19. The Cylindrical Structure of the Wechsler Intelligence Scale for Children--IV: A Retest of the Guttman Model of Intelligence

    Science.gov (United States)

    Cohen, Arie; Fiorello, Catherine A.; Farley, Frank H.

    2006-01-01

    A previous study on the underlying structure of the Wechsler intelligence test (WISC-R; [Wechsler, D. (1974). Manual WISC-R: Wechsler intelligence scale for children-Revised. New York: Psychological Corporation]), using smallest space analysis (SSA) [Guttman, L., and Levy, S. (1991). Two structural laws for intelligence tests.…

  20. Gratitude mediates the effect of emotional intelligence on subjective well-being: A structural equation modeling analysis.

    Science.gov (United States)

    Geng, Yuan

    2016-11-03

    This study investigated the relationship among emotional intelligence, gratitude, and subjective well-being in a sample of university students. A total of 365 undergraduates completed the emotional intelligence scale, the gratitude questionnaire, and the subjective well-being measures. The results of the structural equation model showed that emotional intelligence is positively associated with gratitude and subjective well-being, that gratitude is positively associated with subjective well-being, and that gratitude partially mediates the positive relationship between emotional intelligence and subjective well-being. Bootstrap test results also revealed that emotional intelligence has a significant indirect effect on subjective well-being through gratitude.

  1. Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

    Science.gov (United States)

    Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

    2014-12-01

    This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

  2. LINEAR LAYER AND GENERALIZED REGRESSION COMPUTATIONAL INTELLIGENCE MODELS FOR PREDICTING SHELF LIFE OF PROCESSED CHEESE

    Directory of Open Access Journals (Sweden)

    S. Goyal

    2012-03-01

    Full Text Available This paper highlights the significance of computational intelligence models for predicting shelf life of processed cheese stored at 7-8 g.C. Linear Layer and Generalized Regression models were developed with input parameters: Soluble nitrogen, pH, Standard plate count, Yeast & mould count, Spores, and sensory score as output parameter. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash - Sutcliffo Coefficient were used in order to compare the prediction ability of the models. The study revealed that Generalized Regression computational intelligence models are quite effective in predicting the shelf life of processed cheese stored at 7-8 g.C.

  3. Intelligent Hydraulic Actuator and Exp-based Modelling of Losses in Pumps and .

    DEFF Research Database (Denmark)

    Zhang, Muzhi

    A intelligent fuzzy logic self-organising PD+I controller for a gearrotor hydraulic motor was developed and evaluated. Furthermore, a experimental-based modelling methods with a new software tool 'Dynamodata' for modelling of losses in hydraulic motors and pumps was developed.......A intelligent fuzzy logic self-organising PD+I controller for a gearrotor hydraulic motor was developed and evaluated. Furthermore, a experimental-based modelling methods with a new software tool 'Dynamodata' for modelling of losses in hydraulic motors and pumps was developed....

  4. Optimal model of economic diplomacy of Republic of Croatia in the contexst of global intelligence revolution

    Directory of Open Access Journals (Sweden)

    Zdravko Bazdan

    2010-12-01

    Full Text Available The aim of this study is to point to the fact that economic diplomacy is a relatively new practice in international economics, specifically the expansion of the occurrence of Intelligence Revolution. The history in global relations shows that without economic diplomacy there is no optimal economic growth and social development. It is important to note that economic diplomacy should be important for our country and the political elite, as well as for the administration of Croatian economic subjects that want to compete in international market economy. Comparative analysis are particularly highlighted by French experience. Therefore, Croatia should copy the practice of those countries that are successful in economic diplomacy. And in the curricula - especially of our economic faculties - we should introduce the course of Economic Diplomacy. It is important to note, that in order to form our optimal model of economic diplomacy which would be headed by the President of Republic of Croatia formula should be based on: Intelligence Security Agency (SOA, Intelligence Service of the Ministry of Foreign Affairs and European Integration, Intelligence Service of the Croatian Chamber of Commerce and the Intelligence Service of the Ministry of Economy, Labor and Entrepreneurship. Described model would consist of intelligence subsystem with at least twelve components.

  5. An Evolutionary Model of Bounded Rationality and Intelligence

    OpenAIRE

    Brennan, Thomas J.; Lo, Andrew W.

    2012-01-01

    BACKGROUND: Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia-it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial cri...

  6. Industry Cluster's Adaptive Co-competition Behavior Modeling Inspired by Swarm Intelligence

    Science.gov (United States)

    Xiang, Wei; Ye, Feifan

    Adaptation helps the individual enterprise to adjust its behavior to uncertainties in environment and hence determines a healthy growth of both the individuals and the whole industry cluster as well. This paper is focused on the study on co-competition adaptation behavior of industry cluster, which is inspired by swarm intelligence mechanisms. By referencing to ant cooperative transportation and ant foraging behavior and their related swarm intelligence approaches, the cooperative adaptation and competitive adaptation behavior are studied and relevant models are proposed. Those adaptive co-competition behaviors model can be integrated to the multi-agent system of industry cluster to make the industry cluster model more realistic.

  7. An Intelligent Response Surface Methodology for Modeling of Domain Level Constraints

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    An effective modeling method of domain level constraints in the constraint network for concurrent engineering (CE) was developed. The domain level constraints were analyzed and the framework of modeling of domain level constraints based on simulation and approximate technology was given. An intelligent response surface methodology (IRSM) was proposed, in which artificial intelligence technologies are introduced into the optimization process. The design of crank and connecting rod in the V6 engine as example was given to show the validity of the modeling method.

  8. Joint intelligence operations centers (JIOC) business process model & capabilities evaluation methodology

    OpenAIRE

    Schacher, Gordon; Irvine, Nelson; Hoyt, Roger

    2012-01-01

    A JIOC Business Process Model has been developed for use in evaluating JIOC capabilities. The model is described and depicted through OV5 and organization swim-lane diagrams. Individual intelligence activities diagrams are included. A JIOC evaluation methodology is described.

  9. Effective Stress Management: A Model of Emotional Intelligence, Self-Leadership, and Student Stress Coping

    Science.gov (United States)

    Houghton, Jeffery D.; Wu, Jinpei; Godwin, Jeffrey L.; Neck, Christopher P.; Manz, Charles C.

    2012-01-01

    This article develops and presents a model of the relationships among emotional intelligence, self-leadership, and stress coping among management students. In short, the authors' model suggests that effective emotion regulation and self-leadership, as mediated through positive affect and self-efficacy, has the potential to facilitate stress coping…

  10. From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

    Science.gov (United States)

    Dimitrova, Vania; Brna, Paul

    2016-01-01

    STyLE-OLM (Dimitrova 2003 "International Journal of Artificial Intelligence in Education," 13, 35-78) presented a framework for interactive open learner modelling which entails the development of the means by which learners can "inspect," "discuss" and "alter" the learner model that has been jointly…

  11. Intelligent Hydraulic Actuator and Exp-based Modelling of Losses in Pumps and .

    DEFF Research Database (Denmark)

    Zhang, Muzhi

    A intelligent fuzzy logic self-organising PD+I controller for a gearrotor hydraulic motor was developed and evaluated. Furthermore, a experimental-based modelling methods with a new software tool 'Dynamodata' for modelling of losses in hydraulic motors and pumps was developed....

  12. Effective Stress Management: A Model of Emotional Intelligence, Self-Leadership, and Student Stress Coping

    Science.gov (United States)

    Houghton, Jeffery D.; Wu, Jinpei; Godwin, Jeffrey L.; Neck, Christopher P.; Manz, Charles C.

    2012-01-01

    This article develops and presents a model of the relationships among emotional intelligence, self-leadership, and stress coping among management students. In short, the authors' model suggests that effective emotion regulation and self-leadership, as mediated through positive affect and self-efficacy, has the potential to facilitate stress coping…

  13. A collision model for safety evaluation of autonomous intelligent cruise control.

    Science.gov (United States)

    Touran, A; Brackstone, M A; McDonald, M

    1999-09-01

    This paper describes a general framework for safety evaluation of autonomous intelligent cruise control in rear-end collisions. Using data and specifications from prototype devices, two collision models are developed. One model considers a train of four cars, one of which is equipped with autonomous intelligent cruise control. This model considers the car in front and two cars following the equipped car. In the second model, none of the cars is equipped with the device. Each model can predict the possibility of rear-end collision between cars under various conditions by calculating the remaining distance between cars after the front car brakes. Comparing the two collision models allows one to evaluate the effectiveness of autonomous intelligent cruise control in preventing collisions. The models are then subjected to Monte Carlo simulation to calculate the probability of collision. Based on crash probabilities, an expected value is calculated for the number of cars involved in any collision. It is found that given the model assumptions, while equipping a car with autonomous intelligent cruise control can significantly reduce the probability of the collision with the car ahead, it may adversely affect the situation for the following cars.

  14. A Multi-Scale Energy Demand Model suggests sharing Market Risks with Intelligent Energy Cooperatives

    NARCIS (Netherlands)

    Methenitis, G.; Kaisers, M.; La Poutré, J.A.

    2015-01-01

    In this paper, we propose a multi-scale model of energy demand that is consistent with observations at a macro scale, in our use-case standard load profiles for (residential) electric loads. We employ the model to study incentives to assume the risk of volatile market prices for intelligent energy c

  15. Artificial intelligence in process control: Knowledge base for the shuttle ECS model

    Science.gov (United States)

    Stiffler, A. Kent

    1989-01-01

    The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

  16. Using Game Theory Techniques and Concepts to Develop Proprietary Models for Use in Intelligent Games

    Science.gov (United States)

    Christopher, Timothy Van

    2011-01-01

    This work is about analyzing games as models of systems. The goal is to understand the techniques that have been used by game designers in the past, and to compare them to the study of mathematical game theory. Through the study of a system or concept a model often emerges that can effectively educate students about making intelligent decisions…

  17. An Intelligent Tutoring System for Learning Chinese with a Cognitive Model of the Learner

    Science.gov (United States)

    Kosek, Michal; Lison, Pierre

    2014-01-01

    We present an intelligent tutoring system that lets students of Chinese learn words and grammatical constructions. It relies on a Bayesian, linguistically motivated cognitive model that represents the learner's knowledge. This model is dynamically updated given observations about the learner's behaviour in the exercises, and employed at runtime to…

  18. 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...

  19. Application of an extended equalization-cancellation model to speech intelligibility with spatially distributed maskers.

    Science.gov (United States)

    Wan, Rui; Durlach, Nathaniel I; Colburn, H Steven

    2010-12-01

    An extended version of the equalization-cancellation (EC) model of binaural processing is described and applied to speech intelligibility tasks in the presence of multiple maskers. The model incorporates time-varying jitters, both in time and amplitude, and implements the equalization and cancellation operations in each frequency band independently. The model is consistent with the original EC model in predicting tone-detection performance for a large set of configurations. When the model is applied to speech, the speech intelligibility index is used to predict speech intelligibility performance in a variety of conditions. Specific conditions addressed include different types of maskers, different numbers of maskers, and different spatial locations of maskers. Model predictions are compared with empirical measurements reported by Hawley et al. [J. Acoust. Soc. Am. 115, 833-843 (2004)] and by Marrone et al. [J. Acoust. Soc. Am. 124, 1146-1158 (2008)]. The model succeeds in predicting speech intelligibility performance when maskers are speech-shaped noise or broadband-modulated speech-shaped noise but fails when the maskers are speech or reversed speech.

  20. Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

    Science.gov (United States)

    Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

    Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

  1. Traffic Route Modelling and Assignment with Intelligent Transport System

    Directory of Open Access Journals (Sweden)

    Kunicina Nadezhda

    2014-12-01

    Full Text Available The development of signal transmitting environment for multimodal traffic control will enhance the integration of emergency and specialized transport routing tools in usual traffic control paradigms - it is one of the opportunities offered by modern intelligent traffic control systems. The improvement of effective electric power use in public transport system is an advantage of Intelligent Transport System (ITS. The research is connected with the improvement of on-line traffic control and adaptation of special traffic lighting alternatives by ITS. The assignment of the nearest appropriate transport will be done by passenger request, but unlike information system, the transport planning is done on demand. The task can be solved with the help of modern technical methods and equipment, as well as by applying control paradigms of the distributed systems. The problem is solved with the help of calculations hyper-graph and scheduling theory. The goal of the research is to develop methods, which support scheduling of the emergency transport, using high performance computing.

  2. Means-End based Functional Modeling for Intelligent Control: Modeling and Experiments with an Industrial Heat Pump System

    DEFF Research Database (Denmark)

    Saleem, Arshad

    2007-01-01

    The purpose of this paper is to present a Multilevel Flow Model (MFM) of an industrial heat pump system and its use for diagnostic reasoning. MFM is functional modeling language supporting an explicit means-ends intelligent control strategy for large industrial process plants. The model is used...

  3. Means-End based Functional Modeling for Intelligent Control: Modeling and Experiments with an Industrial Heat Pump System

    DEFF Research Database (Denmark)

    Saleem, Arshad

    2007-01-01

    The purpose of this paper is to present a Multilevel Flow Model (MFM) of an industrial heat pump system and its use for diagnostic reasoning. MFM is functional modeling language supporting an explicit means-ends intelligent control strategy for large industrial process plants. The model is used...

  4. Fractional snow cover mapping from MODIS data using wavelet-artificial intelligence hybrid models

    Science.gov (United States)

    Moosavi, Vahid; Malekinezhad, Hossein; Shirmohammadi, Bagher

    2014-04-01

    This study was carried out to evaluate the wavelet-artificial intelligence hybrid models to produce fractional snow cover maps. At first, cloud cover was removed from MODIS data and cloud free images were produced. SVM-based binary classified ETM+ imagery were then used as reference maps in order to obtain train and test data for sub-pixel classification models. ANN and ANFIS-based modeling were performed using raw data (without wavelet-based preprocessing). In the next step, several mother wavelets and levels were used in order to decompose the original data to obtain wavelet coefficients. Then, the decomposed data were used for further modeling processes. ANN, ANFIS, wavelet-ANN and wavelet-ANFIS models were compared to evaluate the effect of wavelet transformation on the ability of artificial intelligence models. It was demonstrated that wavelet transformation as a preprocessing approach can significantly enhance the performance of ANN and ANFIS models. This study indicated an overall accuracy of 92.45% for wavelet-ANFIS model, 86.13% for wavelet-ANN, 72.23% for ANFIS model and 66.78% for ANN model. In fact, hybrid wavelet-artificial intelligence models can extract the characteristics of the original signals (i.e. model inputs) accurately through decomposing the non-stationary and complex signals into several stationary and simpler signals. The positive effect of fuzzification as well as wavelet transformation in the wavelet-ANFIS model was also confirmed.

  5. A Model of Intelligent Fault Diagnosis of Power Equipment Based on CBR

    Directory of Open Access Journals (Sweden)

    Gang Ma

    2015-01-01

    Full Text Available Nowadays the demand of power supply reliability has been strongly increased as the development within power industry grows rapidly. Nevertheless such large demand requires substantial power grid to sustain. Therefore power equipment’s running and testing data which contains vast information underpins online monitoring and fault diagnosis to finally achieve state maintenance. In this paper, an intelligent fault diagnosis model for power equipment based on case-based reasoning (IFDCBR will be proposed. The model intends to discover the potential rules of equipment fault by data mining. The intelligent model constructs a condition case base of equipment by analyzing the following four categories of data: online recording data, history data, basic test data, and environmental data. SVM regression analysis was also applied in mining the case base so as to further establish the equipment condition fingerprint. The running data of equipment can be diagnosed by such condition fingerprint to detect whether there is a fault or not. Finally, this paper verifies the intelligent model and three-ratio method based on a set of practical data. The resulting research demonstrates that this intelligent model is more effective and accurate in fault diagnosis.

  6. Comparing Models of Intelligence in Project TALENT: The VPR Model Fits Better than the CHC and Extended Gf-Gc Models

    Science.gov (United States)

    Major, Jason T.; Johnson, Wendy; Deary, Ian J.

    2012-01-01

    Three prominent theories of intelligence, the Cattell-Horn-Carroll (CHC), extended fluid-crystallized (Gf-Gc) and verbal-perceptual-image rotation (VPR) theories, provide differing descriptions of the structure of intelligence (McGrew, 2009; Horn & Blankson, 2005; Johnson & Bouchard, 2005b). To compare these theories, models representing them were…

  7. Artificial intelligence and exponential technologies business models evolution and new investment opportunities

    CERN Document Server

    Corea, Francesco

    2017-01-01

    Artificial Intelligence is a huge breakthrough technology that is changing our world. It requires some degrees of technical skills to be developed and understood, so in this book we are going to first of all define AI and categorize it with a non-technical language. We will explain how we reached this phase and what historically happened to artificial intelligence in the last century. Recent advancements in machine learning, neuroscience, and artificial intelligence technology will be addressed, and new business models introduced for and by artificial intelligence research will be analyzed. Finally, we will describe the investment landscape, through the quite comprehensive study of almost 14,000 AI companies and we will discuss important features and characteristics of both AI investors as well as investments. This is the “Internet of Thinks” era. AI is revolutionizing the world we live in. It is augmenting the human experiences, and it targets to amplify human intelligence in a future not so distant from...

  8. Business intelligence tools for radiology: creating a prototype model using open-source tools.

    Science.gov (United States)

    Prevedello, Luciano M; Andriole, Katherine P; Hanson, Richard; Kelly, Pauline; Khorasani, Ramin

    2010-04-01

    Digital radiology departments could benefit from the ability to integrate and visualize data (e.g. information reflecting complex workflow states) from all of their imaging and information management systems in one composite presentation view. Leveraging data warehousing tools developed in the business world may be one way to achieve this capability. In total, the concept of managing the information available in this data repository is known as Business Intelligence or BI. This paper describes the concepts used in Business Intelligence, their importance to modern Radiology, and the steps used in the creation of a prototype model of a data warehouse for BI using open-source tools.

  9. Enhacing CRM Business Intelligence Applications by Web User Experience Model

    Directory of Open Access Journals (Sweden)

    Natheer K. Gharaibeh

    2015-07-01

    Full Text Available several trends are emerging in the field of CRM technology which promises a brighter future of more profitable customers and decreasing costs. One of the most critical trends is enhancing Business Intelligence applications using Web Technologies, Web technologies can improve the CRM BI implementation, but it still need evaluation, The Web has focused the attention of organizations towards the User Experience and the need to learn about their customer, The UX paradigm calls for enhancing CRMBI by Web technologies. This paper deals with this issue and provide a framework for building Web based CRMBI depending on the Process mapping between CRMBI and UX. It provides a conceptual overview of CRM and its relationship to the main disciplines BI, UX and Web.

  10. Modeling collective & intelligent decision making of multi-cellular populations.

    Science.gov (United States)

    Shin, Yong-Jun; Mahrou, Bahareh

    2014-01-01

    In the presence of unpredictable disturbances and uncertainties, cells intelligently achieve their goals by sharing information via cell-cell communication and making collective decisions, which are more reliable compared to individual decisions. Inspired by adaptive sensor network algorithms studied in communication engineering, we propose that a multi-cellular adaptive network can convert unreliable decisions by individual cells into a more reliable cell-population decision. It is demonstrated using the effector T helper (a type of immune cell) population, which plays a critical role in initiating immune reactions in response to invading foreign agents (e.g., viruses, bacteria, etc.). While each individual cell follows a simple adaptation rule, it is the combined coordination among multiple cells that leads to the manifestation of "self-organizing" decision making via cell-cell communication.

  11. The Relations between Implicit Intelligence Beliefs, Autonomous Academic Motivation, and School Persistence Intentions: A Mediation Model

    Science.gov (United States)

    Renaud-Dubé, Andréanne; Guay, Frédéric; Talbot, Denis; Taylor, Geneviève; Koestner, Richard

    2015-01-01

    This study attempts to test a model in which the relation between implicit theories of intelligence and students' school persistence intentions are mediated by intrinsic, identified, introjected, and external regulations. Six hundred and fifty students from a high school were surveyed. Contrary to expectations, results from ESEM analyses indicated…

  12. Intelligent wireless forensic model (IWFM) for moving devices between wireless networks

    CSIR Research Space (South Africa)

    Ngobeni, SJ

    2008-09-01

    Full Text Available for prosecution of the wireless perpetrators. The essence of this study is to develop an Intelligent Wireless Forensic Model (IWFM) for acquiring data for forensic purposes in the event that a device has moved from one wireless network to another...

  13. Teaching Mathematics with Intelligent Support in Natural Language. Tertiary Education Students Working with Parametrized Modelling Activities

    Science.gov (United States)

    Rojano, Teresa; García-Campos, Montserrat

    2017-01-01

    This article reports the outcomes of a study that seeks to investigate the role of feedback, by way of an intelligent support system in natural language, in parametrized modelling activities carried out by a group of tertiary education students. With such a system, it is possible to simultaneously display on a computer screen a dialogue window and…

  14. A New Lease of Life for Thomson's Bonds Model of Intelligence

    Science.gov (United States)

    Bartholomew, David J.; Deary, Ian J.; Lawn, Martin

    2009-01-01

    Modern factor analysis is the outgrowth of Spearman's original "2-factor" model of intelligence, according to which a mental test score is regarded as the sum of a general factor and a specific factor. As early as 1914, Godfrey Thomson realized that the data did not require this interpretation and he demonstrated this by proposing what became…

  15. The Relations between Implicit Intelligence Beliefs, Autonomous Academic Motivation, and School Persistence Intentions: A Mediation Model

    Science.gov (United States)

    Renaud-Dubé, Andréanne; Guay, Frédéric; Talbot, Denis; Taylor, Geneviève; Koestner, Richard

    2015-01-01

    This study attempts to test a model in which the relation between implicit theories of intelligence and students' school persistence intentions are mediated by intrinsic, identified, introjected, and external regulations. Six hundred and fifty students from a high school were surveyed. Contrary to expectations, results from ESEM analyses indicated…

  16. INTELLIGENT CAR STYLING TECHNIQUE AND SYSTEM BASED ON A NEW AERODYNAMIC-THEORETICAL MODEL

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Car styling technique based on a new theoretical model of automotive aerodynamics is introduced, which is proved to be feasible and effective by wind tunnel tests. Development of a multi-module software system from this technique, including modules of knowledge processing, referential styling and ANN aesthetic evaluation etc, capable of assisting car styling works in an intelligent way, is also presented and discussed.

  17. Emotional Intelligence and Negative Feelings: A Gender Specific Moderated Mediation Model

    Science.gov (United States)

    Karakus, Mehmet

    2013-01-01

    This study aims to clarify the effect of emotional intelligence (EI) on negative feelings (stress, anxiety, burnout and depression) in a gender specific model. Four hundred and twenty-five primary school teachers (326 males, 99 females) completed the measures of EI, stress, anxiety, burnout and depression. The multi-group analysis was performed…

  18. Modeling speech intelligibility in quiet and noise in listeners with normal and impaired hearing

    NARCIS (Netherlands)

    K.S. Rhebergen; J. Lyzenga; W.A. Dreschler; J.M. Festen

    2010-01-01

    The speech intelligibility index (SII) is an often used calculation method for estimating the proportion of audible speech in noise. For speech reception thresholds (SRTs), measured in normally hearing listeners using various types of stationary noise, this model predicts a fairly constant speech pr

  19. Artificial intelligence and finite element modelling for monitoring flood defence structures

    NARCIS (Netherlands)

    Pyayt, A.L.; Mokhov, I.I.; Kozionov, A.; Kusherbaeva, V.; Melnikova, N.B.; Krzhizhanovskaya, V.V.; Meijer, R.J.

    2011-01-01

    We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the Urba

  20. The Bar-On model of emotional-social intelligence (ESI).

    Science.gov (United States)

    Bar-On, Reuven

    2006-01-01

    The present manuscript is an empirically based theoretical paper that presents, describes, and examines the Bar-On Model of Emotional-Social Intelligence (ESI) in deep. First, a description of the Emotional Quotient Inventory (the EQ-i), which has played an instrumental role in developing the model, is given. The EQ-i is a self-report measure of emotionally and socially intelligent behaviour. It has been translated into more than 30 languages, and data have been collected around the world. The impact of age, gender, and ethnicity on the Bar-On model is presented. A description of the model's construct and predictive validity is given. Finally, the author summarizes the key points, discusses the limitations of the model, and raises the ideas for developing a future model of ESI.

  1. Intelligent sensor-model automated control of PMR-15 autoclave processing

    Science.gov (United States)

    Hart, S.; Kranbuehl, D.; Loos, A.; Hinds, B.; Koury, J.

    1992-01-01

    An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

  2. Intelligent sensor-model automated control of PMR-15 autoclave processing

    Science.gov (United States)

    Hart, S.; Kranbuehl, D.; Loos, A.; Hinds, B.; Koury, J.

    1992-01-01

    An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

  3. Comparing the Construct and Criterion-Related Validity of Ability-Based and Mixed-Model Measures of Emotional Intelligence

    Science.gov (United States)

    Livingstone, Holly A.; Day, Arla L.

    2005-01-01

    Despite the popularity of the concept of emotional intelligence(EI), there is much controversy around its definition, measurement, and validity. Therefore, the authors examined the construct and criterion-related validity of an ability-based EI measure (Mayer Salovey Caruso Emotional Intelligence Test [MSCEIT]) and a mixed-model EI measure…

  4. An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

    Science.gov (United States)

    Ranganayaki, V; Deepa, S N

    2016-01-01

    Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature.

  5. Hammerstein Model Based RLS Algorithm for Modeling the Intelligent Pneumatic Actuator (IPA System

    Directory of Open Access Journals (Sweden)

    Siti Fatimah Sulaiman

    2017-08-01

    Full Text Available An Intelligent Pneumatic Actuator (IPA system is considered highly nonlinear and subject to nonlinearities which make the precise position control of this actuator is difficult to achieve. Thus, it is appropriate to model the system using nonlinear approach because the linear model sometimes not sufficient enough to represent the nonlinearity of the system in the real process. This study presents a new modeling of an IPA system using Hammerstein model based Recursive Least Square (RLS algorithm. The Hammerstein model is one of the blocks structured nonlinear models often used to model a nonlinear system and it consists of a static nonlinear block followed by a linear block of dynamic element. In this study, the static nonlinear block was represented by a deadzone of the pneumatic valve, while the linear block was represented by a dynamic element of IPA system. A RLS has been employed as the main algorithm in order to estimate the parameters of the Hammerstein model. The validity of the proposed model has been verified by conducting a real-time experiment. All of the criteria as outlined in the system identification’s procedures were successfully complied by the proposed Hammerstein model as it managed to provide a stable system, higher best fit, lower loss function and lower final prediction error than a linear model developed before. The performance of the proposed Hammerstein model in controlling the IPA’s positioning system is also considered good. Thus, this new developed Hammerstein model is sufficient enough to represents the IPA system utilized in this study.

  6. Enhanced Intelligent Driver Model to Access the Impact of Driving Strategies on Traffic Capacity

    CERN Document Server

    Kesting, Arne; Helbing, Dirk

    2009-01-01

    With an increasing number of vehicles equipped with adaptive cruise control (ACC), the impact of such vehicles on the collective dynamics of traffic flow becomes relevant. By means of simulation, we investigate the influence of variable percentages of ACC vehicles on traffic flow characteristics. For simulating the ACC vehicles, we propose a new car-following model that also serves as basis of an ACC implementation in real cars. The model is based on the Intelligent Driver Model [Treiber et al., Physical Review E 62, 1805 (2000)] and inherits its intuitive behavioural parameters: desired velocity, acceleration, comfortable deceleration, and desired minimum time headway. It eliminates, however, the sometimes unrealistic behaviour of the Intelligent Driver Model in cut-in situations with ensuing small gaps that regularly are caused by lane changes of other vehicles in dense or congested traffic. We simulate the influence of different ACC strategies on the maximum capacity before breakdown, and the (dynamic) bot...

  7. Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

    Institute of Scientific and Technical Information of China (English)

    WANG Ya-lin; MA Jie; GUI Wei-hua; YANG Chun-hua; ZHANG Chuan-fu

    2006-01-01

    A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0 %, which effectively stabilizes the agglomerate compositions and the permeability.

  8. 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...to utilize computational models of the auditory periphery and auditory cortex to study the effect of low spontaneous rate ANF loss on the cortical...clinical hearing thresholds is difficulty in understanding speech in noise. Recent animal studies have shown that noise exposure causes selective loss

  9. A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments

    Directory of Open Access Journals (Sweden)

    Jing Mi

    2016-09-01

    Full Text Available Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model.

  10. A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments.

    Science.gov (United States)

    Mi, Jing; Colburn, H Steven

    2016-10-03

    Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model.

  11. A framework for structural modelling of an RFID-enabled intelligent distributed manufacturing control system

    Directory of Open Access Journals (Sweden)

    Barenji, Ali Vatankhah

    2014-08-01

    Full Text Available A modern manufacturing facility typically contains several distributed control systems, such as machining stations, assembly stations, and material handling and storage systems. Integrating Radio Frequency Identification (RFID technology into these control systems provides a basis for monitoring and configuring their components in real-time. With the right structural modelling, it is then possible to evaluate designs and translate them into new operational applications almost immediately. This paper proposes an architecture for the structural modelling of an intelligent distributed control system for a manufacturing facility, by utilising RFID technology. Emphasis is placed on a requirements analysis of the manufacturing system, the design of RFID-enabled intelligent distributed control systems using Unified Modelling Language (UML diagrams, and the use of efficient algorithms and tools for the implementation of these systems.

  12. 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...

  13. Modeling speech intelligibility based on the signal-to-noise envelope power ratio

    DEFF Research Database (Denmark)

    Jørgensen, Søren

    through three commercially available mobile phones. The model successfully accounts for the performance across the phones in conditions with a stationary speech-shaped background noise, whereas deviations were observed in conditions with “Traffic” and “Pub” noise. Overall, the results of this thesis......The intelligibility of speech depends on factors related to the auditory processes involved in sound perception as well as on the acoustic properties of the sound entering the ear. However, a clear understanding of speech perception in complex acoustic conditions and, in particular, a quantitative...... description of the involved auditory processes provides a major challenge in speech and hearing research. This thesis presents a computational model that attempts to predict the speech intelligibility obtained by normal-hearing listeners in various adverse conditions. The model combines the concept...

  14. A multi-resolution envelope-power based model for speech intelligibility.

    Science.gov (United States)

    Jørgensen, Søren; Ewert, Stephan D; Dau, Torsten

    2013-07-01

    The speech-based envelope power spectrum model (sEPSM) presented by Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] estimates the envelope power signal-to-noise ratio (SNRenv) after modulation-frequency selective processing. Changes in this metric were shown to account well for changes of speech intelligibility for normal-hearing listeners in conditions with additive stationary noise, reverberation, and nonlinear processing with spectral subtraction. In the latter condition, the standardized speech transmission index [(2003). IEC 60268-16] fails. However, the sEPSM is limited to conditions with stationary interferers, due to the long-term integration of the envelope power, and cannot account for increased intelligibility typically obtained with fluctuating maskers. Here, a multi-resolution version of the sEPSM is presented where the SNRenv is estimated in temporal segments with a modulation-filter dependent duration. The multi-resolution sEPSM is demonstrated to account for intelligibility obtained in conditions with stationary and fluctuating interferers, and noisy speech distorted by reverberation or spectral subtraction. The results support the hypothesis that the SNRenv is a powerful objective metric for speech intelligibility prediction.

