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Sample records for intelligence production model

  1. 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.

  2. 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.

  3. Intelligent products : A survey

    NARCIS (Netherlands)

    Meyer, G.G.; Främling, K.; Holmström, J.

    This paper presents an overview of the field of Intelligent Products. As Intelligent Products have many facets, this paper is mainly focused on the concept behind Intelligent Products, the technical foundations, and the achievable practical goals of Intelligent Products. A novel classification of

  4. Model business intelligence system design of quality products by using data mining in R Bakery Company

    Science.gov (United States)

    Fitriana, R.; Saragih, J.; Luthfiana, N.

    2017-12-01

    R Bakery company is a company that produces bread every day. Products that produced in that company have many different types of bread. Products are made in the form of sweet bread and wheat bread which have different tastes for every types of bread. During the making process, there were defects in the products which the defective product turns into reject product. Types of defects that are produced include burnt, sodden bread and shapeless bread. To find out the information about the defects that have been produced then by applying a designed model business intelligence system to create database and data warehouse. By using model business Intelligence system, it will generate useful information such as how many defect that produced by each of the bakery products. To make it easier to obtain such information, it can be done by using data mining method which data that we get is deep explored. The method of data mining is using k-means clustering method. The results of this intelligence business model system are cluster 1 with little amount of defect, cluster 2 with medium amount of defect and cluster 3 with high amount of defect. From OLAP Cube method can be seen that the defect generated during the 7 months period of 96,744 pieces.

  5. 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.

  6. 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.

  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. Modelling intelligent behavior

    Science.gov (United States)

    Green, H. S.; Triffet, T.

    1993-01-01

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

  9. A Procedure for Building Product Models in Intelligent Agent-based OperationsManagement

    DEFF Research Database (Denmark)

    Hvam, Lars; Riis, Jesper; Malis, Martin

    2003-01-01

    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 b...

  10. Improving designer productivity. [artificial intelligence

    Science.gov (United States)

    Hill, Gary C.

    1992-01-01

    Designer and design team productivity improves with skill, experience, and the tools available. The design process involves numerous trials and errors, analyses, refinements, and addition of details. Computerized tools have greatly speeded the analysis, and now new theories and methods, emerging under the label Artificial Intelligence (AI), are being used to automate skill and experience. These tools improve designer productivity by capturing experience, emulating recognized skillful designers, and making the essence of complex programs easier to grasp. This paper outlines the aircraft design process in today's technology and business climate, presenting some of the challenges ahead and some of the promising AI methods for meeting these challenges.

  11. An intelligent sales assistant for configurable products

    OpenAIRE

    Molina, Martin

    2001-01-01

    Some of the recent proposals of web-based applications are oriented to provide advanced search services through virtual shops. Within this context, this paper proposes an advanced type of software application that simulates how a sales assistant dialogues with a consumer to dynamically configure a product according to particular needs. The paper presents the general knowl- edge model that uses artificial intelligence and knowledge-based techniques to simulate the configuration process. Finall...

  12. Modelling traffic flows with intelligent cars and intelligent roads

    NARCIS (Netherlands)

    van Arem, Bart; Tampere, Chris M.J.; Malone, Kerry

    2003-01-01

    This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed

  13. Product Line Enabled Intelligent Mobile Middleware

    DEFF Research Database (Denmark)

    Zhang, Weishan; Kunz, Thomas; Hansen, Klaus Marius

    2007-01-01

    research project called PLIMM that focuses on user-centered application scenarios. PLIMM is designed based on software product line ideas which make it possible for specialized customization and optimization for different purposes and hardware/software platforms. To enable intelligence, the middleware...... needs access to a range of context models. We model these contexts with OWL, focusing on user-centered concepts. The basic building block of PLIMM is the enhanced BDI agent where OWL context ontology logic reasoning will add indirect beliefs to the belief sets. Our approach also addresses the handling...

  14. Computational Intelligence Techniques for New Product Design

    CERN Document Server

    Chan, Kit Yan; Dillon, Tharam S

    2012-01-01

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

  15. All-source Information Management and Integration for Improved Collective Intelligence Production

    Science.gov (United States)

    2011-06-01

    Intelligence (ELINT) • Open Source Intelligence ( OSINT ) • Technical Intelligence (TECHINT) These intelligence disciplines produce... intelligence , measurement and signature intelligence , signals intelligence , and open - source data, in the production of intelligence . All- source intelligence ...All- Source Information Integration and Management) R&D Project 3 All- Source Intelligence

  16. Identification of key factors in consumers' adoption behavior of intelligent medical terminals based on a hybrid modified MADM model for product improvement.

    Science.gov (United States)

    Liu, Yupeng; Chen, Yifei; Tzeng, Gwo-Hshiung

    2017-09-01

    As a new application technology of the Internet of Things (IoT), intelligent medical treatment has attracted the attention of both nations and industries through its promotion of medical informatisation, modernisation, and intelligentisation. Faced with a wide variety of intelligent medical terminals, consumers may be affected by various factors when making purchase decisions. To examine and evaluate the key influential factors (and their interrelationships) of consumer adoption behavior for improving and promoting intelligent medical terminals toward achieving set aspiration level in each dimension and criterion. A hybrid modified Multiple Attribute Decision-Making (MADM) model was used for this study, based on three components: (1) the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique, to build an influential network relationship map (INRM) at both 'dimensions' and 'criteria' levels; (2) the DEMATEL-based analytic network process (DANP) method, to determine the interrelationships and influential weights among the criteria and identify the source-influential factors; and (3) the modified Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, to evaluate and improve for reducing the performance gaps to meet the consumers' needs for continuous improvement and sustainable products-development. First, a consensus on the influential factors affecting consumers' adoption of intelligent medical terminals was collected from experts' opinion in practical experience. Next, the interrelationships and influential weights of DANP among dimensions/criteria based on the DEMATEL technique were determined. Finally, two intelligent medicine bottles (AdhereTech, A 1 alternative; and Audio/Visual Alerting Pillbox, A 2 alternative) were reviewed as the terminal devices to verify the accuracy of the MADM model and evaluate its performance on each criterion for improving the total certification gaps by systematics according to the modified VIKOR method

  17. Intelligent structural optimization: Concept, Model and Methods

    International Nuclear Information System (INIS)

    Lu, Dagang; Wang, Guangyuan; Peng, Zhang

    2002-01-01

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

  18. Student Modeling in an Intelligent Tutoring System

    Science.gov (United States)

    1996-12-17

    Multi-Agent Architecture." Advances in Artificial Intelligence : Proceedings of the 12 th Brazilian Symposium on Aritificial Intelligence , edited by...STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D-27 DIMTVMON* fCKAJWINT A Appr"v*d t=i...Air Force Base, Ohio AFIT/GCS/ENG/96D-27 STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D

  19. 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.

  20. 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

  1. Estimating New Product Success with the Use of Intelligent Systems

    Directory of Open Access Journals (Sweden)

    Relich Marcin

    2014-12-01

    Full Text Available The paper presents identifying success factors in new product development and selecting new product portfolio. The critical success factors are identified on the basis of an enterprise system, including the fields of project management, marketing and customer’s comments concerning the previous products. The model of measuring the success of a product includes the indicators such as duration and cost of product development, and net profit from a product. The proposed methodology is based on identification of the relationships between product success and project environment parameters with the use of artificial neural networks and fuzzy neural system that is compared with the results from linear model. The presented method contains the stages of knowledge discovery process such as data selection, data preprocessing, and data mining in the context of an enterprise resource planning system database. The illustrative example enhances a performance comparison of intelligent systems in the context of data preprocessing.

  2. A Research Review on the Key Technologies of Intelligent Design for Customized Products

    Directory of Open Access Journals (Sweden)

    Shuyou Zhang

    2017-10-01

    Full Text Available The development of technologies such as big data and cyber-physical systems (CPSs has increased the demand for product design. Product digital design involves completing the product design process using advanced digital technologies such as geometry modeling, kinematic and dynamic simulation, multi-disciplinary coupling, virtual assembly, virtual reality (VR, multi-objective optimization (MOO, and human-computer interaction. The key technologies of intelligent design for customized products include: a description and analysis of customer requirements (CRs, product family design (PFD for the customer base, configuration and modular design for customized products, variant design for customized products, and a knowledge push for product intelligent design. The development trends in intelligent design for customized products include big-data-driven intelligent design technology for customized products and customized design tools and applications. The proposed method is verified by the design of precision computer numerical control (CNC machine tools.

  3. 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.

  4. Model SH intelligent instrument for thickness measuring

    International Nuclear Information System (INIS)

    Liu Juntao; Jia Weizhuang; Zhao Yunlong

    1995-01-01

    The authors introduce Model SH Intelligent Instrument for thickness measuring by using principle of beta back-scattering and its application range, features, principle of operation, system design, calibration and specifications

  5. An Intelligent Method of Product Scheme Design Based on Product Gene

    Directory of Open Access Journals (Sweden)

    Qing Song Ai

    2013-01-01

    Full Text Available Nowadays, in order to have some featured products, many customers tend to buy customized products instead of buying common ones in supermarket. The manufacturing enterprises, with the purpose of improving their competitiveness, are focusing on providing customized products with high quality and low cost as well. At present, how to produce customized products rapidly and cheaply has been the key challenge to manufacturing enterprises. In this paper, an intelligent modeling approach applied to supporting the modeling of customized products is proposed, which may improve the efficiency during the product design process. Specifically, the product gene (PG method, which is an analogy of biological evolution in engineering area, is employed to model products in a new way. Based on product gene, we focus on the intelligent modeling method to generate product schemes rapidly and automatically. The process of our research includes three steps: (1 develop a product gene model for customized products; (2 find the obtainment and storage method for product gene; and (3 propose a specific genetic algorithm used for calculating the solution of customized product and generating new product schemes. Finally, a case study is applied to test the usefulness of our study.

  6. Electronic tagging and integrated product intelligence

    Science.gov (United States)

    Swerdlow, Martin; Weeks, Brian

    1996-03-01

    The advent of 'intelligent,' electronic data bearing tags is set to revolutionize the way industrial and retail products are identified and tracked throughout their life cycles. The dominant system for unique identification today is the bar code, which is based on printed symbology and regulated by the International Article Numbering Association. Bar codes provide users with significant operational advantages and generate considerable added value to packaging companies, product manufacturers, distributors and retailers, across supply chains in many different sectors, from retailing, to baggage handling and industrial components, e.g., for vehicles or aircraft. Electronic tags offer the potential to: (1) record and store more complex data about the product or any modifications which occur during its life cycle; (2) access (and up-date) stored data in real time in a way which does not involve contact with the product or article; (3) overcome the limitations imposed by systems which rely on line-of-sight access to stored data. Companies are now beginning to consider how electronic data tags can be used, not only to improve the efficiency of their supply chain processes, but also to revolutionize the way they do business. This paper reviews the applications and business opportunities for electronic tags and outlines CEST's strategy for achieving an 'open' standard which will ensure that tags from different vendors can co-exist on an international basis.

  7. A conceptual competitive intelligence quality assurance model

    Directory of Open Access Journals (Sweden)

    Tshilidzi Eric Nenzhelele

    2015-12-01

    Full Text Available Competitive Intelligence (CI improves the quality of product and service, decision-making and it improves quality of life. However, it has been established that decision makers are not happy about the quality of CI. This is because enterprises fail in quality assurance of CI. It has been concluded that most enterprises are clueless concerning CI quality assurance. Studies that previously attempted to resolve CI quality problem were limited in scope and focused too much on the quality of information than the overall CI quality. The purpose of this study is to propose a conceptual CI quality assurance model which will help in quality assurance of CI. The research was qualitative in nature and used content analysis.

  8. 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

  9. Intelligence and the brain: a model-based approach

    NARCIS (Netherlands)

    Kievit, R.A.; van Rooijen, H.; Wicherts, J.M.; Waldorp, L.J.; Kan, K.-J.; Scholte, H.S.; Borsboom, D.

    2012-01-01

    Various biological correlates of general intelligence (g) have been reported. Despite this, however, the relationship between neurological measurements and g is not fully clear. We use structural equation modeling to model the relationship between behavioral Wechsler Adult Intelligence Scale (WAIS)

  10. 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.

  11. 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.

  12. Intelligent Systems Approaches to Product Sound Quality Analysis

    Science.gov (United States)

    Pietila, Glenn M.

    As a product market becomes more competitive, consumers become more discriminating in the way in which they differentiate between engineered products. The consumer often makes a purchasing decision based on the sound emitted from the product during operation by using the sound to judge quality or annoyance. Therefore, in recent years, many sound quality analysis tools have been developed to evaluate the consumer preference as it relates to a product sound and to quantify this preference based on objective measurements. This understanding can be used to direct a product design process in order to help differentiate the product from competitive products or to establish an impression on consumers regarding a product's quality or robustness. The sound quality process is typically a statistical tool that is used to model subjective preference, or merit score, based on objective measurements, or metrics. In this way, new product developments can be evaluated in an objective manner without the laborious process of gathering a sample population of consumers for subjective studies each time. The most common model used today is the Multiple Linear Regression (MLR), although recently non-linear Artificial Neural Network (ANN) approaches are gaining popularity. This dissertation will review publicly available published literature and present additional intelligent systems approaches that can be used to improve on the current sound quality process. The focus of this work is to address shortcomings in the current paired comparison approach to sound quality analysis. This research will propose a framework for an adaptive jury analysis approach as an alternative to the current Bradley-Terry model. The adaptive jury framework uses statistical hypothesis testing to focus on sound pairings that are most interesting and is expected to address some of the restrictions required by the Bradley-Terry model. It will also provide a more amicable framework for an intelligent systems approach

  13. Construction of Intelligence Knowledge Map for Complex Product Development

    Directory of Open Access Journals (Sweden)

    Yan-jie LV,

    2013-11-01

    Full Text Available The complex product design and development is an integrated discipline. A lot of knowledge overloads and knowledge trek phenomenon appeared with the raise of product complexity and the explosion of knowledge and information. To improve the utilization efficiency of the knowledge using and shorten the time and effort spent on the Knowledge screening, avoid missing the knowledge, which is required, the paper proposes a method for the intelligence knowledge map construct model based on knowledge requirements and knowledge connection. Analyzing the context information of the user and giving the method of acquiring the knowledge requirement based on the context information and the user’s personal knowledge structure. This method can get the knowledge requirements of the users to generate the knowledge retrieval expressions to obtain the knowledge points and then construct the intelligent knowledge map through the analysis of multiple dimensions and using the knowledge related to the development of aircraft landing gear as an example to verify the feasibility of this method.

  14. Increasing Organizational Productivity Through Heightened Emotional Intelligence.

    Science.gov (United States)

    Maulding, Wanda S.

    According to psychologist Daniel Goleman, a strong IQ can set the baseline for success but does not guarantee prosperity. Goleman believes that factors contributing to "emotional intelligence" (for example, self-control, zeal and persistence, and ability to motivate oneself) are key to success in the corporate world. Howard Gardner has…

  15. Programming model for distributed intelligent systems

    Science.gov (United States)

    Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.