  15. Intelligent control using multiple models based on on-line learning

    Institute of Scientific and Technical Information of China (English)

    Junyong ZHAI; Shumin FEI; Feipeng DA

    2006-01-01

    In this paper we deal with the problem of plants with large parameter variations under different operating modes. A novel intelligent control algorithm based on multiple models is proposed to improve the dynamical response performance. At the same time adaptive model bank is applied to establish models without prior system information.Multiple models and corresponding controllers are automatically established on-line by a conventionally adaptive model and a re-initialized one. A best controller is chosen by the performance function at every instant. The closed-loop system's stability and asymptotical convergence of tracking error can be guaranteed. Simulation results have confirmed the validity of the proposed method.

  16. Leader emotional intelligence, transformational leadership, trust and team commitment: Testing a model within a team context

    Directory of Open Access Journals (Sweden)

    Anton F. Schlechter

    2008-09-01

    Full Text Available This exploratory study tested a model within a team context consisting of transformational-leadership behaviour, team-leader emotional intelligence, trust (both in the team leader and in the team members and team commitment. It was conducted within six manufacturing plants, with 25 teams participating. Of the 320 surveys distributed to these teams, 178 were received (which equals a 56% response rate. The surveys consisted of the multi-factor leadership questionnaire (MLQ, the Swinburne University emotional intelligence test (SUEIT, the organisational-commitment scale (OCS (adapted for team commitment and the workplace trust survey (WTS. The validity of these scales was established using exploratory factor analysis (EFA and confrmatory factor analysis (CFA. The Cronbach alpha was used to assess the reliability of the scales. The model was tested using structural equation modelling (SEM; an acceptable level of model ft was found. Signifcant positive relationships were further found among all the constructs. Such an integrated model has not been tested in a team context before and the positive fndings therefore add to existing teamwork literature. The fnding that transformational leadership and leader emotional intelligence are positively related to team commitment and trust further emphasises the importance of effective leadership behaviour in team dynamics and performance.

  17. Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2014-01-01

    Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

  18. A Model for Organizational Intelligence in Islamic Azad University (Zone 8

    Directory of Open Access Journals (Sweden)

    Masoumeh Erfani Khanghahi

    2013-08-01

    Full Text Available Today organizations are faced with the rapidly changeable events in economical, technological, social, cultural and political environment. Successful and dynamic reaction of organizations depends on their ability to provide relevant information and to find, at the same time, adequate solutions to the problems they are faced with. In that sense, the attention of organizational theoreticians is focused on designing of intellectual abilities of organization and new concept in organizational theory has developed organizational intelligence (OI. In two decades ago, theoretical models have been developed and little research has been conducted. Having a model for defining and assessing the organizational status of an organization can be very helpful but the key questions facing every manager are; how can the level of collective intelligence be promoted? And what factors influence OI? Therefore this research carried out in order to assess OI and its factors influencing I.A.U. and provide a structural equation model. The subject of the study was 311 faculty members of I.A.U (Zone 8. Faculty members completed OI questionnaire (Cronbach's alpha=0.98, learning climate (Cronbach's alpha=0.94, multifactor leadership questionnaire (Cronbach's alpha =0.92 and organizational learning audit (Cronbach's alpha =0.94. Findings of this research showed that mean of organizational intelligence, organizational learning and learning culture were less than mean and transformational leadership was more than mean of questionnaire. Lisrel project software was applied for confirmatory factor analysis (CFA and structural equation modeling (SEM. Based on the tested structural equation model, transformational leadership style had direct impact on learning culture $(eta=0.78$, learning culture had a direct impact on OI $(eta=0.46$, organizational learning had a direct impact on OI $(eta=0.34$ and learning culture had a direct impact on organizational learning $(eta=0.96$. The

  19. Operator function modeling: Cognitive task analysis, modeling and intelligent aiding in supervisory control systems

    Science.gov (United States)

    Mitchell, Christine M.

    1990-01-01

    The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.

  20. Artificial Intelligence for Constructing Accurate, Low-Cost Models and

    Science.gov (United States)

    2005-01-01

    0.5 1 1.5 2 2.5 -12 -7 -2 3 8 13 AOA C l Equation Model Human Predicition Machine Learning Test Data Figure C-14 NACA 4421 Model Comparison...Natrajan, Anand, and Srinivasan, Sudhir, (1997) “Consistency Maintenance in Multiresolution Simulation”, ACM Transactions on Modeling and

  1. Cognitive-Operative Model of Intelligent Learning Systems Behavior

    Science.gov (United States)

    Laureano-Cruces, Ana Lilia; Ramirez-Rodriguez, Javier; Mora-Torres, Martha; de Arriaga, Fernando; Escarela-Perez, Rafael

    2010-01-01

    In this paper behavior during the teaching-learning process is modeled by means of a fuzzy cognitive map. The elements used to model such behavior are part of a generic didactic model, which emphasizes the use of cognitive and operative strategies as part of the student-tutor interaction. Examples of possible initial scenarios for the…

  2. Cognitive-Operative Model of Intelligent Learning Systems Behavior

    Science.gov (United States)

    Laureano-Cruces, Ana Lilia; Ramirez-Rodriguez, Javier; Mora-Torres, Martha; de Arriaga, Fernando; Escarela-Perez, Rafael

    2010-01-01

    In this paper behavior during the teaching-learning process is modeled by means of a fuzzy cognitive map. The elements used to model such behavior are part of a generic didactic model, which emphasizes the use of cognitive and operative strategies as part of the student-tutor interaction. Examples of possible initial scenarios for the…

  3. Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents

    Directory of Open Access Journals (Sweden)

    Eric Aaron

    2016-11-01

    Full Text Available Intelligent embodied robots are integrated systems: As they move continuously through their environments, executing behaviors and carrying out tasks, components for low-level and high-level intelligence are integrated in the robot's cognitive system, and cognitive and physical processes combine to create their behavior. For a modeling framework to enable the design and analysis of such integrated intelligence, the underlying representations in the design of the robot should be dynamically sensitive, capable of reflecting both continuous motion and micro-cognitive influences, while also directly representing the necessary beliefs and intentions for goal-directed behavior. In this paper, a dynamical intention-based modeling framework is presented that satisfies these criteria, along with a hybrid dynamical cognitive agent (HDCA framework for employing dynamical intentions in embodied agents. This dynamical intention-HDCA (DI-HDCA modeling framework is a fusion of concepts from spreading activation networks, hybrid dynamical system models, and the BDI (belief-desire-intention theory of goal-directed reasoning, adapted and employed unconventionally to meet entailments of environment and embodiment. The paper presents two kinds of autonomous agent learning results that demonstrate dynamical intentions and the multi-faceted integration they enable in embodied robots: with a simulated service robot in a grid-world office environment, reactive-level learning minimizes reliance on deliberative-level intelligence, enabling task sequencing and action selection to be distributed over both deliberative and reactive levels; and with a simulated game of Tag, the cognitive-physical integration of an autonomous agent enables the straightforward learning of a user-specified strategy during gameplay, without interruption to the game. In addition, the paper argues that dynamical intentions are consistent with cognitive theory underlying goal-directed behavior, and

  4. 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.

  5. Modeling the effects of a single reflection on binaural speech intelligibility.

    Science.gov (United States)

    Rennies, Jan; Warzybok, Anna; Brand, Thomas; Kollmeier, Birger

    2014-03-01

    Recently the influence of delay and azimuth of a single speech reflection on speech reception thresholds (SRTs) was systematically investigated using frontal, diffuse, and lateral noise [Warzybok et al. (2013). J. Acoust. Soc. Am. 133, 269-282]. The experiments showed that the benefit of an early reflection was independent of its azimuth and mostly independent of noise type, but that the detrimental effect of a late reflection depended on its direction relative to the noise. This study tests if different extensions of a binaural speech intelligibility model can predict these data. The extensions differ in the order in which binaural processing and temporal integration of early reflections take place. Models employing a correction for the detrimental effects of reverberation on speech intelligibility after performing the binaural processing predict SRTs in symmetric masking conditions (frontal, diffuse), but cannot predict the measured interaction of temporal and spatial integration. In contrast, a model extension accounting for the distinction between useful and detrimental reflections before the binaural processing stage predicts the data with an overall R(2) of 0.95. This indicates that any model framework predicting speech intelligibility in rooms should incorporate an interaction between binaural and temporal integration of reflections at a comparatively early stage.

  6. The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model.

    Science.gov (United States)

    Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei

    2017-06-01

    We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers.

  7. 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.

  8. Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model

    Directory of Open Access Journals (Sweden)

    Hui Chen

    2014-01-01

    Full Text Available Metabolic syndrome is worldwide public health problem and is a serious threat to people's health and lives. Understanding the relationship between metabolic syndrome and the physical symptoms is a difficult and challenging task, and few studies have been performed in this field. It is important to classify adults who are at high risk of metabolic syndrome without having to use a biochemical index and, likewise, it is important to develop technology that has a high economic rate of return to simplify the complexity of this detection. In this paper, an artificial intelligence model was developed to identify adults at risk of metabolic syndrome based on physical signs; this artificial intelligence model achieved more powerful capacity for classification compared to the PCLR (principal component logistic regression model. A case study was performed based on the physical signs data, without using a biochemical index, that was collected from the staff of Lanzhou Grid Company in Gansu province of China. The results show that the developed artificial intelligence model is an effective classification system for identifying individuals at high risk of metabolic syndrome.

  9. An Intelligent System for Modelling, Design and Analysis of Chemical Processes

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    ICAS, Integrated Computer Aided System, is a software that consists of a number of intelligent tools, which are very suitable, among others, for computer aided modelling, sustainable design of chemical and biochemical processes, and design-analysis of product-process monitoring systems. Each...... of these tools are characterized by a framework that follows an established work-flow and data-flow, developed to guide the user through the many steps of the problem solution process. At each, the specific tool knows which data, model and/or algorithm to use. The tool also provides analysis of the calculated...... results so that the user can make intelligent decisions to proceed to the next step. The tools contain in-house databases, especially designed to work in an integrated manner with tool specific ontology for efficient knowledge management. Examples highlighting the use of the tools willl be given, where...

  10. A scaleable architecture for the modeling and simulation of intelligent transportation systems.

    Energy Technology Data Exchange (ETDEWEB)

    Ewing, T.; Tentner, A.

    1999-03-17

    A distributed, scaleable architecture for the modeling and simulation of Intelligent Transportation Systems on a network of workstations or a parallel computer has been developed at Argonne National Laboratory. The resulting capability provides a modular framework supporting plug-in models, hardware, and live data sources; visually realistic graphics displays to support training and human factors studies; and a set of basic ITS models. The models and capabilities are described, along with atypical scenario involving dynamic rerouting of smart vehicles which send probe reports to and receive traffic advisories from a traffic management center capable of incident detection.

  11. SmartWeld/SmartProcess - intelligent model based system for the design and validation of welding processes

    Energy Technology Data Exchange (ETDEWEB)

    Mitchner, J.

    1996-04-01

    Diagrams are presented on an intelligent model based system for the design and validation of welding processes. Key capabilities identified include `right the first time` manufacturing, continuous improvement, and on-line quality assurance.

  12. 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...

  13. Modeling and Simulation of a DG-Integrated Intelligent Microgrid

    Science.gov (United States)

    2010-02-01

    Power is produced by passing of ions formed at one end to the other end of electrodes . Mathematical and dynamic models of fuel cells were...showed fuel cell dynamics as well as its power generation. A mathematical model of PEM fuel cells was presented by [29], which also considered the...dynamic response of the fuel cells in terms of their transient and thermal properties. A mathematical model of PEM fuel cells, together with their

  14. Artificial intelligence techniques for modeling database user behavior

    Science.gov (United States)

    Tanner, Steve; Graves, Sara J.

    1990-01-01

    The design and development of the adaptive modeling system is described. This system models how a user accesses a relational database management system in order to improve its performance by discovering use access patterns. In the current system, these patterns are used to improve the user interface and may be used to speed data retrieval, support query optimization and support a more flexible data representation. The system models both syntactic and semantic information about the user's access and employs both procedural and rule-based logic to manipulate the model.

  15. Hybrid Computation Model for Intelligent System Design by Synergism of Modified EFC with Neural Network

    OpenAIRE

    2015-01-01

    In recent past, it has been seen in many applications that synergism of computational intelligence techniques outperforms over an individual technique. This paper proposes a new hybrid computation model which is a novel synergism of modified evolutionary fuzzy clustering with associated neural networks. It consists of two modules: fuzzy distribution and neural classifier. In first module, mean patterns are distributed into the number of clusters based on the modified evolutionary fuzzy cluste...

  16. Leader emotional intelligence, transformational leadership, trust and team commitment: Testing a model within a team context

    OpenAIRE

    Anton F. Schlechter; Jacoba J. Strauss

    2008-01-01

    This exploratory study tested a model within a team context consisting of transformational-leadership behaviour, team-leader emotional intelligence, trust (both in the team leader and in the team members) and team commitment. It was conducted within six manufacturing plants, with 25 teams participating. Of the 320 surveys distributed to these teams, 178 were received (which equals a 56% response rate). The surveys consisted of the multi-factor leadership questionnaire (MLQ), the Swinburne Uni...

  17. A Heat Dynamic Model for Intelligent Heating of Buildings

    DEFF Research Database (Denmark)

    Thavlov, Anders; Bindner, Henrik W.

    2015-01-01

    This article presents a heat dynamic model for prediction of the indoor temperature in an office building. The model has been used in several flexible load applications, where the indoor temperature is allowed to vary around a given reference to provide power system services by shifting the heati...

  18. Prediction of speech intelligibility based on an auditory preprocessing model

    DEFF Research Database (Denmark)

    Christiansen, Claus Forup Corlin; Pedersen, Michael Syskind; Dau, Torsten

    2010-01-01

    in noise experiment was used for training and an ideal binary mask experiment was used for evaluation. All three models were able to capture the trends in the speech in noise training data well, but the proposed model provides a better prediction of the binary mask test data, particularly when the binary...... masks degenerate to a noise vocoder....

  19. Modelling of Security Principles Within Car-to-Car Communications in Modern Cooperative Intelligent Transportation Systems

    Directory of Open Access Journals (Sweden)

    Jan Durech

    2016-01-01

    Full Text Available Intelligent transportation systems (ITS bring advanced applications that provide innovative services for various transportation modes in the area of traffic control, and enable better awareness for different users. Communication connections between intelligent vehicles with the use of wireless communication standards, so called Vehicular Ad Hoc Networks (VANETs, require ensuring verification of validity of provided services as well as services related to transmission confidentiality and integrity. The goal of this paper is to analyze secure mechanisms utilised in VANET communication within Cooperative Intelligent Transportation Systems (C-ITS with a focus on safety critical applications. The practical part of the contribution is dedicated to modelling of security properties of VANET networks via OPNET Modeler tool extended by the implementation of the OpenSSL library for authentication protocol realisation based on digital signature schemes. The designed models simulate a transmission of authorised alert messages in Car-to-Car communication for several traffic scenarios with recommended Elliptic Curve Integrated Encryption Scheme (ECIES. The obtained results of the throughput and delay in the simulated network are compared for secured and no-secured communications in dependence on the selected digital signature schemes and the number of mobile nodes. The OpenSSL library has also been utilised for the comparison of time demandingness of digital signature schemes based on RSA (Rivest Shamir Adleman, DSA (Digital Signature Algorithm and ECDSA (Elliptic Curve Digital Signature Algorithm for different key-lengths suitable for real time VANET communications for safety-critical applications of C-ITS.

  20. The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

    Science.gov (United States)

    Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

    2017-05-01

    This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

  1. Forensic intelligence framework--Part I: Induction of a transversal model by comparing illicit drugs and false identity documents monitoring.

    Science.gov (United States)

    Morelato, Marie; Baechler, Simon; Ribaux, Olivier; Beavis, Alison; Tahtouh, Mark; Kirkbride, Paul; Roux, Claude; Margot, Pierre

    2014-03-01

    Forensic intelligence is a distinct dimension of forensic science. Forensic intelligence processes have mostly been developed to address either a specific type of trace or a specific problem. Even though these empirical developments have led to successes, they are trace-specific in nature and contribute to the generation of silos which hamper the establishment of a more general and transversal model. Forensic intelligence has shown some important perspectives but more general developments are required to address persistent challenges. This will ensure the progress of the discipline as well as its widespread implementation in the future. This paper demonstrates that the description of forensic intelligence processes, their architectures, and the methods for building them can, at a certain level, be abstracted from the type of traces considered. A comparative analysis is made between two forensic intelligence approaches developed independently in Australia and in Europe regarding the monitoring of apparently very different kind of problems: illicit drugs and false identity documents. An inductive effort is pursued to identify similarities and to outline a general model. Besides breaking barriers between apparently separate fields of study in forensic science and intelligence, this transversal model would assist in defining forensic intelligence, its role and place in policing, and in identifying its contributions and limitations. The model will facilitate the paradigm shift from the current case-by-case reactive attitude towards a proactive approach by serving as a guideline for the use of forensic case data in an intelligence-led perspective. A follow-up article will specifically address issues related to comparison processes, decision points and organisational issues regarding forensic intelligence (part II).

  2. Building energy modeling for green architecture and intelligent dashboard applications

    Science.gov (United States)

    DeBlois, Justin

    Buildings are responsible for 40% of the carbon emissions in the United States. Energy efficiency in this sector is key to reducing overall greenhouse gas emissions. This work studied the passive technique called the roof solar chimney for reducing the cooling load in homes architecturally. Three models of the chimney were created: a zonal building energy model, computational fluid dynamics model, and numerical analytic model. The study estimated the error introduced to the building energy model (BEM) through key assumptions, and then used a sensitivity analysis to examine the impact on the model outputs. The conclusion was that the error in the building energy model is small enough to use it for building simulation reliably. Further studies simulated the roof solar chimney in a whole building, integrated into one side of the roof. Comparisons were made between high and low efficiency constructions, and three ventilation strategies. The results showed that in four US climates, the roof solar chimney results in significant cooling load energy savings of up to 90%. After developing this new method for the small scale representation of a passive architecture technique in BEM, the study expanded the scope to address a fundamental issue in modeling - the implementation of the uncertainty from and improvement of occupant behavior. This is believed to be one of the weakest links in both accurate modeling and proper, energy efficient building operation. A calibrated model of the Mascaro Center for Sustainable Innovation's LEED Gold, 3,400 m2 building was created. Then algorithms were developed for integration to the building's dashboard application that show the occupant the energy savings for a variety of behaviors in real time. An approach using neural networks to act on real-time building automation system data was found to be the most accurate and efficient way to predict the current energy savings for each scenario. A stochastic study examined the impact of the

  3. Application of artificial intelligence models in water quality forecasting.

    Science.gov (United States)

    Yeon, I S; Kim, J H; Jun, K W

    2008-06-01

    The real-time data of the continuous water quality monitoring station at the Pyeongchang river was analyzed separately during the rainy period and non-rainy period. Total organic carbon data observed during the rainy period showed a greater mean value, maximum value and standard deviation than the data observed during the non-rainy period. Dissolved oxygen values during the rainy period were lower than those observed during the non-rainy period. It was analyzed that the discharge due to rain fall from the basin affects the change of the water quality. A model for the forecasting of water quality was constructed and applied using the neural network model and the adaptive neuro-fuzzy inference system. Regarding the models of levenberg-marquardt neural network, modular neural network and adaptive neuro-fuzzy inference system, all three models showed good results for the simulation of total organic carbon. The levenberg-marquardt neural network and modular neural network models showed better results than the adaptive neuro-fuzzy inference system model in the forecasting of dissolved oxygen. The modular neural network model, which was applied with the qualitative data of time in addition to quantitative data, showed the least error.

  4. 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

  5. Advanced intelligent systems

    CERN Document Server

    Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

    2014-01-01

    Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

  6. Intelligent systems

    CERN Document Server

    Irwin, J David

    2011-01-01

    Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system

  7. John Carroll’s Views on Intelligence: Bi-Factor vs. Higher-Order Models

    Directory of Open Access Journals (Sweden)

    A. Alexander Beaujean

    2015-10-01

    Full Text Available The development of factor models is inextricably tied to the history of intelligence research. One of the most commonly-cited scholars in the field is John Carroll, whose three-stratum theory of cognitive ability has been one of the most influential models of cognitive ability in the past 20 years. Nonetheless, there is disagreement about how Carroll conceptualized the factors in his model. Some argue that his model is best represented through a higher-order model, while others argue that a bi-factor model is a better representation. Carroll was explicit about what he perceived the best way to represent his model, but his writings are not always easy to understand. In this article, I clarify his position by first describing the details and implications of bi-factor and higher-order models then show that Carroll’s published views are better represented by a bi-factor model.

  8. Design Intelligent Model base Online Tuning Methodology for Nonlinear System

    Directory of Open Access Journals (Sweden)

    Ali Roshanzamir

    2014-04-01

    Full Text Available In various dynamic parameters systems that need to be training on-line adaptive control methodology is used. In this paper fuzzy model-base adaptive methodology is used to tune the linear Proportional Integral Derivative (PID controller. The main objectives in any systems are; stability, robust and reliability. However PID controller is used in many applications but it has many challenges to control of continuum robot. To solve these problems nonlinear adaptive methodology based on model base fuzzy logic is used. This research is used to reduce or eliminate the PID controller problems based on model reference fuzzy logic theory to control of flexible robot manipulator system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.

  9. Developing energy forecasting model using hybrid artificial intelligence method

    Institute of Scientific and Technical Information of China (English)

    Shahram Mollaiy-Berneti

    2015-01-01

    An important problem in demand planning for energy consumption is developing an accurate energy forecasting model. In fact, it is not possible to allocate the energy resources in an optimal manner without having accurate demand value. A new energy forecasting model was proposed based on the back-propagation (BP) type neural network and imperialist competitive algorithm. The proposed method offers the advantage of local search ability of BP technique and global search ability of imperialist competitive algorithm. Two types of empirical data regarding the energy demand (gross domestic product (GDP), population, import, export and energy demand) in Turkey from 1979 to 2005 and electricity demand (population, GDP, total revenue from exporting industrial products and electricity consumption) in Thailand from 1986 to 2010 were investigated to demonstrate the applicability and merits of the present method. The performance of the proposed model is found to be better than that of conventional back-propagation neural network with low mean absolute error.

  10. Design and Optimization of Intelligent Service Robot Suspension System Using Dynamic Model

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Seong Hoon; Park, Tae Won; Lee, Soo Ho; Jung, Sung Pil; Jun, Kab Jin; Yoon, J. W. [Ajou University, Suwon (Korea, Republic of)

    2010-08-15

    Recently, an intelligent service robot is being developed for use in guiding and providing information to visitors about the building at public institutions. The intelligent robot has a sensor at the bottom to recognize its location. Four wheels, which are arranged in the form of a lozenge, support the robot. This robot cannot be operated on uneven ground because its driving parts are attached to its main body that contains the important internal components. Continuous impact with the ground can change the precise positions of the components and weaken the connection between each structural part. In this paper, the design of the suspension system for such a robot is described. The dynamic model of the robot is created, and the driving characteristics of the robot with the designed suspension system are simulated. Additionally, the suspension system is optimized to reduce the impact for the robot components.

  11. Model Data Warehouse dan Business Intelligence untuk Meningkatkan Penjualan pada PT. S

    Directory of Open Access Journals (Sweden)

    Rudy Rudy

    2011-06-01

    Full Text Available Today a lot of companies use information system in every business activity. Every transaction is stored electronically in the database transaction. The transactional database does not help much to assist the executives in making strategic decisions to improve the company competitiveness. The objective of this research is to analyze the operational database system and the information needed by the management to design a data warehouse model which fits the executive information needs in PT. S. The research method uses the Nine-Step Methodology data warehouse design by Ralph Kimball. The result is a data warehouse featuring business intelligence applications to display information of historical data in tables, graphs, pivot tables, and dashboards and has several points of view for the management. This research concludes that a data warehouse which combines multiple database transactions with business intelligence application can help executives to understand the reports in order to accelerate decision-making processes. 

  12. A multi-agent system model to integrate Virtual Learning Environments and Intelligent Tutoring Systems

    Directory of Open Access Journals (Sweden)

    Giuffra P.

    2013-03-01

    Full Text Available Virtual learning environments (VLEs are used in distance learning and classroom teaching as teachers and students support tools in the teaching–learning process, where teachers can provide material, activities and assessments for students. However, this process is done in the same way for all the students, regardless of their differences in performance and behavior in the environment. The purpose of this work is to develop an agent-based intelligent learning environment model inspired by intelligent tutoring to provide adaptability to distributed VLEs, using Moodle as a case study and taking into account students’ performance on tasks and activities proposed by the teacher, as well as monitoring his/her study material access.

  13. A multi-resolution envelope-power based model for speech intelligibility

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Ewert, Stephan D.; Dau, Torsten

    2013-01-01

    The speech-based envelope power spectrum model (sEPSM) presented by Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] estimates the envelope power signal-to-noise ratio (SNRenv) after modulation-frequency selective processing. Changes in this metric were shown to account well...... for changes of speech intelligibility for normal-hearing listeners in conditions with additive stationary noise, reverberation, and nonlinear processing with spectral subtraction. In the latter condition, the standardized speech transmission index [(2003). IEC 60268-16] fails. However, the sEPSM is limited...... with a modulation-filter dependent duration. The multi-resolution sEPSM is demonstrated to account for intelligibility obtained in conditions with stationary and fluctuating interferers, and noisy speech distorted by reverberation or spectral subtraction. The results support the hypothesis that the SNRenv...

  14. A novel recurrent neural network forecasting model for power intelligence center

    Institute of Scientific and Technical Information of China (English)

    LIU Ji-cheng; NIU Dong-xiao

    2008-01-01

    In order to accurately forecast the load of power system and enhance the stability of the power network, a novel unascertained mathematics based recurrent neural network (UMRNN) for power intelligence center (PIC) was created through three steps. First, by combining with the general project uncertain element transmission theory (GPUET), the basic definitions of stochastic,fuzzy, and grey uncertain elements were given based on the principal types of uncertain information. Second, a power dynamic alliance including four sectors: generation sector, transmission sector, distribution sector and customers was established. The key factors were amended according to the four transmission topologies of uncertain elements, thus the new factors entered the power Intelligence center as the input elements. Finally, in the intelligence handing background of PIC, by performing uncertain and recursive process to the input values of network, and combining unascertained mathematics, the novel load forecasting model was built. Three different approaches were put forward to forecast an eastern regional power grid load in China. The root mean square error (ERMS) demonstrates that the forecasting accuracy of the proposed model UMRNN is 3% higher than that of BP neural network (BPNN), and 5% higher than that of autoregressive integrated moving average (ARIMA). Besides, an example also shows that the average relative error of the first quarter of 2008 forecasted by UMRNN is only 2.59%, which has high precision.

  15. Programming Models and Tools for Intelligent Embedded Systems

    DEFF Research Database (Denmark)

    Sørensen, Peter Verner Bojsen

    Design automation and analysis tools targeting embedded platforms, developed using a component-based design approach, must be able to reason about the capabilities of the platforms. In the general case where nothing is assumed about the components comprising a platform or the platform topology......, analysis must be employed to determine its capabilities. This kind of analysis is the subject of this dissertation. The main contribution of this work is the Service Relation Model used to describe and analyze the flow of service in models of platforms and systems composed of re-usable components...

  16. Intelligent modeling and identification of aircraft nonlinear flight

    Institute of Scientific and Technical Information of China (English)

    Alireza Roudbari; Fariborz Saghafi

    2014-01-01

    In this paper, a new approach has been proposed to identify and model the dynamics of a highly maneuverable fighter aircraft through artificial neural networks (ANNs). In general, air-craft flight dynamics is considered as a nonlinear and coupled system whose modeling through ANNs, unlike classical approaches, does not require any aerodynamic or propulsion information and a few flight test data seem sufficient. In this study, for identification and modeling of the aircraft dynamics, two known structures of internal and external recurrent neural networks (RNNs) and a proposed structure called hybrid combined recurrent neural network have been used and compared. In order to improve the training process, an appropriate evolutionary method has been applied to simultaneously train and optimize the parameters of ANNs. In this research, it has been shown that six ANNs each with three inputs and one output, trained by flight test data, can model the dynamic behavior of the highly maneuverable aircraft with acceptable accuracy and without any priori knowledge about the system.

  17. Construct of emotional intelligence

    OpenAIRE

    Sonja Pečjak in Andreja Avsec

    2003-01-01

    The article highlights the construct of emotional intelligence, that has appeared about then years ago. We present the popular and scientific comprehension of emotional intelligence, briefly describe the development of the concept and than in detail we propose the existing comprehension of emotional intelligence: through the models of Goleman (1995) and Bar-On (1997) we present the comprehension of emotional intelligence as a non-cognitive (personality) traits.

  18. Construct of emotional intelligence

    Directory of Open Access Journals (Sweden)

    Sonja Pečjak in Andreja Avsec

    2003-04-01

    Full Text Available The article highlights the construct of emotional intelligence, that has appeared about then years ago. We present the popular and scientific comprehension of emotional intelligence, briefly describe the development of the concept and than in detail we propose the existing comprehension of emotional intelligence: through the models of Goleman (1995 and Bar-On (1997 we present the comprehension of emotional intelligence as a non-cognitive (personality traits.

  19. A Suitable Artificial Intelligence Model for Inventory Level Optimization

    Directory of Open Access Journals (Sweden)

    Tereza Sustrova

    2016-05-01

    Full Text Available Purpose of the article: To examine suitable methods of artificial neural networks and their application in business operations, specifically to the supply chain management. The article discusses construction of an artificial neural networks model that can be used to facilitate optimization of inventory level and thus improve the ordering system and inventory management. For the data analysis from the area of wholesale trade with connecting material is used. Methodology/methods: Methods used in the paper consists especially of artificial neural networks and ANN-based modelling. For data analysis and preprocessing, MS Office Excel software is used. As an instrument for neural network forecasting MathWorks MATLAB Neural Network Tool was used. Deductive quantitative methods for research are also used. Scientific aim: The effort is directed at finding whether the method of prediction using artificial neural networks is suitable as a tool for enhancing the ordering system of an enterprise. The research also focuses on finding what architecture of the artificial neural networks model is the most suitable for subsequent prediction. Findings of the research show that artificial neural networks models can be used for inventory management and lot-sizing problem successfully. A network with the TRAINGDX training function and TANSIG transfer function and 6-8-1 architecture can be considered the most suitable for artificial neural network, as it shows the best results for subsequent prediction.. Conclusions resulting from the paper are beneficial for further research. It can be concluded that the created model of artificial neural network can be successfully used for predicting order size and therefore for improving the order cycle of an enterprise.

  20. 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...

  1. A Concept Map Knowledge Model of Intelligence Analysis

    Science.gov (United States)

    2011-05-01

    semantics, morphology, and inclusion of a focus question, which are discussed in Sub-section 2.3. A brief history of Novakian CMapping is given in Sub...model and is more interactive; and • It allows the inclusion of numerous resources that can be accessed with a click of a computer mouse, which is...Conéctate al Conocimiento: Una Estrategia Nacional de Panamá basada en Mapas Conceptuales. In Second International Conference on Concept Mapping

  2. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    Science.gov (United States)

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.

  3. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    Science.gov (United States)

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model. PMID:28120889

  4. Hybrid Modeling and Optimization of Manufacturing Combining Artificial Intelligence and Finite Element Method

    CERN Document Server

    Quiza, Ramón; Davim, J Paulo

    2012-01-01

    Artificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes.