    1988-01-01

    A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

  16. 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

  17. 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 ...

  18. U.S. intelligence system: model for corporate chiefs?

    Science.gov (United States)

    Gilad, B

    1991-01-01

    A fully dedicated intelligence support function for senior management is no longer a luxury but a necessity. Companies can enhance their intelligence capabilities by using the government model as a rough blueprint to structure such a program.

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

    Indian Academy of Sciences (India)

    This study proposes an application of two techniques of artificial intelligence (AI) ... (2006) applied rainfall–runoff modeling using ANN ... in artificial intelligence, engineering and science .... usually be estimated from a sample of observations.

  20. The Development of an Intelligent Leadership Model for State Universities

    OpenAIRE

    Aleme Keikha; Reza Hoveida; Nour Mohammad Yaghoubi

    2017-01-01

    Higher education and intelligent leadership are considered important parts of every country’s education system, which could potentially play a key role in accomplishing the goals of society. In theories of leadership, new patterns attempt to view leadership through the prism of creative and intelligent phenomena. This paper aims to design and develop an intelligent leadership model for public universities. A qualitativequantitative research method was used to design a basic model of intellige...

  1. Synergy between Software Product Line and Intelligent Mobile Middleware

    DEFF Research Database (Denmark)

    Zhang, Weishan; Hansen, Klaus Marius

    2007-01-01

    with OWL ontology reasoning enhanced BDI (belief-desire-intention) agents in an ongoing research project called PLIMM (product line enabled intelligent mobile middleware), in which Frame based software product line techniques are applied. Besides the advantages of a software product line, our approach can...... handle ontology evolution and keep all related assets in a consistent state. Ontology evolution is a problem that has not been addressed by current mobile middleware. Another advantage is the ability to configure Jadex BDI agents for different purpose and enhance agent intelligence by adding logic...

  2. Model architecture of intelligent data mining oriented urban transportation information

    Science.gov (United States)

    Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

    2007-06-01

    Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

  3. 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...... 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...... 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....

  4. Modeling speech intelligibility in adverse conditions

    DEFF Research Database (Denmark)

    Dau, Torsten

    2012-01-01

    ) 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...... understanding speech when more than one person is talking, even when reduced audibility has been fully compensated for by a hearing aid. The reasons for these difficulties are not well understood. This presentation highlights recent concepts of the monaural and binaural signal processing strategies employed...... 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...

  5. Modeling Speech Intelligibility in Hearing Impaired Listeners

    DEFF Research Database (Denmark)

    Scheidiger, Christoph; Jørgensen, Søren; Dau, Torsten

    2014-01-01

    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...... is not yet available. As a firrst step towards such a model, this study investigates to what extent eects of hearing impairment on SI can be modeled in the sEPSM framework. Preliminary results show that, by only modeling the loss of audibility, the model cannot account for the higher speech reception...

  6. Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

    OpenAIRE

    Edy Legowo

    2017-01-01

    Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilita...

  7. 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.

  8. Swarm Intelligence for Urban Dynamics Modelling

    International Nuclear Information System (INIS)

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

    2009-01-01

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  9. Swarm Intelligence for Urban Dynamics Modelling

    Science.gov (United States)

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

    2009-04-01

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  10. Application of artificial intelligence to forecast hydrocarbon production from shales

    Directory of Open Access Journals (Sweden)

    Palash Panja

    2018-03-01

    Full Text Available Artificial intelligence (AI methods and applications have recently gained a great deal of attention in many areas, including fields of mathematics, neuroscience, economics, engineering, linguistics, gaming, and many others. This is due to the surge of innovative and sophisticated AI techniques applications to highly complex problems as well as the powerful new developments in high speed computing. Various applications of AI in everyday life include machine learning, pattern recognition, robotics, data processing and analysis, etc. The oil and gas industry is not behind either, in fact, AI techniques have recently been applied to estimate PVT properties, optimize production, predict recoverable hydrocarbons, optimize well placement using pattern recognition, optimize hydraulic fracture design, and to aid in reservoir characterization efforts. In this study, three different AI models are trained and used to forecast hydrocarbon production from hydraulically fractured wells. Two vastly used artificial intelligence methods, namely the Least Square Support Vector Machine (LSSVM and the Artificial Neural Networks (ANN, are compared to a traditional curve fitting method known as Response Surface Model (RSM using second order polynomial equations to determine production from shales. The objective of this work is to further explore the potential of AI in the oil and gas industry. Eight parameters are considered as input factors to build the model: reservoir permeability, initial dissolved gas-oil ratio, rock compressibility, gas relative permeability, slope of gas oil ratio, initial reservoir pressure, flowing bottom hole pressure, and hydraulic fracture spacing. The range of values used for these parameters resemble real field scenarios from prolific shale plays such as the Eagle Ford, Bakken, and the Niobrara in the United States. Production data consists of oil recovery factor and produced gas-oil ratio (GOR generated from a generic hydraulically

  11. Development of Intelligent Spray Systems for Nursery Crop Production

    Science.gov (United States)

    Two intelligent sprayer prototypes were developed to increase pesticide application efficiency in nursery production. The first prototype was a hydraulic vertical boom system using ultrasonic sensors to detect tree size and volume for liner-sized trees and the second prototype was an air-assisted sp...

  12. Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

    Directory of Open Access Journals (Sweden)

    Edy Legowo

    2017-03-01

    Full Text Available Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilitasi guru dapat menstimulasi multiple intelligences siswa. Evaluasi hasil belajar siswa dari pandangan penerapan teori multiple intelligences seharusnya dilakukan menggunakan authentic assessment dan portofolio yang lebih memfasilitasi para siswa mengungkapkan atau mengaktualisasikan hasil belajarnya melalui berbagai cara sesuai dengan kekuatan jenis inteligensinya.

  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. Implications of intelligent, integrated microsystems for product design and development

    International Nuclear Information System (INIS)

    MYERS, DAVID R.; MCWHORTER, PAUL J.

    2000-01-01

    Intelligent, integrated microsystems combine some or all of the functions of sensing, processing information, actuation, and communication within a single integrated package, and preferably upon a single silicon chip. As the elements of these highly integrated solutions interact strongly with each other, the microsystem can be neither designed nor fabricated piecemeal, in contrast to the more familiar assembled products. Driven by technological imperatives, microsystems will best be developed by multi-disciplinary teams, most likely within the flatter, less hierarchical organizations. Standardization of design and process tools around a single, dominant technology will expedite economically viable operation under a common production infrastructure. The production base for intelligent, integrated microsystems has elements in common with the mathematical theory of chaos. Similar to chaos theory, the development of microsystems technology will be strongly dependent on, and optimized to, the initial product requirements that will drive standardization--thereby further rewarding early entrants to integrated microsystem technology

  16. Predicting Exposure to Consumer-Products Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence and Empirically -Based Scheduling Models

    Science.gov (United States)

    Information on human behavior and consumer product use is important for characterizing exposures to chemicals in consumer products and in indoor environments. Traditionally, exposure-assessors have relied on time-use surveys to obtain information on exposure-related behavior. In ...

  17. An Intelligent Model for Stock Market Prediction

    Directory of Open Access Journals (Sweden)

    IbrahimM. Hamed

    2012-08-01

    Full Text Available This paper presents an intelligent model for stock market signal prediction using Multi-Layer Perceptron (MLP Artificial Neural Networks (ANN. Blind source separation technique, from signal processing, is integrated with the learning phase of the constructed baseline MLP ANN to overcome the problems of prediction accuracy and lack of generalization. Kullback Leibler Divergence (KLD is used, as a learning algorithm, because it converges fast and provides generalization in the learning mechanism. Both accuracy and efficiency of the proposed model were confirmed through the Microsoft stock, from wall-street market, and various data sets, from different sectors of the Egyptian stock market. In addition, sensitivity analysis was conducted on the various parameters of the model to ensure the coverage of the generalization issue. Finally, statistical significance was examined using ANOVA test.

  18. Artificial intelligence model for sustain ability measurement

    International Nuclear Information System (INIS)

    Navickiene, R.; Navickas, K.

    2012-01-01

    The article analyses the main dimensions of organizational sustain ability, their possible integrations into artificial neural network. In this article authors performing analyses of organizational internal and external environments, their possible correlations with 4 components of sustain ability, and the principal determination models for sustain ability of organizations. Based on the general principles of sustainable development organizations, a artificial intelligence model for the determination of organizational sustain ability has been developed. The use of self-organizing neural networks allows the identification of the organizational sustain ability and the endeavour to explore vital, social, antropogenical and economical efficiency. The determination of the forest enterprise sustain ability is expected to help better manage the sustain ability. (Authors)

  19. 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.

  20. Intelligent Information Systems for Web Product Search

    NARCIS (Netherlands)

    D. Vandic (Damir)

    2017-01-01

    markdownabstractOver the last few years, we have experienced an increase in online shopping. Consequently, there is a need for efficient and effective product search engines. The rapid growth of e-commerce, however, has also introduced some challenges. Studies show that users can get overwhelmed by

  1. Issues in Intelligence Production: Summary of Interviews with Canadian Managers of Intelligence Analysts

    Science.gov (United States)

    2010-12-01

    range of activities. Treverton and Gabbard (2008) described a pyramid of analytic tasks, which includes five levels of processing information from...Herman 1996, Johnston 2005, Treverton and Gabbard 2008). Stages in the cycle (e.g., collection and analysis) might overlap rather than being...clearly distinguished as implied by the model (Treverton and Gabbard 2008). Adjustments to the sequence and contents of stages in the intelligence cycle

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. A New Layered Model on Emotional Intelligence

    Science.gov (United States)

    Drigas, Athanasios S.

    2018-01-01

    Emotional Intelligence (EI) has been an important and controversial topic during the last few decades. Its significance and its correlation with many domains of life has made it the subject of expert study. EI is the rudder for feeling, thinking, learning, problem-solving, and decision-making. In this article, we present an emotional–cognitive based approach to the process of gaining emotional intelligence and thus, we suggest a nine-layer pyramid of emotional intelligence and the gradual development to reach the top of EI. PMID:29724021

  8. Model of intelligent information searching system

    International Nuclear Information System (INIS)

    Yastrebkov, D.I.

    2004-01-01

    A brief description of the technique to search for electronic documents in large archives as well as drawbacks is presented. A solution close to intelligent information searching systems is proposed. (author)

  9. 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 ...

  10. From Product Models to Product State Models

    DEFF Research Database (Denmark)

    Larsen, Michael Holm

    1999-01-01

    A well-known technology designed to handle product data is Product Models. Product Models are in their current form not able to handle all types of product state information. Hence, the concept of a Product State Model (PSM) is proposed. The PSM and in particular how to model a PSM is the Research...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-07-01

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

  12. Production models

    DEFF Research Database (Denmark)

    Svensson, Carsten

    2002-01-01

    The Project is co-financed with Nilpeter A/S and investigates the industrialization of build to order production. Project content: - Enterprise engineering - Specification processes - Mass Customization/ Build To Order - Knowledge/information management - Configuration - Supply Chain Management...

  13. How smart is your BEOL? productivity improvement through intelligent automation

    Science.gov (United States)

    Schulz, Kristian; Egodage, Kokila; Tabbone, Gilles; Garetto, Anthony

    2017-07-01

    accommodate for the variability and complexity in mask shops today, individual workflows can be supported according to the needs of any particular manufacturing line with respect to necessary measurement and production steps. At the same time the efficiency of assets is increased by avoiding unneeded cycle time and waste of resources due to the presence of process steps that are very crucial for a given technology. In this paper we present details of which areas of the BEOL can benefit most from intelligent automation, what solutions exist and the quantification of benefits to a mask shop with full automation by the use of a back end of line model.

  14. Artificial intelligence applications in offshore oil and gas production

    International Nuclear Information System (INIS)

    Attia, F.G.

    1994-01-01

    The field of Artificial Intelligence (AI) has gained considerable acceptance in virtually all fields, of engineering applications. Artificial intelligence is now being applied in several areas of offshore oil and gas operations, such as drilling, well testing, well logging and interpretation, reservoir engineering, planning and economic evaluation, process control, and risk analysis. Current AI techniques offer a new and exciting technology for solving problems in the oil and gas industry. Expert systems, fuzzy logic systems, neural networks and genetic algorithms are major AI technologies which have made an impact on the petroleum industry. Presently, these technologies are at different stages of maturity with expert systems being the most mature and genetic algorithms the least. However, all four technologies have evolved such that practical applications were produced. This paper describes the four major Al techniques and their many applications in offshore oil and gas production operations. A summary description of future developments in Al technology that will affect the execution and productivity of offshore operations will be also provided

  15. 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

  16. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

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

  17. 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.

  18. 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.

  19. 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.

  20. 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. PMID:22162724

  1. Computational Intelligence Agent-Oriented Modelling

    Czech Academy of Sciences Publication Activity Database

    Neruda, Roman

    2006-01-01

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

  2. 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...

  3. The Relationship between Emotional Intelligence and Productive Language Skills

    Science.gov (United States)

    Genç, Gülten; Kulusakh, Emine; Aydin, Savas

    2016-01-01

    Emotional intelligence has recently attracted educators' attention around the world. Educators who try to investigate the factors in language learning achievement have decided to pave the way to success through emotional intelligence. The relationship between emotional intelligence and language learning is the major concern of this study. The…

  4. Integrating artificial and human intelligence into tablet production process.

    Science.gov (United States)

    Gams, Matjaž; Horvat, Matej; Ožek, Matej; Luštrek, Mitja; Gradišek, Anton

    2014-12-01

    We developed a new machine learning-based method in order to facilitate the manufacturing processes of pharmaceutical products, such as tablets, in accordance with the Process Analytical Technology (PAT) and Quality by Design (QbD) initiatives. Our approach combines the data, available from prior production runs, with machine learning algorithms that are assisted by a human operator with expert knowledge of the production process. The process parameters encompass those that relate to the attributes of the precursor raw materials and those that relate to the manufacturing process itself. During manufacturing, our method allows production operator to inspect the impacts of various settings of process parameters within their proven acceptable range with the purpose of choosing the most promising values in advance of the actual batch manufacture. The interaction between the human operator and the artificial intelligence system provides improved performance and quality. We successfully implemented the method on data provided by a pharmaceutical company for a particular product, a tablet, under development. We tested the accuracy of the method in comparison with some other machine learning approaches. The method is especially suitable for analyzing manufacturing processes characterized by a limited amount of data.

  5. Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

    Science.gov (United States)

    Guikema, Seth

    2012-07-01

    Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

  6. Sustainability Reporting Process Model using Business Intelligence

    OpenAIRE

    Alxneit, Thorsten Julius

    2015-01-01

    Sustainability including the reporting requirements is one of the most relevant topics for companies. In recent years, many software providers have launched new software tools targeting companies committed to implementing sustainability reporting. But it’s not only companies willing to use their Business Intelligence (BI) solution, there are also basic principles such as the single source of truth and tendencies to combine sustainability reporting with the financial reporting (...

  7. 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.

  8. 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.

  9. 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

  10. Electron beam lithographic modeling assisted by artificial intelligence technology

    Science.gov (United States)

    Nakayamada, Noriaki; Nishimura, Rieko; Miura, Satoru; Nomura, Haruyuki; Kamikubo, Takashi

    2017-07-01

    We propose a new concept of tuning a point-spread function (a "kernel" function) in the modeling of electron beam lithography using the machine learning scheme. Normally in the work of artificial intelligence, the researchers focus on the output results from a neural network, such as success ratio in image recognition or improved production yield, etc. In this work, we put more focus on the weights connecting the nodes in a convolutional neural network, which are naturally the fractions of a point-spread function, and take out those weighted fractions after learning to be utilized as a tuned kernel. Proof-of-concept of the kernel tuning has been demonstrated using the examples of proximity effect correction with 2-layer network, and charging effect correction with 3-layer network. This type of new tuning method can be beneficial to give researchers more insights to come up with a better model, yet it might be too early to be deployed to production to give better critical dimension (CD) and positional accuracy almost instantly.

  11. Intelligent technologies in process of highly-precise products manufacturing

    Science.gov (United States)

    Vakhidova, K. L.; Khakimov, Z. L.; Isaeva, M. R.; Shukhin, V. V.; Labazanov, M. A.; Ignatiev, S. A.

    2017-10-01

    One of the main control methods of the surface layer of bearing parts is the eddy current testing method. Surface layer defects of bearing parts, like burns, cracks and some others, are reflected in the results of the rolling surfaces scan. The previously developed method for detecting defects from the image of the raceway was quite effective, but the processing algorithm is complicated and lasts for about 12 ... 16 s. The real non-stationary signals from an eddy current transducer (ECT) consist of short-time high-frequency and long-time low-frequency components, therefore a transformation is used for their analysis, which provides different windows for different frequencies. The wavelet transform meets these conditions. Based on aforesaid, a methodology for automatically detecting and recognizing local defects in bearing parts surface layer has been developed on the basis of wavelet analysis using integral estimates. Some of the defects are recognized by the amplitude component, otherwise an automatic transition to recognition by the phase component of information signals (IS) is carried out. The use of intelligent technologies in the manufacture of bearing parts will, firstly, significantly improve the quality of bearings, and secondly, significantly improve production efficiency by reducing (eliminating) rejections in the manufacture of products, increasing the period of normal operation of the technological equipment (inter-adjustment period), the implementation of the system of Flexible facilities maintenance, as well as reducing production costs.

  12. Systems in Science: Modeling Using Three Artificial Intelligence Concepts.

    Science.gov (United States)

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

    2003-01-01

    Describes an interdisciplinary course focusing on modeling scientific systems. Investigates elementary education majors' applications of three artificial intelligence concepts used in modeling scientific systems before and after the course. Reveals a great increase in understanding of concepts presented but inconsistent application. (Author/KHR)

  13. Lexical effects on speech production and intelligibility in Parkinson's disease

    Science.gov (United States)

    Chiu, Yi-Fang

    Individuals with Parkinson's disease (PD) often have speech deficits that lead to reduced speech intelligibility. Previous research provides a rich database regarding the articulatory deficits associated with PD including restricted vowel space (Skodda, Visser, & Schlegel, 2011) and flatter formant transitions (Tjaden & Wilding, 2004; Walsh & Smith, 2012). However, few studies consider the effect of higher level structural variables of word usage frequency and the number of similar sounding words (i.e. neighborhood density) on lower level articulation or on listeners' perception of dysarthric speech. The purpose of the study is to examine the interaction of lexical properties and speech articulation as measured acoustically in speakers with PD and healthy controls (HC) and the effect of lexical properties on the perception of their speech. Individuals diagnosed with PD and age-matched healthy controls read sentences with words that varied in word frequency and neighborhood density. Acoustic analysis was performed to compare second formant transitions in diphthongs, an indicator of the dynamics of tongue movement during speech production, across different lexical characteristics. Young listeners transcribed the spoken sentences and the transcription accuracy was compared across lexical conditions. The acoustic results indicate that both PD and HC speakers adjusted their articulation based on lexical properties but the PD group had significant reductions in second formant transitions compared to HC. Both groups of speakers increased second formant transitions for words with low frequency and low density, but the lexical effect is diphthong dependent. The change in second formant slope was limited in the PD group when the required formant movement for the diphthong is small. The data from listeners' perception of the speech by PD and HC show that listeners identified high frequency words with greater accuracy suggesting the use of lexical knowledge during the

  14. Intelligent Cloud Learning Model for Online Overseas Chinese Education

    Directory of Open Access Journals (Sweden)

    Yidong Chen

    2015-02-01

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

  15. A situation-response model for intelligent pilot aiding

    Science.gov (United States)

    Schudy, Robert; Corker, Kevin

    1987-01-01

    An intelligent pilot aiding system needs models of the pilot information processing to provide the computational basis for successful cooperation between the pilot and the aiding system. By combining artificial intelligence concepts with the human information processing model of Rasmussen, an abstraction hierarchy of states of knowledge, processing functions, and shortcuts are developed, which is useful for characterizing the information processing both of the pilot and of the aiding system. This approach is used in the conceptual design of a real time intelligent aiding system for flight crews of transport aircraft. One promising result was the tentative identification of a particular class of information processing shortcuts, from situation characterizations to appropriate responses, as the most important reliable pathway for dealing with complex time critical situations.

  16. 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.

  17. 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.

  18. Increasing the Intelligence of Virtual Sales Assistants through Knowledge Modeling Techniques

    OpenAIRE

    Molina, Martin

    2001-01-01

    Shopping agents are web-based applications that help consumers to find appropriate products in the context of e-commerce. In this paper we argue about the utility of advanced model-based techniques that recently have been proposed in the fields of Artificial Intelligence and Knowledge Engineering, in order to increase the level of support provided by this type of applications. We illustrate this approach with a virtual sales assistant that dynamically configures a product according to the nee...

  19. 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.

  20. A generic model for camera based intelligent road crowd control ...

    African Journals Online (AJOL)

    This research proposes a model for intelligent traffic flow control by implementing camera based surveillance and feedback system. A series of cameras are set minimum three signals ahead from the target junction. The complete software system is developed to help integrating the multiple camera on road as feedback to ...

  1. 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.

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

    Indian Academy of Sciences (India)

    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 diff- erent ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods ...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-07-01

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

  4. 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...

  5. An evolutionary model of bounded rationality and intelligence.

    Directory of Open Access Journals (Sweden)

    Thomas J Brennan

    Full Text Available 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 crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions. METHODS AND FINDINGS: Here we propose to reconcile these contradictory perspectives by developing a simple binary-choice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions. CONCLUSIONS: Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that

  6. An evolutionary model of bounded rationality and intelligence.

    Science.gov (United States)

    Brennan, Thomas J; Lo, Andrew W

    2012-01-01

    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 crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions. Here we propose to reconcile these contradictory perspectives by developing a simple binary-choice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions. Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that arise from natural selection. The key to understanding which types of

  7. Pay attention to the enterprise competitive intelligence analysis research promotion enterprise scientific research production and product development

    International Nuclear Information System (INIS)

    Yang Yan

    2014-01-01

    This article covers the competitive intelligence content and five characteristics, and on the American Competitive intelligence Outstanding Company's place situation, shows fully the competitive intelligence constructs the core competitive power regarding the enterprise to have the significant function, Its contribution has already hold the pivotal status in the world famous enterprise. It is an important cornerstone for enterprises which construct the core competitive power. Along with the enterprise competition environment rapid change, the competitive intelligence importance suddenly to reveal day by day. Just like the world richest family Microsoft Corporation president Bill. Gates asserted that, How to collect, How to analysis, how to manage and how to use information, lt will decide the enterprise victory and loss. And unified the enterprise scientific research production the special details, take 'To develop the SF_6 New Product' to introduce as the example how did the enterprise competition intelligence, as well as how did the information development and using in it. (author)

  8. Employing the intelligence cycle process model within the Homeland Security Enterprise

    OpenAIRE

    Stokes, Roger L.

    2013-01-01

    CHDS State/Local The purpose of this thesis was to examine the employment and adherence of the intelligence cycle process model within the National Network of Fusion Centers and the greater Homeland Security Enterprise by exploring the customary intelligence cycle process model established by the United States Intelligence Community (USIC). This thesis revealed there are various intelligence cycle process models used by the USIC and taught to the National Network. Given the numerous differ...

  9. National Water Model: Providing the Nation with Actionable Water Intelligence

    Science.gov (United States)

    Aggett, G. R.; Bates, B.

    2017-12-01

    The National Water Model (NWM) provides national, street-level detail of water movement through time and space. Operating hourly, this flood of information offers enormous benefits in the form of water resource management, natural disaster preparedness, and the protection of life and property. The Geo-Intelligence Division at the NOAA National Water Center supplies forecasters and decision-makers with timely, actionable water intelligence through the processing of billions of NWM data points every hour. These datasets include current streamflow estimates, short and medium range streamflow forecasts, and many other ancillary datasets. The sheer amount of NWM data produced yields a dataset too large to allow for direct human comprehension. As such, it is necessary to undergo model data post-processing, filtering, and data ingestion by visualization web apps that make use of cartographic techniques to bring attention to the areas of highest urgency. This poster illustrates NWM output post-processing and cartographic visualization techniques being developed and employed by the Geo-Intelligence Division at the NOAA National Water Center to provide national actionable water intelligence.

  10. ASSESSMENT OF A WIND TURBINE INTELLIGENT CONTROLLER FOR ENHANCED ENERGY PRODUCTION AND POLLUTION REDUCTION

    Science.gov (United States)

    This study assessed the enhanced energy production which is possible when variable-speed wind turbines are electronically controlled by an intelligent controller for efficiency optimization and performance improvement. The control system consists of three fuzzy- logic controllers...

  11. Intelligent Human Machine Interface Design for Advanced Product Life Cycle Management Systems

    OpenAIRE

    Ahmed, Zeeshan

    2010-01-01

    Designing and implementing an intelligent and user friendly human machine interface for any kind of software or hardware oriented application is always be a challenging task for the designers and developers because it is very difficult to understand the psychology of the user, nature of the work and best suit of the environment. This research paper is basically about to propose an intelligent, flexible and user friendly machine interface for Product Life Cycle Management products or PDM Syste...

  12. The role of artificial intelligence and expert systems in increasing STS operations productivity

    Science.gov (United States)

    Culbert, C.

    1985-01-01

    Artificial Intelligence (AI) is discussed. A number of the computer technologies pioneered in the AI world can make significant contributions to increasing STS operations productivity. Application of expert systems, natural language, speech recognition, and other key technologies can reduce manpower while raising productivity. Many aspects of STS support lend themselves to this type of automation. The artificial intelligence section of the mission planning and analysis division has developed a number of functioning prototype systems which demonstrate the potential gains of applying AI technology.

  13. 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...

  14. A Cybernetic Model to Enhance Organizational Intelligence

    OpenAIRE

    Schwaninger, Markus

    2003-01-01

    The present paper focuses on the modeling of cognitive processes in organizations. This issue is approached from the perspective of Organizational Cybernetics, the science of control and communication applied to the management of organizations. First, the Team Syntegrity Model is described, which provides a structural architecture for processes of planning, knowledge generation and innovation in turbulent environments. The model is holographic and based on the mathematical structure of polyhe...

  15. Modeling culture in intelligent virtual agents

    OpenAIRE

    Mascarenhas, S.; Degens, N.; Paiva, A.; Prada, R.; Hofstede, G.J.; Beulens, A.J.M.; Aylett, R.

    2016-01-01

    This work addresses the challenge of creating virtual agents that are able to portray culturally appropriate behavior when interacting with other agents or humans. Because culture influences how people perceive their social reality it is important to have agent models that explicitly consider social elements, such as existing relational factors. We addressed this necessity by integrating culture into a novel model for simulating human social behavior. With this model, we operationalized a par...

  16. 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.

  17. Intelligent spatial ecosystem modeling using parallel processors

    International Nuclear Information System (INIS)

    Maxwell, T.; Costanza, R.

    1993-01-01

    Spatial modeling of ecosystems is essential if one's modeling goals include developing a relatively realistic description of past behavior and predictions of the impacts of alternative management policies on future ecosystem behavior. Development of these models has been limited in the past by the large amount of input data required and the difficulty of even large mainframe serial computers in dealing with large spatial arrays. These two limitations have begun to erode with the increasing availability of remote sensing data and GIS systems to manipulate it, and the development of parallel computer systems which allow computation of large, complex, spatial arrays. Although many forms of dynamic spatial modeling are highly amenable to parallel processing, the primary focus in this project is on process-based landscape models. These models simulate spatial structure by first compartmentalizing the landscape into some geometric design and then describing flows within compartments and spatial processes between compartments according to location-specific algorithms. The authors are currently building and running parallel spatial models at the regional scale for the Patuxent River region in Maryland, the Everglades in Florida, and Barataria Basin in Louisiana. The authors are also planning a project to construct a series of spatially explicit linked ecological and economic simulation models aimed at assessing the long-term potential impacts of global climate change

  18. Intelligent-based Structural Damage Detection Model

    International Nuclear Information System (INIS)

    Lee, Eric Wai Ming; Yu, K.F.

    2010-01-01

    This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

  19. Intelligent-based Structural Damage Detection Model

    Science.gov (United States)

    Lee, Eric Wai Ming; Yu, Kin Fung

    2010-05-01

    This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

  20. 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.

  1. 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.

  2. Modeling intelligent agent beliefs in a card game scenario

    Science.gov (United States)

    Gołuński, Marcel; Tomanek, Roman; WÄ siewicz, Piotr

    In this paper we explore the problem of intelligent agent beliefs. We model agent beliefs using multimodal logics of belief, KD45(m) system implemented as a directed graph depicting Kripke semantics, precisely. We present a card game engine application which allows multiple agents to connect to a given game session and play the card game. As an example simplified version of popular Saboteur card game is used. Implementation was done in Java language using following libraries and applications: Apache Mina, LWJGL.

  3. Neuro-Based Artificial Intelligence Model for Loan Decisions

    OpenAIRE

    Shorouq F. Eletter; Saad G. Yaseen; Ghaleb A. Elrefae

    2010-01-01

    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 backpr...

  4. Thermal Models for Intelligent Heating of Buildings

    DEFF Research Database (Denmark)

    Thavlov, Anders; Bindner, Henrik W.

    2012-01-01

    the comfort of residents, proper prediction models for indoor temperature have to be developed. This paper presents a model for prediction of indoor temperature and power consumption from electrical space heating in an office building, using stochastic differential equations. The heat dynamic model is build......The Danish government has set the ambitious goal that the share of the total Danish electricity consumption, covered by wind energy, should be increased to 50% by year 2020. This asks for radical changes in how we utilize and transmit electricity in the future power grid. To fully utilize the high...... share of renewable power generation, which is in general intermittent and non-controllable, the consumption side has to be much more flexible than today. To achieve such flexibility, methods for moving power consumption in time, within the hourly timescale, have to be developed. One approach currently...