  5. Predicting speech intelligibility in adverse conditions: evaluation of the speech-based envelope power spectrum model

    DEFF Research Database (Denmark)

    2011-01-01

    The speech-based envelope power spectrum model (sEPSM) [Jørgensen and Dau (2011). J. Acoust. Soc. Am., 130 (3), 1475–1487] estimates the envelope signal-to-noise ratio (SNRenv) of distorted speech and accurately describes the speech recognition thresholds (SRT) for normal-hearing listeners...... conditions by comparing predictions to measured data from [Kjems et al. (2009). J. Acoust. Soc. Am. 126 (3), 1415-1426] where speech is mixed with four different interferers, including speech-shaped noise, bottle noise, car noise, and cafe noise. The model accounts well for the differences in intelligibility...

  6. A Business Intelligence Model to Predict Bankruptcy using Financial Domain Ontology with Association Rule Mining Algorithm

    CERN Document Server

    Martin, A; Venkatesan, Dr V Prasanna

    2011-01-01

    Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement of a business. One of the best bankruptcy prediction models is Altman Z-score model. Altman Z-score method uses financial rations to predict bankruptcy. From the financial ontological model the relation between financial data is discovered by using data mining algorithm. By combining financial domain ontological model with association rule mining algorithm and Zscore model a new business intelligence model is developed to predict the bankruptcy.

  7. Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs)

    Science.gov (United States)

    Roushangar, Kiyoumars; Mehrabani, Fatemeh Vojoudi; Shiri, Jalal

    2014-06-01

    This study presents Artificial Intelligence (AI)-based modeling of total bed material load through developing the accuracy level of the predictions of traditional models. Gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS)-based models were developed and validated for estimations. Sediment data from Qotur River (Northwestern Iran) were used for developing and validation of the applied techniques. In order to assess the applied techniques in relation to traditional models, stream power-based and shear stress-based physical models were also applied in the studied case. The obtained results reveal that developed AI-based models using minimum number of dominant factors, give more accurate results than the other applied models. Nonetheless, it was revealed that k-fold test is a practical but high-cost technique for complete scanning of applied data and avoiding the over-fitting.

  8. Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction

    Science.gov (United States)

    Afan, Haitham Abdulmohsin; El-shafie, Ahmed; Mohtar, Wan Hanna Melini Wan; Yaseen, Zaher Mundher

    2016-10-01

    An accurate model for sediment prediction is a priority for all hydrological researchers. Many conventional methods have shown an inability to achieve an accurate prediction of suspended sediment. These methods are unable to understand the behaviour of sediment transport in rivers due to the complexity, noise, non-stationarity, and dynamism of the sediment pattern. In the past two decades, Artificial Intelligence (AI) and computational approaches have become a remarkable tool for developing an accurate model. These approaches are considered a powerful tool for solving any non-linear model, as they can deal easily with a large number of data and sophisticated models. This paper is a review of all AI approaches that have been applied in sediment modelling. The current research focuses on the development of AI application in sediment transport. In addition, the review identifies major challenges and opportunities for prospective research. Throughout the literature, complementary models superior to classical modelling.

  9. INFOGRAPHIC MODELING OF THE MAN-MACHINERY-ENVIRONMENT SYSTEM EXEMPLIFIED BY AN INTELLIGENT BUILDING WITHIN THE FRAMEWORK OF INNOVATIVE CONFLICTS

    OpenAIRE

    Volkov Andrey Anatolevich; Rakhmonov Emomali Karimovich

    2012-01-01

    The authors consider the problems that accompany development of construction conflict management techniques using infographic modeling. The authors analyze comprehensive safety and comfort assurance requirements applicable to an intelligent building. The authors provide a brief overview of systems that comprise an intelligent building. The authors argue that there is a pressing need for the study of the fundamentals of construction conflict management as a new theoretical and a...

  10. Meetei Mayek Unicode Modeling Using Swarm Intelligence and Neural Networks

    Directory of Open Access Journals (Sweden)

    Wahengbam Kanan Kumar

    2014-04-01

    Full Text Available The Different techniques have evolved for better optical character recognition for many scripts, yet very little literature has been found for Meetei Mayek script. The current paper exhibits a new approach to model and simulate handwritten Meetei mayek script by using advanced segmentation tools and recognition algorithms. Preprocessing of the acquired images is needed before segmentation and recognition steps; segmentation is done by using PSOFCM segmentation, while multilayer feed forward neural network with back propagation learning is used for the recognition purpose. It may be noted that PSOFCM segmentation proved useful for MRI image processing in our previous paper, the same technique is used for enhancing the characters. The detailed procedures along with the results are discussed in the sections shown below

  11. Modeling speech intelligibility in quiet and noise in listeners with normal and impaired hearing.

    Science.gov (United States)

    Rhebergen, Koenraad S; Lyzenga, Johannes; Dreschler, Wouter A; Festen, Joost M

    2010-03-01

    The speech intelligibility index (SII) is an often used calculation method for estimating the proportion of audible speech in noise. For speech reception thresholds (SRTs), measured in normally hearing listeners using various types of stationary noise, this model predicts a fairly constant speech proportion of about 0.33, necessary for Dutch sentence intelligibility. However, when the SII model is applied for SRTs in quiet, the estimated speech proportions are often higher, and show a larger inter-subject variability, than found for speech in noise near normal speech levels [65 dB sound pressure level (SPL)]. The present model attempts to alleviate this problem by including cochlear compression. It is based on a loudness model for normally hearing and hearing-impaired listeners of Moore and Glasberg [(2004). Hear. Res. 188, 70-88]. It estimates internal excitation levels for speech and noise and then calculates the proportion of speech above noise and threshold using similar spectral weighting as used in the SII. The present model and the standard SII were used to predict SII values in quiet and in stationary noise for normally hearing and hearing-impaired listeners. The present model predicted SIIs for three listener types (normal hearing, noise-induced, and age-induced hearing loss) with markedly less variability than the standard SII.

  12. Addressing diverse learner preferences and intelligences with emerging technologies: Matching models to online opportunities

    Directory of Open Access Journals (Sweden)

    Ke Zhang

    2009-03-01

    Full Text Available This paper critically reviews various learning preferences and human intelligence theories and models with a particular focus on the implications for online learning. It highlights a few key models, Gardner’s multiple intelligences, Fleming and Mills’ VARK model, Honey and Mumford’s Learning Styles, and Kolb’s Experiential Learning Model, and attempts to link them to trends and opportunities in online learning with emerging technologies. By intersecting such models with online technologies, it offers instructors and instructional designers across educational sectors and situations new ways to think about addressing diverse learner needs, backgrounds, and expectations. Learning technologies are important for effective teaching, as are theories and models and theories of learning. We argue that more immense power can be derived from connections between the theories, models and learning technologies. Résumé : Cet article passe en revue de manière critique les divers modèles et théories sur les préférences d’apprentissage et l’intelligence humaine, avec un accent particulier sur les implications qui en découlent pour l’apprentissage en ligne. L’article présente quelques-uns des principaux modèles (les intelligences multiples de Gardner, le modèle VAK de Fleming et Mills, les styles d’apprentissage de Honey et Mumford et le modèle d’apprentissage expérientiel de Kolb et tente de les relier à des tendances et occasions d’apprentissage en ligne qui utilisent les nouvelles technologies. En croisant ces modèles avec les technologies Web, les instructeurs et concepteurs pédagogiques dans les secteurs de l’éducation ou en situation éducationnelle se voient offrir de nouvelles façons de tenir compte des divers besoins, horizons et attentes des apprenants. Les technologies d’apprentissage sont importantes pour un enseignement efficace, tout comme les théories et les modèles d’apprentissage. Nous sommes d

  13. Modeling of gene therapy for regenerative cells using intelligent agents.

    Science.gov (United States)

    Adly, Aya Sedky; Aboutabl, Amal Elsayed; Ibrahim, M Shaarawy

    2011-01-01

    Gene therapy is an exciting field that has attracted much interest since the first submission of clinical trials. Preliminary results were very encouraging and prompted many investigators and researchers. However, the ability of stem cells to differentiate into specific cell types holds immense potential for therapeutic use in gene therapy. Realization of this potential depends on efficient and optimized protocols for genetic manipulation of stem cells. It is widely recognized that gain/loss of function approaches using gene therapy are essential for understanding specific genes functions, and such approaches would be particularly valuable in studies involving stem cells. A significant complexity is that the development stage of vectors and their variety are still not sufficient to be efficiently applied in stem cell therapy. The development of scalable computer systems constitutes one step toward understanding dynamics of its potential. Therefore, the primary goal of this work is to develop a computer model that will support investigations of virus' behavior and organization on regenerative tissues including genetically modified stem cells. Different simulation scenarios were implemented, and their results were encouraging compared to ex vivo experiments, where the error rate lies in the range of acceptable values in this domain of application.

  14. Multiple Intelligences and quotient spaces

    OpenAIRE

    Malatesta, Mike; Quintana, Yamilet

    2006-01-01

    The Multiple Intelligence Theory (MI) is one of the models that study and describe the cognitive abilities of an individual. In [7] is presented a referential system which allows to identify the Multiple Intelligences of the students of a course and to classify the level of development of such Intelligences. Following this tendency, the purpose of this paper is to describe the model of Multiple Intelligences as a quotient space, and also to study the Multiple Intelligences of an individual in...

  15. An Intelligent System for Modelling, Design and Analysis of Chemical Processes

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    ICAS, Integrated Computer Aided System, is a software that consists of a number of intelligent tools, which are very suitable, among others, for computer aided modelling, sustainable design of chemical and biochemical processes, and design-analysis of product-process monitoring systems. Each...... the computer aided modelling tool will illustrate how to generate a desired process model, how to analyze the model equations, how to extract data and identify the model and make it ready for various types of application. In sustainable process design, the example will highlight the issue of integration...... of these tools are characterized by a framework that follows an established work-flow and data-flow, developed to guide the user through the many steps of the problem solution process. At each, the specific tool knows which data, model and/or algorithm to use. The tool also provides analysis of the calculated...

  16. An Intelligent Master Model of Computer Aided Process Planning for Large Complicated Stampings

    Institute of Scientific and Technical Information of China (English)

    Zheng Jinqiao; Wang Yilin; Li Zhigang

    2005-01-01

    Process planning for large complicated stampings is more complicated, illegible and multiform than that for common stampings.In this paper, an intelligent master model of computer aided process planning (CAPP) for large complicated stampings has been developed based on knowledge based engineering (KBE) and feature technology. This innovative model consists of knowledge base ( KB), process control structure (PCS), process information model (PIM), multidisciplinary design optimization (MDO), model link environment (MLE) and simulation engine (SE), to realize process planning, optimization, simulation and management integrated to complete intelligent CAPP system. In this model, KBE provides knowledge base, open architecture and knowledge reuse ability to deal with the multi-domain and multi-expression of process knowledge, and forms an integrated environment. With PIM,all the knowledge consisting of objects, constraints, experience and decision-makings is carried by object-oriented method dynamically for knowledge-reasoning. PCS makes dynamical knowledge modified and updated timely and accordingly. MLE provides sev eral methods to make CAPP system associated and integrated. SE provides a programmable mechanism to interpret simulation course and result. Meanwhile, collaborative optimization, one method of MDO, is imported to deal with the optimization distributed for multiple purposes. All these make CAPP system integrated and open to other systems, such as die design and manufacturing system.

  17. Experimental Exploration of RSSI Model for the Vehicle Intelligent Position System

    Directory of Open Access Journals (Sweden)

    Zhichao Cao

    2015-01-01

    Full Text Available Vehicle intelligent position systems based on Received Signal Strength Indicator (RSSI in Wireless Sensor Networks (WSNs are efficiently utilized. The vehicle’s position accuracy is of great importance for transportation behaviors, such as dynamic vehicle routing problems and multiple pedestrian routing choice behaviors and so on. Therefore, a precise position and available optimization is necessary for total parameters of conventional RSSI model. In this papar, we investigate the experimental performance of translating the power measurements to corresponding distance between each pair of nodes. The priori knowledge about the environment interference could impact the accuracy of vehicles’s position and the reliability of paremeters greatly. Based on the real-world outdoor experiments, we compares different regression analysis of the RSSI model, in order to establish a calibration scheme on RSSI model. We showed that the average error of RSSI model is able to decrease throughout the rules of environmental factor n and shadowing factor ? respectively. Moreover, the calculation complexity is reduced. Since variation tendency of environmental factor n, shadowing factor ? with distance and signal strength could be simulated respectively, RSSI model fulfills the precision of the vehicle intelligent position system.

  18. A fuzzy TOPSIS model to evaluate the Business Intelligence competencies of Port Community Systems

    Directory of Open Access Journals (Sweden)

    Ghazanfari Mehdi

    2014-04-01

    Full Text Available Evaluation of the Business Intelligence (BI competencies of port community systems before they are bought and deployed is a vital importance for establishment of a decision-support environment for managers. This study proposes a new model which provides a simple approach to the assessment of the BI competencies of port community systems in organization. This approach helps decision-makers to select an enterprise system with appropriate intelligence requirements to support the managers’ decision-making tasks. Thirtyfour criteria for BI specifications are determined from a thorough review of the literature. The proposed model uses the fuzzy TOPSIS technique, which employs fuzzy weights of the criteria and fuzzy judgments of port community systems to compute the evaluation scores and rankings. The application of the model is realized in the evaluation, ranking and selecting of the needed port community systems in a port and maritime organization, in order to validate the proposed model with a real application. With utilizing the proposed model organizations can assess, select, and purchase port community systems which will provide a better decision-support environment for their business systems.

  19. Artificial intelligence based models for stream-flow forecasting: 2000-2015

    Science.gov (United States)

    Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

    2015-11-01

    The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

  20. Research on integrated naval ship design model and its intelligent algorithm

    Institute of Scientific and Technical Information of China (English)

    HOU Yuan-hang; HUANG Sheng

    2016-01-01

    Pointing at naval ship projects creation and evaluation at stage of naval ship concept design,in the mechanism of integrated design based on naval ship synthesis model, ship projects creation and intelligent fuzzy evaluation method is researched, thus the applicability of each algorithm is obtained. Firstly,the naval ship synthesis model is introduced to design process, value and application status of synthesis model in integrated design is then exposed. Then the applicability of single target and multi targets SA algorithm is improved, and the quick generation of naval ship projects is done. After that, multiple projects evaluation method based on Vague fuzzy set is introduced to established the intelligent evaluation model, which can integrate effectively the quantitative and qualitative indexes. At last, the analysis of results comparison shows the advancement and rationality of each method. The example shows the integrated design process researched in this paper can be a great orientation of naval ship project design, and can also be used in other parts of naval ship development.

  1. The Impact of Intelligent Transport Systems on Office Location Attractiveness: Testing the Predictive Validity of a Location Choice Model

    NARCIS (Netherlands)

    Argiolu, R.; Van der Heijden, R.; Bos, I.; Marchau, V.A.W.J.

    2013-01-01

    In recent years, a model was developed describing effects of Intelligent Transport Systems (ITS) on location preferences of office-keeping organisations in urbanised. The model is based on a Hierarchical Information Integration Approach, using Stated Preference data. The model indicates that ITS

  2. Applying Intelligent Computing Techniques to Modeling Biological Networks from Expression Data

    Institute of Scientific and Technical Information of China (English)

    Wei-Po Lee; Kung-Cheng Yang

    2008-01-01

    Constructing biological networks is one of the most important issues in system sbiology. However, constructing a network from data manually takes a considerable large amount of time, therefore an automated procedure is advocated. To automate the procedure of network construction, in this work we use two intelligent computing techniques, genetic programming and neural computation, to infer two kinds of network models that use continuous variables. To verify the presented approaches, experiments have been conducted and the preliminary results show that both approaches can be used to infer networks successfully.

  3. Advanced Emergency Braking Control Based on a Nonlinear Model Predictive Algorithm for Intelligent Vehicles

    Directory of Open Access Journals (Sweden)

    Ronghui Zhang

    2017-05-01

    Full Text Available Focusing on safety, comfort and with an overall aim of the comprehensive improvement of a vision-based intelligent vehicle, a novel Advanced Emergency Braking System (AEBS is proposed based on Nonlinear Model Predictive Algorithm. Considering the nonlinearities of vehicle dynamics, a vision-based longitudinal vehicle dynamics model is established. On account of the nonlinear coupling characteristics of the driver, surroundings, and vehicle itself, a hierarchical control structure is proposed to decouple and coordinate the system. To avoid or reduce the collision risk between the intelligent vehicle and collision objects, a coordinated cost function of tracking safety, comfort, and fuel economy is formulated. Based on the terminal constraints of stable tracking, a multi-objective optimization controller is proposed using the theory of non-linear model predictive control. To quickly and precisely track control target in a finite time, an electronic brake controller for AEBS is designed based on the Nonsingular Fast Terminal Sliding Mode (NFTSM control theory. To validate the performance and advantages of the proposed algorithm, simulations are implemented. According to the simulation results, the proposed algorithm has better integrated performance in reducing the collision risk and improving the driving comfort and fuel economy of the smart car compared with the existing single AEBS.

  4. An Intelligent Mediating Model for Collaborative e-Learning Management Systems

    Directory of Open Access Journals (Sweden)

    Akanbi Caleb Olufisoye

    2011-07-01

    Full Text Available E-learning management systems(e- LMSs lack ontologies for sharing their domain knowledge learning objects with others due to differences or non-uniformity in architectures, platforms, protocols and representations. The effect of this on e-learners is that collaboration with other e-LMS during learning processes is not permitted. Hence, learning process is restricted only to the knowledge base of a particular E-LMS adopted by an institution, which may limit the mastery level of learners. To provide a remedy to this problem, an intelligent multi-agent mediating system model is proposed in this study using hybrid rule and case based reasoning scheme. Unified Modeling Language(UML is used as a design tool to specify the active and passive entities of the model in form class The model proposed provides a collaborative platform for sharing of the learning objects across multiple e-LMSs, during learning processes.

  5. An extension of the technology acceptance model for business intelligence systems: project management maturity perspective

    Directory of Open Access Journals (Sweden)

    Mirjana Pejić Bach

    2017-01-01

    Full Text Available Business intelligence systems (BISs refer to wide range of technologies and applications useful for retrieving and analyzing the large amount of information with the goal to generate knowledge useful for making effective business decision. In order to investigate adoption of BISs in companies, we propose a model based on the technology acceptance model (TAM that is expanded by variables representing the concept of a project management maturity (PMM. The survey on the sample of USA companies has been conducted with the chief information officer (CIO as the main informant. Structural equations model has been developed in order to test the research model. Results indicate that TAM expanded with the notion of PMM is useful in increasing understanding of BISs adoption in companies.

  6. Rolling force prediction for strip casting using theoretical model and artificial intelligence

    Institute of Scientific and Technical Information of China (English)

    CAO Guang-ming; LI Cheng-gang; ZHOU Guo-ping; LIU Zhen-yu; WU Di; WANG Guo-dong; LIU Xiang-hua

    2010-01-01

    Rolling force for strip casting of 1Cr17 ferritic stainless steel was predicted using theoretical model and artificial intelligence.Solution zone was classified into two parts by kiss point position during casting strip.Navier-Stokes equation in fluid mechanics and stream function were introduced to analyze the rheological property of liquid zone and mushy zone,and deduce the analytic equation of unit compression stress distribution.The traditional hot rolling model was still used in the solid zone.Neural networks based on feedforward training algorithm in Bayesian regularization were introduced to build model for kiss point position.The results show that calculation accuracy for verification data of 94.67% is in the range of+7.0%,which indicates that the predicting accuracy of this model is very high.

  7. Development of a semantic-enabled cybersecurity threat intelligence sharing model

    CSIR Research Space (South Africa)

    Mtsweni, Jabu

    2016-03-01

    Full Text Available intelligence solutions lack the semantic knowledge essential for automated sharing of timely and context-aware information within a specific operating domain. Moreover, existing cybersecurity information sharing solutions lack the visualization and intelligence...

  8. Application of a Cognitive Model for Army Training: Handbook for Strategic Intelligence Analysis.

    Science.gov (United States)

    Phelps, Ruth H.; And Others

    This technical report has two purposes. One purpose is to present an end product of a multi-year research investigation into the cognitive skills involved in performing intelligence analysis. The product is a "Handbook for Strategic Intelligence Analysis" developed for the United States Army Intelligence and Threat Analysis Center…

  9. Laccase immobilized manganese ferrite nanoparticle: synthesis and LSSVM intelligent modeling of decolorization.

    Science.gov (United States)

    Mahmoodi, Niyaz Mohammad; Arabloo, Milad; Abdi, Jafar

    2014-12-15

    Laccase was immobilized onto manganese ferrite nanoparticle (MFN) and dye decolorization from single and binary systems was studied. The characteristics of laccase immobilized manganese ferrite nanoparticle (LIMFN) were investigated using Fourier transform infrared (FTIR) and scanning electron microscopy (SEM). Direct red 31 (DR31), Acid blue 92 (AB92) and Direct green 6 (DG6) were used. A least square support vector machine (LSSVM) was developed to predict the decolorization efficiency of various single and binary systems based on the obtained laboratory data under different experimental conditions. Statistical and graphical quality measures were also employed to evaluate the performance and accuracy of the developed intelligent models. It is shown that the predictions of the designed LSSVM models are in close agreement with the experimental data. The effects of LIMFN dosage, pH and dye concentration on dye decolorization from single and binary systems were evaluated. Decolorization kinetics followed Michaelis-Menten Model.

  10. Improved 2D Intelligent Driver Model simulating synchronized flow and evolution concavity in traffic flow

    CERN Document Server

    Tian, Junfang; Li, Geng; Treiber, Martin; Zhu, Chenqiang; Jia, Bin

    2016-01-01

    This paper firstly show that 2 Dimensional Intelligent Driver Model (Jiang et al., PloS one, 9(4), e94351, 2014) is not able to replicate the synchronized traffic flow. Then we propose an improved model by considering the difference between the driving behaviors at high speeds and that at low speeds. Simulations show that the improved model can reproduce the phase transition from synchronized flow to wide moving jams, the spatiotemporal patterns of traffic flow induced by traffic bottleneck, and the evolution concavity of traffic oscillations (i.e. the standard deviation of the velocities of vehicles increases in a concave/linear way along the platoon). Validating results show that the empirical time series of traffic speed obtained from Floating Car Data can be well simulated as well.

  11. A Knowledge-reuse Based Intelligent Reasoning Model for Worsted Process Optimization

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The textile process planning is a knowledge reuse process in nature, which depends on the expert's knowledge and experience. It seems to be very difficult to build up an integral mathematical model to optimize hundreds of the processing parameters. In fact, the existing process cases which were recorded to ensure the ability to trace production steps can also be used to optimize the process itself. This paper presents a novel knowledge-reuse based hybrid intelligent reasoning model (HIRM) for worsted process optimization. The model architecture and reasoning mechanism are respectively described. An applied case with HIRM is given to demonstrate that the best process decision can be made, and important processing parameters such as for raw material optimized.

  12. Ontology, Epistemology, and Teleology for Modeling and Simulation Philosophical Foundations for Intelligent M&S Applications

    CERN Document Server

    2013-01-01

    In this book, internationally recognized experts in philosophy of science, computer science, and modeling and simulation are contributing to the discussion on how ontology, epistemology, and teleology will contribute to enable the next generation of intelligent modeling and simulation applications. It is well understood that a simulation can provide the technical means to display the behavior of a system over time, including following observed trends to predict future possible states, but how reliable and trustworthy are such predictions? The questions about what we can know (ontology), how we gain new knowledge (epistemology), and what we do with this knowledge (teleology) are therefore illuminated from these very different perspectives, as each experts uses a different facet to look at these challenges. The result of bringing these perspectives into one book is a challenging compendium that gives room for a spectrum of challenges: from general philosophy questions, such as can we use modeling and simulation...

  13. The use of emotional intelligence models in the assessment of management practices

    Directory of Open Access Journals (Sweden)

    L M Polyanova

    2014-12-01

    Full Text Available In the face of constant changes and instability, every organization feels an increasing demand to develop personal qualities of the staff for the effective functioning. As a result of the formation of intangible assets management, we have obtained methods for managing emotions as a part of the intellectual capital. The article discusses the basic models and techniques for measuring emotional intelligence of the head of a company, in particular, J. Mayer, D. Caruso and P. Salovey model of abilities (test MSCEIT V2.0 and mixed model (D. Lusin EmIn test and R. Bar-On EQ-i test, their advantages, limitations and heuristic value when applied to the study of organizations.

  14. Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong

    2011-12-01

    Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

  15. Modelo de un Personaje en un Entorno Virtual Inteligente Character Model in an Intelligent Virtual Environment

    Directory of Open Access Journals (Sweden)

    Sandra P Mateus

    2012-01-01

    Full Text Available Este artículo propone un modelo de referencia de un personaje, con base en su percepción y razonamiento, con el fin de alcanzar un realismo visual en un Entorno Virtual Inteligente (EVI. Las etapas propuestas para llegar a la obtención del modelo son: i caracterización de objetos y el personaje de un EVI; ii diseño del modelo del EVI; iii especificación de la técnica de Inteligencia Artificial (IA; iv definición del nivel de física y creación del sistema semántico para la integración del personaje con el entorno; v validación del modelo propuesto mediante un prototipo; y vi evaluación de resultados. El modelo propuesto permite generar un dinamismo adecuado entre el personaje y los elementos de un entorno virtual, requerido en diversas aplicaciones.In this paper, a character reference model, based on its perception and reasoning, with the objective of achieving visual realism in an Intelligent Virtual Environment (IVE is proposed. The necessary steps for obtaining the model are: i to identify the characteristics of the objects and of the virtual character of the IVE; ii design of the IVE model; iii specification of the Artificial Intelligence technique (AI; iv defining the physical level and semantic system for the integration of the character with the environment; v validation of the proposed model in a prototype; and vi evaluation of the results. The proposed model allows generating an appropriate dynamics between the character en the elements of the virtual environment, which is required in several applications.

  16. Learning vector quantization neural network–based model reference adaptive control method for intelligent lower-limb prosthesis

    Directory of Open Access Journals (Sweden)

    Jia-Qiang Yang

    2016-04-01

    Full Text Available This article focuses on the design of a control system for intelligent prostheses. Learning vector quantization neural network–based model reference adaptive control method is employed to implement real-time trajectory tracking and damp torque control of intelligent lower-limb prosthesis. The method is then analyzed and proposed. A model reference control system is first built with two learning vector quantization neural networks. One neural network is used for output prediction, and the other is used for input control. The angle information of the prosthetic knee joint is utilized to train these two neural networks with the given learning algorithm. The testing results of different movement patterns verify the effectiveness of the proposed method and its suitability for intelligent lower-limb prostheses.

  17. Network-based modeling and intelligent data mining of social media for improving care.

    Science.gov (United States)

    Akay, Altug; Dragomir, Andrei; Erlandsson, Bjorn-Erik

    2015-01-01

    Intelligently extracting knowledge from social media has recently attracted great interest from the Biomedical and Health Informatics community to simultaneously improve healthcare outcomes and reduce costs using consumer-generated opinion. We propose a two-step analysis framework that focuses on positive and negative sentiment, as well as the side effects of treatment, in users' forum posts, and identifies user communities (modules) and influential users for the purpose of ascertaining user opinion of cancer treatment. We used a self-organizing map to analyze word frequency data derived from users' forum posts. We then introduced a novel network-based approach for modeling users' forum interactions and employed a network partitioning method based on optimizing a stability quality measure. This allowed us to determine consumer opinion and identify influential users within the retrieved modules using information derived from both word-frequency data and network-based properties. Our approach can expand research into intelligently mining social media data for consumer opinion of various treatments to provide rapid, up-to-date information for the pharmaceutical industry, hospitals, and medical staff, on the effectiveness (or ineffectiveness) of future treatments.

  18. MyMiCROscope: intelligent virtual microscopy in a blended learning model at Ulm University.

    Science.gov (United States)

    Schmidt, C; Reinehr, M; Leucht, O; Behrendt, N; Geiler, S; Britsch, S

    2011-10-20

    The growing diversity among students and the rapid increase in new technologies entering the system of higher education, demand reconsideration of traditional learning methods. To improve the individual student's learning situation we developed and integrated a novel virtual microscope, MyMiCROscope, into a face-to-face approach for teaching microscopic anatomy. The intelligent virtual microscope has not only enabled self-directed learning of the students at their individual learning speed independent of time and place but also offered new possibilities to interact with the user because it implements systematic annotations accessible from different operational levels. Furthermore the alteration of a sole instructor-led course into a blended learning model resulted in a change of the learning behaviour of the students: group work and social interactions were facilitated. The results of this study show the advantages that intelligent virtual microscopy incorporates for self-directed learning and that blended learning in undergraduate medical education is able to fulfil the individual needs of the students and support social interactions without disregarding practical skills.

  19. An extended car-following model accounting for the average headway effect in intelligent transportation system

    Science.gov (United States)

    Kuang, Hua; Xu, Zhi-Peng; Li, Xing-Li; Lo, Siu-Ming

    2017-04-01

    In this paper, an extended car-following model is proposed to simulate traffic flow by considering average headway of preceding vehicles group in intelligent transportation systems environment. The stability condition of this model is obtained by using the linear stability analysis. The phase diagram can be divided into three regions classified as the stable, the metastable and the unstable ones. The theoretical result shows that the average headway plays an important role in improving the stabilization of traffic system. The mKdV equation near the critical point is derived to describe the evolution properties of traffic density waves by applying the reductive perturbation method. Furthermore, through the simulation of space-time evolution of the vehicle headway, it is shown that the traffic jam can be suppressed efficiently with taking into account the average headway effect, and the analytical result is consistent with the simulation one.

  20. 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.

  1. Cognitive Tutoring based on Intelligent Decision Support in the PENTHA Instructional Design Model

    Science.gov (United States)

    dall'Acqua, Luisa

    2010-06-01

    The research finality of this paper is how to support Authors to develop rule driven—subject oriented, adaptable course content, meta-rules—representing the disciplinary epistemology, model of teaching, Learning Path structure, and assessment parameters—for intelligent Tutoring actions in a personalized, adaptive e-Learning environment. The focus is to instruct the student to be a decision manager for himself, able to recognize the elements of a problem, select the necessary information with the perspective of factual choices. In particular, our research intends to provide some fundamental guidelines for the definition of didactical rules and logical relations, that Authors should provide to a cognitive Tutoring system through the use of an Instructional Design method (PENTHA Model) which proposes an educational environment, able to: increase productivity and operability, create conditions for a cooperative dialogue, developing participatory research activities of knowledge, observations and discoveries, customizing the learning design in a complex and holistic vision of the learning / teaching processes.

  2. A NOVEL INTELLIGENT MODEL FOR ENTERPRISE INFORMATION SYSTEM BASED ON WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    OUAIL ABROUN

    2014-05-01

    Full Text Available Wireless Sensor Network (WSN technologies became a leading solution in many significant fields, by offering the desired high accuracy in a large variety of control applications under rational cost. However, for the sake of generating optimal decisions and choosing adequate reactions, the current information systems used as enterprise service require more accurate and real-time data. In this work, we propose a novel model of Enterprise Information System (EIS, which integrates the WSN technologies benefits, to make an intelligent hardware and software architecture which is able to generate business managing decisions for several enterprise services with high accurateness. This paper explains the different elements treated to integrate WSN into the EIS, through presenting our suggested integration architecture, then the integration middleware layer, and finally the decisional model analysis and results.

  3. Towards intelligent diagnostic system employing integration of mathematical and engineering model

    Science.gov (United States)

    Isa, Nor Ashidi Mat

    2015-05-01

    The development of medical diagnostic system has been one of the main research fields during years. The goal of the medical diagnostic system is to place a nosological system that could ease the diagnostic evaluation normally performed by scientists and doctors. Efficient diagnostic evaluation is essentials and requires broad knowledge in order to improve conventional diagnostic system. Several approaches on developing the medical diagnostic system have been designed and tested since the earliest 60s. Attempts on improving their performance have been made which utilizes the fields of artificial intelligence, statistical analyses, mathematical model and engineering theories. With the availability of the microcomputer and software development as well as the promising aforementioned fields, medical diagnostic prototypes could be developed. In general, the medical diagnostic system consists of several stages, namely the 1) data acquisition, 2) feature extraction, 3) feature selection, and 4) classifications stages. Data acquisition stage plays an important role in converting the inputs measured from the real world physical conditions to the digital numeric values that can be manipulated by the computer system. One of the common medical inputs could be medical microscopic images, radiographic images, magnetic resonance image (MRI) as well as medical signals such as electrocardiogram (ECG) and electroencephalogram (EEG). Normally, the scientist or doctors have to deal with myriad of data and redundant to be processed. In order to reduce the complexity of the diagnosis process, only the significant features of the raw data such as peak value of the ECG signal or size of lesion in the mammogram images will be extracted and considered in the subsequent stages. Mathematical models and statistical analyses will be performed to select the most significant features to be classified. The statistical analyses such as principal component analysis and discriminant analysis as well

  4. Towards intelligent diagnostic system employing integration of mathematical and engineering model

    Energy Technology Data Exchange (ETDEWEB)

    Isa, Nor Ashidi Mat [Imaging and Intelligent System Research Team (ISRT), School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang (Malaysia)

    2015-05-15

    The development of medical diagnostic system has been one of the main research fields during years. The goal of the medical diagnostic system is to place a nosological system that could ease the diagnostic evaluation normally performed by scientists and doctors. Efficient diagnostic evaluation is essentials and requires broad knowledge in order to improve conventional diagnostic system. Several approaches on developing the medical diagnostic system have been designed and tested since the earliest 60s. Attempts on improving their performance have been made which utilizes the fields of artificial intelligence, statistical analyses, mathematical model and engineering theories. With the availability of the microcomputer and software development as well as the promising aforementioned fields, medical diagnostic prototypes could be developed. In general, the medical diagnostic system consists of several stages, namely the 1) data acquisition, 2) feature extraction, 3) feature selection, and 4) classifications stages. Data acquisition stage plays an important role in converting the inputs measured from the real world physical conditions to the digital numeric values that can be manipulated by the computer system. One of the common medical inputs could be medical microscopic images, radiographic images, magnetic resonance image (MRI) as well as medical signals such as electrocardiogram (ECG) and electroencephalogram (EEG). Normally, the scientist or doctors have to deal with myriad of data and redundant to be processed. In order to reduce the complexity of the diagnosis process, only the significant features of the raw data such as peak value of the ECG signal or size of lesion in the mammogram images will be extracted and considered in the subsequent stages. Mathematical models and statistical analyses will be performed to select the most significant features to be classified. The statistical analyses such as principal component analysis and discriminant analysis as well

  5. Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

    Science.gov (United States)

    Niwas, Ram; Osama, Khwaja; Khan, Saif; Haque, Shafiul; Tripathi, C. K. M.; Mishra, B. N.

    2015-01-01

    Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500. PMID:26368924

  6. Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

    Science.gov (United States)

    Pathak, Lakshmi; Singh, Vineeta; Niwas, Ram; Osama, Khwaja; Khan, Saif; Haque, Shafiul; Tripathi, C K M; Mishra, B N

    2015-01-01

    Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500.

  7. Fractionating human intelligence.

    Science.gov (United States)

    Hampshire, Adam; Highfield, Roger R; Parkin, Beth L; Owen, Adrian M

    2012-12-20

    What makes one person more intellectually able than another? Can the entire distribution of human intelligence be accounted for by just one general factor? Is intelligence supported by a single neural system? Here, we provide a perspective on human intelligence that takes into account how general abilities or "factors" reflect the functional organization of the brain. By comparing factor models of individual differences in performance with factor models of brain functional organization, we demonstrate that different components of intelligence have their analogs in distinct brain networks. Using simulations based on neuroimaging data, we show that the higher-order factor "g" is accounted for by cognitive tasks corecruiting multiple networks. Finally, we confirm the independence of these components of intelligence by dissociating them using questionnaire variables. We propose that intelligence is an emergent property of anatomically distinct cognitive systems, each of which has its own capacity.

  8. An Intelligent Optimal Genetic Model to Investigate the User Usage Behaviour on World Wide Web

    Directory of Open Access Journals (Sweden)

    V.V.R. Maheswara Rao

    2013-04-01

    Full Text Available The unexpected wide spread use of WWW and dynamically increasing nature of the web creates new challenges in the web mining since the data in the web inherently unlabelled, incomplete, non linear, and heterogeneous. The investigation of user usage behaviour on WWW is real time problem which involves multiple conflicting measures of performance. These measures make not only computational intensive butalso needs to the possibility of be unable to find the exact solution. Unfortunately, the conventional methods are limited to optimization problems due to the absence of semantic certainty and presence of human intervention. In handling such data and overcome the limitations of conventional methodologies it is necessary to use a soft computing model that can work intelligently to attain optimal solution. To achieve the optimized solution for investigating the web user usage behaviour, the authors in the present paper proposes an Intelligent Optimal Genetic Model, IOGM, which is designed as an optimization tool based on the concept of natural genetic systems. Initially, IOGM comprise a set of individual solutions or chromosomes called the initial population. Later, biologically inspired operators create a new and potentially better population. Finally, by the theory of evolution, survive only optimal individuals from the population and then generate the next biological population. This process is terminated as when an acceptable optimal set of visited patterns is found or after fixed time limit. Additionally, IOGM strengthen by its ability to estimate the optimal stopping time of process. The proposed soft computing model ensures the identifiable features like learning, adaptability, self-maintenance and self-improvement. To validate the proposed system, several experiments were conducted and results proven this are claimed in this paper

  9. AN INTELLIGENT OPTIMAL GENETIC MODEL TO INVESTIGATE THE USER USAGE BEHAVIOUR ON WORLD WIDE WEB

    Directory of Open Access Journals (Sweden)

    V.V.R. Maheswara Rao

    2013-03-01

    Full Text Available The unexpected wide spread use of WWW and dynamically increasing nature of the web creates new challenges in the web mining since the data in the web inherently unlabelled, incomplete, non linear, and heterogeneous. The investigation of user usage behaviour on WWW is real time problem which involves multiple conflicting measures of performance. These measures make not only computational intensive but also needs to the possibility of be unable to find the exact solution. Unfortunately, the conventional methods are limited to optimization problems due to the absence of semantic certainty and presence of human intervention. In handling such data and overcome the limitations of conventional methodologies it is necessary to use a soft computing model that can work intelligently to attain optimal solution. To achieve the optimized solution for investigating the web user usage behaviour, the authors in the present paper proposes an Intelligent Optimal Genetic Model, IOGM, which is designed as an optimization tool based on the concept of natural genetic systems. Initially, IOGM comprise a set of individual solutions or chromosomes called the initial population. Later, biologically inspired operators create a new and potentially better population. Finally, by the theory of evolution, survive only optimal individuals from the population and then generate the next biological population. This process is terminated as when an acceptable optimal set of visited patterns is found or after fixed time limit. Additionally, IOGM strengthen by its ability to estimate the optimal stopping time of process. The proposed soft computing model ensures the identifiable features like learning, adaptability, self-maintenance and self-improvement. To validate the proposed system, several experiments were conducted and results proven this are claimed in this paper.

  10. Intelligence Analysis: Once Again

    Science.gov (United States)

    2008-02-01

    least touch on the subject of intelligence analysis. However, while still a large body of work, it is a considerably smaller set that specifically...meaning is influenced by the analyst’s mindset, mental model, or frame of mind . Kent (1949, p. 199) indicated “…an intelligence staff which must...or a top-down process are not unique to the intelligence literature. In the scientific literature, arguments date back to Descartes (1596- 1650

  11. A Fuzzy ANP Model Integrated with Benefits, Opportunities, Costs, and Risks to Prioritize Intelligent Power Grid Systems

    Directory of Open Access Journals (Sweden)

    Hsing Hung Chen

    2013-01-01

    Full Text Available Although growth of renewable energy is envisaged, many concerns are critical like the ability to maintain the balance between demands and supply and the variability, noncontrollability, and flexibility of the sources. Then, what will be the future concerns about the main composition of intelligent power grid systems in the future? There is no such research tackled before. Thus, this paper first finds critical success criteria of intelligent power grid systems and then constructs a multiple criteria and decision making model to help in identifying the suitable trends under complex economic performance, environmental impacts, and rapid technological and marketing changes. After empirical demonstration, the paper summarizes that the most suitable composition of future intelligent power grid systems should be constituted by “DHT” P2P grid, “C&D workflow” P2P scheduling, “GARCM” trustworthy P2P grid, and “multipurpose” grid applications in the future.

  12. Do Narcissism and Emotional Intelligence Win Us Friends? Modeling Dynamics of Peer Popularity Using Inferential Network Analysis.

    Science.gov (United States)

    Czarna, Anna Z; Leifeld, Philip; Śmieja, Magdalena; Dufner, Michael; Salovey, Peter

    2016-09-27

    This research investigated effects of narcissism and emotional intelligence (EI) on popularity in social networks. In a longitudinal field study, we examined the dynamics of popularity in 15 peer groups in two waves (N = 273). We measured narcissism, ability EI, and explicit and implicit self-esteem. In addition, we measured popularity at zero acquaintance and 3 months later. We analyzed the data using inferential network analysis (temporal exponential random graph modeling, TERGM) accounting for self-organizing network forces. People high in narcissism were popular, but increased less in popularity over time than people lower in narcissism. In contrast, emotionally intelligent people increased more in popularity over time than less emotionally intelligent people. The effects held when we controlled for explicit and implicit self-esteem. These results suggest that narcissism is rather disadvantageous and that EI is rather advantageous for long-term popularity.

  13. Resilience moderates the relationship between emotional intelligence and clinical communication ability among Chinese practice nursing students: A structural equation model analysis.

    Science.gov (United States)

    Kong, Linghua; Liu, Yun; Li, Guopeng; Fang, Yueyan; Kang, Xiaofei; Li, Ping

    2016-11-01

    To examine the positive association between emotional intelligence and clinical communication ability among practice nursing students, and to determine whether resilience plays a moderating role in the relationship between emotional intelligence and clinical communication ability among Chinese practice nursing students. Three hundred and seventy-seven practice nursing students from three hospitals participated in this study. They completed questionnaires including the Emotional Intelligence Inventory (EII), Connor-Davidson Resilience Scale (CD-RISC-10), and Clinical Communication Ability Scale (CCAS). Structural equation modeling was used to analyze the relationships among emotional intelligence, resilience, and clinical communication ability. Emotional intelligence was positively associated with clinical communication ability (Pintelligence and clinical communication ability (Pintelligence is positively related to clinical communication ability among Chinese practice nursing students, and resilience moderates the relationship between emotional intelligence and clinical communication ability, which may provide scientific evidence to aid in developing intervention strategies to improve clinical communication ability. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Model Predictive Controller for Active Demand Side Management with PV Self-consumption in an Intelligent Building

    DEFF Research Database (Denmark)

    Zong, Yi; Mihet-Popa, Lucian; Kullmann, Daniel

    2012-01-01

    This paper presents a Model Predictive Controller (MPC) for electrical heaters’ predictive power consumption including maximizing the use of local generation (e.g. solar power) in an intelligent building. The MPC is based on dynamic power price and weather forecast, considering users’ comfort...

  15. Fuzzy Logic, Neural Networks, Genetic Algorithms: Views of Three Artificial Intelligence Concepts Used in Modeling Scientific Systems

    Science.gov (United States)

    Sunal, Cynthia Szymanski; Karr, Charles L.; Sunal, Dennis W.

    2003-01-01

    Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…

  16. Teaching Culture and Language through the Multiple Intelligences Film Teaching Model in the ESL/EFL Classroom

    Science.gov (United States)

    Yeh, Ellen

    2014-01-01

    This paper will demonstrate how to enhance second language (L2) learners' linguistic and cultural competencies through the use of the Multiple Intelligences Film Teaching (MIFT) model. The paper will introduce two ideas to teachers of English as a Second/Foreign Language (ESL/EFL). First, the paper shows how L2 learners learn linguistic and…

  17. Modeling of Steam Distillation Mechanism during Steam Injection Process Using Artificial Intelligence

    Science.gov (United States)

    Ahadi, Arash; Kharrat, Riyaz

    2014-01-01

    Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods. PMID:24883365

  18. Modeling of steam distillation mechanism during steam injection process using artificial intelligence.

    Science.gov (United States)

    Daryasafar, Amin; Ahadi, Arash; Kharrat, Riyaz

    2014-01-01

    Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods.

  19. Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

    Science.gov (United States)

    Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

    2017-07-01

    Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

  20. Implicit theories of intelligence, perceived academic competence, and school achievement: testing alternative models.

    Science.gov (United States)

    Gonida, Eleftheria; Kiosseoglou, Grigoris; Leondari, Angeliki

    2006-01-01

    In the present study 3 alternative causal models concerning the relationships between implicit theories of intelligence, perceived academic competence, and school achievement were tested. The direction of changes in implicit theories and perceived competence during early adolescence also was examined. A total of 187 fifth and sixth graders were tested and retested a year later, when they were sixth and seventh graders, respectively. Cross-lagged regression analyses indicated that school achievement determined the adoption of a particular implicit theory through the mediation of perceived competence. Implicit theories were found to change toward the adoption of more incremental beliefs and perceived academic competence declined; however, high achievers, as compared with their low- and middle-level classmates, adopted more incremental beliefs and had significantly higher perceived competence.

  1. Challenges in phenotype definition in the whole-genome era: multivariate models of memory and intelligence.

    Science.gov (United States)

    Sabb, F W; Burggren, A C; Higier, R G; Fox, J; He, J; Parker, D S; Poldrack, R A; Chu, W; Cannon, T D; Freimer, N B; Bilder, R M

    2009-11-24

    Refining phenotypes for the study of neuropsychiatric disorders is of paramount importance in neuroscience. Poor phenotype definition provides the greatest obstacle for making progress in disorders like schizophrenia, bipolar disorder, Attention Deficit/Hyperactivity Disorder (ADHD), and autism. Using freely available informatics tools developed by the Consortium for Neuropsychiatric Phenomics (CNP), we provide a framework for defining and refining latent constructs used in neuroscience research and then apply this strategy to review known genetic contributions to memory and intelligence in healthy individuals. This approach can help us begin to build multi-level phenotype models that express the interactions between constructs necessary to understand complex neuropsychiatric diseases. These results are available online through the http://www.phenowiki.org database. Further work needs to be done in order to provide consensus-building applications for the broadly defined constructs used in neuroscience research.

  2. Design and Implementation of an Intelligent Educational Model Based on Personality and Learner's Emotion

    CERN Document Server

    Fatahi, Somayeh

    2010-01-01

    The Personality and emotions are effective parameters in learning process. Thus, virtual learning environments should pay attention to these parameters. In this paper, a new e-learning model is designed and implemented according to these parameters. The Virtual learning environment that is presented here uses two agents: Virtual Tutor Agent (VTA), and Virtual Classmate Agent (VCA). During the learning process and depending on events happening in the environment, learner's emotions are changed. In this situation, learning style should be revised according to the personality traits as well as the learner's current emotions. VTA selects suitable learning style for the learners based on their personality traits. To improve the learning process, the system uses VCA in some of the learning steps. VCA is an intelligent agent and has its own personality. It is designed so that it can present an attractive and real learning environment in interaction with the learner. To recognize the learner's personality, this syste...

  3. The NIST Real-Time Control System (RCS): A Reference Model Architecture for Computational Intelligence

    Science.gov (United States)

    Albus, James S.

    1996-01-01

    The Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades defines a reference model architecture for design and analysis of complex intelligent control systems. The RCS architecture consists of a hierarchically layered set of functional processing modules connected by a network of communication pathways. The primary distinguishing feature of the layers is the bandwidth of the control loops. The characteristic bandwidth of each level is determined by the spatial and temporal integration window of filters, the temporal frequency of signals and events, the spatial frequency of patterns, and the planning horizon and granularity of the planners that operate at each level. At each level, tasks are decomposed into sequential subtasks, to be performed by cooperating sets of subordinate agents. At each level, signals from sensors are filtered and correlated with spatial and temporal features that are relevant to the control function being implemented at that level.

  4. 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

  5. Automatic intelligibility assessment of speakers after laryngeal cancer by means of acoustic modeling.

    Science.gov (United States)

    Bocklet, Tobias; Riedhammer, Korbinian; Nöth, Elmar; Eysholdt, Ulrich; Haderlein, Tino

    2012-05-01

    One aspect of voice and speech evaluation after laryngeal cancer is acoustic analysis. Perceptual evaluation by expert raters is a standard in the clinical environment for global criteria such as overall quality or intelligibility. So far, automatic approaches evaluate acoustic properties of pathologic voices based on voiced/unvoiced distinction and fundamental frequency analysis of sustained vowels. Because of the high amount of noisy components and the increasing aperiodicity of highly pathologic voices, a fully automatic analysis of fundamental frequency is difficult. We introduce a purely data-driven system for the acoustic analysis of pathologic voices based on recordings of a standard text. Short-time segments of the speech signal are analyzed in the spectral domain, and speaker models based on this information are built. These speaker models act as a clustered representation of the acoustic properties of a person's voice and are thus characteristic for speakers with different kinds and degrees of pathologic conditions. The system is evaluated on two different data sets with speakers reading standardized texts. One data set contains 77 speakers after laryngeal cancer treated with partial removal of the larynx. The other data set contains 54 totally laryngectomized patients, equipped with a Provox shunt valve. Each speaker was rated by five expert listeners regarding three different criteria: strain, voice quality, and speech intelligibility. We show correlations for each data set with r and ρ≥0.8 between the automatic system and the mean value of the five raters. The interrater correlation of one rater to the mean value of the remaining raters is in the same range. We thus assume that for selected evaluation criteria, the system can serve as a validated objective support for acoustic voice and speech analysis. Copyright © 2012 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

  6. Operator modeling in commerical aviation: Cognitive models, intelligent displays, and pilot's assistants

    Science.gov (United States)

    Govindaraj, T.; Mitchell, C. M.

    1994-01-01

    One of the goals of the National Aviation Safety/Automation program is to address the issue of human-centered automation in the cockpit. Human-centered automation is automation that, in the cockpit, enhances or assists the crew rather than replacing them. The Georgia Tech research program focused on this general theme, with emphasis on designing a computer-based pilot's assistant, intelligent (i.e, context-sensitive) displays, and an intelligent tutoring system for understanding and operating the autoflight system. In particular, the aids and displays were designed to enhance the crew's situational awareness of the current state of the automated flight systems and to assist the crew's situational awareness of the current state of the automated flight systems and to assist the crew in coordinating the autoflight system resources. The activities of this grant included: (1) an OFMspert to understand pilot navigation activities in a 727 class aircraft; (2) an extension of OFMspert to understand mode control in a glass cockpit, Georgia Tech Crew Activity Tracking System (GT-CATS); (3) the design of a training system to teach pilots about the vertical navigation portion of the flight management system -VNAV Tutor; and (4) a proof-of-concept display, using existing display technology, to facilitate mode awareness, particularly in situations in which controlled flight into terrain (CFIT) is a potential.

  7. A prediction model based on an artificial intelligence system for moderate to severe obstructive sleep apnea.

    Science.gov (United States)

    Sun, Lei Ming; Chiu, Hung-Wen; Chuang, Chih Yuan; Liu, Li

    2011-09-01

    Obstructive sleep apnea (OSA) is a major concern in modern medicine; however, it is difficult to diagnose. Screening questionnaires such as the Berlin questionnaire, Rome questionnaire, and BASH'IM score are used to identify patients with OSA. However, the sensitivity and specificity of these tools are not satisfactory. We aim to introduce an artificial intelligence method to screen moderate to severe OSA patients (apnea-hypopnea index ≧15). One hundred twenty patients were asked to complete a newly developed questionnaire before undergoing an overnight polysomnography (PSG) study. One hundred ten validated questionnaires were enrolled in this study. Genetic algorithm (GA) was used to build the five best models based on these questionnaires. The same data were analyzed with logistic regression (LR) for comparison. The sensitivity of the GA models varied from 81.8% to 88.0%, with a specificity of 95% to 97%. On the other hand, the sensitivity and specificity of the LR model were 55.6% and 57.9%, respectively. GA provides a good solution to build models for screening moderate to severe OSA patients, who require PSG evaluation and medical intervention. The questionnaire did not require any special biochemistry data and was easily self-administered. The sensitivity and specificity of the GA models are satisfactory and may improve when more patients are recruited.

  8. Structural Equation Modeling of Classification Managers Based on the Communication Skills and Cultural Intelligence in Sport Organizations

    Directory of Open Access Journals (Sweden)

    Rasool NAZARI

    2015-03-01

    Full Text Available The purpose of this research is to develop structural equation model category managers on communication skills and cultural intelligence agencies had Isfahan Sports. Hence study was of structural equation modeling. The statistical population of this research formed the provincial sports administrators that according formal statistical was 550 people. Research sample size the sample of 207subjects was randomly selected. Cochran's sample size formula was used to determine. Measuring research and Communication Skills (0.81, Cultural Intelligence Scale (0.85 category manager's questionnaire (0.86, respectively. For analysis descriptive and inferential statistics SPSS and LISREL was used. Model results, communication skills, cultural intelligence and athletic directors classification of the fit was good (RMSEA=0.037, GFI= 0.902, AGFI= 0.910, NFT= 0.912. The prerequisite for proper planning to improve communication skills and cultural intelligence managers as influencing exercise essential while the authorial shave the right to choose directors analyst and intuitive strategies for management position shave because it looks better with the managers can be expected to exercise a clearer perspective.

  9. Application of a short-time version of the Equalization-Cancellation model to speech intelligibility experiments with speech maskers.

    Science.gov (United States)

    Wan, Rui; Durlach, Nathaniel I; Colburn, H Steven

    2014-08-01

    A short-time-processing version of the Equalization-Cancellation (EC) model of binaural processing is described and applied to speech intelligibility tasks in the presence of multiple maskers, including multiple speech maskers. This short-time EC model, called the STEC model, extends the model described by Wan et al. [J. Acoust. Soc. Am. 128, 3678-3690 (2010)] to allow the EC model's equalization parameters τ and α to be adjusted as a function of time, resulting in improved masker cancellation when the dominant masker location varies in time. Using the Speech Intelligibility Index, the STEC model is applied to speech intelligibility with maskers that vary in number, type, and spatial arrangements. Most notably, when maskers are located on opposite sides of the target, this STEC model predicts improved thresholds when the maskers are modulated independently with speech-envelope modulators; this includes the most relevant case of independent speech maskers. The STEC model describes the spatial dependence of the speech reception threshold with speech maskers better than the steady-state model. Predictions are also improved for independently speech-modulated noise maskers but are poorer for reversed-speech maskers. In general, short-term processing is useful, but much remains to be done in the complex task of understanding speech in speech maskers.

  10. 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

  11. The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

    Science.gov (United States)

    Rice, Amanda; Parris, Frank; Nerren, Philip

    2000-01-01

    Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and

  12. Spatiotemporal groundwater level modeling using hybrid artificial intelligence-meshless method

    Science.gov (United States)

    Nourani, Vahid; Mousavi, Shahram

    2016-05-01

    Uncertainties of the field parameters, noise of the observed data and unknown boundary conditions are the main factors involved in the groundwater level (GL) time series which limit the modeling and simulation of GL. This paper presents a hybrid artificial intelligence-meshless model for spatiotemporal GL modeling. In this way firstly time series of GL observed in different piezometers were de-noised using threshold-based wavelet method and the impact of de-noised and noisy data was compared in temporal GL modeling by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). In the second step, both ANN and ANFIS models were calibrated and verified using GL data of each piezometer, rainfall and runoff considering various input scenarios to predict the GL at one month ahead. In the final step, the simulated GLs in the second step of modeling were considered as interior conditions for the multiquadric radial basis function (RBF) based solve of governing partial differential equation of groundwater flow to estimate GL at any desired point within the plain where there is not any observation. In order to evaluate and compare the GL pattern at different time scales, the cross-wavelet coherence was also applied to GL time series of piezometers. The results showed that the threshold-based wavelet de-noising approach can enhance the performance of the modeling up to 13.4%. Also it was found that the accuracy of ANFIS-RBF model is more reliable than ANN-RBF model in both calibration and validation steps.

  13. 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.

  14. Application of Intelligence Based Genetic Algorithm for Job Sequencing Problem on Parallel Mixed-Model Assembly Line

    Directory of Open Access Journals (Sweden)

    A. Norozi

    2010-01-01

    Full Text Available Problem statement: In the area of globalization the degree of competition in the market increased and many companies attempted to manufacture the products efficiently to overcome the challenges faced. Approach: Mixed model assembly line was able to provide continuous flow of material and flexibility with regard to model change. The problem under study attempted to describe the mathematical programming limitation for minimizing the overall make-span and balancing objective for set of parallel lines. Results: A proposed mixed-integer model only able to find the best job sequence in each line to meet the problem objectives for the given number of job allotted to each line. Hence using the proposed mathematical model for large size problem was time consuming and inefficient as so many job allocation values should be checked. This study presented an intelligence based genetic algorithm approach to optimize the considered problem objectives through reducing the problem complexity. A heuristic algorithm was introduced to generate the initial population for intelligence based genetic algorithm. Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. By this means, intelligence based genetic algorithm only concentrated on those initial populations that produce better solutions instead of probing the entire search space. Conclusion/Recommendations: The results obtained from intelligence based genetic algorithm were used as an initial point for fine-tuning by simulated annealing to increase the quality of solution. In order to check the capability of proposed algorithm, several experimentations on the set of problems were done. As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.

  15. A Study on Intelligent User-Centric Logistics Service Model Using Ontology

    Directory of Open Access Journals (Sweden)

    Saraswathi Sivamani

    2014-01-01

    Full Text Available Much research has been undergone in the smart logistics environment for the prompt delivery of the product in the right place at the right time. Most of the services were based on time management, routing technique, and location based services. The services in the recent logistics environment aim for situation based logistics service centered around the user by utilizing various information technologies such as mobile devices, computer systems, and GPS. This paper proposes a smart logistics service model for providing user-centric intelligent logistics service by utilizing smartphones in a smart environment. We also develop an OWL based ontology model for the smart logistics for the better understanding among the context information. In addition to basic delivery information, the proposed service model makes use of the location and situation information of the delivery vehicle and user, to draw the route information according to the user’s requirement. With the increase of internet usage, the real-time situations are received which helps to create a more reliable relationship, owing to the Internet of Things. Through this service model, it is possible to engage in the development of various IT and logistics convergence services based on situation information between the deliverer and user which occurs in real time.

  16. HCCI Intelligent Rapid Modeling by Artificial Neural Network and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    AbdoulAhad Validi

    2012-01-01

    Full Text Available A Dynamic model of Homogeneous Charge Compression Ignition (HCCI, based on chemical kinetics principles and artificial intelligence, is developed. The model can rapidly predict the combustion probability, thermochemistry properties, and exact timing of the Start of Combustion (SOC. A realization function is developed on the basis of the Sandia National Laboratory chemical kinetics model, and GRI3.0 methane chemical mechanism. The inlet conditions are optimized by Genetic Algorithm (GA, so that combustion initiates and SOC timing posits in the desired crank angle. The best SOC timing to achieve higher performance and efficiency in HCCI engines is between 5 and 15 degrees crank angle (CAD after top dead center (TDC. To achieve this SOC timing, in the first case, the inlet temperature and equivalence ratio are optimized simultaneously and in the second case, compression ratio is optimized by GA. The model’s results are validated with previous works. The SOC timing can be predicted in less than 0.01 second and the CPU time savings are encouraging. This model can successfully be used for real engine control applications.

  17. AUTOMATIC TOPOLOGY DERIVATION FROM IFC BUILDING MODEL FOR IN-DOOR INTELLIGENT NAVIGATION

    Directory of Open Access Journals (Sweden)

    S. J. Tang

    2015-05-01

    Full Text Available With the goal to achieve an accuracy navigation within the building environment, it is critical to explore a feasible way for building the connectivity relationships among 3D geographical features called in-building topology network. Traditional topology construction approaches for indoor space always based on 2D maps or pure geometry model, which remained information insufficient problem. Especially, an intelligent navigation for different applications depends mainly on the precise geometry and semantics of the navigation network. The trouble caused by existed topology construction approaches can be smoothed by employing IFC building model which contains detailed semantic and geometric information. In this paper, we present a method which combined a straight media axis transformation algorithm (S-MAT with IFC building model to reconstruct indoor geometric topology network. This derived topology aimed at facilitating the decision making for different in-building navigation. In this work, we describe a multi-step deviation process including semantic cleaning, walkable features extraction, Multi-Storey 2D Mapping and S-MAT implementation to automatically generate topography information from existing indoor building model data given in IFC.

  18. Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    M. Sudha

    2015-12-01

    Full Text Available Uncertain atmosphere is a prevalent factor affecting the existing prediction approaches. Rough set and fuzzy set theories as proposed by Pawlak and Zadeh have become an effective tool for handling vagueness and fuzziness in the real world scenarios. This research work describes the impact of Hybrid Intelligent System (HIS for strategic decision support in meteorology. In this research a novel exhaustive search based Rough set reduct Selection using Genetic Algorithm (RSGA is introduced to identify the significant input feature subset. The proposed model could identify the most effective weather parameters efficiently than other existing input techniques. In the model evaluation phase two adaptive techniques were constructed and investigated. The proposed Artificial Neural Network based on Back Propagation learning (ANN-BP and Adaptive Neuro Fuzzy Inference System (ANFIS was compared with existing Fuzzy Unordered Rule Induction Algorithm (FURIA, Structural Learning Algorithm on Vague Environment (SLAVE and Particle Swarm OPtimization (PSO. The proposed rainfall prediction models outperformed when trained with the input generated using RSGA. A meticulous comparison of the performance indicates ANN-BP model as a suitable HIS for effective rainfall prediction. The ANN-BP achieved 97.46% accuracy with a nominal misclassification rate of 0.0254 %.

  19. Intelligence and Metacognition as Predictors of Foreign Language Achievement: A Structural Equation Modeling Approach

    Science.gov (United States)

    Pishghadam, Reza; Khajavy, Gholam Hassan

    2013-01-01

    This study examined the role of metacognition and intelligence in foreign language achievement on a sample of 143 Iranian English as a Foreign Language (EFL) learners. Participants completed Raven's Advanced Progressive Matrices as a measure of intelligence, and Metacognitive Awareness Inventory as a measure of metacognition. Learners' scores at…

  20. Intelligence and Metacognition as Predictors of Foreign Language Achievement: A Structural Equation Modeling Approach

    Science.gov (United States)

    Pishghadam, Reza; Khajavy, Gholam Hassan

    2013-01-01

    This study examined the role of metacognition and intelligence in foreign language achievement on a sample of 143 Iranian English as a Foreign Language (EFL) learners. Participants completed Raven's Advanced Progressive Matrices as a measure of intelligence, and Metacognitive Awareness Inventory as a measure of metacognition. Learners' scores at…

  1. Binaural Model-Based Speech Intelligibility Enhancement and Assessment in Hearing Aids

    NARCIS (Netherlands)

    Schlesinger, A.