  5. Two intelligent spraying systems developed for tree crop production

    Science.gov (United States)

    Precision pesticide application technologies are needed to achieve efficient and effective spray deposition on target areas and minimize off-target losses. Two variable-rate intelligent sprayers were developed as an introduction of new generation sprayers for tree crop applications. The first spraye...

  6. 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.

  7. Modeling culture in intelligent virtual agents

    NARCIS (Netherlands)

    Mascarenhas, S.; Degens, N.; Paiva, A.; Prada, R.; Hofstede, G.J.; Beulens, A.J.M.; Aylett, R.

    2016-01-01

    This work addresses the challenge of creating virtual agents that are able to portray culturally appropriate behavior when interacting with other agents or humans. Because culture influences how people perceive their social reality it is important to have agent models that explicitly consider social

  8. Towards a universal competitive intelligence process model

    Directory of Open Access Journals (Sweden)

    Rene Pellissier

    2013-08-01

    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.

  9. Modelling fuel cell performance using artificial intelligence

    Science.gov (United States)

    Ogaji, S. O. T.; Singh, R.; Pilidis, P.; Diacakis, M.

    Over the last few years, fuel cell technology has been increasing promisingly its share in the generation of stationary power. Numerous pilot projects are operating worldwide, continuously increasing the amount of operating hours either as stand-alone devices or as part of gas turbine combined cycles. An essential tool for the adequate and dynamic analysis of such systems is a software model that enables the user to assess a large number of alternative options in the least possible time. On the other hand, the sphere of application of artificial neural networks has widened covering such endeavours of life such as medicine, finance and unsurprisingly engineering (diagnostics of faults in machines). Artificial neural networks have been described as diagrammatic representation of a mathematical equation that receives values (inputs) and gives out results (outputs). Artificial neural networks systems have the capacity to recognise and associate patterns and because of their inherent design features, they can be applied to linear and non-linear problem domains. In this paper, the performance of the fuel cell is modelled using artificial neural networks. The inputs to the network are variables that are critical to the performance of the fuel cell while the outputs are the result of changes in any one or all of the fuel cell design variables, on its performance. Critical parameters for the cell include the geometrical configuration as well as the operating conditions. For the neural network, various network design parameters such as the network size, training algorithm, activation functions and their causes on the effectiveness of the performance modelling are discussed. Results from the analysis as well as the limitations of the approach are presented and discussed.

  10. Modelling fuel cell performance using artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Ogaji, S.O.T.; Singh, R.; Pilidis, P.; Diacakis, M. [Power Propulsion and Aerospace Engineering Department, Centre for Diagnostics and Life Cycle Costs, Cranfield University (United Kingdom)

    2006-03-09

    Over the last few years, fuel cell technology has been increasing promisingly its share in the generation of stationary power. Numerous pilot projects are operating worldwide, continuously increasing the amount of operating hours either as stand-alone devices or as part of gas turbine combined cycles. An essential tool for the adequate and dynamic analysis of such systems is a software model that enables the user to assess a large number of alternative options in the least possible time. On the other hand, the sphere of application of artificial neural networks has widened covering such endeavours of life such as medicine, finance and unsurprisingly engineering (diagnostics of faults in machines). Artificial neural networks have been described as diagrammatic representation of a mathematical equation that receives values (inputs) and gives out results (outputs). Artificial neural networks systems have the capacity to recognise and associate patterns and because of their inherent design features, they can be applied to linear and non-linear problem domains. In this paper, the performance of the fuel cell is modelled using artificial neural networks. The inputs to the network are variables that are critical to the performance of the fuel cell while the outputs are the result of changes in any one or all of the fuel cell design variables, on its performance. Critical parameters for the cell include the geometrical configuration as well as the operating conditions. For the neural network, various network design parameters such as the network size, training algorithm, activation functions and their causes on the effectiveness of the performance modelling are discussed. Results from the analysis as well as the limitations of the approach are presented and discussed. (author)

  11. Artificial intelligence in pharmaceutical product formulation: neural computing

    OpenAIRE

    Svetlana Ibrić; Jelena Petrović; Jelena Parojčić; Zorica Djurić

    2009-01-01

    The properties of a formulation are determined not only by the ratios in which the ingredients are combined but also by the processing conditions. Although the relationships between the ingredient levels, processing conditions, and product performance may be known anecdotally, they can rarely be quantified. In the past, formulators tended to use statistical techniques to model their formulations, relying on response surfaces to provide a mechanism for optimazation. However, the optimization b...

  12. Conceptual Model of Business Value of Business Intelligence Systems

    OpenAIRE

    Popovič, Aleš; Turk, Tomaž; Jaklič, Jurij

    2010-01-01

    With advances in the business intelligence area, there is an increasing interest for the introduction of business intelligence systems into organizations. Although the opinion about business intelligence and its creation of business value is generally accepted, economic justification of investments into business intelligence systems is not always clear. Measuring the business value of business intelligence in practice is often not carried out due to the lack of measurement methods and resourc...

  13. Heuristic decision model for intelligent nuclear power systems design

    International Nuclear Information System (INIS)

    Nassersharif, B.; Portal, M.G.; Gaeta, M.J.

    1989-01-01

    The objective of this project was to investigate intelligent nuclear power systems design. A theoretical model of the design process has been developed. A fundamental process in this model is the heuristic decision making for design (i.e., selection of methods, components, materials, etc.). Rule-based expert systems do not provide the completeness that is necessary to generate good design. A new method, based on the fuzzy set theory, has been developed and is presented here. A feedwater system knowledge base (KB) was developed for a prototype software experiment to benchmark the theory

  14. 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

  15. 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.

  16. Intelligent model-based diagnostics for vehicle health management

    Science.gov (United States)

    Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

    2003-08-01

    The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

  17. Dynamic intelligent cleaning model of dirty electric load data

    International Nuclear Information System (INIS)

    Zhang Xiaoxing; Sun Caixin

    2008-01-01

    There are a number of dirty data in the load database derived from the supervisory control and data acquisition (SCADA) system. Thus, the data must be carefully and reasonably adjusted before it is used for electric load forecasting or power system analysis. This paper proposes a dynamic and intelligent data cleaning model based on data mining theory. Firstly, on the basis of fuzzy soft clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means soft clustering. Then, the proposed dynamic algorithm can automatically find the new clustering center (the characteristic curve of the data) with the updated sample data; At last, it is composed with radial basis function neural network (RBFNN), and then, an intelligent adjusting model is proposed to identify the dirty data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results of electrical load data analysis in Chongqing

  18. A Lightweight Intelligent Virtual Cinematography System for Machinima Production

    Science.gov (United States)

    2007-01-01

    portmanteau of machine and cinema , machinima refers to the innovation of leveraging video game technology to greatly ease the creation of computer...selecting camera angles to capture the action of an a priori unknown script as aesthetically appropriate cinema . There are a number of challenges therein...Proc. of the 4th International Conf. on Autonomous Agents. Young, R.M. and Riedl, M.O. 2003. Towards an Architecture for Intelligent Control of Narrative in Interactive Virtual Worlds. In Proc. of IUI 2003.

  19. Modeling the Structure and Effectiveness of Intelligence Organizations: Dynamic Information Flow Simulation

    National Research Council Canada - National Science Library

    Behrman, Robert; Carley, Kathleen

    2003-01-01

    This paper describes the Dynamic Information Flow Simulation (DIFS), an abstract model for analyzing the structure and function of intelligence support organizations and the activities of entities within...

  20. 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.

  1. 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...

  2. 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.

  3. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Terrorism Risk Modeling for Intelligence Analysis and Infrastructure Protection

    National Research Council Canada - National Science Library

    Willis, Henry H; LaTourrette, Tom; Kelly, Terrence K; Hickey, Scot; Neill, Samuel

    2007-01-01

    ...? The Office of Intelligence and Analysis (OI&A) at DHS is responsible for using information and intelligence from multiple sources to identify and assess current and future threats to the United States...

  5. DEVELOPING A HUMAN CONTROLLED MODEL FOR SAFE ARTIFICIAL INTELLIGENCE SYSTEMS

    OpenAIRE

    KÖSE, Utku

    2018-01-01

    Artificial Intelligence is known as one of the most effective research field of nowadays and the future. But rapid rise of Artificial Intelligence and its potential to solve all real world problems autonomously, it has caused also several anxieties. Some scientists think that intelligent systems can reach to a level, which is dangerous for the humankind so because of that some precautions should be taken. So, many sub-research fields like Machine Ethics or Artificial Intelligence Safety have ...

  6. Product and Process Modelling

    DEFF Research Database (Denmark)

    Cameron, Ian T.; Gani, Rafiqul

    . These approaches are put into the context of life cycle modelling, where multiscale and multiform modelling is increasingly prevalent in the 21st century. The book commences with a discussion of modern product and process modelling theory and practice followed by a series of case studies drawn from a variety......This book covers the area of product and process modelling via a case study approach. It addresses a wide range of modelling applications with emphasis on modelling methodology and the subsequent in-depth analysis of mathematical models to gain insight via structural aspects of the models...... to biotechnology applications, food, polymer and human health application areas. The book highlights to important nature of modern product and process modelling in the decision making processes across the life cycle. As such it provides an important resource for students, researchers and industrial practitioners....

  7. Systems Intelligence in Knowledge Management Implementation: A Momentum of the SECI Model

    OpenAIRE

    Sasaki, Yasuo

    2014-01-01

    This paper discusses the role of systems intelligence in knowledge management implementations, in particular, in the SECI model, a widely acknowledged knowledge creation process in an organization identified by Nonaka and Takeuchi (1995). The SECI model deals with interactions and conversions of tacit knowledge and explicit knowledge and mainly consists of four stages. The author illustrates systems intelligence, a certain kind of human intelligence focusing on systems thinking perspective pr...

  8. 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...

  9. 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.

  10. On prognostic models, artificial intelligence and censored observations.

    Science.gov (United States)

    Anand, S S; Hamilton, P W; Hughes, J G; Bell, D A

    2001-03-01

    The development of prognostic models for assisting medical practitioners with decision making is not a trivial task. Models need to possess a number of desirable characteristics and few, if any, current modelling approaches based on statistical or artificial intelligence can produce models that display all these characteristics. The inability of modelling techniques to provide truly useful models has led to interest in these models being purely academic in nature. This in turn has resulted in only a very small percentage of models that have been developed being deployed in practice. On the other hand, new modelling paradigms are being proposed continuously within the machine learning and statistical community and claims, often based on inadequate evaluation, being made on their superiority over traditional modelling methods. We believe that for new modelling approaches to deliver true net benefits over traditional techniques, an evaluation centric approach to their development is essential. In this paper we present such an evaluation centric approach to developing extensions to the basic k-nearest neighbour (k-NN) paradigm. We use standard statistical techniques to enhance the distance metric used and a framework based on evidence theory to obtain a prediction for the target example from the outcome of the retrieved exemplars. We refer to this new k-NN algorithm as Censored k-NN (Ck-NN). This reflects the enhancements made to k-NN that are aimed at providing a means for handling censored observations within k-NN.

  11. Artificial intelligence in pharmaceutical product formulation: neural computing

    Directory of Open Access Journals (Sweden)

    Svetlana Ibrić

    2009-10-01

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

  12. #%Applications of artificial intelligence in intelligent manufacturing: a review

    Institute of Scientific and Technical Information of China (English)

    #

    2017-01-01

    #%Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of 'Internet plus AI', which is triggering a great change in the models, means, and ecosystems of the manufacturing industry, as well as in the development of AI. We then propose new models, means, and forms of intelligent manufacturing, intelligent manufacturing system architecture, and intelligent man-ufacturing technology system, based on the integration of AI technology with information communications, manufacturing, and related product technology. Moreover, from the perspectives of intelligent manufacturing application technology, industry, and application demonstration, the current development in intelligent manufacturing is discussed. Finally, suggestions for the appli-cation of AI in intelligent manufacturing in China are presented.

  13. Product Platform Modeling

    DEFF Research Database (Denmark)

    Pedersen, Rasmus

    for customisation of products. In many companies these changes in the business environment have created a controversy between the need for a wide variety of products offered to the marketplace and a desire to reduce variation within the company in order to increase efficiency. Many companies use the concept...... other. These groups can be varied and combined to form different product variants without increasing the internal variety in the company. Based on the Theory of Domains, the concept of encapsulation in the organ domain is introduced, and organs are formulated as platform elements. Included......This PhD thesis has the title Product Platform Modelling. The thesis is about product platforms and visual product platform modelling. Product platforms have gained an increasing attention in industry and academia in the past decade. The reasons are many, yet the increasing globalisation...

  14. Software module for geometric product modeling and NC tool path generation

    International Nuclear Information System (INIS)

    Sidorenko, Sofija; Dukovski, Vladimir

    2003-01-01

    The intelligent CAD/CAM system named VIRTUAL MANUFACTURE is created. It is consisted of four intelligent software modules: the module for virtual NC machine creation, the module for geometric product modeling and automatic NC path generation, the module for virtual NC machining and the module for virtual product evaluation. In this paper the second intelligent software module is presented. This module enables feature-based product modeling carried out via automatic saving of the designed product geometric features as knowledge data. The knowledge data are afterwards applied for automatic NC program generation for the designed product NC machining. (Author)

  15. The Construction of Intelligent English Teaching Model Based on Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Xiaoguang Li

    2017-12-01

    Full Text Available In order to build a modernized tool platform that can help students improve their English learning efficiency according to their mastery of knowledge and personality, this paper develops an online intelligent English learning system that uses Java and artificial intelligence language Prolog as the software system. This system is a creative reflection of the thoughts of expert system in artificial intelligence. Established on the Struts Spring Hibernate lightweight JavaEE framework, the system modules are coupled with each other in a much lower degree, which is convenient to future function extension. Combined with the idea of expert system in artificial intelligence, the system developed appropriate learning strategies to help students double the learning effect with half the effort; Finally, the system takes into account the forgetting curve of memory, on which basis the knowledge that has been learned will be tested periodically, intending to spare students’ efforts to do a sea of exercises and obtain better learning results.

  16. Research on Digital Product Modeling Key Technologies of Digital Manufacturing

    Institute of Scientific and Technical Information of China (English)

    DING Guoping; ZHOU Zude; HU Yefa; ZHAO Liang

    2006-01-01

    With the globalization and diversification of the market and the rapid development of Information Technology (IT) and Artificial Intelligence (AI), the digital revolution of manufacturing is coming. One of the key technologies in digital manufacturing is product digital modeling. This paper firstly analyzes the information and features of the product digital model during each stage in the product whole lifecycle, then researches on the three critical technologies of digital modeling in digital manufacturing-product modeling, standard for the exchange of product model data and digital product data management. And the potential signification of the product digital model during the process of digital manufacturing is concluded-product digital model integrates primary features of each stage during the product whole lifecycle based on graphic features, applies STEP as data exchange mechanism, and establishes PDM system to manage the large amount, complicated and dynamic product data to implement the product digital model data exchange, sharing and integration.