    2012-01-01

    The enhancement of speech intelligibility in noise is still the main subject in hearing aid research. Based on the advanced results obtained with the hearing glasses, in the present research the speech intelligibility is even further improved by the application of binaural post-filters. The function

  2. Quality Model and Artificial Intelligence Base Fuel Ratio Management with Applications to Automotive Engine

    Directory of Open Access Journals (Sweden)

    Mojdeh Piran

    2014-01-01

    Full Text Available In this research, manage the Internal Combustion (IC engine modeling and a multi-input-multi-output artificial intelligence baseline chattering free sliding mode methodology scheme is developed with guaranteed stability to simultaneously control fuel ratios to desired levels under various air flow disturbances by regulating the mass flow rates of engine PFI and DI injection systems. Modeling of an entire IC engine is a very important and complicated process because engines are nonlinear, multi inputs-multi outputs and time variant. One purpose of accurate modeling is to save development costs of real engines and minimizing the risks of damaging an engine when validating controller designs. Nevertheless, developing a small model, for specific controller design purposes, can be done and then validated on a larger, more complicated model. Analytical dynamic nonlinear modeling of internal combustion engine is carried out using elegant Euler-Lagrange method compromising accuracy and complexity. A baseline estimator with varying parameter gain is designed with guaranteed stability to allow implementation of the proposed state feedback sliding mode methodology into a MATLAB simulation environment, where the sliding mode strategy is implemented into a model engine control module (“software”. To estimate the dynamic model of IC engine fuzzy inference engine is applied to baseline sliding mode methodology. The fuzzy inference baseline sliding methodology performance was compared with a well-tuned baseline multi-loop PID controller through MATLAB simulations and showed improvements, where MATLAB simulations were conducted to validate the feasibility of utilizing the developed controller and state estimator for automotive engines. The proposed tracking method is designed to optimally track the desired FR by minimizing the error between the trapped in-cylinder mass and the product of the desired FR and fuel mass over a given time interval.

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

    Science.gov (United States)

    Khalid, Mohammad Hassan; Kazemi, Pezhman; Perez-Gandarillas, Lucia; Michrafy, Abderrahim; Szlęk, Jakub; Jachowicz, Renata; Mendyk, Aleksander

    2017-01-01

    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 behavior when presented with a challenging external validation data set (best achieved symbolic regression: NRMSE =3%). Symbolic regression demonstrates the transition from the black box modeling paradigm to more transparent predictive models. Predictive performance and feature selection behavior of CI models hints at the most important variables within this factor space.

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

    Science.gov (United States)

    Khalid, Mohammad Hassan; Kazemi, Pezhman; Perez-Gandarillas, Lucia; Michrafy, Abderrahim; Szlęk, Jakub; Jachowicz, Renata; Mendyk, Aleksander

    2017-01-01

    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 behavior when presented with a challenging external validation data set (best achieved symbolic regression: NRMSE =3%). Symbolic regression demonstrates the transition from the black box modeling paradigm to more transparent predictive models. Predictive performance and feature selection behavior of CI models hints at the most important variables within this factor space. PMID:28138223

  5. Modeling the binding affinity of structurally diverse industrial chemicals to carbon using the artificial intelligence approaches.

    Science.gov (United States)

    Gupta, Shikha; Basant, Nikita; Rai, Premanjali; Singh, Kunwar P

    2015-11-01

    Binding affinity of chemical to carbon is an important characteristic as it finds vast industrial applications. Experimental determination of the adsorption capacity of diverse chemicals onto carbon is both time and resource intensive, and development of computational approaches has widely been advocated. In this study, artificial intelligence (AI)-based ten different qualitative and quantitative structure-property relationship (QSPR) models (MLPN, RBFN, PNN/GRNN, CCN, SVM, GEP, GMDH, SDT, DTF, DTB) were established for the prediction of the adsorption capacity of structurally diverse chemicals to activated carbon following the OECD guidelines. Structural diversity of the chemicals and nonlinear dependence in the data were evaluated using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. The generalization and prediction abilities of the constructed models were established through rigorous internal and external validation procedures performed employing a wide series of statistical checks. In complete dataset, the qualitative models rendered classification accuracies between 97.04 and 99.93%, while the quantitative models yielded correlation (R(2)) values of 0.877-0.977 between the measured and the predicted endpoint values. The quantitative prediction accuracies for the higher molecular weight (MW) compounds (class 4) were relatively better than those for the low MW compounds. Both in the qualitative and quantitative models, the Polarizability was the most influential descriptor. Structural alerts responsible for the extreme adsorption behavior of the compounds were identified. Higher number of carbon and presence of higher halogens in a molecule rendered higher binding affinity. Proposed QSPR models performed well and outperformed the previous reports. A relatively better performance of the ensemble learning models (DTF, DTB) may be attributed to the strengths of the bagging and boosting algorithms which enhance the predictive accuracies. The

  6. Humanoid Intelligent Management System

    Institute of Scientific and Technical Information of China (English)

    DU Jun-ping; TU Xu-yan

    2004-01-01

    This paper proposes a concept and design strategy for the humanoid intelligent management system (HIMS) based on artificial life. Various topics are discussed including the design method and implementation techniques for the dual management scheme (DMS), humanoid intelligent management model (HIMM), central-decentralized management pattern, and multi-grade coordination function.

  7. Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

    Directory of Open Access Journals (Sweden)

    Lakshmi Pathak

    Full Text Available Cholesterol oxidase (COD is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM, artificial neural network (ANN and genetic algorithm (GA have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500.

  8. Tele-Immersive Interaction with Intelligent Virtual Agents Based on Real-Time 3D Modeling

    Directory of Open Access Journals (Sweden)

    Shujun Zhang

    2012-02-01

    Full Text Available To enable intelligent agents interacting smoothly with human users, researchers have been deploying novel interaction modalities (e.g. non-verbal cue, vision and touch in addition to agents’ conversational skills. Models of multi-modality interaction can enhance agents’ real-time perception, cognition and reaction towards the user. In this paper we report a novel tele-immersive interaction system developed using real-time 3D modelling techniques. In such system user’s full body is reconstructed using multi-view cameras and CUDA based visual hull reconstruction algorithm. User’s mesh model is then loaded into a virtual environment for interacting with an autonomous agent. Technical details and initial results of the system are illustrated in this paper. Following that a novel interaction scenario is proposed which links the virtual agent with a remote physical robot who takes the role of mediating interactions between two geographically separated users. Finally we discuss in depth the implications of such human-agent interaction and possible future improvements and directions.

  9. Student Modelling in an Intelligent Tutoring System for the Passive Voice of English Language

    Directory of Open Access Journals (Sweden)

    Dimitris Maras

    2000-01-01

    Full Text Available This paper describes an intelligent multimedia tutoring system for the passive voice of the English grammar. The system may be used to present theoretical issues about the passive voice and to provide exercises that the student may solve. The main focus of the tutor is on the student's error diagnosis process, which is performed by the student modelling component. When the student types the solution to an exercise, the system examines the correctness of the answer. If the student's answer has been erroneous it attempts to diagnose the underlying misconception of the mistake. In order to provide individualised help, the system holds a profile for every student, the long term student model. The student’s progress and his/her usual mistakes are recorded to this long term student model. This kind of information is used for the individualised error diagnosis of the student in subsequent sessions. In addition, the information stored about the student can also be used for the resolution of an arising ambiguity, as to what the underlying cause of a student error has been.

  10. Risk modelling of food fraud motivation:'NSF fraud protection model' intelligent risk model scoping project FS 246004: final report

    OpenAIRE

    Jack, Lisa

    2015-01-01

    Following the detection of horse meat in beef products, the project considered food fraud risk with a focus on anti-fraud tools and intelligence gathering from both the food and financial sector. It developed a framework that was tested by evaluation by stakeholders.

  11. Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

    Science.gov (United States)

    Taylan, Osman

    2017-02-01

    High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.

  12. Towards an intelligent learning management system under blended learning trends, profiles and modeling perspectives

    CERN Document Server

    Dias, Sofia B; Hadjileontiadis, Leontios J

    2013-01-01

    This book offers useful information that evokes initiatives towards rethinking of the value, efficiency, inclusiveness, effectiveness and personalization of the intelligent learning management systems-based blended-learning environment.

  13. A Simple Correlation-Based Model of Intelligibility for Nonlinear Speech Enhancement and Separation

    DEFF Research Database (Denmark)

    Boldt, Jesper; Ellis, Daniel P. W.

    2009-01-01

    propose a measure based on the simi- larity between the time-varying spectral envelopes of target speech and system output, as measured by correlation. As with previous correlation-based intelligibility measures, our system can broadly match subjective intelligibility for a range of enhanced signals. Our...... system, however, is notably simpler and we explain the practical motivation behind each stage. This measure, freely available as a small Matlab implementation, can provide a more meaningful eval- uation measure for nonlinear speech enhancement systems, as well as providing a transparent objective......Applying a binary mask to a pure noise signal can result in speech that is highly intelligible, despite the absence of any of the target speech signal. Therefore, to estimate the intelligibility benefit of highly nonlinear speech enhancement techniques, we contend that SNR is not useful; instead we...

  14. Business intelligence

    Directory of Open Access Journals (Sweden)

    Cebotarean Elena

    2011-02-01

    Full Text Available Business intelligence (BI refers to computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes. BI technologies provide historical, current, and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, business performance management, benchmarking, text mining, and predictive analytics. Business intelligence aims to support better business decision-making. Thus a BI system can be called a decision support system (DSS. Though the term business intelligence is sometimes used as a synonym for competitive intelligence, because they both support decision making, BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes and disseminates information with a topical focus on company competitors. Business intelligence understood broadly can include the subset of competitive intelligence.

  15. Artificial Intelligence.

    Science.gov (United States)

    Waltz, David L.

    1982-01-01

    Describes kinds of results achieved by computer programs in artificial intelligence. Topics discussed include heuristic searches, artificial intelligence/psychology, planning program, backward chaining, learning (focusing on Winograd's blocks to explore learning strategies), concept learning, constraint propagation, language understanding…

  16. Artificial intelligence for the modeling and control of combustion processes: a review

    Energy Technology Data Exchange (ETDEWEB)

    Soteris A. Kalogirou, [Higher Technical Institute, Nicosia (Cyprus). Department of Mechanical Engineering

    2003-07-01

    Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. AI systems comprise areas like, expert systems, artificial neural networks, genetic algorithms, fuzzy logic and various hybrid systems, which combine two or more techniques. The major objective of this paper is to illustrate how AI techniques might play an important role in modeling and prediction of the performance and control of combustion process. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in the different disciplines of combustion engineering. The various applications of AI are presented in a thematic rather than a chronological or any other order. Problems presented include two main areas: combustion systems and internal combustion (IC) engines. Combustion systems include boilers, furnaces and incinerators modeling and emissions prediction, whereas, IC engines include diesel and spark ignition engines and gas engines modeling and control. Results presented in this paper, are testimony to the potential of AI as a design tool in many areas of combustion engineering. 109 refs., 31 figs., 11 tabs.

  17. Artificial intelligence for the modeling and control of combustion processes: a review

    Energy Technology Data Exchange (ETDEWEB)

    Kalogirou, S.A. [Higher Technical Inst., Nicosia, Cyprus (Greece). Dept. of Mechanical Engineering

    2003-07-01

    Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. Al systems comprise areas like, expert systems, artificial neural networks, genetic algorithms, fuzzy logic and various hybrid systems, which combine two or more techniques. The major objective of this paper is to illustrate how Al techniques might play an important role in modeling and prediction of the performance and control of combustion process. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in the different disciplines of combustion engineering. The various applications of AI are presented in a thematic rather than a chronological or any other order. Problems presented include two main areas: combustion systems and internal combustion (IC) engines. Combustion systems include boilers, furnaces and incinerators modeling and emissions prediction, whereas, IC engines include diesel and spark ignition engines and gas engines modeling and control. Results presented in this paper, are testimony to the potential of Al as a design tool in many areas of combustion engineering. (author)

  18. Development of a Techno-economic Model of Intelligent Transportation System (ITS) for Deployment in Ghana

    DEFF Research Database (Denmark)

    Adjin, Daniel Michael Okwabi; Tadayoni, Reza

    2011-01-01

    The concept of Intelligent Transportation System (ITS) is about the development and deployment of advanced Traffic Management Systems, Traveler Information Systems, Commercial Vehicle Operations, Public and Private Transportation Systems, and Rural Transportation Systems. Several key technologies....... The results show that deployment of Intelligent Vehicle Tracking Technology (IVTT) will address the problems of inefficiencies experienced in the Ghanaian road transport haulage tracking industry. Research for ITS development and eployment in these countries should be cost effective....

  19. Employing the Intelligence Cycle Process Model Within the Homeland Security Enterprise

    Science.gov (United States)

    2013-12-01

    http:// ipv6 .dhs.gov/journal/leadership/labels/Intelligence%20and%20Analysis%20Directorate.html. 73 The DHS also supports formal degree granting...institutions, there are far more intelligence focused training opportunities presented to state and local officials through on-site mobile training events...Institute of Intergovernmental Research delivers on-site mobile training opportunities to the National Network, as well as the state and local members of

  20. Nontraditional Intelligence Testing: Samples of Humorous Instruments.

    Science.gov (United States)

    Lemire, David

    In keeping with a model of intelligence that identifies at least 12 intelligence "talents," formal and informal intelligence or talent assessments have been developed. This paper presents some of these informal instruments that can be used to assess convergent and divergent forms of intelligence. These nontraditional instruments have been designed…

  1. Exploring emotional intelligence. Implications for nursing leaders.

    Science.gov (United States)

    Vitello-Cicciu, Joan M

    2002-04-01

    Emotional intelligence is being touted in the popular literature as an important characteristic for successful leaders. However, caution needs to be exercised regarding the connection between emotional intelligence and workplace success. The author contrasts 2 current models of emotional intelligence, the measurements being used, and the ability of emotional intelligence to predict success. Implications for the workplace are discussed.

  2. 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…

  3. Application of an Intelligent Fuzzy Regression Algorithm in Road Freight Transportation Modeling

    Directory of Open Access Journals (Sweden)

    Pooya Najaf

    2013-07-01

    Full Text Available Road freight transportation between provinces of a country has an important effect on the traffic flow of intercity transportation networks. Therefore, an accurate estimation of the road freight transportation for provinces of a country is so crucial to improve the rural traffic operation in a large scale management. Accordingly, the focused case study database in this research is the information related to Iran’s provinces in the year 2008. Correlation between road freight transportation with variables such as transport cost and distance, population, average household income and Gross Domestic Product (GDP of each province is calculated. Results clarify that the population is the most effective factor in the prediction of provinces’ transported freight. Linear Regression Model (LRM is calibrated based on the population variable, and afterwards Fuzzy Regression Algorithm (FRA is generated on the basis of the LRM. The proposed FRA is an intelligent modified algorithm with an accurate prediction and fitting ability. This methodology can be significantly useful in macro-level planning problems where decreasing prediction error values is one of the most important concerns for decision makers. In addition, Back-Propagation Neural Network (BPNN is developed to evaluate the prediction capability of the models and to be compared with FRA. According to the final results, the modified FRA estimates road freight transportation values more accurately than the BPNN and LRM. Finally, in order to predict the road freight transportation values, the reliability of the calibrated models is analyzed using the information of the year 2009. Results show higher reliability for the proposed modified FRA.

  4. The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

    Science.gov (United States)

    Rice, Amanda; Parris, Frank; Nerren, Philip

    2000-01-01

    Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and

  5. The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

    Science.gov (United States)

    Rice, Amanda; Parris, Frank; Nerren, Philip

    2000-01-01

    Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and

  6. Comparison of intelligent systems, artificial neural networks and neural fuzzy model for prediction of gas hydrate formation rate

    Directory of Open Access Journals (Sweden)

    Mohammad Javad Jalalnezhad

    2014-05-01

    Full Text Available The main objective of this study was to present a novel approach for predication of gas hydrate formation rate based on the Intelligent Systems. Using a data set including about 470 data obtained from flow tests in a mini-loop apparatus, different predictive models were developed. From the results predicted by these models, it can be pointed out that the developed models can be used as powerful tools for prediction of gas hydrate formation rate with total errors of less than 4%.

  7. Intelligence Ethics:

    DEFF Research Database (Denmark)

    Rønn, Kira Vrist

    2016-01-01

    Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...

  8. Intelligent non-linear modelling of an industrial winding process using recurrent local linear neuro-fuzzy networks

    Institute of Scientific and Technical Information of China (English)

    Hasan ABBASI NOZARI; Hamed DEHGHAN BANADAKI; Mohammad MOKHTARE; Somaveh HEKMATI VAHED

    2012-01-01

    This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system.A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT),which is an incremental tree-based learning algorithm.The proposed NF models are compared with other known intelligent identifiers,namely multilayer perceptron (MLP) and radial basis function (RBF).Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system.Experimental results show the effectiveness of our proposed NF modelling approach.

  9. Model of facilitation of emotional intelligence to promote wholeness of neophyte critical care nurses in South Africa

    Directory of Open Access Journals (Sweden)

    A. Towell

    2015-06-01

    Full Text Available This study was undertaken in order to develop a model of facilitation of emotional intelligence to promote wholeness in neophyte critical care nurses in South Africa. A theory-generative, explorative, descriptive, contextual research design was used. The model was developed utilising the four steps of theory generation as proposed by Dickoff, James, and Wiedenbach (1968, Chinn and Kramer (2011 and Walker and Avant (2011. Step one dealt with the empirical phase in which the concepts were distilled. The facilitation of inherent affective and mental resourcefulness and resilience was the main concept of the model. Step two comprised the definition and classification of central and related concepts. Step three provides a description of the model. The model operates in three phases namely the dependent phase, partially dependent phase and the independent phase. Step four entailed the description of guidelines for operationalizing the model. During the three phases of the model a new nurse who starts to work in critical care moves from a latent ability to develop an inherent affective and mental resourcefulness and resilience to a state of developing an inherent affective and mental resourcefulness and resilience. This model provides a structured framework for the facilitation of emotional intelligence (EI to promote wholeness in nurses who commence to work in critical care units.

  10. The necessities for building a model to evaluate Business Intelligence projects- Literature Review

    CERN Document Server

    Farrokhi, Vahid

    2012-01-01

    In recent years Business Intelligence (BI) systems have consistently been rated as one of the highest priorities of Information Systems (IS) and business leaders. BI allows firms to apply information for supporting their processes and decisions by combining its capabilities in both of organizational and technical issues. Many of companies are being spent a significant portion of its IT budgets on business intelligence and related technology. Evaluation of BI readiness is vital because it serves two important goals. First, it shows gaps areas where company is not ready to proceed with its BI efforts. By identifying BI readiness gaps, we can avoid wasting time and resources. Second, the evaluation guides us what we need to close the gaps and implement BI with a high probability of success. This paper proposes to present an overview of BI and necessities for evaluation of readiness. Key words: Business intelligence, Evaluation, Success, Readiness

  11. Eye gaze in intelligent user interfaces gaze-based analyses, models and applications

    CERN Document Server

    Nakano, Yukiko I; Bader, Thomas

    2013-01-01

    Remarkable progress in eye-tracking technologies opened the way to design novel attention-based intelligent user interfaces, and highlighted the importance of better understanding of eye-gaze in human-computer interaction and human-human communication. For instance, a user's focus of attention is useful in interpreting the user's intentions, their understanding of the conversation, and their attitude towards the conversation. In human face-to-face communication, eye gaze plays an important role in floor management, grounding, and engagement in conversation.Eye Gaze in Intelligent User Interfac

  12. Analysis and Modeling of the Galvanic Skin Response Spontaneous Component in the context of Intelligent Biofeedback Systems Development

    Science.gov (United States)

    Unakafov, A.

    2009-01-01

    The paper presents an approach to galvanic skin response (GSR) spontaneous component analysis and modeling. In the study a classification of biofeedback training methods is given, importance of intelligent methods development is shown. The INTENS method, which is perspective for intellectualization, is presented. An important problem of biofeedback training method intellectualization - estimation of the GSR spontaneous component - is solved in the main part of the work. Its main characteristics are described; results of GSR spontaneous component modeling are shown. Results of small research of an optimum material for GSR probes are presented.

  13. 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...

  14. Commitment to the Study of International Business and Cultural Intelligence: A Multilevel Model

    Science.gov (United States)

    Ramsey, Jase R.; Barakat, Livia L.; Aad, Amine Abi

    2014-01-01

    Adopting a multilevel theoretical framework, we examined how metacognitive and motivational cultural intelligence influence an individual's commitment to the study of international business (IB). Data from 292 undergraduate and graduate business students nested in 12 U.S. business school classes demonstrated that individuals' metacognitive and…

  15. Commitment to the Study of International Business and Cultural Intelligence: A Multilevel Model

    Science.gov (United States)

    Ramsey, Jase R.; Barakat, Livia L.; Aad, Amine Abi

    2014-01-01

    Adopting a multilevel theoretical framework, we examined how metacognitive and motivational cultural intelligence influence an individual's commitment to the study of international business (IB). Data from 292 undergraduate and graduate business students nested in 12 U.S. business school classes demonstrated that individuals'…

  16. An Agent-Based Model for the Development of Intelligent Mobile Services

    NARCIS (Netherlands)

    Koch, F.L.

    2009-01-01

    The next generation of mobile services must invisible, convenient, and useful. It requires new techniques to design and develop mobile computing applications, based on user-centred, environment-aware, adaptive behaviour. I propose an alternative technology for the development of intelligent mobile s

  17. Developing a fluid intelligence scale through a combination of Rasch modeling and cognitive psychology.

    Science.gov (United States)

    Primi, Ricardo

    2014-09-01

    Ability testing has been criticized because understanding of the construct being assessed is incomplete and because the testing has not yet been satisfactorily improved in accordance with new knowledge from cognitive psychology. This article contributes to the solution of this problem through the application of item response theory and Susan Embretson's cognitive design system for test development in the development of a fluid intelligence scale. This study is based on findings from cognitive psychology; instead of focusing on the development of a test, it focuses on the definition of a variable for the creation of a criterion-referenced measure for fluid intelligence. A geometric matrix item bank with 26 items was analyzed with data from 2,797 undergraduate students. The main result was a criterion-referenced scale that was based on information from item features that were linked to cognitive components, such as storage capacity, goal management, and abstraction; this information was used to create the descriptions of selected levels of a fluid intelligence scale. The scale proposed that the levels of fluid intelligence range from the ability to solve problems containing a limited number of bits of information with obvious relationships through the ability to solve problems that involve abstract relationships under conditions that are confounded with an information overload and distraction by mixed noise. This scale can be employed in future research to provide interpretations for the measurements of the cognitive processes mastered and the types of difficulty experienced by examinees.

  18. Personality Traits and General Intelligence as Predictors of Academic Performance: A Structural Equation Modelling Approach

    Science.gov (United States)

    Rosander, Pia; Backstrom, Martin; Stenberg, Georg

    2011-01-01

    The aim of the present study was to investigate the extent to which personality traits, after controlling for general intelligence, predict academic performance in different school subjects. Upper secondary school students in Sweden (N=315) completed the Wonderlic IQ test (Wonderlic, 1992) and the IPIP-NEO-PI test (Goldberg, 1999). A series of…

  19. A 5 generation reference model for intelligent cars in the Twenty-First Century

    NARCIS (Netherlands)

    Sol, E.J.; Arem, B. van; Hagemeier, F.

    2008-01-01

    Sensors and communication electronics will ease the motorist’s life, improve the utilisation of road capacity and reduce emission levels in the coming decades. But all in its own time. Replacing technology is a gradual, evolutionary process. This paper describes the possible development of intellige

  20. Research contributions to the modelling and design of Intelligent Manufacturing Systems

    DEFF Research Database (Denmark)

    Langer, Gilad; Sørensen, Christian; Stylios, C.;

    1999-01-01

    This joint paper is the result of the work of cluster 3-4 within the Esprit WG no. 21955 on Intelligent Manufacturing Systems (IMS) working group. The paper conveys the results of a co-operative research effort between LAR Patras (Greece), DTU (Denmark), CRAN/GSIP (France) and Aachen WZL (Germany...

  1. Personality Traits and General Intelligence as Predictors of Academic Performance: A Structural Equation Modelling Approach

    Science.gov (United States)

    Rosander, Pia; Backstrom, Martin; Stenberg, Georg

    2011-01-01

    The aim of the present study was to investigate the extent to which personality traits, after controlling for general intelligence, predict academic performance in different school subjects. Upper secondary school students in Sweden (N=315) completed the Wonderlic IQ test (Wonderlic, 1992) and the IPIP-NEO-PI test (Goldberg, 1999). A series of…

  2. Emotional Intelligence: Theory and Description--A Competency Model for Interpersonal Effectiveness

    Science.gov (United States)

    Kunnanatt, James Thomas

    2008-01-01

    Purpose: Despite the crucial role that emotional intelligence (EI) could play in improving individuals' performance and career prospects in organizations, employees, executives and career professionals across the world are still in search of practical frameworks for understanding the concept. This is because EI research outputs from academics…

  3. Commitment to the Study of International Business and Cultural Intelligence: A Multilevel Model

    Science.gov (United States)

    Ramsey, Jase R.; Barakat, Livia L.; Aad, Amine Abi

    2014-01-01

    Adopting a multilevel theoretical framework, we examined how metacognitive and motivational cultural intelligence influence an individual's commitment to the study of international business (IB). Data from 292 undergraduate and graduate business students nested in 12 U.S. business school classes demonstrated that individuals' metacognitive and…

  4. Reproducing the Wechsler Intelligence Scale for Children-Fifth Edition: Factor Model Results

    Science.gov (United States)

    Beaujean, A. Alexander

    2016-01-01

    One of the ways to increase the reproducibility of research is for authors to provide a sufficient description of the data analytic procedures so that others can replicate the results. The publishers of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) do not follow these guidelines when reporting their confirmatory factor…

  5. Joint Intelligence Operations Center (JIOC) Baseline Business Process Model & Capabilities Evaluation Methodology

    Science.gov (United States)

    2012-03-01

    Targeting Review Board OPLAN Operations Plan OPORD Operations Order OPSIT Operational Situation OSINT Open Source Intelligence OV...Analysis Evaluate FLTREPs MISREPs Unit Assign Assets Feedback Asset Shortfalls Multi-Int Collection Political & Embasy Law Enforcement HUMINT OSINT ...Embassy Information OSINT Manage Theater HUMINT Law Enforcement Collection Sort Requests Platform Information Agency Information M-I Collect

  6. Swarm Intelligence

    OpenAIRE

    Thampi, Sabu M.

    2009-01-01

    Biologically inspired computing is an area of computer science which uses the advantageous properties of biological systems. It is the amalgamation of computational intelligence and collective intelligence. Biologically inspired mechanisms have already proved successful in achieving major advances in a wide range of problems in computing and communication systems. The consortium of bio-inspired computing are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial i...

  7. Intelligent Elements for ISHM

    Science.gov (United States)

    Schmalzel, John L.; Morris, Jon; Turowski, Mark; Figueroa, Fernando; Oostdyk, Rebecca

    2008-01-01

    There are a number of architecture models for implementing Integrated Systems Health Management (ISHM) capabilities. For example, approaches based on the OSA-CBM and OSA-EAI models, or specific architectures developed in response to local needs. NASA s John C. Stennis Space Center (SSC) has developed one such version of an extensible architecture in support of rocket engine testing that integrates a palette of functions in order to achieve an ISHM capability. Among the functional capabilities that are supported by the framework are: prognostic models, anomaly detection, a data base of supporting health information, root cause analysis, intelligent elements, and integrated awareness. This paper focuses on the role that intelligent elements can play in ISHM architectures. We define an intelligent element as a smart element with sufficient computing capacity to support anomaly detection or other algorithms in support of ISHM functions. A smart element has the capabilities of supporting networked implementations of IEEE 1451.x smart sensor and actuator protocols. The ISHM group at SSC has been actively developing intelligent elements in conjunction with several partners at other Centers, universities, and companies as part of our ISHM approach for better supporting rocket engine testing. We have developed several implementations. Among the key features for these intelligent sensors is support for IEEE 1451.1 and incorporation of a suite of algorithms for determination of sensor health. Regardless of the potential advantages that can be achieved using intelligent sensors, existing large-scale systems are still based on conventional sensors and data acquisition systems. In order to bring the benefits of intelligent sensors to these environments, we have also developed virtual implementations of intelligent sensors.

  8. Modeling Mental Speed: Decomposing Response Time Distributions in Elementary Cognitive Tasks and Correlations with Working Memory Capacity and Fluid Intelligence

    Directory of Open Access Journals (Sweden)

    Florian Schmitz

    2016-10-01

    Full Text Available Previous research has shown an inverse relation between response times in elementary cognitive tasks and intelligence, but findings are inconsistent as to which is the most informative score. We conducted a study (N = 200 using a battery of elementary cognitive tasks, working memory capacity (WMC paradigms, and a test of fluid intelligence (gf. Frequently used candidate scores and model parameters derived from the response time (RT distribution were tested. Results confirmed a clear correlation of mean RT with WMC and to a lesser degree with gf. Highly comparable correlations were obtained for alternative location measures with or without extreme value treatment. Moderate correlations were found as well for scores of RT variability, but they were not as strong as for mean RT. Additionally, there was a trend towards higher correlations for slow RT bands, as compared to faster RT bands. Clearer evidence was obtained in an ex-Gaussian decomposition of the response times: the exponential component was selectively related to WMC and gf in easy tasks, while mean response time was additionally predictive in the most complex tasks. The diffusion model parsimoniously accounted for these effects in terms of individual differences in drift rate. Finally, correlations of model parameters as trait-like dispositions were investigated across different tasks, by correlating parameters of the diffusion and the ex-Gaussian model with conventional RT and accuracy scores.

  9. Modelling force deployment from army intelligence using the transportation system capability (TRANSCAP) model : a standardized approach.

    Energy Technology Data Exchange (ETDEWEB)

    Burke, J. F., Jr.; Love, R. J.; Macal, C. M.; Decision and Information Sciences

    2004-07-01

    Argonne National Laboratory (Argonne) developed the transportation system capability (TRANSCAP) model to simulate the deployment of forces from Army bases, in collaboration with and under the sponsorship of the Military Transportation Management Command Transportation Engineering Agency (MTMCTEA). TRANSCAP's design separates its pre- and post-processing modules (developed in Java) from its simulation module (developed in MODSIM III). This paper describes TRANSCAP's modelling approach, emphasizing Argonne's highly detailed, object-oriented, multilanguage software design principles. Fundamental to these design principles is TRANSCAP's implementation of an improved method for standardizing the transmission of simulated data to output analysis tools and the implementation of three Army deployment/redeployment community standards, all of which are in the final phases of community acceptance. The first is the extensive hierarchy and object representation for transport simulations (EXHORT), which is a reusable, object-oriented deployment simulation source code framework of classes. The second and third are algorithms for rail deployment operations at a military base.