  17. 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.

  18. Modelling and Intelligent Control of an Elastic Link Robot Manipulator

    Directory of Open Access Journals (Sweden)

    Malik Loudini

    2013-01-01

    Full Text Available In this paper, precise control of the end-point position of a planar single-link elastic manipulator robot is discussed. The Timoshenko beam theory (TBT has been used to characterize the structural link elasticity including important damping mechanisms. A suitable nonlinear model is derived based on the Lagrangian assumed modes method. Elastic link manipulators are classified as systems possessing highly complex dynamics. In addition, the environment in which they operate may have a lot of disturbances. These give rise to special problems that may be solved using intelligent control techniques. The application of two advanced control strategies based on fuzzy set theory is investigated. The first closed-loop control scheme to be applied is the standard Proportional-Derivative (PD type fuzzy logic controller (FLC, also known as PD-type Mamdani's FLC (MPDFLC. Then, a genetic algorithm (GA is used to optimize the MPDFLC parameters with innovative tuning procedures. Both the MPDFLC and the GA optimized FLC (GAOFLC are implemented and tested to achieve a precise control of the manipulator end-point. The performances of the adopted closed-loop intelligent control strategies are examined via simulation experiments.

  19. Design, product structuring and modelling of mechatronic products and systems

    DEFF Research Database (Denmark)

    Conrad, Finn; Sørensen, Torben

    2003-01-01

    Information Technology offers software and hardware for improvement of the engineering design, structuring and control systems, and industrial applications. The latest progress in IT makes integration of an overall design and manufacturing IT- concept feasible and commercially attractive. An IT......-tool concept for modelling, simulation and design of mechatronic products and systems is proposed in this paper. It built on results from a Danish mechatronic research program on intelligent motion control as well as from the Esprit project SWING on IT-tools for rapid prototyping of fluid power components...

  20. Customer Data Analysis Model using Business Intelligence Tools in Telecommunication Companies

    Directory of Open Access Journals (Sweden)

    Monica LIA

    2015-10-01

    Full Text Available This article presents a customer data analysis model in a telecommunication company and business intelligence tools for data modelling, transforming, data visualization and dynamic reports building . For a mature market, knowing the information inside the data and making forecast for strategic decision become more important in Romanian Market. Business Intelligence tools are used in business organization as support for decision making.

  1. 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

  2. Novel approach for dam break flow modeling using computational intelligence

    Science.gov (United States)

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

    2018-04-01

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

  3. 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.

  4. Modelling Retail Floorspace Productivity

    NARCIS (Netherlands)

    A.R. Thurik (Roy); P. Kooiman

    1986-01-01

    textabstractThis research note presents a "switching regime" model to investigate the impact of environmental factors on floorspace productivity of individual retail stores. The model includes independent supply and demand functions, which are incorporated within a sales maximizing framework. Unlike

  5. Multi-Working Modes Product-Color Planning Based on Evolutionary Algorithms and Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Man Ding

    2010-01-01

    Full Text Available In order to assist designer in color planning during product development, a novel synthesized evaluation method is presented to evaluate color-combination schemes of multi-working modes products (MMPs. The proposed evaluation method considers color-combination images in different working modes as evaluating attributes, to which the corresponding weights are assigned for synthesized evaluation. Then a mathematical model is developed to search for optimal color-combination schemes of MMP based on the proposed evaluation method and two powerful search techniques known as Evolution Algorithms (EAs and Swarm Intelligence (SI. In the experiments, we present a comparative study for two EAs, namely, Genetic Algorithm (GA and Difference Evolution (DE, and one SI algorithm, namely, Particle Swarm Optimization (PSO, on searching for color-combination schemes of MMP problem. All of the algorithms are evaluated against a test scenario, namely, an Arm-type aerial work platform, which has two working modes. The results show that the DE obtains the superior solution than the other two algorithms for color-combination scheme searching problem in terms of optimization accuracy and computation robustness. Simulation results demonstrate that the proposed method is feasible and efficient.

  6. A Lightweight Intelligent Virtual Cinematography System for Machinima Production

    National Research Council Canada - National Science Library

    Elson, David K; Riedl, Mark O

    2007-01-01

    Machinima is a low-cost alternative to full production filmmaking. However, creating quality cinematic visualizations with existing machinima techniques still requires a high degree of talent and effort...

  7. The intelligent clinical laboratory as a tool to increase cancer care management productivity.

    Science.gov (United States)

    Mohammadzadeh, Niloofar; Safdari, Reza

    2014-01-01

    Studies of the causes of cancer, early detection, prevention or treatment need accurate, comprehensive, and timely cancer data. The clinical laboratory provides important cancer information needed for physicians which influence clinical decisions regarding treatment, diagnosis and patient monitoring. Poor communication between health care providers and clinical laboratory personnel can lead to medical errors and wrong decisions in providing cancer care. Because of the key impact of laboratory information on cancer diagnosis and treatment the quality of the tests, lab reports, and appropriate lab management are very important. A laboratory information management system (LIMS) can have an important role in diagnosis, fast and effective access to cancer data, decrease redundancy and costs, and facilitate the integration and collection of data from different types of instruments and systems. In spite of significant advantages LIMS is limited by factors such as problems in adaption to new instruments that may change existing work processes. Applications of intelligent software simultaneously with existing information systems, in addition to remove these restrictions, have important benefits including adding additional non-laboratory-generated information to the reports, facilitating decision making, and improving quality and productivity of cancer care services. Laboratory systems must have flexibility to change and have the capability to develop and benefit from intelligent devices. Intelligent laboratory information management systems need to benefit from informatics tools and latest technologies like open sources. The aim of this commentary is to survey application, opportunities and necessity of intelligent clinical laboratory as a tool to increase cancer care management productivity.

  8. Space Environment Modelling with the Use of Artificial Intelligence Methods

    Science.gov (United States)

    Lundstedt, H.; Wintoft, P.; Wu, J.-G.; Gleisner, H.; Dovheden, V.

    1996-12-01

    Space based technological systems are affected by the space weather in many ways. Several severe failures of satellites have been reported at times of space storms. Our society also increasingly depends on satellites for communication, navigation, exploration, and research. Predictions of the conditions in the satellite environment have therefore become very important. We will here present predictions made with the use of artificial intelligence (AI) techniques, such as artificial neural networks (ANN) and hybrids of AT methods. We are developing a space weather model based on intelligence hybrid systems (IHS). The model consists of different forecast modules, each module predicts the space weather on a specific time-scale. The time-scales range from minutes to months with the fundamental time-scale of 1-5 minutes, 1-3 hours, 1-3 days, and 27 days. Solar and solar wind data are used as input data. From solar magnetic field measurements, either made on the ground at Wilcox Solar Observatory (WSO) at Stanford, or made from space by the satellite SOHO, solar wind parameters can be predicted and modelled with ANN and MHD models. Magnetograms from WSO are available on a daily basis. However, from SOHO magnetograms will be available every 90 minutes. SOHO magnetograms as input to ANNs will therefore make it possible to even predict solar transient events. Geomagnetic storm activity can today be predicted with very high accuracy by means of ANN methods using solar wind input data. However, at present real-time solar wind data are only available during part of the day from the satellite WIND. With the launch of ACE in 1997, solar wind data will on the other hand be available during 24 hours per day. The conditions of the satellite environment are not only disturbed at times of geomagnetic storms but also at times of intense solar radiation and highly energetic particles. These events are associated with increased solar activity. Predictions of these events are therefore

  9. 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

  10. The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

    Science.gov (United States)

    Hali, Nur Ihsan

    2017-01-01

    This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by…

  11. Misbehaving Peer Models in the Classroom: An Investigation of the Effects of Social Class and Intelligence.

    Science.gov (United States)

    Kniveton, Bromley H.

    1987-01-01

    Investigates the effects on young male students of differing social backgrounds and varying levels of intelligence, of seeing a peer misbehave. Notes that working class boys imitated the misbehaving model significantly more than middle-class boys. Level of intelligence was not found to relate to the amount a student imitated a misbehaving peer.…

  12. Penerapan Model Pembelajaran Atraktif Berbasis Multiple Intelligences Tentang Pemantulan Cahaya pada Cermin

    Directory of Open Access Journals (Sweden)

    Intan Kusumawati

    2016-03-01

    Full Text Available Penelitian ini bertujuan untuk mengetahui efektivitas penerapan model pembelajaran atraktif berbasis multiple intelligences dalam meremediasi miskonsepsi siswa tentang pemantulan cahaya pada cermin. Pada penelitian ini digunakan bentuk pre-eksperimental design dengan rancangan one group pretest-post test design. Alat pengumpulan data berupa tes pilihan ganda dengan reasoning. Hasil validitas sebesar 4,08 dan reliabilitas 0,537. Siswa dibagi menjadi lima kelompok kecerdasan, yaitu kelompok linguistic intelligence, mathematical-logical intelligence, visual-spatial intelligence, bodily-khinestetic intelligence, dan musical intelligence. Siswa membahas konsep fisika sesuai kelompok kecerdasannya dalam bentuk pembuatan pantun-puisi, teka-teki silang, menggambar kreatif, drama, dan mengarang lirik lagu. Efektivitas penerapan model pembelajaran multiple intelligences menggunakan persamaan effect size. Ditemukan bahwa skor effect size masing-masing kelompok berkategori tinggi sebesar 5,76; 3,76; 4,60; 1,70; dan 1,34. Penerapan model pembelajaran atraktif berbasis multiple intelligences efektif dalam meremediasi miskonsepsi siswa. Penelitian ini diharapkan dapat digunakan pada materi fisika dan sekolah lainnya.

  13. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

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

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

    Science.gov (United States)

    Wilson, Eric Lee

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

  15. Innovation Production Models

    Directory of Open Access Journals (Sweden)

    Tamam N. Guseinova

    2016-01-01

    Full Text Available The article is dedicated to the study of the models of production of innovations at enterprise and state levels. The shift towards a new technology wave induces a change in systems of division of labour as well as establishment of new forms of cooperation that are reflected both in theory and practice of innovation policy and management. Within the scope of the research question we have studied different generation of innovation process, starting with simple linear models - "technology push" and "market pull" - and ending with a complex integrated model of open innovations. There are two organizational models of innovation production at the enterprise level: start-ups in the early stages of their development and ambidextrous organizations. The former are prone to linear models of innovation process, while the latter create innovation within more sophisticated inclusive processes. Companies that effectuate reciprocal ambidexterity stand out from all the rest, since together with start-ups, research and development centres, elements of innovation infrastructure and other economic agents operating in the same value chain they constitute the core of most advanced forms of national innovation systems, namely Triple Helix and Quadruple Helix systems. National innovation systems - models of innovation production at the state level - evolve into systems with a more profound division of labour that enable "line production" of innovations. These tendencies are closely related to the advent and development of the concept of serial entrepreneurship that transforms entrepreneurship into a new type of profession. International experience proves this concept to be efficient in various parts of the world. Nevertheless, the use of above mentioned models and concepts in national innovation system should be justified by socioeconomic conditions of economic regions, since they determine the efficiency of implementation of certain innovation processes and

  16. Synergy between Software Product Line and Intelligent Pervasive Middleware-a PLIPerM Approach

    DEFF Research Database (Denmark)

    Zhang, Weishan

    2008-01-01

    with OWL ontology reasoning enhanced BDI (Belief-Desire-Intention) agents, which are the basic building blocks of PLIPerM. Besides the advantages of a software product line, our approachcan handle ontology evolution and keep all related assets in a consistent state. Other advantages include the ability...... to configure Jadex BDI agents for different purpose and to enhance agent intelligence by adding logic reasoning capabilities indirectly to agent beliefs....

  17. 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.

  18. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    OpenAIRE

    Daniel-Petru GHENCEA; Miron ZAPCIU; Claudiu-Florinel BISU; Elena-Iuliana BOTEANU; Elena-Luminiţa OLTEANU

    2017-01-01

    The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic). The paper presents a prediction mode obtaining valid range of values f...

  19. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    International Nuclear Information System (INIS)

    Saini, K. K.; Saini, Sanju

    2008-01-01

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  20. The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

    Directory of Open Access Journals (Sweden)

    Nur Ihsan Halil

    2017-10-01

    Full Text Available This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by developing and constructing an existing concept, namely the concept of linguistic intelligence, which is disseminated into a literature-based learning of verbal-linguistic intelligence. The purpose of this paper is to answer the question of how to apply the literary learning model based on the verbal-linguistic intelligence. Then, regarding Gardner's concept, the author formulated a literary learning model based on the verbal-linguistic intelligence through a story-telling learning model with five steps namely arguing, discussing, interpreting, speaking, and writing about literary works. In short, the writer draw a conclusion that learning-based models of verbal-linguistic intelligence can be designed with attention into five components namely (1 definition, (2 characteristics, (3 teaching strategy, (4 final learning outcomes, and (5 figures.

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

    Directory of Open Access Journals (Sweden)

    Rojek G.

    2016-06-01

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

  2. 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.

  3. Model of key success factors for Business Intelligence implementation

    OpenAIRE

    Peter Mesaros; Tomas Mandicak; Daniela Mackova; Stefan Carnicky; Martina Habinakova; Marcela Spisakova

    2016-01-01

    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 a...

  4. 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.

  5. How to learn from intelligent products : the structuring of incoherent field feedback data in two case studies

    NARCIS (Netherlands)

    Bruin, de R.; Lu, Y.; Brombacher, A.C.; Smith, M.J.; Salvendy, G.

    2009-01-01

    A growing number of products - particularly highly innovative and intelligent products - are being returned by customers, while analysis shows that many of these products are in fact functioning according to their technical specifications. Product developers are recognizing the need for information

  6. 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.

  7. An Analytical Model / Emotional Intelligence Quotient and QOL in Mothers with Infants in Japan

    OpenAIRE

    Ohashi, Junko; Katsura, Toshiki; Hoshino, Akiko; Usui, Kanae

    2013-01-01

    Objective: The purpose of this study was to examine the relationship between the emotional intelligence quotient and health-related quality of life using structural equation modeling. Methods: A self-administered questionnaire survey was conducted among 1,911 mothers who visited the Health Center for an infant medical examination. A hypothetical model was constructed using variables of the emotional intelligence quotient, social support, coping, parenting stress, and perceived health competen...

  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...representation of speech intelligibility in noise. The auditory-periphery model of Zilany et al. (JASA 2009,2014) is used to make predictions of...auditory nerve (AN) responses to speech stimuli under a variety of difficult listening conditions. The resulting cochlear neurogram, a spectrogram

  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. Product Knowledge Modelling and Management

    DEFF Research Database (Denmark)

    Zhang, Y.; MacCallum, K. J.; Duffy, Alex

    1996-01-01

    function-oriented design. Both Specific Product Knowledge and Product Domain Knowledge are modelled at two levels, a meta-model and an information-level.Following that, a computer-based scheme to manage the proposed product lknowledge models within a dynamically changing environment is presented.......The term, Product Knowledge is used to refer to two related but distinct concepts; the knowledge of a specific product (Specific Product Knowledge) and the knowledge of a product domain (Product Domain Knowledge). Modelling and managing Product Knowlege is an essential part of carrying out design.......A scheme is presented in this paper to model, i.e. classify, structure and formalise the product knowledge for the purpose of supporting function-oriented design. The product design specification and four types of required attributes of a specific product have been identified to form the Specific Product...

  12. 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.

  13. 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...

  14. THE EFFECTS OF LEARNING MODELS AND LINGUISTIC INTELLIGENCE ON THE PERSUASIVE WRITING SKILL

    OpenAIRE

    Yusri, Yusri; Emzir, Emzir

    2017-01-01

    The objective of this study is to know the effects of learning models (problem solving and project based learning) and linguistic intelligence  on the students of persuasive writing skill of the fourth semester students  of English Department, State Polytechnic of Sriwijaya Palembang, in the academic year of 2016-2017. The writer used linguistic intelligence test and persuasive writing test to collect the data. The data was analyzed  statistically by using two-factor ANOVA a...

  15. Application of Contemporary Intelligence Models in Terms of Transformation and Security Sector Reform

    OpenAIRE

    Dojcinovski, Metodija; Ackoski, Jugoslav

    2011-01-01

    This paper presents a new approach to the contemporary methods of organizing, establishing and functioning of intelligence systems in a way of offering solutions against security threats and challenges of the 21st century. The effectiveness of implementing the measures and activities depends on the intelligence models, identified as functioning in relation to the structured elements of the represented and realistically created segments, standard operative procedures, security procedures and m...

  16. 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...

  17. Modeling and Evaluation of LTE in Intelligent Transportation Systems

    NARCIS (Netherlands)

    Trichias, K.; van den Berg, Hans Leo; de Jongh, J.; Litjens, R.; Dimitrova, D.C.; Brogle, M.; Braun, T.; Heijenk, Gerhard J.; Meratnia, Nirvana

    The term Intelligent Transportation Systems (ITS) refers to adding information and communications technology to transport infrastructure and ve- hicles. The IEEE 802.11p standard is considered the main candidate for com- munication within the context of ITS and it performs well for active safety use

  18. On Model Design for Simulation of Collective Intelligence

    NARCIS (Netherlands)

    Schut, M.C.

    2010-01-01

    The study of collective intelligence (CI) systems is increasingly gaining interest in a variety of research and application domains. Those domains range from existing research areas such as computer networks and collective robotics to upcoming areas of agent-based and insect-based computing; also

  19. 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...manage conflict within the workplace enhances his or her ability to Build Trust among followers and Create s Positive Environment. Conflict management

  20. 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

  1. Schizotypal traits in painters: Relations with intelligence, creativity and creative productivity

    Directory of Open Access Journals (Sweden)

    Međedović Janko

    2017-01-01

    Full Text Available In the present research we explored the presence of schizotypal traits in painters. Furthermore, the relations of schizotypy and creativity-related variables (intelligence, creativity and creative productivity were analyzed. Study participants were divided into the criterion (132 students of art academy and art high school and control group (119 psychology students and members of grammar school. Two hypotheses were set: 1 schizotypal traits are more pronounced in painters than in control group; 2 schizotypy is more closely associated with the creativitylinked variables in the criterion than in control group. Schizotypy was operationalized by Disintegration construct and measured via DELTA 10 inventory. Intelligence was assessed by Advanced Progressive Matrices-18; creativity was measured by the same labeled scale from HEXACO-PI-R inventory and creative productivity was explored by a set of questions regarding the frequency of creative behavior. Results showed that Magical thinking, Enhanced awareness, Somatoform Dysregulation, Perceptual distortions and Social anhedonia were the schizotypal traits which were more pronounced in painters as compared to the control group. Factor analyses performed in each group separately revealed a latent component loaded both with schizotypal traits, creativity and creative productivity, but only in the group of painters: schizotypy and creativity were not so closely related in the control group. Thus, the study hypotheses were largely confirmed. Results provide a more detailed understanding of the relations between schizotypy and creativity.

  2. Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production.

    Science.gov (United States)

    Nabavi-Pelesaraei, Ashkan; Rafiee, Shahin; Mohtasebi, Seyed Saeid; Hosseinzadeh-Bandbafha, Homa; Chau, Kwok-Wing

    2018-08-01

    Prediction of agricultural energy output and environmental impacts play important role in energy management and conservation of environment as it can help us to evaluate agricultural energy efficiency, conduct crops production system commissioning, and detect and diagnose faults of crop production system. Agricultural energy output and environmental impacts can be readily predicted by artificial intelligence (AI), owing to the ease of use and adaptability to seek optimal solutions in a rapid manner as well as the use of historical data to predict future agricultural energy use pattern under constraints. This paper conducts energy output and environmental impact prediction of paddy production in Guilan province, Iran based on two AI methods, artificial neural networks (ANNs), and adaptive neuro fuzzy inference system (ANFIS). The amounts of energy input and output are 51,585.61MJkg -1 and 66,112.94MJkg -1 , respectively, in paddy production. Life Cycle Assessment (LCA) is used to evaluate environmental impacts of paddy production. Results show that, in paddy production, in-farm emission is a hotspot in global warming, acidification and eutrophication impact categories. ANN model with 12-6-8-1 structure is selected as the best one for predicting energy output. The correlation coefficient (R) varies from 0.524 to 0.999 in training for energy input and environmental impacts in ANN models. ANFIS model is developed based on a hybrid learning algorithm, with R for predicting output energy being 0.860 and, for environmental impacts, varying from 0.944 to 0.997. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output and environmental indices of agricultural production systems owing to its higher speed of computation processes compared to ANN model, despite ANN's higher accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. 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.…

  4. 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....

  5. Hospital-based nurses' perceptions of the adoption of Web 2.0 tools for knowledge sharing, learning, social interaction and the production of collective intelligence.

    Science.gov (United States)

    Lau, Adela S M

    2011-11-11

    Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson's correlation analysis and t tests were used for data analysis. Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence.

  6. Hospital-Based Nurses’ Perceptions of the Adoption of Web 2.0 Tools for Knowledge Sharing, Learning, Social Interaction and the Production of Collective Intelligence

    Science.gov (United States)

    2011-01-01

    Background Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. Objectives The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. Methods The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson’s correlation analysis and t tests were used for data analysis. Results Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence. PMID:22079851

  7. 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.

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

    Science.gov (United States)

    Geng, Yuan

    2016-11-01

    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.

  9. Use of artificial intelligence in the production of high quality minced meat

    Science.gov (United States)

    Kapovsky, B. R.; Pchelkina, V. A.; Plyasheshnik, P. I.; Dydykin, A. S.; Lazarev, A. A.

    2017-09-01

    A design for an automatic line for minced meat production according to new production technology based on an innovative meat milling method is proposed. This method allows the necessary degree of raw material comminution at the stage of raw material preparation to be obtained, which leads to production intensification due to the traditional meat mass comminution equipment being unnecessary. To ensure consistent quality of the product obtained, the use of on-line automatic control of the technological process for minced meat production is envisaged. This system has been developed using artificial intelligence methods and technologies. The system is trainable during the operation process, adapts to changes in processed raw material characteristics and to external impacts that affect the system operation, and manufactures meat shavings with minimal dispersion of the typical particle size. The control system includes equipment for express analysis of the chemical composition of the minced meat and its temperature after comminution. In this case, the minced meat production process can be controlled strictly as a function of time, which excludes subjective factors for assessing the degree of finished product readiness. This will allow finished meat products with consistent, targeted high quality to be produced.

  10. Comparison of learning models based on mathematics logical intelligence in affective domain

    Science.gov (United States)

    Widayanto, Arif; Pratiwi, Hasih; Mardiyana

    2018-04-01

    The purpose of this study was to examine the presence or absence of different effects of multiple treatments (used learning models and logical-mathematical intelligence) on the dependent variable (affective domain of mathematics). This research was quasi experimental using 3x3 of factorial design. The population of this research was VIII grade students of junior high school in Karanganyar under the academic year 2017/2018. Data collected in this research was analyzed by two ways analysis of variance with unequal cells using 5% of significance level. The result of the research were as follows: (1) Teaching and learning with model TS lead to better achievement in affective domain than QSH, teaching and learning with model QSH lead to better achievement in affective domain than using DI; (2) Students with high mathematics logical intelligence have better achievement in affective domain than students with low mathematics logical intelligence have; (3) In teaching and learning mathematics using learning model TS, students with moderate mathematics logical intelligence have better achievement in affective domain than using DI; and (4) In teaching and learning mathematics using learning model TS, students with low mathematics logical intelligence have better achievement in affective domain than using QSH and DI.

  11. Exploring an Emotional Intelligence Model With Psychiatric Mental Health Nurses.

    Science.gov (United States)

    Sims, Traci T

    A lack of emotional skills may affect a nurse's personal well-being and have negative effects on patient outcomes. To compare psychiatric-mental health nurses' (PMHN) scores on the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) to a normed population and compare the emotional intelligence (EI) scores of PMHNs using two tools, MSCEIT and Self-Rated Emotional Intelligence Scale (SREIS). Comparative descriptive and correlational study. PMHNs in the study had a higher mean EI compared with that of 5,000 participants in the normed MSCEIT sample. Significant weak correlations were seen between the perceiving and understanding emotion branches of the MSCEIT and SREIS. The current study added data about a sample of PMHN's EI levels in the United States, which may encourage dialog about EI among PMHNs. Future research is needed to examine the relationship between self-report EI tools (e.g., SREIS) and performance tools (e.g., MSCEIT) to determine if they are measuring the same construct.

  12. Cognitive model of image interpretation for artificial intelligence applications

    International Nuclear Information System (INIS)

    Raju, S.

    1988-01-01

    A cognitive model of imaging diagnosis was devised to aid in the development of expert systems that assist in the interpretation of diagnostic images. In this cognitive model, a small set of observations that are strongly predictive of a particular diagnosis lead to a search for other observations that would support this diagnosis but are not necessarily specific for it. Then a set of alternative diagnoses is considered. This is followed by a search for observations that might allow differentiation of the primary diagnostic consideration from the alternatives. The production rules needed to implement this model can be classified into three major categories, each of which have certain general characteristics. Knowledge of these characteristics simplifies the development of these expert systems

  13. Intelligence Issues for Congress

    Science.gov (United States)

    2013-04-23

    open source information— osint (newspapers...by user agencies. Section 1052 of the Intelligence Reform Act expressed the sense of Congress that there should be an open source intelligence ...center to coordinate the collection, analysis, production, and dissemination of open source intelligence to other intelligence agencies. An Open Source

  14. Past, current and potential utilisation of active and intelligent packaging systems for meat and muscle-based products: A review.

    Science.gov (United States)

    Kerry, J P; O'Grady, M N; Hogan, S A

    2006-09-01

    Interest in the use of active and intelligent packaging systems for meat and meat products has increased in recent years. Active packaging refers to the incorporation of additives into packaging systems with the aim of maintaining or extending meat product quality and shelf-life. Active packaging systems discussed include oxygen scavengers, carbon dioxide scavengers and emitters, moisture control agents and anti-microbial packaging technologies. Intelligent packaging systems are those that monitor the condition of packaged foods to give information regarding the quality of the packaged food during transport and storage. The potential of sensor technologies, indicators (including integrity, freshness and time-temperature (TTI) indicators) and radio frequency identification (RFID) are evaluated for potential use in meat and meat products. Recognition of the benefits of active and intelligent packaging technologies by the food industry, development of economically viable packaging systems and increased consumer acceptance is necessary for commercial realisation of these packaging technologies.

  15. Modeling Novo Nordisk Production Systems

    DEFF Research Database (Denmark)

    Miller, Thomas Dedenroth

    1997-01-01

    This report describes attributes of models and systems, and how models can be used for description of production systems. There are special attention on the 'Theory of Domains'.......This report describes attributes of models and systems, and how models can be used for description of production systems. There are special attention on the 'Theory of Domains'....

  16. Enabling intelligent copernicus services for carbon and water balance modeling of boreal forest ecosystems - North State

    Science.gov (United States)

    Häme, Tuomas; Mutanen, Teemu; Rauste, Yrjö; Antropov, Oleg; Molinier, Matthieu; Quegan, Shaun; Kantzas, Euripides; Mäkelä, Annikki; Minunno, Francesco; Atli Benediktsson, Jon; Falco, Nicola; Arnason, Kolbeinn; Storvold, Rune; Haarpaintner, Jörg; Elsakov, Vladimir; Rasinmäki, Jussi

    2015-04-01

    The objective of project North State, funded by Framework Program 7 of the European Union, is to develop innovative data fusion methods that exploit the new generation of multi-source data from Sentinels and other satellites in an intelligent, self-learning framework. The remote sensing outputs are interfaced with state-of-the-art carbon and water flux models for monitoring the fluxes over boreal Europe to reduce current large uncertainties. This will provide a paradigm for the development of products for future Copernicus services. The models to be interfaced are a dynamic vegetation model and a light use efficiency model. We have identified four groups of variables that will be estimated with remote sensed data: land cover variables, forest characteristics, vegetation activity, and hydrological variables. The estimates will be used as model inputs and to validate the model outputs. The earth observation variables are computed as automatically as possible, with an objective to completely automatic estimation. North State has two sites for intensive studies in southern and northern Finland, respectively, one in Iceland and one in state Komi of Russia. Additionally, the model input variables will be estimated and models applied over European boreal and sub-arctic region from Ural Mountains to Iceland. The accuracy assessment of the earth observation variables will follow statistical sampling design. Model output predictions are compared to earth observation variables. Also flux tower measurements are applied in the model assessment. In the paper, results of hyperspectral, Sentinel-1, and Landsat data and their use in the models is presented. Also an example of a completely automatic land cover class prediction is reported.

  17. Extending Galactic Habitable Zone Modeling to Include the Emergence of Intelligent Life.

    Science.gov (United States)

    Morrison, Ian S; Gowanlock, Michael G

    2015-08-01

    Previous studies of the galactic habitable zone have been concerned with identifying those regions of the Galaxy that may favor the emergence of complex life. A planet is deemed habitable if it meets a set of assumed criteria for supporting the emergence of such complex life. In this work, we extend the assessment of habitability to consider the potential for life to further evolve to the point of intelligence--termed the propensity for the emergence of intelligent life, φI. We assume φI is strongly influenced by the time durations available for evolutionary processes to proceed undisturbed by the sterilizing effects of nearby supernovae. The times between supernova events provide windows of opportunity for the evolution of intelligence. We developed a model that allows us to analyze these window times to generate a metric for φI, and we examine here the spatial and temporal variation of this metric. Even under the assumption that long time durations are required between sterilizations to allow for the emergence of intelligence, our model suggests that the inner Galaxy provides the greatest number of opportunities for intelligence to arise. This is due to the substantially higher number density of habitable planets in this region, which outweighs the effects of a higher supernova rate in the region. Our model also shows that φI is increasing with time. Intelligent life emerged at approximately the present time at Earth's galactocentric radius, but a similar level of evolutionary opportunity was available in the inner Galaxy more than 2 Gyr ago. Our findings suggest that the inner Galaxy should logically be a prime target region for searches for extraterrestrial intelligence and that any civilizations that may have emerged there are potentially much older than our own.