  10. Artificial intelligence versus statistical modeling and optimization of continuous bead milling process for bacterial cell lysis

    Directory of Open Access Journals (Sweden)

    Shafiul Haque

    2016-11-01

    Full Text Available AbstractFor a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD was studied in a continuous bead milling process. A full factorial Response Surface Model (RSM design was employed and compared to Artificial Neural Networks coupled with Genetic Algorithm (ANN-GA. Significant process variables, cell slurry feed rate (A, bead load (B, cell load (C and run time (D, were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v, cell loading OD600 nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN coupled with GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h: 258.08, bead loading (%, v/v: 80%, cell loading (OD600 nm: 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN in combination with evolutionary optimization (GA for representing undefined biological functions which is the case for common industrial processes involving biological moieties.

  11. 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...

  12. Genes, evolution and intelligence.

    Science.gov (United States)

    Bouchard, Thomas J

    2014-11-01

    I argue that the g factor meets the fundamental criteria of a scientific construct more fully than any other conception of intelligence. I briefly discuss the evidence regarding the relationship of brain size to intelligence. A review of a large body of evidence demonstrates that there is a g factor in a wide range of species and that, in the species studied, it relates to brain size and is heritable. These findings suggest that many species have evolved a general-purpose mechanism (a general biological intelligence) for dealing with the environments in which they evolved. In spite of numerous studies with considerable statistical power, we know of very few genes that influence g and the effects are very small. Nevertheless, g appears to be highly polygenic. Given the complexity of the human brain, it is not surprising that that one of its primary faculties-intelligence-is best explained by the near infinitesimal model of quantitative genetics.

  13. Intelligent Design

    DEFF Research Database (Denmark)

    Hjorth, Poul G.

    2005-01-01

    Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig.......Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig....

  14. Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

    Directory of Open Access Journals (Sweden)

    Tang Xiaofeng

    2014-01-01

    Full Text Available The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow.

  15. Understanding Visitors’ Responses to Intelligent Transportation System in a Tourist City with a Mixed Ranked Logit Model

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2017-01-01

    Full Text Available One important function of Intelligent Transportation System (ITS applied in tourist cities is to improve visitors’ mobility by releasing real-time transportation information and then shifting tourists from individual vehicles to intelligent public transit. The objective of this research is to quantify visitors’ psychological and behavioral responses to tourism-related ITS. Designed with a Mixed Ranked Logit Model (MRLM with random coefficients that was capable of evaluating potential effects from information uncertainty and other relevant factors on tourists’ transport choices, an on-site and a subsequent web-based stated preference survey were conducted in a representative tourist city (Chengde, China. Simulated maximum-likelihood procedure was used to estimate random coefficients. Results indicate that tourists generally perceive longer travel time and longer wait time if real-time information is not available. ITS information is able to reduce tourists’ perceived uncertainty and stimulating transport modal shifts. This novel MRLM contributes a new derivation model to logit model family and for the first time proposes an applicable methodology to assess useful features of ITS for tourists.

  16. Data mining predictive models for pervasive intelligent decision support in intensive care medicine

    OpenAIRE

    Portela, Filipe; Pinto, Filipe; Santos, Manuel Filipe

    2012-01-01

    The introduction of an Intelligent Decision Support System (IDSS) in a critical area like the Intensive Medicine is a complex and difficult process. In this area, their professionals don’t have much time to document the cases, because the patient direct care is always first. With the objective to reduce significantly the manual records and, enabling, at the same time, the possibility of developing an IDSS which can help in the decision making process, all data acquisition process ...

  17. Gastroprotective effects of new diterpenoid derivatives from Azorella cuatrecasasii Mathias & Constance obtained using a β-cyclodextrin complex with microbial and chemical transformations.

    Science.gov (United States)

    Sepúlveda, Beatriz; Quispe, Cristina; Simirgiotis, Mario; García-Beltrán, Olimpo; Areche, Carlos

    2016-07-15

    Mulinane diterpenoids isolated from Azorella species have displayed gastroprotective effects in animal models. In this study we have transformed the main constituent, mulin-11,13-dien-20 oic acid from this plant using the filamentous fungus Mucor plumbeus and a β-cyclodextrin inclusion complex and we have obtained two main products with good yields (33% and 15% for compound 4 and 5, respectively) for further preparation of semisynthetic derivatives to evaluate their gastroprotective effects. In addition, one of the compounds isolated from Azorella cuatrecasasii was new (9-epi-13α-hydroxymulinene 1). Six new derivatives 4a-4c and 5a-5c were then prepared by simple chemical transformations. The structures of all compounds were elucidated by spectroscopic means based on 1D and 2D-NMR techniques. Some 8 diterpenes were evaluated for their gastroprotective effects in the ethanol/HCl-induced ulcer model in mice at 20mg/kg. The highest gastroprotective activity was shown by 7α,16-dihydroxymulin-11,13-dien-20-oic acid 5, which was higher than the reference drug lansoprazole, while 16-hydroxymulin-11,13-dien-20-oic acid 4 was as active as lansoprazole.

  18. A Study on Maneuvering Obstacle Motion State Estimation for Intelligent Vehicle Using Adaptive Kalman Filter Based on Current Statistical Model

    Directory of Open Access Journals (Sweden)

    Bao Han

    2015-01-01

    Full Text Available The obstacle motion state estimation is an essential task in intelligent vehicle. The ASCL group has developed such a system that uses a radar and GPS/INS. When running on the road, the acceleration of the vehicle is always changing, so it is hard for constant velocity (CV model and constant acceleration (CA model to describe the motion state of the vehicle. This paper introduced Current Statistical (CS model from military field, which uses the modified Rayleigh distribution to describe acceleration. The adaptive Kalman filter based on CS model was used to estimate the motion state of the target. We conducted simulation experiments and real vehicle tests, and the results showed that the estimation of position, velocity, and acceleration can be precise.

  19. TIE: an ability test of emotional intelligence

    National Research Council Canada - National Science Library

    Śmieja, Magdalena; Orzechowski, Jarosław; Stolarski, Maciej S

    2014-01-01

    The Test of Emotional Intelligence (TIE) is a new ability scale based on a theoretical model that defines emotional intelligence as a set of skills responsible for the processing of emotion-relevant information...

  20. The Internal Structure of Responses to the Trait Emotional Intelligence Questionnaire-Short Form: An Exploratory Structural Equation Modeling Approach.

    Science.gov (United States)

    Perera, Harsha N

    2015-01-01

    Notwithstanding the wide use of the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) as a brief assessment of trait emotional intelligence (TEI), the psychometric properties of this measure have not been systematically examined. This article reports on research conducted to evaluate the latent structure underlying TEIQue-SF item data and test the gender invariance of scores as critical initial steps in determining the psychometric robustness of the inventory. In doing so, the article demonstrates an application of exploratory structural equation modeling as an alternative to the more restrictive independent clusters model of confirmatory factor analysis for examining factorially complex personality data. On the basis of 476 responses to the TEIQue-SF, evidence was obtained for the multidimensionality of the inventory reflected in a retained correlated traits solution. Tests of gender invariance revealed equivalence of item factor loadings, intercepts, uniquenesses, correlated uniquenesses, and the factor variance-covariance matrix, but not latent means. Men were found to be moderately higher on self-control and sociability than women, whereas women scored marginally higher on emotionality than men. No significant gender differences were found on mean levels of well-being. The benefits of the multidimensionality of the TEIQue-SF, limitations of the study, and directions for future research are discussed.

  1. Mindfulness facets, trait emotional intelligence, emotional distress, and multiple health behaviors: A serial two-mediator model.

    Science.gov (United States)

    Jacobs, Ingo; Wollny, Anna; Sim, Chu-Won; Horsch, Antje

    2016-06-01

    In the present study, we tested a serial mindfulness facets-trait emotional intelligence (TEI)-emotional distress-multiple health behaviors mediation model in a sample of N = 427 German-speaking occupational therapists. The mindfulness facets-TEI-emotional distress section of the mediation model revealed partial mediation for the mindfulness facets Act with awareness (Act/Aware) and Accept without judgment (Accept); inconsistent mediation was found for the Describe facet. The serial two-mediator model included three mediational pathways that may link each of the four mindfulness facets with multiple health behaviors. Eight out of 12 indirect effects reached significance and fully mediated the links between Act/Aware and Describe to multiple health behaviors; partial mediation was found for Accept. The mindfulness facet Observe was most relevant for multiple health behaviors, but its relation was not amenable to mediation. Implications of the findings will be discussed.

  2. Modelling public transport passenger flows in the era of intelligent transport systems COST Action TU1004 (TransITs)

    CERN Document Server

    Noekel, Klaus

    2016-01-01

    This book shows how transit assignment models can be used to describe and predict the patterns of network patronage in public transport systems. It provides a fundamental technical tool that can be employed in the process of designing, implementing and evaluating measures and/or policies to improve the current state of transport systems within given financial, technical and social constraints. The book offers a unique methodological contribution to the field of transit assignment because, moving beyond “traditional” models, it describes more evolved variants that can reproduce: • intermodal networks with high- and low-frequency services; • realistic behavioural hypotheses underpinning route choice; • time dependency in frequency-based models; and • assumptions about the knowledge that users have of network conditions that are consistent with the present and future level of information that intelligent transport systems (ITS) can provide. The book also considers the practical perspective of practit...

  3. Pathways into psychopathology: Modeling the effects of trait emotional intelligence, mindfulness, and irrational beliefs in a clinical sample.

    Science.gov (United States)

    Petrides, K V; Gómez, María G; Pérez-González, Juan-Carlos

    2017-09-01

    We investigated possible pathways into mental illness via the combined effects of trait emotional intelligence (trait EI), mindfulness, and irrational beliefs. The sample comprised 121 psychiatric outpatients (64.5% males, mean age = 38.8 years) with a variety of formal clinical diagnoses. Psychopathology was operationalized by means of 3 distinct indicators from the Millon Clinical Multi-Axial Inventory (mild pathology, severe pathology, and clinical symptomatology). A structural equation model confirmed significant direct trait EI and mindfulness effects on irrational beliefs and psychopathology. Trait EI also had a significant indirect effect on psychopathology via mindfulness. Together, the 3 constructs accounted for 44% of the variance in psychopathology. A series of hierarchical regressions demonstrated that trait EI is a stronger predictor of psychopathology than mindfulness and irrational beliefs combined. We conclude that the identified pathways can provide the basis for the development of safe and effective responses to the ongoing mental health and overmedication crises. Self-perception constructs concerning one's beliefs about oneself have a major impact on the likelihood of developing psychopathological symptoms. Emotional perceptions captured by trait emotional intelligence were stronger predictors of psychopathology than either or both mindfulness and irrational beliefs in a clinical sample of adults. If the seed factors of psychopathology are mainly psychological, rather than mainly biological, and given that psychological constructs, like trait emotional intelligence, mindfulness, and irrational beliefs, are amenable to training and optimization, the findings herein provide the impetus for a much needed shift of emphasis from pharmacological to psychological treatments. Copyright © 2017 John Wiley & Sons, Ltd.

  4. NA22 Model Cities Project - LL244T An Intelligent Transportation System-Based Radiation Alert and Detection System

    Energy Technology Data Exchange (ETDEWEB)

    Peglow, S

    2004-02-24

    The purpose of this project was twofold: first, provide an understanding of the technical foundation and planning required for deployment of Intelligent Transportation System (ITS)-based system architectures for the protection of New York City from a terrorist attack using a vehicle-deployed nuclear device; second, work with stakeholders to develop mutual understanding of the technologies and tactics required for threat detection/identification and establish guidelines for designing operational systems and procedures. During the course of this project we interviewed and coordinated analysis with people from the New Jersey State Attorney General's office, the New Jersey State Police, the Port Authority of New York/New Jersey, the Counterterrorism Division of the New York City Police Department, the New Jersey Transit Authority, the State of New Jersey Department of Transportation, TRANSCOM and a number of contractors involved with state and federal intelligent transportation development and implementation. The basic system architecture is shown in the figure below. In an actual system deployment, radiation sensors would be co-located with existing ITS elements and the data will be sent to the Traffic Operations Center. A key element of successful system operation is the integration of vehicle data, such as license plate, EZ pass ID, vehicle type/color and radiation signature. A threat data base can also be implemented and utilized in cases where there is a suspect vehicle identified from other intelligence sources or a mobile detector system. Another key aspect of an operational architecture is the procedures used to verify the threat and plan interdiction. This was a major focus of our work and discussed later in detail. In support of the operational analysis, we developed a detailed traffic simulation model that is described extensively in the body of the report.

  5. Intelligent playgrounds

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2009-01-01

    This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

  6. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  7. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  8. Adaptive Artificial Intelligence Based Model Base Controller: Applied to Surgical Endoscopy Telemanipulator

    Directory of Open Access Journals (Sweden)

    Farzin Piltan

    2013-08-01

    Full Text Available This research involved developing a surgical robot assistant using an articulated PUMA robot running on a linear or nonlinear axis. The research concentrated on studying the artificial intelligence based switching computed torque controller to localization of an endoscopic tool. Results show that the switching artificial nonlinear control algorithm is capable to design a stable controller. For this system, error was used as the performance metric. Positioning of the endoscopic manipulator relative to the world coordinate frame was possible to within 0.05 inch. Error in maintaining a constant point in space is evident during repositioning however this was caused by limitations in the robot arm.

  9. TIS: an Intelligent Gateway Computer for information and modeling networks. Overview

    Energy Technology Data Exchange (ETDEWEB)

    Hampel, V.E.; Bailey, C.; Kawin, R.A.; Lann, N.A.; McGrogan, S.K.; Scott, W.S.; Stammers, S.M.; Thomas, J.L.

    1983-08-01

    The Technology Information System (TIS) is being used to develop software for Intelligent Gateway Computers (IGC) suitable for the prototyping of advanced, integrated information networks. Dedicated to information management, TIS leads the user to available information resources, on TIS or elsewhere, by means of a master directory and automated access procedures. Other geographically distributed information centers accessible through TIS include federal and commercial systems like DOE/RECON, NASA/RECON, DOD/DROLS, DOT/TIC, CIS, and DIALOG in the United States, the chemical information systems DARC in France, and DECHEMA in West Germany. New centers are added as required.

  10. A model of strategic intelligence of industrial property information and in the field of clean energy; Un modelo de inteligencia estrategica de la informacion y propiedad industrial en el campo de las energias limpias

    Energy Technology Data Exchange (ETDEWEB)

    Fuente O' Conor, J. L. de la

    2011-07-01

    In this article, the model Intelligence Cell, as an Internet based strategic intelligence element for the management of interim key information of a company, is presented. The model has been profusely tested for technology watch, economic intelligence, and competitive intelligence related purposes within a general framework of technology deployment in a clean and renewable focused innovation department. As a practical example, is proposed, step by step, how to launch a fully operative specialized cell for analyzing how to deal with electric mobility, battery technologies and electric car issues so that challenges, opportunities, and threats can be tracked and anticipated so that a business strategy might be established. (Author) 8 refs.

  11. Business intelligence

    National Research Council Canada - National Science Library

    Cebotarean Elena

    2011-01-01

    Business intelligence (BI) refers to computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes...

  12. 1st International Conference on Robot Intelligence Technology and Applications

    CERN Document Server

    Matson, Eric; Myung, Hyun; Xu, Peter

    2013-01-01

    In recent years, robots have been built based on cognitive architecture which has been developed to model human cognitive ability. The cognitive architecture can be a basis for intelligence technology to generate robot intelligence. In this edited book the robot intelligence is classified into six categories: cognitive intelligence, social intelligence, behavioral intelligence, ambient intelligence, collective intelligence and genetic intelligence. This classification categorizes the intelligence of robots based on the different aspects of awareness and the ability to act deliberately as a result of such awareness. This book aims at serving researchers and practitioners with a timely dissemination of the recent progress on robot intelligence technology and its applications, based on a collection of papers presented at the 1st International Conference on Robot Intelligence Technology and Applications (RiTA), held in Gwangju, Korea, December 16-18, 2012. For a better readability, this edition has the total 101 ...

  13. The location of the Trait Emotional Intelligence in the Zuckerman's Personality Model space and the role of General Intelligence and social status.

    Science.gov (United States)

    Blanco, Eduardo; García, Luis Francisco; Aluja, Anton

    2016-10-01

    The aim of this study was to investigate the relationships between Emotional Intelligence (EI) measured by the Trait Emotional Intelligence Questionnaire (TEIQue) and personality measured by the Zuckerman-Kuhlman-Aluja Personality Questionnaire (ZKA-PQ) with the purpose of analyzing similarities and differences of both psychological constructs. Additionally, we studied the relationship among EI, personality, General Intelligence (GI) and a social position index (SPI). Results showed that the ZKA-PQ predicts the 66% (facets) and the 64% (factors) of the TEIQue. High scores in EI correlated negatively with Neuroticism (r: -0.66) and Aggressiveness (r: -0.27); and positively with Extraversion (r: 0.62). Oblique factorial analyses demonstrated that TEIQue scales were located basically in the Neuroticism and Extraversion factors. The SPI and GI no loaded in any factor. These findings showed that EI is a not a distinct construct of personality and it cannot be isolated in the ZKA-PQ personality space. GI is related with the SPI (r: 0.26), and EI correlated with GI (r: 0.18) and SPI (r: 0.16). Nevertheless, we found differences between GI high groups and the TEIQue and ZKA-PQ factors when controlling age and sex. These findings are discussed in the individual differences context.

  14. 2367-IJBCS-Article-Koffi Mathias Yao

    African Journals Online (AJOL)

    hp

    développés après le tabac et l'hypertension, et le onzième dans ... troubles physiques et mentaux, parmi lesquels ... adultes, à Abidjan, en Côte d'Ivoire. Par ... activité professionnelle ? Si oui, laquelle ? 3- Avez-vous consommé de l'alcool, au.

  15. Mathias Klotz: Restaurante Dominó, Santiago

    OpenAIRE

    Klotz,Mathias

    2010-01-01

    El proyecto consiste en la construcción de un local icónico para Dominó, una de las más conocidas fuentes de soda de Santiago, que cuenta con casi 60 años de existencia. El directorio de la empresa decidió inaugurar un nuevo local en calle Isidora Goyenechea, ubicada en el barrio El Golf, nuevo centro financiero de Santiago.

  16. Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks

    Directory of Open Access Journals (Sweden)

    Ramanpreet Kaur

    2017-02-01

    Full Text Available Intelligent prediction of neighboring node (k well defined neighbors as specified by the dht protocol dynamism is helpful to improve the resilience and can reduce the overhead associated with topology maintenance of structured overlay networks. The dynamic behavior of overlay nodes depends on many factors such as underlying user’s online behavior, geographical position, time of the day, day of the week etc. as reported in many applications. We can exploit these characteristics for efficient maintenance of structured overlay networks by implementing an intelligent predictive framework for setting stabilization parameters appropriately. Considering the fact that human driven behavior usually goes beyond intermittent availability patterns, we use a hybrid Neuro-fuzzy based predictor to enhance the accuracy of the predictions. In this paper, we discuss our predictive stabilization approach, implement Neuro-fuzzy based prediction in MATLAB simulation and apply this predictive stabilization model in a chord based overlay network using OverSim as a simulation tool. The MATLAB simulation results present that the behavior of neighboring nodes is predictable to a large extent as indicated by the very small RMSE. The OverSim based simulation results also observe significant improvements in the performance of chord based overlay network in terms of lookup success ratio, lookup hop count and maintenance overhead as compared to periodic stabilization approach.

  17. Modeling, control, and simulation of grid connected intelligent hybrid battery/photovoltaic system using new hybrid fuzzy-neural method.

    Science.gov (United States)

    Rezvani, Alireza; Khalili, Abbas; Mazareie, Alireza; Gandomkar, Majid

    2016-07-01

    Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current-voltage or power-voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.

  18. Stupid Tutoring Systems, Intelligent Humans

    Science.gov (United States)

    Baker, Ryan S.

    2016-01-01

    The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…

  19. Intention recognition, commitment and their roles in the evolution of cooperation from artificial intelligence techniques to evolutionary game theory models

    CERN Document Server

    Han, The Anh

    2013-01-01

    This original and timely monograph describes a unique self-contained excursion that reveals to the readers the roles of two basic cognitive abilities, i.e. intention recognition and arranging commitments, in the evolution of cooperative behavior. This book analyses intention recognition, an important ability that helps agents predict others’ behavior, in its artificial intelligence and evolutionary computational modeling aspects, and proposes a novel intention recognition method. Furthermore, the book presents a new framework for intention-based decision making and illustrates several ways in which an ability to recognize intentions of others can enhance a decision making process. By employing the new intention recognition method and the tools of evolutionary game theory, this book introduces computational models demonstrating that intention recognition promotes the emergence of cooperation within populations of self-regarding agents. Finally, the book describes how commitment provides a pathway to the evol...

  20. The Analysis of the Intelligence Game by CPM Model%脑筋急转弯的CPM模型研究

    Institute of Scientific and Technical Information of China (English)

    陈丽慧

    2011-01-01

    The present study will explain the process of the intelligence game' construal by CPM model within the framework of cognitive linguistics.CPM model is constructed on the basis of conceptual blending theory,the theory of prominence and the theory of metaph%从认知的视角出发,基于概念整合理论、突显理论与隐喻理论,提出CPM模型。利用该模型对脑筋急转弯的形成机制、解答过程及产生幽默效果进行解释,并根据突显内容的不同,将脑筋急转弯进行分类。

  1. Stabilization effect of traffic flow in an extended car-following model based on an intelligent transportation system application.

    Science.gov (United States)

    Ge, H X; Dai, S Q; Dong, L Y; Xue, Y

    2004-12-01

    An extended car following model is proposed by incorporating an intelligent transportation system in traffic. The stability condition of this model is obtained by using the linear stability theory. The results show that anticipating the behavior of more vehicles ahead leads to the stabilization of traffic systems. The modified Korteweg-de Vries equation (the mKdV equation, for short) near the critical point is derived by applying the reductive perturbation method. The traffic jam could be thus described by the kink-antikink soliton solution for the mKdV equation. From the simulation of space-time evolution of the vehicle headway, it is shown that the traffic jam is suppressed efficiently with taking into account the information about the motion of more vehicles in front, and the analytical result is consonant with the simulation one.

  2. Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

    Science.gov (United States)

    Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

    2015-01-01

    The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

  3. Multistep Wind Speed Forecasting Using a Novel Model Hybridizing Singular Spectrum Analysis, Modified Intelligent Optimization, and Rolling Elman Neural Network

    Directory of Open Access Journals (Sweden)

    Zhongshan Yang

    2016-01-01

    Full Text Available Wind speed high-accuracy forecasting, an important part of the electrical system monitoring and control, is of the essence to protect the safety of wind power utilization. However, the wind speed signals are always intermittent and intrinsic complexity; therefore, it is difficult to forecast them accurately. Many traditional wind speed forecasting studies have focused on single models, which leads to poor prediction accuracy. In this paper, a new hybrid model is proposed to overcome the shortcoming of single models by combining singular spectrum analysis, modified intelligent optimization, and the rolling Elman neural network. In this model, except for the multiple seasonal patterns used to reduce interferences from the original data, the rolling model is utilized to forecast the multistep wind speed. To verify the forecasting ability of the proposed hybrid model, 10 min and 60 min wind speed data from the province of Shandong, China, were proposed in this paper as the case study. Compared to the other models, the proposed hybrid model forecasts the wind speed with higher accuracy.

  4. J. Piaget's theory of intelligence: operational aspect

    Directory of Open Access Journals (Sweden)

    Xenia Naidenova

    2001-08-01

    Full Text Available The Piaget's theory of intelligence is considered from the point of view of genesis and gradual development of human thinking operations. Attention is given to operational aspects of cognitive structures and knowledge. The significance of the Piaget's theory of intelligence is revealed for modeling conceptual reasoning in the framework of artificial intelligence.

  5. QGA-VPMCD intelligent diagnosis model%QGA-VPMCD 智能诊断模型研究

    Institute of Scientific and Technical Information of China (English)

    杨宇; 李紫珠; 何知义; 程军圣

    2015-01-01

    针对多变量预测模型模式识别(Variable Predictive Model-based Class Discriminate,VPMCD)分类方法中只选择了某单一模型的缺陷,提出一种基于量子遗传算法优化的多变量智能诊断模型(Quantum Genetic Algorithm-Variable Predictive Model-Based Class Discriminate,QGA-VPMCD)。该模型采用最优权值矩阵来综合考虑各诊断模型对分类结果的影响。即首先通过样本训练来建立多个 SVPM(Subordinate Variable Predictive Model,SVPM);然后采用量子遗传优化算法求出各 SVPM的权值,从而得到最优权值矩阵;最后用最优权值矩阵加权融合测试样本的 SVPM特征变量预测值,得到最佳特征变量预测值,并以预测误差平方和最小为判别函数来识别故障的类型。滚动轴承振动信号的分析结果表明了该模型的有效性。%Aiming at the defect that only a single model is selected in the variable predictive model-based class discriminate (VPMCD)classification method,an intelligent diagnosis model called quantum genetic algorithm -variable predictive model-based class discriminate (QGA-VPMCD) was presented.The optimal weight matrix was used to comprehensively consider the effect of each diagnosis model on classification results with this new model.Firstly,multiple subordinate variable predictive models (SVPMs)were established through samples-training.Secondly,the intelligent quantum genetic algorithm was used to acquire the weight value of each SVPM and the optimal weight matrix was obtained.Finally,the optimal weight matrix was used to get the optimal feature variable predictions through weighted fusing feature variable predictions of SVPMs of test samples.Fault types were identified according to the minimum error square sum taken as the discrimination function.The analysis results of vibration signals of rolling bearings verified the effectiveness of the proposed model.

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

    Science.gov (United States)

    Kazemi, Pezhman; Khalid, Mohammad Hassan; Pérez Gago, Ana; Kleinebudde, Peter; Jachowicz, Renata; Szlęk, Jakub; Mendyk, Aleksander

    2017-01-01

    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 determination (R(2)) were used for model assessment. The best fit was obtained by Cubist model (normalized root-mean-squared error =3.22%, R(2)=0.95). Based on the results, it was confirmed that the material properties (true density) followed by compaction force have the most significant effect on GSD.

  7. Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agent’s Location Using Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Cédric Beaulac

    2017-01-01

    Full Text Available We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile agent’s position using the forward algorithm. Second, it uses the Baum–Welch algorithm as a statistical learning tool to gain knowledge of the mobile target. Finally, an experimental environment is proposed, namely, a video game that we use to test our artificial intelligence. We present statistical and graphical results to illustrate the efficiency of our method.

  8. Systems thinking intelligence in action

    CERN Document Server

    Mella, Piero

    2012-01-01

    The core belief underlying this book is that the most useful and effective models to strengthen our intelligence are system ones, developed following the logic of Systems Thinking. Such models can explore complexity, dynamics, and change, and it is the author's view that intelligence depends on the ability to construct models of this nature. The book is designed to allow the reader not only to acquire simple information on Systems Thinking but above all to gradually learn the logic and techniques that make this way of thinking an instrument for the improvement of intelligence. In order to aid

  9. Modeling the effects of light and sucrose on in vitro propagated plants: a multiscale system analysis using artificial intelligence technology.

    Directory of Open Access Journals (Sweden)

    Jorge Gago

    Full Text Available BACKGROUND: Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale. Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. METHODOLOGY AND PRINCIPAL FINDINGS: In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122-130 µmol m(-2 s(-1. CONCLUSIONS: Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work.

  10. Modeling the Effects of Light and Sucrose on In Vitro Propagated Plants: A Multiscale System Analysis Using Artificial Intelligence Technology

    Science.gov (United States)

    Gago, Jorge; Martínez-Núñez, Lourdes; Landín, Mariana; Flexas, Jaume; Gallego, Pedro P.

    2014-01-01

    Background Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. Methodology and Principal Findings In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122–130 µmol m−2 s−1. Conclusions Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work. PMID:24465829

  11. A conceptual model for worksite intelligent physical exercise training - IPET - intervention for decreasing life style health risk indicators among employees

    DEFF Research Database (Denmark)

    Sjøgaard, Gisela; Justesen, Just Bendix; Murray, Mike

    2014-01-01

    with a conceptual model for planning the optimal individually tailored physical exercise training for each worker based on individual health check, existing guidelines and state of the art sports science training recommendations in the broad categories of cardiorespiratory fitness, muscle strength in specific body......BACKGROUND: Health promotion at the work site in terms of physical activity has proven positive effects but optimization of relevant exercise training protocols and implementation for high adherence are still scanty.Methods/design: The aim of this paper is to present a study protocol...... parts, and functional training including balance training. The hypotheses of this research are that individually tailored worksite-based intelligent physical exercise training, IPET, among workers with inactive job categories will: 1) Improve cardiorespiratory fitness and/or individual health risk...

  12. An intelligent control framework for robot-aided resistance training using hybrid system modeling and impedance estimation.

    Science.gov (United States)

    Xu, Guozheng; Guo, Xiaobo; Zhai, Yan; Li, Huijun

    2015-08-01

    This study presents a novel therapy control method for robot-assisted resistance training using the hybrid system modeling technology and the estimated patient's bio-impedance changes. A new intelligent control framework based on hybrid system theory is developed, to automatically generate the desired resistive force and to make accommodating emergency behavior, when monitoring the changes of the impaired limb's muscle strength or the unpredictable safety-related occurrences during the execution of the training task. The impaired limb's muscle strength progress is online evaluated using its bio-damping and bio-stiffness estimation results. The proposed method is verified with a custom constructed therapeutic robot system featuring a Barrett WAM™ compliant manipulator. A typical inpatient stroke subject was recruited and enrolled in a ten-week resistance training program. Preliminary results show that the proposed therapeutic strategy can enhance the impaired limb's muscle strength and has practicability for robot-aided rehabilitation training.

  13. Co-evolution of intelligent socio-technical systems modelling and applications in large scale emergency and transport domains

    CERN Document Server

    2013-01-01

    As the interconnectivity between humans through technical devices is becoming ubiquitous, the next step is already in the making: ambient intelligence, i.e. smart (technical) environments, which will eventually play the same active role in communication as the human players, leading to a co-evolution in all domains where real-time communication is essential. This topical volume, based on the findings of the Socionical European research project, gives equal attention to two highly relevant domains of applications: transport, specifically traffic, dynamics from the viewpoint of a socio-technical interaction and evacuation scenarios for large-scale emergency situations. Care was taken to investigate as much as possible the limits of scalability and to combine the modeling using complex systems science approaches with relevant data analysis.

  14. Synthetic collective intelligence.

    Science.gov (United States)

    Solé, Ricard; Amor, Daniel R; Duran-Nebreda, Salva; Conde-Pueyo, Núria; Carbonell-Ballestero, Max; Montañez, Raúl

    2016-10-01

    Intelligent systems have emerged in our biosphere in different contexts and achieving different levels of complexity. The requirement of communication in a social context has been in all cases a determinant. The human brain, probably co-evolving with language, is an exceedingly successful example. Similarly, social insects complex collective decisions emerge from information exchanges between many agents. The difference is that such processing is obtained out of a limited individual cognitive power. Computational models and embodied versions using non-living systems, particularly involving robot swarms, have been used to explore the potentiality of collective intelligence. Here we suggest a novel approach to the problem grounded in the genetic engineering of unicellular systems, which can be modified in order to interact, store memories or adapt to external stimuli in collective ways. What we label as Synthetic Swarm Intelligence defines a parallel approach to the evolution of computation and swarm intelligence and allows to explore potential embodied scenarios for decision making at the microscale. Here, we consider several relevant examples of collective intelligence and their synthetic organism counterparts.