  18. 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...... in several diagnostic experiments analyzing different fault scenarios. The model and results of the experiments are explained and it is shown how MFM based intelligent modeling and automated reasoning can improve the fault diagnosis process significantly....

  19. 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.

  20. An Analytical Model / Emotional Intelligence Quotient and QOL in Mothers with Infants in Japan.

    Science.gov (United States)

    Ohashi, Junko; Katsura, Toshiki; Hoshino, Akiko; Usui, Kanae

    2013-01-01

    The purpose of this study was to examine the relationship between the emotional intelligence quotient and health-related quality of life using structural equation modeling. A self-administered questionnaire survey was conducted among 1,911 mothers who visited the Health Center for an infant medical examination. A hypothetical model was constructed using variables of the emotional intelligence quotient, social support, coping, parenting stress, and perceived health competence. There were a total of 1,104 valid responses (57.8%). Significant standardized estimates were obtained, confirming the goodness of fit issues with the model. The emotional intelligence quotient had a strong impact on physical and psychological quality of life, and showed the greatest association with coping. This study differed from previous studies in that, due to the inclusion of social support and explanatory variables in coping, an increase in coping strategies was more highly associated with emotional intelligence quotient levels than with social support. An enhanced emotional intelligence quotient should be considered a primary objective to promote the health of mothers with infant children.

  1. 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.

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

    Science.gov (United States)

    Park, Ok-choon; Seidel, Robert J.

    1989-01-01

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

  3. 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.

  4. 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…

  5. 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…

  6. 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…

  7. Investigation of an artificial intelligence technology--Model trees. Novel applications for an immediate release tablet formulation database.

    Science.gov (United States)

    Shao, Q; Rowe, R C; York, P

    2007-06-01

    This study has investigated an artificial intelligence technology - model trees - as a modelling tool applied to an immediate release tablet formulation database. The modelling performance was compared with artificial neural networks that have been well established and widely applied in the pharmaceutical product formulation fields. The predictability of generated models was validated on unseen data and judged by correlation coefficient R(2). Output from the model tree analyses produced multivariate linear equations which predicted tablet tensile strength, disintegration time, and drug dissolution profiles of similar quality to neural network models. However, additional and valuable knowledge hidden in the formulation database was extracted from these equations. It is concluded that, as a transparent technology, model trees are useful tools to formulators.

  8. PRODUCT STRUCTURE DIGITAL MODEL

    Directory of Open Access Journals (Sweden)

    V.M. Sineglazov

    2005-02-01

    Full Text Available  Research results of representation of product structure made by means of CADDS5 computer-aided design (CAD system, Product Data Management Optegra (PDM system and Product Life Cycle Management Wind-chill system (PLM, are examined in this work. Analysis of structure component development and its storage in various systems is carried out. Algorithms of structure transformation required for correct representation of the structure are considered. Management analysis of electronic mockup presentation of the product structure is carried out for Windchill system.

  9. A Multidisciplinary Artificial Intelligence Model of an Affective Robot

    Directory of Open Access Journals (Sweden)

    Hooman Aghaebrahimi Samani

    2012-03-01

    Full Text Available A multidisciplinary approach to a novel artificial intelligence system for an affective robot is presented in this paper. The general objective of the system is to develop a robotic system which strives to achieve a high level of emotional bond between humans and robot by exploring human love. Such a relationship is a contingent process of attraction, affection and attachment from humans towards robots, and the belief of the vice versa from robots to humans. The advanced artificial intelligence of the system includes three modules, namely Probabilistic Love Assembly (PLA, based on the psychology of love, Artificial Endocrine System (AES, based on the physiology of love, and Affective State Transition (AST, based on emotions. The PLA module employs a Bayesian network to incorporate psychological parameters of affection in the robot. The AES module employs artificial emotional and biological hormones via a Dynamic Bayesian Network (DBN. The AST module uses a novel transition method for handling affective states of the robot. These three modules work together to manage emotional behaviours of the robot.

  10. 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.

  11. The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

    Science.gov (United States)

    Manapa, I. Y. H.; Budiyono; Subanti, S.

    2018-03-01

    The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

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

    OpenAIRE

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

    2017-01-01

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

  13. 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...

  14. Artificial intelligence system for the monitoring of natural gas production systems; Intelligente Ueberwachung von Erdgasfoerderanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Tschaetsch, H.U.

    2001-02-01

    The article explains a novel, artificial intelligence-based system called HISS (Human Interface Supervision System) which has been installed as a prototype for the monitoring of a natural gas production site at Thoense near Hannover/Germany. The system is capable to perform audio-visual and smelling functions, analogous to the human sensory perception. (orig./CB) [German] Die Aufrechterhaltung eines einwandfreien Betriebszustandes von technischen Anlagen durch staendige Kontrollen und regelmaessige Wartungsarbeiten ist haeufig eine aufwendige und kostspielige Angelegenheit. Gleichwohl ist sie - sowohl was die Frage der Sicherheit als auch des Umweltschutzes anbelangt - unentbehrlich. Die Erdgasfoerderanlage Thoense bei Hannover wird von einem intelligenten Ueberwachungssystem, HISS - Human Interface Supervision System, kontrolliert, das die menschlichen Eigenschaften sehen, hoeren und riechen beherrscht. (orig.)

  15. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    Directory of Open Access Journals (Sweden)

    Daniel-Petru GHENCEA

    2017-06-01

    Full Text Available The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic. The paper presents a prediction mode obtaining valid range of values for spindles with similar characteristics based on measured data sets from a few spindles test without additional measures being required. Extracting polynomial functions of graphs resulting from simultaneous measurements and predict the dynamics of the two features with multi-objective criterion is the main advantage of this method.

  16. Microfoundations for Sustainable Growth with Eco-Intelligent Product Service-Arrangements

    Directory of Open Access Journals (Sweden)

    Najine Ameli

    2013-03-01

    Full Text Available This paper argues that the contemporary growth paradigm needs to be reconsidered on a micro level of consumption and product service-systems. This becomes necessary since a dynamic link between macro strategies and micro implementation of sustainable growth is missing up to date. Therefore, mainstream sustainability strategies of efficiency and consistency are extended by sufficiency in order to integrate strategies for individual welfare within their social environment. Limits to and drivers for growth are revised and updated socially in terms of qualitative values, diminishing marginal utility or symbolic social distinction. We elaborate a definition of sustainable growth that fosters individual welfare by enhancing social enactment within the boundaries of environmental space. Shifting focus on social aspects in design fosters more sustainable production and consumption patterns while sustaining individual welfare. We derive latent indications for eco-intelligent product service-arrangements and evaluate to concepts by referring to introduced definitions and according indications. With doing so, we illustrate new pathways for the translation of sustainable growth and strategies into product service-systems.

  17. Intelligent judgements over health risks in a spatial agent-based model.

    Science.gov (United States)

    Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

    2018-03-20

    Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

  18. 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.

  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. 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...

  1. 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.

  2. 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…

  3. 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

  4. Towards a value model for collaborative, business intelligence-supported risk assessment

    NARCIS (Netherlands)

    Liu, L.; Daniëls, H.A.M.; Johannesson, P.

    2012-01-01

    Collaborative business intelligence supports risk assessment and in return enhances management control on a business network. Nonetheless, it needs an incentive basis in the first place before it can be implemented, that is, the value model. Starting from the managerial challenges which arise from

  5. Design of an Intelligent Support Agent Model for People with a Cognitive Vulnerability

    NARCIS (Netherlands)

    Aziz, A.A.; Klein, M.C.A.; Zhang, B.; Wang, Y.; Kinser, W.

    2010-01-01

    This paper presents the design of an intelligent agent application aimed at supporting people with a cognitive vulnerability to prevent the onset of a depression. For this, a computational model of the cognitive processes around depression is used. The agent application uses the principles of

  6. A Multidirectional Model for Assessing Learning Disabled Students' Intelligence: An Information-Processing Framework.

    Science.gov (United States)

    Swanson, H. Lee

    1982-01-01

    An information processing approach to the assessment of learning disabled students' intellectual performance is presented. The model is based on the assumption that intelligent behavior is comprised of a variety of problem- solving strategies. An account of child problem solving is explained and illustrated with a "thinking aloud" protocol.…

  7. Artificial intelligence based modeling and optimization of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) production process by using Azohydromonas lata MTCC 2311 from cane molasses supplemented with volatile fatty acids: a genetic algorithm paradigm.

    Science.gov (United States)

    Zafar, Mohd; Kumar, Shashi; Kumar, Surendra; Dhiman, Amit K

    2012-01-01

    The present work describes the optimization of medium variables for the production of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) [P(3HB-co-3HV)] by Azohydromonas lata MTCC 2311 using cane molasses supplemented with propionic acid. Genetic algorithm (GA) has been used for the optimization of P(3HB-co-3HV) production through the simulation of artificial neural network (ANN) and response surface methodology (RSM). The predictions by ANN are better than those of RSM and in good agreement with experimental findings. The highest P(3HB-co-3HV) concentration and 3HV content have been reported as 7.35 g/l and 16.84 mol%, respectively by hybrid ANN-GA. Upon validation, 7.20 g/l and 16.30 mol% of P(3HB-co-3HV) concentration and 3HV content have been found in the shake flask, whereas 6.70 g/l and 16.35 mol%, have been observed in a 3 l bioreactor, respectively. The specific growth rate and P(3HB-co-3HV) accumulation rate of 0.29 per h and 0.16 g/lh determined with cane molasses are comparable to those observed on pure substrates. Copyright © 2011 Elsevier Ltd. All rights reserved.

  8. Market Intelligence Precursors for the Entrepreneurial Resilience Approach: The Case of the Romanian Eco-Label Product Retailers

    Directory of Open Access Journals (Sweden)

    Adrian Micu

    2018-01-01

    Full Text Available The entrepreneurial resilience of eco-label product retailers emphasises their adaptive capability for renewal after the economic crisis. This paper explores the resilience of the market intelligence techniques adopted by the eco-label product retailers in order to contribute to sustainable development of this market in Romania. The research, conducted on a sample of Romanian retailers of eco-label products, analyses the main sources for gathering data about their competitors, the reasons for monitoring the strategic options of their competitors and the specific market intelligence techniques employed within the entrepreneurial resilience approach, aiming to overcome the negative crisis effects. The research outlines, from an entrepreneurial resilience perspective, several positioning opportunities of the eco-label product retailers after the crisis, which have affected the Romanian economy in the period 2008–2009 and have implicitly affected the eco-label market.

  9. Social intelligence of parents with autism spectrum disorders impacts their emotional behaviour: A new proposed model for stabilising emotionality of these parents impacting their social intelligence

    Directory of Open Access Journals (Sweden)

    Vidya Bhagat

    2017-01-01

    Full Text Available Autism spectrum disorder (ASD may affect all spheres of a child's life. Indeed, parents and siblings also live with emotional instabilities in the family. The experience of parents with ASD child can be distressing since they need to make more adjustments to the demanding need to cope with their life situations. Perhaps, their life is drastically exaggerated with their complexities of life. Particularly, their social life is radically affected. The presence of pervasive and severe deficits in children with ASD isolates these parents from their social life; demanding adjustments to their social environment of parents in their life situations shove them into distress and unstable emotions. Finally, they culminate being shattered in their interpersonal relationship, their family and social life. Indeed, these aspects of distress mask social intelligence of these parents, thus narrow down their focus more on the treatment rather than holistic management of their child. Thus, the management of ASD with these parents of the deficit children to reach their fullest abilities remains doubtful. Therefore, the objectives of this study are as follows: (a to examine the impact of emotionality on social intelligence of parents blessed with autistic child, (b to develop awareness regarding social intelligence and its significance among these parents, (c to propose a new model stabilising emotionality of these parents through developing social adaption skills and (d to suggest a new model as a guide in the current intervention regimens to ensure the emotional well-being and better social adoption. This study is made based on the keenly examined past evidence with the correlation of emotionality and its impact on social intelligence of the parents with ASD children. The results reveal that the social intelligence is perceived as lowered evidenced by poor social adjustment reflected in social isolation observed in the parents of children with ASD. A new model

  10. 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.

  11. 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. © The Author(s) 2016.

  12. European oil product supply modelling

    International Nuclear Information System (INIS)

    Saint-Antonin, V.

    1998-01-01

    Over the last few years, trends in European oil product consumption (in terms of level as structure and quality) has important implications of the refining industry. In this context, the purpose of this thesis consists in building a mathematical programming model applied to the European refineries in order to determine oil product supply prices, European refining industry investments and oil product exchanges of the European Union. The first part presents the reason for our choice for a long-term aggregate multi-refineries linear programming model, based on European refineries characteristics and the objectives of our model. Its dual properties are studied in detail and we focus particularly on the European exchange modelling. In the second part, an analysis of the European refining trends leads us to identify parameters and variables of the model that are essential to the aggregate representation of the European oil product supply. The third part is devoted to the use of this model, regarding two scenarios of increasingly stringent specifications for gasoline and diesel oil. Our interest for these products is due to their important share of the European oil product consumption and the not insignificant responsibility of the transport sector for atmospheric pollution. Finally, in order to have the use of an overall picture of the European refining industry, we build a regression model summarizing, though a few equations, the main relations between the major endogenous and exogenous variables o the LP model. Based on pseudo-data, this kind of model provides a simple and robust representation of the oil product supply. But a more specialized analysis of the refining industry operations, turning on a technical assessment of processing units, is reliant on the use of an optimization model such as the model we have built. (author)

  13. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

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

  14. Geometrical model of multiple production

    International Nuclear Information System (INIS)

    Chikovani, Z.E.; Jenkovszky, L.L.; Kvaratshelia, T.M.; Struminskij, B.V.

    1988-01-01

    The relation between geometrical and KNO-scaling and their violation is studied in a geometrical model of multiple production of hadrons. Predictions concerning the behaviour of correlation coefficients at future accelerators are given

  15. 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...

  16. Model of facilitation of emotional intelligence to promote wholeness ...

    African Journals Online (AJOL)

    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 ...

  17. 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

    2008-06-01

    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.

  18. 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.

  19. 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

  20. 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.