  15. Intelligent Potroom Operation

    Energy Technology Data Exchange (ETDEWEB)

    Jan Berkow; Larry Banta

    2003-07-29

    The Intelligent Potroom Operation project focuses on maximizing the performance of an aluminum smelter by innovating components for an intelligent manufacturing system. The Intelligent Potroom Advisor (IPA) monitors process data to identify reduction cells exhibiting behaviors that require immediate attention. It then advises operational personnel on those heuristic-based actions to bring the cell back to an optimal operating state in order to reduce the duration and frequency of substandard reduction cell performance referred to as ''Off-Peak Modes'' (OPMs). Techniques developed to identify cells exhibiting OPMs include the use of a finite element model-based cell state estimator for defining the cell's current operating state via advanced cell noise analyses. In addition, rule induction was also employed to identify statistically significant complex behaviors that occur prior to OPMs. The intelligent manufacturing system design, concepts and formalisms developed in this project w ere used as a basis for an intelligent manufacturing system design. Future research will incorporate an adaptive component to automate continuous process improvement, a technology platform with the potential to improve process performance in many of the other Industries of the Future applications as well.

  16. Artificial intelligence and psychiatry.

    Science.gov (United States)

    Servan-Schreiber, D

    1986-04-01

    This paper provides a brief historical introduction to the new field of artificial intelligence and describes some applications to psychiatry. It focuses on two successful programs: a model of paranoid processes and an expert system for the pharmacological management of depressive disorders. Finally, it reviews evidence in favor of computerized psychotherapy and offers speculations on the future development of research in this area.

  17. 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.

  18. The Spatio-Temporal Modeling of Urban Growth Using Remote Sensing and Intelligent Algorithms, Case of Mahabad, Iran

    Directory of Open Access Journals (Sweden)

    Alì Soltani

    2013-06-01

    Full Text Available The simulation of urban growth can be considered as a useful way for analyzing the complex process of urban physical evolution. The aim of this study is to model and simulate the complex patterns of land use change by utilizing remote sensing and artificial intelligence techniques in the fast growing city of Mahabad, north-west of Iran which encountered with several environmental subsequences. The key subject is how to allocate optimized weight into effective parameters upon urban growth and subsequently achieving an improved simulation. Artificial Neural Networks (ANN algorithm was used to allocate the weight via an iteration approach. In this way, weight allocation was carried out by the ANN training accomplishing through time-series satellite images representing urban growth process. Cellular Automata (CA was used as the principal motor of the model and then ANN applied to find suitable scale of parameters and relations between potential factors affecting urban growth. The general accuracy of the suggested model and obtained Fuzzy Kappa Coefficient confirms achieving better results than classic CA models in simulating nonlinear urban evolution process.

  19. The Relationship of Business Intelligence Systems to Organizational Performance Benefits: A Structural Equation Modeling of Management Decision Making

    Science.gov (United States)

    Sparks, Betsy H.

    2014-01-01

    Business Intelligence is a major expenditure in many organizations and necessary for competitive advantage. These expenditures do not result in maximum benefits for the organization if the information obtained from the Business Intelligence System (BIS) is not used in the management decision-making process. This quantitative research study used an…

  20. The Relationship of Business Intelligence Systems to Organizational Performance Benefits: A Structural Equation Modeling of Management Decision Making

    Science.gov (United States)

    Sparks, Betsy H.

    2014-01-01

    Business Intelligence is a major expenditure in many organizations and necessary for competitive advantage. These expenditures do not result in maximum benefits for the organization if the information obtained from the Business Intelligence System (BIS) is not used in the management decision-making process. This quantitative research study used an…

  1. Civic Intelligence.

    Science.gov (United States)

    Mathews, David

    1985-01-01

    Social studies must educate students to be socially responsible, civically competent persons. In addition to encouraging civic literacy, civic values, and civic skill, teachers need to help students develop civic-mindedness. The objective of the NCSS' National Issues Forum in the Classroom Project is to develop students' civic intelligence. (RM)

  2. Speech Intelligibility

    Science.gov (United States)

    Brand, Thomas

    Speech intelligibility (SI) is important for different fields of research, engineering and diagnostics in order to quantify very different phenomena like the quality of recordings, communication and playback devices, the reverberation of auditoria, characteristics of hearing impairment, benefit using hearing aids or combinations of these things.

  3. Ambient intelligence

    OpenAIRE

    Sanders, David; Gegov, Alexander

    2006-01-01

    This paper considers some history and the state of the art of Ambient Intelligence and from that seeks to identify new topics and future work. Ubiquitous computing, communications, human-centric computer interaction, embedded systems, context awareness, adaptive systems and distributed device networks are considered.

  4. A Dynamic Neuro-Fuzzy Model Providing Bio-State Estimation and Prognosis Prediction for Wearable Intelligent Assistants

    Directory of Open Access Journals (Sweden)

    Winters Jack M

    2005-06-01

    Full Text Available Abstract Background Intelligent management of wearable applications in rehabilitation requires an understanding of the current context, which is constantly changing over the rehabilitation process because of changes in the person's status and environment. This paper presents a dynamic recurrent neuro-fuzzy system that implements expert-and evidence-based reasoning. It is intended to provide context-awareness for wearable intelligent agents/assistants (WIAs. Methods The model structure includes the following types of signals: inputs, states, outputs and outcomes. Inputs are facts or events which have effects on patients' physiological and rehabilitative states; different classes of inputs (e.g., facts, context, medication, therapy have different nonlinear mappings to a fuzzy "effect." States are dimensionless linguistic fuzzy variables that change based on causal rules, as implemented by a fuzzy inference system (FIS. The FIS, with rules based on expertise and evidence, essentially defines the nonlinear state equations that are implemented by nuclei of dynamic neurons. Outputs, a function of weighing of states and effective inputs using conventional or fuzzy mapping, can perform actions, predict performance, or assist with decision-making. Outcomes are scalars to be extremized that are a function of outputs and states. Results The first example demonstrates setup and use for a large-scale stroke neurorehabilitation application (with 16 inputs, 12 states, 5 outputs and 3 outcomes, showing how this modelling tool can successfully capture causal dynamic change in context-relevant states (e.g., impairments, pain as a function of input event patterns (e.g., medications. The second example demonstrates use of scientific evidence to develop rule-based dynamic models, here for predicting changes in muscle strength with short-term fatigue and long-term strength-training. Conclusion A neuro-fuzzy modelling framework is developed for estimating

  5. Intelligence, education, and myopia in males.

    Science.gov (United States)

    Rosner, M; Belkin, M

    1987-11-01

    We conducted a nationwide study of the relationship among refractive error, intelligence scores, and years of schooling in 157,748 males aged 17 to 19 years. We found a strong association of myopia with both intelligence and years of school attendance. The prevalence of myopia was found to be significantly higher in the more intelligent and more educated groups. By fitting models of logistic regressions, we worked out a formula expressing the relationship among the rate of myopia, years of schooling, and intelligence level. We found that years of schooling and intelligence weigh equally in the relationship with myopia.

  6. Artificial Intelligence vs. Statistical Modeling and Optimization of Continuous Bead Milling Process for Bacterial Cell Lysis.

    Science.gov (United States)

    Haque, Shafiul; Khan, Saif; Wahid, Mohd; Dar, Sajad A; Soni, Nipunjot; Mandal, Raju K; Singh, Vineeta; Tiwari, Dileep; Lohani, Mohtashim; Areeshi, Mohammed Y; Govender, Thavendran; Kruger, Hendrik G; Jawed, Arshad

    2016-01-01

    For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v), cell loading OD600nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN-GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h): 258.08, bead loading (%, v/v): 80%, cell loading (OD600nm): 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN) in combination with evolutionary optimization (GA) for representing undefined biological functions which is the case for common industrial processes involving biological moieties.

  7. 3Es System Optimization under Uncertainty Using Hybrid Intelligent Algorithm: A Fuzzy Chance-Constrained Programming Model

    Directory of Open Access Journals (Sweden)

    Jiekun Song

    2016-01-01

    Full Text Available Harmonious development of 3Es (economy-energy-environment system is the key to realize regional sustainable development. The structure and components of 3Es system are analyzed. Based on the analysis of causality diagram, GDP and industrial structure are selected as the target parameters of economy subsystem, energy consumption intensity is selected as the target parameter of energy subsystem, and the emissions of COD, ammonia nitrogen, SO2, and NOX and CO2 emission intensity are selected as the target parameters of environment system. Fixed assets investment of three industries, total energy consumption, and investment in environmental pollution control are selected as the decision variables. By regarding the parameters of 3Es system optimization as fuzzy numbers, a fuzzy chance-constrained goal programming (FCCGP model is constructed, and a hybrid intelligent algorithm including fuzzy simulation and genetic algorithm is proposed for solving it. The results of empirical analysis on Shandong province of China show that the FCCGP model can reflect the inherent relationship and evolution law of 3Es system and provide the effective decision-making support for 3Es system optimization.

  8. Heuristic Analysis Model of Nitrided Layers' Formation Consisting of the Image Processing and Analysis and Elements of Artificial Intelligence.

    Science.gov (United States)

    Wójcicki, Tomasz; Nowicki, Michał

    2016-04-01

    The article presents a selected area of research and development concerning the methods of material analysis based on the automatic image recognition of the investigated metallographic sections. The objectives of the analyses of the materials for gas nitriding technology are described. The methods of the preparation of nitrided layers, the steps of the process and the construction and operation of devices for gas nitriding are given. We discuss the possibility of using the methods of digital images processing in the analysis of the materials, as well as their essential task groups: improving the quality of the images, segmentation, morphological transformations and image recognition. The developed analysis model of the nitrided layers formation, covering image processing and analysis techniques, as well as selected methods of artificial intelligence are presented. The model is divided into stages, which are formalized in order to better reproduce their actions. The validation of the presented method is performed. The advantages and limitations of the developed solution, as well as the possibilities of its practical use, are listed.

  9. Research on the Model Description of Human Competitive Intelligence Network%企业人际竞争情报网络模型描述方法研究

    Institute of Scientific and Technical Information of China (English)

    吴晓伟; 楼文高; 龙青云; 李丹

    2011-01-01

    提出了企业人际竞争情报网络模型描述的方法论.社会网络模型是当前人际竞争情报网络模型描述的主流方法,其基本工具是图论和矩阵.但社会网络模型只能对同质网络进行分析,不能解决行动者的"多质"、"多层"问题,限制了人际竞争情报应用领域的拓展.用行动者网络理论确定人际竞争情报网络建模的主体,可以明确"多质"行动者对竞争情报分析的必要性.用超网络工具可以解决"多质"、"多层"网络描述问题.用社会网络可以精确对"同质"网络进行分析.人际竞争情报网络模型描述方法的完善需要社会网络、行动者网络、超网络三大工具的协同应用.%The methodology to describe network model of human competitive intelligence for business is proposed. Thesocial network, primarily based on graph theory and matrix theory, is the prevailing method to model human competitive intelligence network. However, the imperfection of social network that it can not analyze heterogeneous and multi-layer but homogeneous network limits the application of human competitive intelligence. Actor-network theory is used to identify the subjects-heterogeneous actors- in the network model of human competitive intelligence which is necessary in the analysis of competitive intelligence. Super-networks theory is capable of modeling heterogeneous and multi-layer network. So collaborative applying of social network, actor-network, super-networks, is very helpful to refine the model description of human competitive intelligence network.

  10. Team B Intelligence Coups

    Science.gov (United States)

    Mitchell, Gordon R.

    2006-01-01

    The 2003 Iraq prewar intelligence failure was not simply a case of the U.S. intelligence community providing flawed data to policy-makers. It also involved subversion of the competitive intelligence analysis process, where unofficial intelligence boutiques "stovepiped" misleading intelligence assessments directly to policy-makers and…

  11. Extraordinary intelligence and the care of infants.

    Science.gov (United States)

    Piantadosi, Steven T; Kidd, Celeste

    2016-06-21

    We present evidence that pressures for early childcare may have been one of the driving factors of human evolution. We show through an evolutionary model that runaway selection for high intelligence may occur when (i) altricial neonates require intelligent parents, (ii) intelligent parents must have large brains, and (iii) large brains necessitate having even more altricial offspring. We test a prediction of this account by showing across primate genera that the helplessness of infants is a particularly strong predictor of the adults' intelligence. We discuss related implications, including this account's ability to explain why human-level intelligence evolved specifically in mammals. This theory complements prior hypotheses that link human intelligence to social reasoning and reproductive pressures and explains how human intelligence may have become so distinctive compared with our closest evolutionary relatives.

  12. Cooperation and the evolution of intelligence.

    Science.gov (United States)

    McNally, Luke; Brown, Sam P; Jackson, Andrew L

    2012-08-01

    The high levels of intelligence seen in humans, other primates, certain cetaceans and birds remain a major puzzle for evolutionary biologists, anthropologists and psychologists. It has long been held that social interactions provide the selection pressures necessary for the evolution of advanced cognitive abilities (the 'social intelligence hypothesis'), and in recent years decision-making in the context of cooperative social interactions has been conjectured to be of particular importance. Here we use an artificial neural network model to show that selection for efficient decision-making in cooperative dilemmas can give rise to selection pressures for greater cognitive abilities, and that intelligent strategies can themselves select for greater intelligence, leading to a Machiavellian arms race. Our results provide mechanistic support for the social intelligence hypothesis, highlight the potential importance of cooperative behaviour in the evolution of intelligence and may help us to explain the distribution of cooperation with intelligence across taxa.

  13. Recent Advances on Hybrid Intelligent Systems

    CERN Document Server

    Melin, Patricia; Kacprzyk, Janusz

    2013-01-01

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

  14. Artificial Intelligence.

    Science.gov (United States)

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

  15. Intelligence is what the intelligence test measures. Seriously

    NARCIS (Netherlands)

    H.L.J. van der Maas; K.-J. Kan; D. Borsboom

    2014-01-01

    The mutualism model, an alternative for the g-factor model of intelligence, implies a formative measurement model in which "g" is an index variable without a causal role. If this model is accurate, the search for a genetic of brain instantiation of "g" is deemed useless. This also implies that the (

  16. Intelligence Revisited

    Science.gov (United States)

    2005-05-01

    environment (i.e., culture , class, family, educational 2 Chapter 23 Intelligence Revisited opportunities, gender) shapes our intellect, and there are no...connectivity is going to be rather problematic, to say the least. A single nano-bot cruising this Disneyland of synaptic wonderment is certainly... cultures ). Embodiment – A sense of being anchored to our physical bodies. Agency – A sense of free will, wherein we are in charge of our own

  17. A Procedure for Building Product Models in Intelligent Agent-based OperationsManagement

    DEFF Research Database (Denmark)

    Hvam, Lars; Riis, Jesper; Malis, Martin;

    2003-01-01

    by product models. The next phase includes an analysis of the product assortment, and the set up of a so-called product master. Finally the product model is designed and implemented by using object oriented modelling. The procedure is developed in order to ensure that the product models constructed are fit......This article presents a procedure for building product models to support the specification processes dealing with sales, design of product variants and production preparation. The procedure includes, as the first phase, an analysis and redesign of the business processes that are to be supported...

  18. The evolution of general intelligence.

    Science.gov (United States)

    Burkart, Judith M; Schubiger, Michèle N; van Schaik, Carel P

    2016-07-28

    The presence of general intelligence poses a major evolutionary puzzle, which has led to increased interest in its presence in nonhuman animals. The aim of this review is to critically evaluate this puzzle, and to explore the implications for current theories about the evolution of cognition. We first review domain-general and domain-specific accounts of human cognition in order to situate attempts to identify general intelligence in nonhuman animals. Recent studies are consistent with the presence of general intelligence in mammals (rodents and primates). However, the interpretation of a psychometric g-factor as general intelligence needs to be validated, in particular in primates, and we propose a range of such tests. We then evaluate the implications of general intelligence in nonhuman animals for current theories about its evolution and find support for the cultural intelligence approach, which stresses the critical importance of social inputs during the ontogenetic construction of survival-relevant skills. The presence of general intelligence in nonhumans implies that modular abilities can arise in two ways, primarily through automatic development with fixed content and secondarily through learning and automatization with more variable content. The currently best-supported model, for humans and nonhuman vertebrates alike, thus construes the mind as a mix of skills based on primary and secondary modules. The relative importance of these two components is expected to vary widely among species, and we formulate tests to quantify their strength.

  19. 基于计算智能的土地适宜性评价模型%Model of Land Suitability Evaluation Based on Computational Intelligence

    Institute of Scientific and Technical Information of China (English)

    焦利民; 刘耀林

    2007-01-01

    A novel model of land suitability evaluation is built based on computational intelligence (CI). A fuzzy neural network (FNN) is constructed by the integration of fuzzy logic and artificial neural network (ANN). The structure and process of this network is clear. Fuzzy rules (knowledge) are expressed in the model explicitly, and can be self-adjusted by learning from samples. Genetic algorithm (GA) is employed as the learning algorithm to train the network, and makes the training of the model efficient. This model is a self-learning and self-adaptive system with a rule set revised by training.

  20. Data and Knowledge Base on the Basis of the Expanded Matrix Model of Their Representation for the Intelligent System of Road-Climatic Zoning of Territories

    Science.gov (United States)

    Yankovskaya, A.; Cherepanov, D.; Selivanikova, O.

    2016-08-01

    An extended matrix model of data and knowledge representation on the investigated area, as well as a matrix model of data representation on the territory under investigation, are proposed for the intelligent system of road-climatic zoning of territories (RCZT) - the main information technology of RCZT. A part of the West Siberian region has been selected as the investigated territory. The extended matrix model of knowledge representation is filled out by knowledge engineers with participation of highly qualified experts in the field of RCZT. The matrix model of data representation on the territory under investigation is filled out by persons concerned in RCZT of the motor-roads management system.

  1. Mathematical Model and Its Hybrid Dynamic Mechanism in Intelligent Control of Ironmaking

    Institute of Scientific and Technical Information of China (English)

    LIU Xiang-guan; ZENG Jiu-sun; ZHAO Min

    2007-01-01

    A hybrid dynamic model was proposed, which considered both the hydrokinetic and the chaotic properties of the blast furnace ironmaking process; and great emphasis was put on its mechanism. The new model took the high complexity of the blast furnace as well as the effects of main parameters of the model into account, and the predicted results were in very good agreement with actual data.

  2. Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies

    OpenAIRE

    Natarajan, Sriraam; Tadepalli, Prasad; Fern, Alan

    2008-01-01

    Statitsical relational models have been successfully used to model static probabilistic relationships between the entities of the domain. In this talk, we illustrate their use in a dynamic decison-theoretic setting where the task is to assist a user by inferring his intentional structure and taking appropriate assistive actions. We show that the statistical relational models can be used to succintly express the system's prior knowledge about the user's goal-subgoal structure...

  3. Algorithms for Efficient Intelligence Collection

    Science.gov (United States)

    2013-09-01

    Software Implementation . . . . . . . . . . . . . . . . . . . . . . . 11 3 Creating Sample Intelligence Networks 15 3.1 The Enron Corpus...graphical model. . . . 10 Figure 3.1 A distribution of the edge pe values in the complete Enron network. . . 18 Figure 3.2 A histogram showing the...distribution of the number of total items avail- able for screening on the edges of the complete Enron network. . . . . 18 Figure 3.3 A small intelligence

  4. An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube

    Science.gov (United States)

    2009-01-01

    Modeling of water flow in carbon nanotubes is still a challenge for the classic models of fluid dynamics. In this investigation, an adaptive-network-based fuzzy inference system (ANFIS) is presented to solve this problem. The proposed ANFIS approach can construct an input–output mapping based on both human knowledge in the form of fuzzy if-then rules and stipulated input–output data pairs. Good performance of the designed ANFIS ensures its capability as a promising tool for modeling and prediction of fluid flow at nanoscale where the continuum models of fluid dynamics tend to break down. PMID:20596382

  5. An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube

    Directory of Open Access Journals (Sweden)

    Ahadian Samad

    2009-01-01

    Full Text Available Abstract Modeling of water flow in carbon nanotubes is still a challenge for the classic models of fluid dynamics. In this investigation, an adaptive-network-based fuzzy inference system (ANFIS is presented to solve this problem. The proposed ANFIS approach can construct an input–output mapping based on both human knowledge in the form of fuzzy if-then rules and stipulated input–output data pairs. Good performance of the designed ANFIS ensures its capability as a promising tool for modeling and prediction of fluid flow at nanoscale where the continuum models of fluid dynamics tend to break down.

  6. Trends in Artificial Intelligence.

    Science.gov (United States)

    Hayes, Patrick

    1978-01-01

    Discusses the foundations of artificial intelligence as a science and the types of answers that may be given to the question, "What is intelligence?" The paradigms of artificial intelligence and general systems theory are compared. (Author/VT)

  7. Examination of mitral regurgitation with a goat heart model for the development of intelligent artificial papillary muscle.

    Science.gov (United States)

    Shiraishi, Y; Yambe, T; Yoshizawa, M; Hashimoto, H; Yamada, A; Miura, H; Hashem, M; Kitano, T; Shiga, T; Homma, D

    2012-01-01

    Annuloplasty for functional mitral or tricuspid regurgitation has been made for surgical restoration of valvular diseases. However, these major techniques may sometimes be ineffective because of chamber dilation and valve tethering. We have been developing a sophisticated intelligent artificial papillary muscle (PM) by using an anisotropic shape memory alloy fiber for an alternative surgical reconstruction of the continuity of the mitral structural apparatus and the left ventricular myocardium. This study exhibited the mitral regurgitation with regard to the reduction in the PM tension quantitatively with an originally developed ventricular simulator using isolated goat hearts for the sophisticated artificial PM. Aortic and mitral valves with left ventricular free wall portions of isolated goat hearts (n=9) were secured on the elastic plastic membrane and statically pressurized, which led to valvular leaflet-papillary muscle positional change and central mitral regurgitation. PMs were connected to the load cell, and the relationship between the tension of regurgitation and PM tension were measured. Then we connected the left ventricular specimen model to our hydraulic ventricular simulator and achieved hemodynamic simulation with the controlled tension of PMs.

  8. Intelligent modeling and control for nonlinear systems with rate-dependent hysteresis

    Institute of Scientific and Technical Information of China (English)

    MAO JianQin; DING HaiShan

    2009-01-01

    A new modeling approach for nonlinear systems with rate-dependent hysteresis is proposed. The ap-proach is used for the modeling of the giant magnetostrictive actuator, which has the rate-dependent nonlinear property. The models built are simpler than the existed approaches. Compared with the exper-intent result, the model built can well describe the hysteresis nonlinear of the actuator for Input signals with complex frequency. An adaptive direct inverse control approach is proposed based on the fuzzy tree model and Inverse learning and special learning that are used in neural network broadly. In this approach, the inverse model of the plant is identified to be the initial controller firstly. Then, the inverse model Is connected with the plant in series and the linear parameters of the controller are adjusted using the least mean square algorithm by on-line manner. The direct Inverse control approach based on the fuzzy tree model is applied on the tracing control of the actuator by simulation. The simulation results show the correctness of the approach.

  9. I-Interaction: An Intelligent In-Vehicle User Interaction Model

    CERN Document Server

    Liu, Li; 10.5121/iju.2010.1305

    2010-01-01

    The automobile is always a point of interest where new technology has been deployed. Because of this interest, human-vehicle interaction has been an appealing area for much research in recent years. The current in-vehicle design has been improved but still possesses some of the design from the traditional interaction style. In this paper, we propose a new user-oriented model for in-vehicle interaction model known as i-Interaction. The i-Interaction model provides user with an intuitive approach to interact with the In-Vehicle Information System (IVIS) by the keypad entry. It is the intent that the proposed usability testing for this model will help improve the way research and development is implemented from this topic. This model does not only provide the user with a direct interaction in vehicles but also introduce a new prospective that other research has not addressed.

  10. Fostering collective intelligence education

    Directory of Open Access Journals (Sweden)

    Jaime Meza

    2016-06-01

    Full Text Available New educational models are necessary to update learning environments to the digitally shared communication and information. Collective intelligence is an emerging field that already has a significant impact in many areas and will have great implications in education, not only from the side of new methodologies but also as a challenge for education. This paper proposes an approach to a collective intelligence model of teaching using Internet to combine two strategies: idea management and real time assessment in the class. A digital tool named Fabricius has been created supporting these two elements to foster the collaboration and engagement of students in the learning process. As a result of the research we propose a list of KPI trying to measure individual and collective performance. We are conscious that this is just a first approach to define which aspects of a class following a course can be qualified and quantified.

  11. Hourly runoff forecasting for flood risk management: Application of various computational intelligence models

    Science.gov (United States)

    Badrzadeh, Honey; Sarukkalige, Ranjan; Jayawardena, A. W.

    2015-10-01

    Reliable river flow forecasts play a key role in flood risk mitigation. Among different approaches of river flow forecasting, data driven approaches have become increasingly popular in recent years due to their minimum information requirements and ability to simulate nonlinear and non-stationary characteristics of hydrological processes. In this study, attempts are made to apply four different types of data driven approaches, namely traditional artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), wavelet neural networks (WNN), and, hybrid ANFIS with multi resolution analysis using wavelets (WNF). Developed models applied for real time flood forecasting at Casino station on Richmond River, Australia which is highly prone to flooding. Hourly rainfall and runoff data were used to drive the models which have been used for forecasting with 1, 6, 12, 24, 36 and 48 h lead-time. The performance of models further improved by adding an upstream river flow data (Wiangaree station), as another effective input. All models perform satisfactorily up to 12 h lead-time. However, the hybrid wavelet-based models significantly outperforming the ANFIS and ANN models in the longer lead-time forecasting. The results confirm the robustness of the proposed structure of the hybrid models for real time runoff forecasting in the study area.

  12. Intelligence Is What the Intelligence Test Measures. Seriously

    Directory of Open Access Journals (Sweden)

    Han L. J. van der Maas

    2014-02-01

    Full Text Available The mutualism model, an alternative for the g-factor model of intelligence, implies a formative measurement model in which “g” is an index variable without a causal role. If this model is accurate, the search for a genetic of brain instantiation of “g” is deemed useless. This also implies that the (weighted sum score of items of an intelligence test is just what it is: a weighted sum score. Preference for one index above the other is a pragmatic issue that rests mainly on predictive value.

  13. I-Interaction: An Intelligent In-Vehicle User Interaction Model

    Directory of Open Access Journals (Sweden)

    Li Liu

    2010-07-01

    Full Text Available The automobile is always a point of interest where new technology has been deployed. Because of thisinterest, human-vehicle interaction has been an appealing area for much research in recent years. Thecurrent in-vehicle design has been improved but still possesses some of the design from the traditionalinteraction style. In this paper, we propose a new user-oriented model for in-vehicle interaction modelknown as i-Interaction. The i-Interaction model provides user with an intuitive approach to interact withthe In-Vehicle Information System (IVIS by the keypad entry. It is the intent that the proposed usabilitytesting for this model will help improve the way research and development is implemented from this topic.This model does not only provide the user with a direct interaction in vehicles but also introduce a newprospective that other research has not addressed.

  14. Intelligent PID controllers

    OpenAIRE

    Fliess, Michel; Join, Cédric

    2008-01-01

    International audience; Intelligent PID controllers, or i-PID controllers, are PID controllers where the unknown parts of the plant, which might be highly nonlinear and/or time-varying, are taken into account without any modeling procedure. Our main tool is an online numerical differentiator, which is based on easily implementable fast estimation and identification techniques. Several numerical experiments demonstrate the efficiency of our method when compared to more classic PID regulators.

  15. Artificial intelligence modeling to evaluate field performance of photocatalytic asphalt pavement for ambient air purification.

    Science.gov (United States)

    Asadi, Somayeh; Hassan, Marwa; Nadiri, Ataallah; Dylla, Heather

    2014-01-01

    In recent years, the application of titanium dioxide (TiO₂) as a photocatalyst in asphalt pavement has received considerable attention for purifying ambient air from traffic-emitted pollutants via photocatalytic processes. In order to control the increasing deterioration of ambient air quality, urgent and proper risk assessment tools are deemed necessary. However, in practice, monitoring all process parameters for various operating conditions is difficult due to the complex and non-linear nature of air pollution-based problems. Therefore, the development of models to predict air pollutant concentrations is very useful because it can provide early warnings to the population and also reduce the number of measuring sites. This study used artificial neural network (ANN) and neuro-fuzzy (NF) models to predict NOx concentration in the air as a function of traffic count (Tr) and climatic conditions including humidity (H), temperature (T), solar radiation (S), and wind speed (W) before and after the application of TiO₂ on the pavement surface. These models are useful for modeling because of their ability to be trained using historical data and because of their capability for modeling highly non-linear relationships. To build these models, data were collected from a field study where an aqueous nano TiO₂ solution was sprayed on a 0.2-mile of asphalt pavement in Baton Rouge, LA. Results of this study showed that the NF model provided a better fitting to NOx measurements than the ANN model in the training, validation, and test steps. Results of a parametric study indicated that traffic level, relative humidity, and solar radiation had the most influence on photocatalytic efficiency.

  16. An Intelligent Web Pre-fetching Based on Hidden Markov Model

    Institute of Scientific and Technical Information of China (English)

    许欢庆; 金鑫

    2004-01-01

    Web pre-fetching is one of the most popular strategies,which are proposed for reducing the perceived access delay and improving the service quality of web server. In this paper, we present a pre-fetching model based on the hidden Markov model, which mines the latent information requirement concepts that the user's access path contains and makes semantic-based pre-fetching decisions.Experimental results show that our scheme has better predictive pre-fetching precision.

  17. Before and Beyond Anticipatory Intelligence: Assessing the Potential for Crowdsourcing and Intelligence Studies

    Directory of Open Access Journals (Sweden)

    Alexander Halman

    2015-10-01

    Full Text Available Crowdsourcing is a new tool for businesses, academics, and now intelligence analysts. Enabled by recent technology, crowdsourcing allows researchers to harness the wisdom of crowds and provide recommendations and insight into complex problems. This paper examines the potential benefits and limitations of crowdsourcing for intelligence analysis and the intelligence community beyond its primary use: anticipatory intelligence. The author constructs a model and compares it to existing crowdsourcing theories in business, information science, and public policy. Finally, he offers advice for intelligence analysis and public policy.

  18. 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 ...

  19. Hybrid artificial intelligence approach based on neural fuzzy inference model and metaheuristic optimization for flood susceptibilitgy modeling in a high-frequency tropical cyclone area using GIS

    Science.gov (United States)

    Tien Bui, Dieu; Pradhan, Biswajeet; Nampak, Haleh; Bui, Quang-Thanh; Tran, Quynh-An; Nguyen, Quoc-Phi

    2016-09-01

    This paper proposes a new artificial intelligence approach based on neural fuzzy inference system and metaheuristic optimization for flood susceptibility modeling, namely MONF. In the new approach, the neural fuzzy inference system was used to create an initial flood susceptibility model and then the model was optimized using two metaheuristic algorithms, Evolutionary Genetic and Particle Swarm Optimization. A high-frequency tropical cyclone area of the Tuong Duong district in Central Vietnam was used as a case study. First, a GIS database for the study area was constructed. The database that includes 76 historical flood inundated areas and ten flood influencing factors was used to develop and validate the proposed model. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Receiver Operating Characteristic (ROC) curve, and area under the ROC curve (AUC) were used to assess the model performance and its prediction capability. Experimental results showed that the proposed model has high performance on both the training (RMSE = 0.306, MAE = 0.094, AUC = 0.962) and validation dataset (RMSE = 0.362, MAE = 0.130, AUC = 0.911). The usability of the proposed model was evaluated by comparing with those obtained from state-of-the art benchmark soft computing techniques such as J48 Decision Tree, Random Forest, Multi-layer Perceptron Neural Network, Support Vector Machine, and Adaptive Neuro Fuzzy Inference System. The results show that the proposed MONF model outperforms the above benchmark models; we conclude that the MONF model is a new alternative tool that should be used in flood susceptibility mapping. The result in this study is useful for planners and decision makers for sustainable management of flood-prone areas.

  20. Predicting Defects Using Information Intelligence Process Models in the Software Technology Project.

    Science.gov (United States)

    Selvaraj, Manjula Gandhi; Jayabal, Devi Shree; Srinivasan, Thenmozhi; Balasubramanie, Palanisamy

    2015-01-01

    A key differentiator in a competitive market place is customer satisfaction. As per Gartner 2012 report, only 75%-80% of IT projects are successful. Customer satisfaction should be considered as a part of business strategy. The associated project parameters should be proactively managed and the project outcome needs to be predicted by a technical manager. There is lot of focus on the end state and on minimizing defect leakage as much as possible. Focus should be on proactively managing and shifting left in the software life cycle engineering model. Identify the problem upfront in the project cycle and do not wait for lessons to be learnt and take reactive steps. This paper gives the practical applicability of using predictive models and illustrates use of these models in a project to predict system testing defects thus helping to reduce residual defects.

  1. Modeling and Optimization of Food Cold-chain Intelligent Logistics Distribution Network

    Directory of Open Access Journals (Sweden)

    Wuxue Jiang

    2015-03-01

    Full Text Available Aiming at improving the efficiency of food cold-chain logistics network, shortening the logistic time of food and reducing the logistics cost of food, this study analyzes the optimization strategy and various cost factors of the supply network of food cold chain and establishes and expands a kind of logistics network model adapting to the food cold-chain logistics. We use an improved genetic algorithm to solve the model and design an effective coding scheme, through the modified adaptive crossover probability and mutation probability, we integrate them into the elitism strategy, which has effectively avoided the prematurity of the algorithm and improved the operation efficiency of the algorithm. In the same instance, compared with the simple genetic algorithm, this study puts forward that the average running time and the average iteration number of the improved genetic algorithm have reduced nearly 50%, which has proved the feasibility and the effectiveness of the model and the algorithm.

  2. Organizing intelligence: development of behavioral science and the research based model of business education.

    Science.gov (United States)

    Bottom, William P

    2009-01-01

    Conventional history of the predominant, research-based model of business education (RBM) traces its origins to programs initiated by the Ford Foundation after World War II. This paper maps the elite network responsible for developing behavioral science and the Ford Foundation agenda. Archival records of the actions taken by central nodes in the network permit identification of the original vision statement for the model. Analysis also permits tracking progress toward realizing that vision over several decades. Behavioral science was married to business education from the earliest stages of development. The RBM was a fundamental promise made by advocates for social science funding. Appraisals of the model and recommendations for reform must address its full history, not the partial, distorted view that is the conventional account. Implications of this more complete history for business education and for behavioral theory are considered.

  3. Intelligent modified internal model control for speed control of nonlinear uncertain heavy duty vehicles.

    Science.gov (United States)

    Yadav, Anil Kumar; Gaur, Prerna

    2015-05-01

    The objective of this paper is to control the speed of heavy duty vehicle (HDV) through angular position of throttle valve. Modified internal model control (IMC) schemes with fuzzy supervisor as an adaptive tuning are proposed to control the speed of HDV. Internal model (IM) plays a key role in design of various IMC structures with robust and adaptive features. The motivation to design an IM is to produce nearly stable performance as of the system itself. Clustering algorithm and Hankel approximation based model order reduction techniques are used for the design of suitable IM. The time domain performance specifications such as overshoot, settling time, rise time and integral error performance indices such as the integral of the absolute error and the integral of the square of error are taken into consideration for performance analysis of HDV for various uncertainties.

  4. PENGARUH PENDEKATAN MULTIPLE INTELLIGENCES MELALUI MODEL PEMBELAJARAN LANGSUNG TERHADAP SIKAP DAN HASIL BELAJAR KIMIA PESERTA DIDIK DI SMA NEGERI I TELLU LIMPOE

    Directory of Open Access Journals (Sweden)

    I. K. Safitri

    2013-10-01

    Full Text Available Telah dilakukan penelitian yang bertujuan untuk mengetahui pengaruh pendekatan Multiple Intelligences melalui Model Pembelajaran Langsung (Direct Instruction terhadap sikap dan hasil belajar Kimia peserta didik serta korelasinya pada kelas XI IPA SMA Negeri I Tellu Limpoe. Penelitian ini merupakan penelitian eksperimen dengan desain Posttest-Only Control Group Design. Hasil analisis statistik deskriptif menunjukkan bahwa sikap dan hasil belajar Kimia peserta didik pada kelas eksperimen lebih baik dibandingkan kelas kontrol. Selanjutnya, hasil analisis statistik inferensial menunjukkan bahwa terdapat pengaruh yang signifikan pendekatan Multiple Intellegences terhadap sikap dan hasil belajar Kimia peserta didik serta memiliki korelasi positif sebesar 0,522 (korelasi sedang. A research has been conducted which aims to determine the effect of Multiple Intelligences approach through Direct Learning Model (Direct Instruction toward the learners’ attitude and their Chemistry learning outcomes and their correlation to class XI Science SMAN I Tellu Limpoe. This study is an experimental research design with Posttest-Only Control Group Design. The descriptive statistical analysis of the results shows that the learners’ attitudes and chemistry learning outcomes in experimental class were better than the control class. Then, the result of inferential statistical analysis shows that there is a significant influence of Multiple intelligences approach toward the learners’ attitude and their Chemistry learning outcomes and has a positive correlation of 0.522 (moderate correlation.

  5. ICT-Supported Gaming for Competitive Intelligence

    NARCIS (Netherlands)

    Achterbergh, J.M.I.M.

    2005-01-01

    Collecting and processing competitive intelligence for the purpose of strategy formulation are complex activities requiring deep insight in and models of the “organization in its environment.” These insights and models need to be not only shared between CI (competitive intelligence) practitioners fo

  6. ICT-Supported Gaming for Competitive Intelligence

    NARCIS (Netherlands)

    Achterbergh, J.M.I.M.

    2005-01-01

    Collecting and processing competitive intelligence for the purpose of strategy formulation are complex activities requiring deep insight in and models of the “organization in its environment.” These insights and models need to be not only shared between CI (competitive intelligence) practitioners fo

  7. A Native Intelligence Metric for Artificial Systems

    Science.gov (United States)

    2002-08-01

    models of intelligence that will readily yield a NIM. Why not use linear systems theory as a model for a NIM? The successes of traditional linear...intelligence would be easily perceived by all. 1.5 The nature of a NIM Perhaps the solution is not in an analogy to linear systems theory , as has

  8. HISTORIC BUILDING INFORMATION MODELLING – ADDING INTELLIGENCE TO LASER AND IMAGE BASED SURVEYS

    Directory of Open Access Journals (Sweden)

    M. Murphy

    2012-09-01

    Full Text Available Historic Building Information Modelling (HBIM is a novel prototype library of parametric objects based on historic data and a system of cross platform programmes for mapping parametric objects onto a point cloud and image survey data. The HBIM process begins with remote collection of survey data using a terrestrial laser scanner combined with digital photo modelling. The next stage involves the design and construction of a parametric library of objects, which are based on the manuscripts ranging from Vitruvius to 18th century architectural pattern books. In building parametric objects, the problem of file format and exchange of data has been overcome within the BIM ArchiCAD software platform by using geometric descriptive language (GDL. The plotting of parametric objects onto the laser scan surveys as building components to create or form the entire building is the final stage in the reverse engin- eering process. The final HBIM product is the creation of full 3D models including detail behind the object's surface concerning its methods of construction and material make-up. The resultant HBIM can automatically create cut sections, details and schedules in addition to the orthographic projections and 3D models (wire frame or textured.

  9. A comprehensive driver behavior model for the evaluation of intelligent intersections

    NARCIS (Netherlands)

    Schaap, Nina; Arem, van Bart

    2006-01-01

    Many traffic problems occur on urban intersections. Advanced Driver Assistance Systems aim to solve these problems. However, their effects cannot be deduced directly from observing normal driving behavior, because adding a system alters the driving task. A model must be used to represent both normal

  10. The Intelligent Ventilator Project: Application of Physiological Models in Decision Support

    DEFF Research Database (Denmark)

    Rees, Stephen Edward; Karbing, Dan Stieper; Allerød, Charlotte

    2011-01-01

    Management of mechanical ventilation in intensive care patients is complicated by conflicting clinical goals. Decision support systems (DSS) may support clinicians in finding the correct balance. The objective of this study was to evaluate a computerized model-based DSS for its advice on inspired...

  11. Design Appropriate Models Based on Intelligent Dimension in Fars Education Organization

    Science.gov (United States)

    Goodarzi, Shahbaz; Fallah, Vahid; Saffarian, Saeid

    2016-01-01

    The purpose of this study is to determine the dimensions of smart schools in the Fars education system and provide a suitable model. The research method is descriptive survey. The study population consisted of all school principals Fars Province in the academic 2014-2015 and number of them was 1364. The sample volume using Cochran method was 302…

  12. The Intelligent Ventilator Project: Application of Physiological Models in Decision Support

    DEFF Research Database (Denmark)

    Rees, Stephen Edward; Karbing, Dan Stieper; Allerød, Charlotte

    2011-01-01

    Management of mechanical ventilation in intensive care patients is complicated by conflicting clinical goals. Decision support systems (DSS) may support clinicians in finding the correct balance. The objective of this study was to evaluate a computerized model-based DSS for its advice on inspired...

  13. Historic Building Information Modelling - Adding Intelligence to Laser and Image Based Surveys

    Science.gov (United States)

    Murphy, M.; McGovern, E.; Pavia, S.

    2011-09-01

    Historic Building Information Modelling (HBIM) is a novel prototype library of parametric objects based on historic data and a system of cross platform programmes for mapping parametric objects onto a point cloud and image survey data. The HBIM process begins with remote collection of survey data using a terrestrial laser scanner combined with digital photo modelling. The next stage involves the design and construction of a parametric library of objects, which are based on the manuscripts ranging from Vitruvius to 18th century architectural pattern books. In building parametric objects, the problem of file format and exchange of data has been overcome within the BIM ArchiCAD software platform by using geometric descriptive language (GDL). The plotting of parametric objects onto the laser scan surveys as building components to create or form the entire building is the final stage in the reverse engin- eering process. The final HBIM product is the creation of full 3D models including detail behind the object's surface concerning its methods of construction and material make-up. The resultant HBIM can automatically create cut sections, details and schedules in addition to the orthographic projections and 3D models (wire frame or textured).

  14. Historic Building Information Modelling - Adding intelligence to laser and image based surveys of European classical architecture

    Science.gov (United States)

    Murphy, Maurice; McGovern, Eugene; Pavia, Sara

    2013-02-01

    Historic Building Information Modelling (HBIM) is a novel prototype library of parametric objects, based on historic architectural data and a system of cross platform programmes for mapping parametric objects onto point cloud and image survey data. The HBIM process begins with remote collection of survey data using a terrestrial laser scanner combined with digital photo modelling. The next stage involves the design and construction of a parametric library of objects, which are based on the manuscripts ranging from Vitruvius to 18th century architectural pattern books. In building parametric objects, the problem of file format and exchange of data has been overcome within the BIM ArchiCAD software platform by using geometric descriptive language (GDL). The plotting of parametric objects onto the laser scan surveys as building components to create or form the entire building is the final stage in the reverse engineering process. The final HBIM product is the creation of full 3D models including detail behind the object's surface concerning its methods of construction and material make-up. The resultant HBIM can automatically create cut sections, details and schedules in addition to the orthographic projections and 3D models (wire frame or textured) for both the analysis and conservation of historic objects, structures and environments.

  15. Leak Detection Modeling and Simulation for Oil Pipeline with Artificial Intelligence Method

    Directory of Open Access Journals (Sweden)

    Pudjo Sukarno

    2007-05-01

    Full Text Available Leak detection is always interesting research topic, where leak location and leak rate are two pipeline leaking parameters that should be determined accurately to overcome pipe leaking problems. In this research those two parameters are investigated by developing transmission pipeline model and the leak detection model which is developed using Artificial Neural Network. The mathematical approach needs actual leak data to train the leak detection model, however such data could not be obtained from oil fields. Therefore, for training purposes hypothetical data are developed using the transmission pipeline model, by applying various physical configuration of pipeline and applying oil properties correlations to estimate the value of oil density and viscosity. The various leak locations and leak rates are also represented in this model. The prediction of those two leak parameters will be completed until the total error is less than certain value of tolerance, or until iterations level is reached. To recognize the pattern, forward procedure is conducted. The application of this approach produces conclusion that for certain pipeline network configuration, the higher number of iterations will produce accurate result. The number of iterations depend on the leakage rate, the smaller leakage rate, the higher number of iterations are required. The accuracy of this approach is clearly determined by the quality of training data. Therefore, in the preparation of training data the results of pressure drop calculations should be validated by the real measurement of pressure drop along the pipeline. For the accuracy purposes, there are possibility to change the pressure drop and fluid properties correlations, to get the better results. The results of this research are expected to give real contribution for giving an early detection of oil-spill in oil fields.

  16. A New Era of Intelligence Research

    Directory of Open Access Journals (Sweden)

    Andrew R. A. Conway

    2014-04-01

    Full Text Available A consensus definition of intelligence remains elusive but there are many reasons to believe that the field of intelligence is entering a new era of significant progress. The convergence of recent advances in psychometrics, cognitive psychology, and neuroscience has set the stage for the development of stronger theories and more sophisticated models. The establishment of a new open access journal as an outlet for new intelligence research is evidence that the new era has begun.

  17. A New Era of Intelligence Research

    OpenAIRE

    Conway, Andrew R. A.

    2014-01-01

    A consensus definition of intelligence remains elusive but there are many reasons to believe that the field of intelligence is entering a new era of significant progress. The convergence of recent advances in psychometrics, cognitive psychology, and neuroscience has set the stage for the development of stronger theories and more sophisticated models. The establishment of a new open access journal as an outlet for new intelligence research is evidence that the new era has begun.

  18. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  19. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  20. Assessing Intelligence in Children and Youth Living in the Netherlands

    Science.gov (United States)

    Hurks, Petra P. M.; Bakker, Helen

    2016-01-01

    In this article, we briefly describe the history of intelligence test use with children and youth in the Netherlands, explain which models of intelligence guide decisions about test use, and detail how intelligence tests are currently being used in Dutch school settings. Empirically supported and theoretical models studying the structure of human…

  1. Business Intelligence

    OpenAIRE

    Strejčková, Lucie

    2006-01-01

    Cílem této bakalářské práce je seznámení s Business Intelligence a zpracování vývojového trendu, který ovlivňuje podobu řešení Business Intelligence v podniku ? Business Activity Monitoring. Pro zpracování tohoto tématu byla použita metoda studia odborných pramenů, a to jak v českém, tak v anglickém jazyce. Hlavním přínosem práce je ucelený, v českém jazyce zpracovaný materiál pojednávající o Business Activity Monitoring. Práce je rozdělena do šesti hlavních kapitol. Prvních pět je věnováno p...

  2. Business Intelligence

    OpenAIRE

    Strejčková, Lucie

    2001-01-01

    Cílem této bakalářské práce je seznámení s Business Intelligence a zpracování vývojového trendu, který ovlivňuje podobu řešení Business Intelligence v podniku ? Business Activity Monitoring. Pro zpracování tohoto tématu byla použita metoda studia odborných pramenů, a to jak v českém, tak v anglickém jazyce. Hlavním přínosem práce je ucelený, v českém jazyce zpracovaný materiál pojednávající o Business Activity Monitoring. Práce je rozdělena do šesti hlavních kapitol. Prvních pět je věnováno p...

  3. EHRs Connect Research and Practice: Where Predictive Modeling, Artificial Intelligence, and Clinical Decision Support Intersect

    CERN Document Server

    Bennett, Casey; Selove, Rebecca

    2012-01-01

    Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and genetic information as well, and, as such, can be seen as repositories of increasingly valuable information about patients' health conditions and responses to treatment over time. Methods: We describe a case study of 423 patients treated by Centerstone within Tennessee and Indiana in which we utilized electronic health record data to generate predictive algorithms of individual patient treatment response. Multiple models were constructed using predictor variables derived from clinical, financial and geographic data. Results: For the 423 patients, 101 deteriorated, 223 improved and in 99 there was no change in clinical condition. Based on modeling of various clinical indicators at baseline, the high...

  4. Design Novel Model Reference Artificial Intelligence Based Methodology to Optimized Fuel Ratio in IC Engine

    Directory of Open Access Journals (Sweden)

    FarzinPiltan

    2013-08-01

    Full Text Available In this research, model reference fuzzy based control is presented as robust controls for IC engine. The objective of the study is to design controls for IC engines without the knowledge of the boundary of uncertainties and dynamic information by using fuzzy model reference PD plus mass of air while improve the robustness of the PD plus mass of air control. A PD plus mass of air provides for eliminate the mass of air and ultimate accuracy in the presence of the bounded disturbance/uncertainties, although this methods also causes some oscillation. The fuzzy PD plus mass of air is proposed as a solution to the problems crated by unstability. This method has a good performance in presence of uncertainty.

  5. B-tree search reinforcement learning for model based intelligent agent

    Science.gov (United States)

    Bhuvaneswari, S.; Vignashwaran, R.

    2013-03-01

    Agents trained by learning techniques provide a powerful approximation of active solutions for naive approaches. In this study using B - Trees implying reinforced learning the data search for information retrieval is moderated to achieve accuracy with minimum search time. The impact of variables and tactics applied in training are determined using reinforcement learning. Agents based on these techniques perform satisfactory baseline and act as finite agents based on the predetermined model against competitors from the course.

  6. Software-aided Service Bundling : Intelligent Methods and Tools for Graphical Service Modeling

    OpenAIRE

    Baida, Z.S.

    2006-01-01

    Services, such as insurances, transport, medical treatments and more, have been subject to extensive research business science for decennia. When services are offered, bought or consumed online, we refer to them as e-services. This PhD thesis focuses on an ontological foundation for service description and configuration. Such a conceptual modeling approach facilitates complex e-service scenarios, in which a customer can define a bundle of services, possibly supplied by multiple suppliers, bas...

  7. Sensor performance and weather effects modeling for intelligent transportation systems (ITS) applications

    Science.gov (United States)

    Everson, Jeffrey H.; Kopala, Edward W.; Lazofson, Laurence E.; Choe, Howard C.; Pomerleau, Dean A.

    1995-01-01

    Optical sensors are used for several ITS applications, including lateral control of vehicles, traffic sign recognition, car following, autonomous vehicle navigation, and obstacle detection. This paper treats the performance assessment of a sensor/image processor used as part of an on-board countermeasure system to prevent single vehicle roadway departure crashes. Sufficient image contrast between objects of interest and backgrounds is an essential factor influencing overall system performance. Contrast is determined by material properties affecting reflected/radiated intensities, as well as weather and visibility conditions. This paper discusses the modeling of these parameters and characterizes the contrast performance effects due to reduced visibility. The analysis process first involves generation of inherent road/off- road contrasts, followed by weather effects as a contrast modification. The sensor is modeled as a charge coupled device (CCD), with variable parameters. The results of the sensor/weather modeling are used to predict the performance on an in-vehicle warning system under various levels of adverse weather. Software employed in this effort was previously developed for the U.S. Air Force Wright Laboratory to determine target/background detection and recognition ranges for different sensor systems operating under various mission scenarios.

  8. Levy-like behaviour in deterministic models of intelligent agents exploring heterogeneous environments

    Energy Technology Data Exchange (ETDEWEB)

    Boyer, D; Miramontes, O [Departamento de Sistemas Complejos, Instituto de Fisica, Universidad Nacional Autonoma de Mexico, DF 04510 (Mexico); Larralde, H [Instituto de Ciencias Fisicas, Universidad Nacional Autonoma de Mexico, Apartado Postal 48-3, Cuernavaca, 62251 Morelos (Mexico)], E-mail: boyer@fisica.unam.mx, E-mail: octavio@fisica.unam.mx, E-mail: hernan@ce.fis.unam.mx

    2009-10-30

    Many studies on animal and human movement patterns report the existence of scaling laws and power-law distributions. Whereas a number of random walk models have been proposed to explain observations, in many situations individuals actually rely on mental maps to explore strongly heterogeneous environments. In this work, we study a model of a deterministic walker, visiting sites randomly distributed on the plane and with varying weight or attractiveness. At each step, the walker minimizes a function that depends on the distance to the next unvisited target (cost) and on the weight of that target (gain). If the target weight distribution is a power law, p(k) {approx} k{sup -{beta}}, in some range of the exponent {beta}, the foraging medium induces movements that are similar to Levy flights and are characterized by non-trivial exponents. We explore variations of the choice rule in order to test the robustness of the model and argue that the addition of noise has a limited impact on the dynamics in strongly disordered media.

  9. Lévy-like behaviour in deterministic models of intelligent agents exploring heterogeneous environments

    Science.gov (United States)

    Boyer, D.; Miramontes, O.; Larralde, H.

    2009-10-01

    Many studies on animal and human movement patterns report the existence of scaling laws and power-law distributions. Whereas a number of random walk models have been proposed to explain observations, in many situations individuals actually rely on mental maps to explore strongly heterogeneous environments. In this work, we study a model of a deterministic walker, visiting sites randomly distributed on the plane and with varying weight or attractiveness. At each step, the walker minimizes a function that depends on the distance to the next unvisited target (cost) and on the weight of that target (gain). If the target weight distribution is a power law, p(k) ~ k-β, in some range of the exponent β, the foraging medium induces movements that are similar to Lévy flights and are characterized by non-trivial exponents. We explore variations of the choice rule in order to test the robustness of the model and argue that the addition of noise has a limited impact on the dynamics in strongly disordered media.

  10. Computational Intelligence Based Data Fusion Algorithm for Dynamic sEMG and Skeletal Muscle Force Modelling

    Energy Technology Data Exchange (ETDEWEB)

    Chandrasekhar Potluri,; Madhavi Anugolu; Marco P. Schoen; D. Subbaram Naidu

    2013-08-01

    In this work, an array of three surface Electrography (sEMG) sensors are used to acquired muscle extension and contraction signals for 18 healthy test subjects. The skeletal muscle force is estimated using the acquired sEMG signals and a Non-linear Wiener Hammerstein model, relating the two signals in a dynamic fashion. The model is obtained from using System Identification (SI) algorithm. The obtained force models for each sensor are fused using a proposed fuzzy logic concept with the intent to improve the force estimation accuracy and resilience to sensor failure or misalignment. For the fuzzy logic inference system, the sEMG entropy, the relative error, and the correlation of the force signals are considered for defining the membership functions. The proposed fusion algorithm yields an average of 92.49% correlation between the actual force and the overall estimated force output. In addition, the proposed fusionbased approach is implemented on a test platform. Experiments indicate an improvement in finger/hand force estimation.

  11. Intelligence in children

    Directory of Open Access Journals (Sweden)

    Martín Nader

    2015-09-01

    Full Text Available Partial results of an investigation are presented whose primary objective is to adapt and to standardize the neurocognitive assessment battery C.A.S. of Das and Naglieri (1997 in a child sample. The test is an operationalization of a non traditional intelligence model (PASS that considers the intelligent behaviors as a group of four cognitive basic processes (planning, attention, simultaneous and successive processing. The objectives of this work are to obtain the psychometric properties of the instrument and also, to analyze if differences exist according to sex and age. The study type is crosswise - transactional. It was administered the CAS to 150 children residents in Buenos Aires among the ages of 6 to 12 years (population general non consultant and the WISC-III to a sample of 50 children. 

  12. Intelligent Sensors Security

    Directory of Open Access Journals (Sweden)

    Andrzej Bialas

    2010-01-01

    Full Text Available The paper is focused on the security issues of sensors provided with processors and software and used for high-risk applications. Common IT related threats may cause serious consequences for sensor system users. To improve their robustness, sensor systems should be developed in a restricted way that would provide them with assurance. One assurance creation methodology is Common Criteria (ISO/IEC 15408 used for IT products and systems. The paper begins with a primer on the Common Criteria, and then a general security model of the intelligent sensor as an IT product is discussed. The paper presents how the security problem of the intelligent sensor is defined and solved. The contribution of the paper is to provide Common Criteria (CC related security design patterns and to improve the effectiveness of the sensor development process.

  13. Intelligent Sensors Security

    Science.gov (United States)

    Bialas, Andrzej

    2010-01-01

    The paper is focused on the security issues of sensors provided with processors and software and used for high-risk applications. Common IT related threats may cause serious consequences for sensor system users. To improve their robustness, sensor systems should be developed in a restricted way that would provide them with assurance. One assurance creation methodology is Common Criteria (ISO/IEC 15408) used for IT products and systems. The paper begins with a primer on the Common Criteria, and then a general security model of the intelligent sensor as an IT product is discussed. The paper presents how the security problem of the intelligent sensor is defined and solved. The contribution of the paper is to provide Common Criteria (CC) related security design patterns and to improve the effectiveness of the sensor development process. PMID:22315571

  14. Computational Intelligence Modeling of the Macromolecules Release from PLGA Microspheres-Focus on Feature Selection.

    Directory of Open Access Journals (Sweden)

    Hossam M Zawbaa

    Full Text Available Poly-lactide-co-glycolide (PLGA is a copolymer of lactic and glycolic acid. Drug release from PLGA microspheres depends not only on polymer properties but also on drug type, particle size, morphology of microspheres, release conditions, etc. Selecting a subset of relevant properties for PLGA is a challenging machine learning task as there are over three hundred features to consider. In this work, we formulate the selection of critical attributes for PLGA as a multiobjective optimization problem with the aim of minimizing the error of predicting the dissolution profile while reducing the number of attributes selected. Four bio-inspired optimization algorithms: antlion optimization, binary version of antlion optimization, grey wolf optimization, and social spider optimization are used to select the optimal feature set for predicting the dissolution profile of PLGA. Besides these, LASSO algorithm is also used for comparisons. Selection of crucial variables is performed under the assumption that both predictability and model simplicity are of equal importance to the final result. During the feature selection process, a set of input variables is employed to find minimum generalization error across different predictive models and their settings/architectures. The methodology is evaluated using predictive modeling for which various tools are chosen, such as Cubist, random forests, artificial neural networks (monotonic MLP, deep learning MLP, multivariate adaptive regression splines, classification and regression tree, and hybrid systems of fuzzy logic and evolutionary computations (fugeR. The experimental results are compared with the results reported by Szlȩk. We obtain a normalized root mean square error (NRMSE of 15.97% versus 15.4%, and the number of selected input features is smaller, nine versus eleven.

  15. Active load management in an intelligent building using model predictive control strategy

    DEFF Research Database (Denmark)

    Zong, Yi; Kullmann, Daniel; Thavlov, Anders

    2011-01-01

    This paper introduces PowerFlexHouse, a research facility for exploring the technical potential of active load management in a distributed power system (SYSLAB) with a high penetration of renewable energy and presents in detail on how to implement a thermal model predictive controller for load...... shifting in PowerFlexHouse heaters' power consumption scheme. With this demand side control study, it is expected that this method of demand response can dramatically raise energy efficiencies and improve grid reliability, when there is a high penetration of intermittent energy resources in the power...

  16. Object as a model of intelligent robot in the virtual workspace

    Science.gov (United States)

    Foit, K.; Gwiazda, A.; Banas, W.; Sekala, A.; Hryniewicz, P.

    2015-11-01

    The contemporary industry requires that every element of a production line will fit into the global schema, which is connected with the global structure of business. There is the need to find the practical and effective ways of the design and management of the production process. The term “effective” should be understood in a manner that there exists a method, which allows building a system of nodes and relations in order to describe the role of the particular machine in the production process. Among all the machines involved in the manufacturing process, industrial robots are the most complex ones. This complexity is reflected in the realization of elaborated tasks, involving handling, transporting or orienting the objects in a work space, and even performing simple machining processes, such as deburring, grinding, painting, applying adhesives and sealants etc. The robot also performs some activities connected with automatic tool changing and operating the equipment mounted on the wrist of the robot. Because of having the programmable control system, the robot also performs additional activities connected with sensors, vision systems, operating the storages of manipulated objects, tools or grippers, measuring stands, etc. For this reason the description of the robot as a part of production system should take into account the specific nature of this machine: the robot is a substitute of a worker, who performs his tasks in a particular environment. In this case, the model should be able to characterize the essence of "employment" in the sufficient way. One of the possible approaches to this problem is to treat the robot as an object, in the sense often used in computer science. This allows both: to describe certain operations performed on the object, as well as describing the operations performed by the object. This paper focuses mainly on the definition of the object as the model of the robot. This model is confronted with the other possible descriptions. The

  17. Investment Cost Model in Business Process Intelligence in Banking and Electricity Company

    Directory of Open Access Journals (Sweden)

    Arta Moro Sundjaja

    2016-06-01

    organizations and some cost model to calculate the investment of BPI solutions. This paper shows the success in BPI application of banks and assurance companies in German and electricity work in Australia aims to give a vision about the importance of BPI application. Many challenges in BPI application of companies in German and Australia, BPI solution, and data warehouse design development have been discussed to add insight in future BPI development. And the last is an explanation about how to analyze cost associated with BPI solution investment.

  18. Application of a Cognitive Model for Army Training: Handbook for Strategic Intelligence Analysis

    Science.gov (United States)

    1984-10-01

    Thompson, Hopf-Weichel, & Geisel - man, 1984 for initial and updated versions of the model; see also Montgomery, "- Thompson, & Katter, 1980 for an...6.2.2 6-1 Retraining 6.2.3 6-2 Exploitation of Library Resources 6.3 6-2 Academic Training and the Strategic Analyst 6.4 6-3 BIBLIOGRAPHY BIB-1...SQ3R: Mnemonic Strategy for Organized Material 5-8 6-8. (U) Mnemonic Strategy For Unrelated items 5-9 5-9. (U) Assets of the Technical Library 5-10 5-10

  19. Incomplete Intelligence: Is the Information Sharing Environment an Effective Platform?

    Science.gov (United States)

    2012-09-01

    these measures (spoiler: it fails). The ISE is evaluated using a Business Intelligence maturity 6 model, in which it scores at the low end of both the...2015: A Globally Networked and Integrated Intelligence Enterprise, 2008, p. 9). The use of business intelligence in the commercial arena, including...the world with a distinct set of biases. The use of business intelligence and Big Data across numerous sectors is described. Reference models for

  20. Neural networks with multiple general neuron models: a hybrid computational intelligence approach using Genetic Programming.

    Science.gov (United States)

    Barton, Alan J; Valdés, Julio J; Orchard, Robert

    2009-01-01

    Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.