  1. EDITORIAL: Advances in Measurement Technology and Intelligent Instruments for Production Engineering

    Science.gov (United States)

    Gao, Wei; Takaya, Yasuhiro; Gao, Yongsheng; Krystek, Michael

    2008-08-01

    Measurement and instrumentation have long played an important role in Production Engineering, through supporting both the traditional field of manufacturing and the new field of micro/nano-technology. Papers published in this special feature were selected and updated from those presented at The 8th International Symposium on Measurement Technology and Intelligent Instruments (ISMTII 2007) held at Tohoku University, Sendai, Japan, on 24-27 September 2007. ISMTII 2007 was organized by ICMI (The International Committee on Measurements and Instrumentation), Japan Society for Precision Engineering (JSPE, Technical Committee of Intelligent Measurement with Nanoscale), Korean Society for Precision Engineering (KSPE), Chinese Society for Measurement (CSM) and Tohoku University. The conference was also supported by Center for Precision Metrology of UNC Charlotte and Singapore Institute of Manufacturing Technology. A total of 220 papers, including four keynote papers, were presented at ISMTII 2007, covering a wide range of topics, including micro/nano-metrology, precision measurement, online & in-process measurement, surface metrology, optical metrology & image processing, biomeasurement, sensor technology, intelligent measurement & instrumentation, uncertainty, traceability & calibration, and signal processing algorithms. The guest editors recommended publication of updated versions of some of the best ISMTII 2007 papers in this special feature of Measurement Science and Technology. The first two papers were presented in ISMTII 2007 as keynote papers. Takamasu et al from The University of Tokyo report uncertainty estimation for coordinate metrology, in which methods of estimating uncertainties using the coordinate measuring system after calibration are formulated. Haitjema, from Mitutoyo Research Center Europe, treats the most often used interferometric measurement techniques (displacement interferometry and surface interferometry) and their major sources of errors. Among

  2. Robust intelligent sliding model control using recurrent cerebellar model articulation controller for uncertain nonlinear chaotic systems

    International Nuclear Information System (INIS)

    Peng Yafu

    2009-01-01

    In this paper, a robust intelligent sliding model control (RISMC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This RISMC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control (SMC) due to unknown system dynamics, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. Moreover, the Taylor linearization technique is employed to derive the linearized model of the RCMAC. The all adaptation laws of the RISMC system are derived based on the Lyapunov stability analysis and projection algorithm, so that the stability of the system can be guaranteed. Finally, the proposed RISMC system is applied to control a Van der Pol oscillator, a Genesio chaotic system and a Chua's chaotic circuit. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. In addition, the advantages of the proposed RISMC are indicated in comparison with a SMC system

  3. Analysis of traversable pits model to make intelligent wheeled vehicles

    Directory of Open Access Journals (Sweden)

    F. Abbasi

    2017-11-01

    Full Text Available In this paper, the issue of passing wheeled vehicles from pits is discussed. The issue is modeled by defining the limits of passing wheeled vehicles. The proposed model has been studied based on changes in the effective parameters. Finally, in order to describe the problem, the proposed model has been solved for wheeled vehicles based on the effective parameters by using one of the numerical methods.

  4. 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

  5. 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 heating...... of the building in time. This way the thermal mass of the building can be used to absorb energy from renewable energy source when available and postpone heating in periods with lack of renewable energy generation. The model is used in a model predictive controller to ensure the residential comfort over a given...

  6. Integrated Intelligent Modeling, Design and Control of Crystal Growth Processes

    National Research Council Canada - National Science Library

    Prasad, V

    2000-01-01

    .... This MURI program took an integrated approach towards modeling, design and control of crystal growth processes and in conjunction with growth and characterization experiments developed much better...

  7. 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.

  8. Forecasting Rubber Production Using Intelligent Time Series Analysis to Support Decision Makers

    OpenAIRE

    Subsorn, Panida; Xiao, Jitian; Clayden, Judy

    2010-01-01

    This chapter has investigated the best-fitting forecasting model for national rubber production forecasting for 2007 and 2008. The methods used in this study were based on non-neural network training and neural network training techniques to compare with the actual rubber production data for the best-fitting forecasting model. Hence, neural network training was presented to obtain more accurate forecasts for 2007 and 2008. To our knowledge, this is the preliminary study that brings a new pers...

  9. 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.

  10. 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.

  11. 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

    2017-01-01

    Background: We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. Methods: 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. Results: 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. Conclusion: 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. PMID:28828316

  12. 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.

  13. 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.

  14. Cost Analysis of Spatial Data Production as Part of Business Intelligence Within the Mapping Department

    Science.gov (United States)

    Kisa, A.; Erkek, B.; Çolak, S.

    2012-07-01

    Business intelligence is becoming an important strategic tool for business management. Companies have invested significant resources in applications for customer relationship management (CRM), supply chain management (SCM), enterprise resource planning (ERP), e-commerce, among others, which collect vast amounts of data. Today, these same companies are realizing that no matter how robust their application feature sets are, without an equally robust BI mechanism to make use of the collected data, these applications are ultimately coming up short. They do not provide actionable information to end users nor can they give a global understanding among all the organization's information from the various databases for accounting, CRM, and so on. General Directorate of Land Registry and Cadastre (GDLRC) is the leader organizations in Turkey on the field of mapping-land registry-cadastre. GDLRC has executed spatial based projects on the way National Spatial Data Infrastructure especially from the beginnings of 2000s. such as; Continuously Operating GPS Reference Stations (TUSAGA-Aktif), Geo-Metadata Portal (HBB), Orthophoto-Base Map Production and web services, Completion of Initial Cadastre, Cadastral Renovation Project (TKMP), Land Registry and Cadastre Information System (TAKBIS), Turkish National Spatial Data Infrastructure Project (TNSDI), Ottoman Land Registry Archive Information System (TARBIS). Most of this project has been completed. Some software has been developed within the mentioned project, especially reporting for management level to take decision. In the year of 2010 a new law launched and forced to reorganization of General Directorate of Land Registry and Cadastre. The new structural changes effected to whole organization, management understanding, carrier understanding so on. Even in mapping department which is spatial data producer, now there is no technician, there is no section; there are new carrier as experts. Because of that, all procedures and

  15. An intelligent trust-based access control model for affective ...

    African Journals Online (AJOL)

    In this study, a fuzzy expert system Trust-Based Access Control (TBAC) model for improving the Quality of crowdsourcing using emotional affective computing is presented. This model takes into consideration a pre-processing module consisting of three inputs such as crowd-workers category, trust metric and emotional ...

  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

    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....

  17. Modeling Environmental Impacts on Cognitive Performance for Artificially Intelligent Entities

    Science.gov (United States)

    2017-06-01

    Mavor, 1998). It should be noted that the authors mention the military user audience as a key constituent that must be able to trust the validity...modeling efforts in cognitive architectures. Ultimately, the Task Group 128 report finds that “modeling of post- receptive perceptual processes such

  18. An analysis of urban collisions using an artificial intelligence model.

    Science.gov (United States)

    Mussone, L; Ferrari, A; Oneta, M

    1999-11-01

    Traditional studies on road accidents estimate the effect of variables (such as vehicular flows, road geometry, vehicular characteristics), and the calculation of the number of accidents. A descriptive statistical analysis of the accidents (those used in the model) over the period 1992-1995 is proposed. The paper describes an alternative method based on the use of artificial neural networks (ANN) in order to work out a model that relates to the analysis of vehicular accidents in Milan. The degree of danger of urban intersections using different scenarios is quantified by the ANN model. Methodology is the first result, which allows us to tackle the modelling of urban vehicular accidents by the innovative use of ANN. Other results deal with model outputs: intersection complexity may determine a higher accident index depending on the regulation of intersection. The highest index for running over of pedestrian occurs at non-signalised intersections at night-time.

  19. 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

  20. MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS

    OpenAIRE

    Alexandridis, Konstantinos T.; Pijanowski, Bryan C.

    2002-01-01

    The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving g...

  1. Designing distributed user interfaces for ambient intelligent environments using models and simulations

    OpenAIRE

    LUYTEN, Kris; VAN DEN BERGH, Jan; VANDERVELPEN, Chris; CONINX, Karin

    2006-01-01

    There is a growing demand for design support to create interactive systems that are deployed in ambient intelligent environments. Unlike traditional interactive systems, the wide diversity of situations these type of user interfaces need to work in require tool support that is close to the environment of the end-user on the one hand and provide a smooth integration with the application logic on the other hand. This paper shows how the model-based user interface development methodology can be ...

  2. Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

    Science.gov (United States)

    Krishnan, G. S.

    1997-01-01

    A cost effective model which uses the artificial intelligence techniques in the selection and approval of parts is presented. The knowledge which is acquired from the specialists for different part types are represented in a knowledge base in the form of rules and objects. The parts information is stored separately in a data base and is isolated from the knowledge base. Validation, verification and performance issues are highlighted.

  3. Simulation Modeling of Intelligent Control Algorithms for Constructing Autonomous Power Supply Systems with Improved Energy Efficiency

    Directory of Open Access Journals (Sweden)

    Gimazov Ruslan

    2018-01-01

    Full Text Available The paper considers the issue of supplying autonomous robots by solar batteries. Low efficiency of modern solar batteries is a critical issue for the whole industry of renewable energy. The urgency of solving the problem of improved energy efficiency of solar batteries for supplying the robotic system is linked with the task of maximizing autonomous operation time. Several methods to improve the energy efficiency of solar batteries exist. The use of MPPT charge controller is one these methods. MPPT technology allows increasing the power generated by the solar battery by 15 – 30%. The most common MPPT algorithm is the perturbation and observation algorithm. This algorithm has several disadvantages, such as power fluctuation and the fixed time of the maximum power point tracking. These problems can be solved by using a sufficiently accurate predictive and adaptive algorithm. In order to improve the efficiency of solar batteries, autonomous power supply system was developed, which included an intelligent MPPT charge controller with the fuzzy logic-based perturbation and observation algorithm. To study the implementation of the fuzzy logic apparatus in the MPPT algorithm, in Matlab/Simulink environment, we developed a simulation model of the system, including solar battery, MPPT controller, accumulator and load. Results of the simulation modeling established that the use of MPPT technology had increased energy production by 23%; introduction of the fuzzy logic algorithm to MPPT controller had greatly increased the speed of the maximum power point tracking and neutralized the voltage fluctuations, which in turn reduced the power underproduction by 2%.

  4. Technologies for conceptual modelling and intelligent query formulation

    CSIR Research Space (South Africa)

    Alberts, R

    2008-11-01

    Full Text Available The aim of the project is to devise and evaluate algorithms, methodologies, techniques and interaction paradigms to build a tool for conceptual modelling and query management of complex data repositories based on a framework with solid formal...

  5. 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...

  6. 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.

  7. Modeling and Control of Multivariable Process Using Intelligent Techniques

    Directory of Open Access Journals (Sweden)

    Subathra Balasubramanian

    2010-10-01

    Full Text Available For nonlinear dynamic systems, the first principles based modeling and control is difficult to implement. In this study, a fuzzy controller and recurrent fuzzy controller are developed for MIMO process. Fuzzy logic controller is a model free controller designed based on the knowledge about the process. In fuzzy controller there are two types of rule-based fuzzy models are available: one the linguistic (Mamdani model and the other is Takagi–Sugeno model. Of these two, Takagi-Sugeno model (TS has attracted most attention. The fuzzy controller application is limited to static processes due to their feedforward structure. But, most of the real-time processes are dynamic and they require the history of input/output data. In order to store the past values a memory unit is needed, which is introduced by the recurrent structure. The proposed recurrent fuzzy structure is used to develop a controller for the two tank heating process. Both controllers are designed and implemented in a real time environment and their performance is compared.

  8. 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.

  9. A review on integration of artificial intelligence into water quality modelling.

    Science.gov (United States)

    Chau, Kwok-wing

    2006-07-01

    With the development of computing technology, numerical models are often employed to simulate flow and water quality processes in coastal environments. However, the emphasis has conventionally been placed on algorithmic procedures to solve specific problems. These numerical models, being insufficiently user-friendly, lack knowledge transfers in model interpretation. This results in significant constraints on model uses and large gaps between model developers and practitioners. It is a difficult task for novice application users to select an appropriate numerical model. It is desirable to incorporate the existing heuristic knowledge about model manipulation and to furnish intelligent manipulation of calibration parameters. The advancement in artificial intelligence (AI) during the past decade rendered it possible to integrate the technologies into numerical modelling systems in order to bridge the gaps. The objective of this paper is to review the current state-of-the-art of the integration of AI into water quality modelling. Algorithms and methods studied include knowledge-based system, genetic algorithm, artificial neural network, and fuzzy inference system. These techniques can contribute to the integrated model in different aspects and may not be mutually exclusive to one another. Some future directions for further development and their potentials are explored and presented.

  10. Spiritual Intelligence, Emotional Intelligence and Auditor’s Performance

    OpenAIRE

    Hanafi, Rustam

    2010-01-01

    The objective of this research was to investigate empirical evidence about influence audi-tor spiritual intelligence on the performance with emotional intelligence as a mediator variable. Linear regression models are developed to examine the hypothesis and path analysis. The de-pendent variable of each model is auditor performance, whereas the independent variable of model 1 is spiritual intelligence, of model 2 are emotional intelligence and spiritual intelligence. The parameters were estima...

  11. 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.

  12. Intelligent Models Performance Improvement Based on Wavelet Algorithm and Logarithmic Transformations in Suspended Sediment Estimation

    Directory of Open Access Journals (Sweden)

    R. Hajiabadi

    2016-10-01

    Full Text Available Introduction One reason for the complexity of hydrological phenomena prediction, especially time series is existence of features such as trend, noise and high-frequency oscillations. These complex features, especially noise, can be detected or removed by preprocessing. Appropriate preprocessing causes estimation of these phenomena become easier. Preprocessing in the data driven models such as artificial neural network, gene expression programming, support vector machine, is more effective because the quality of data in these models is important. Present study, by considering diagnosing and data transformation as two different preprocessing, tries to improve the results of intelligent models. In this study two different intelligent models, Artificial Neural Network and Gene Expression Programming, are applied to estimation of daily suspended sediment load. Wavelet transforms and logarithmic transformation is used for diagnosing and data transformation, respectively. Finally, the impacts of preprocessing on the results of intelligent models are evaluated. Materials and Methods In this study, Gene Expression Programming and Artificial Neural Network are used as intelligent models for suspended sediment load estimation, then the impacts of diagnosing and logarithmic transformations approaches as data preprocessor are evaluated and compared to the result improvement. Two different logarithmic transforms are considered in this research, LN and LOG. Wavelet transformation is used to time series denoising. In order to denoising by wavelet transforms, first, time series can be decomposed at one level (Approximation part and detail part and second, high-frequency part (detail will be removed as noise. According to the ability of gene expression programming and artificial neural network to analysis nonlinear systems; daily values of suspended sediment load of the Skunk River in USA, during a 5-year period, are investigated and then estimated.4 years of

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

    Science.gov (United States)

    2010-02-01

    17. The I-V curve from the manufacturer for BP-4175 175W PV module...........................32   Fig. 18. Wind turbine model...33   Fig. 19. Electrical outputs of wind turbine... PMSG : Permanent Magnet Synchronous Generator PLL : Phase Lock Loop PV : Photovoltaic PWM : Pulse Width Modulation TOU : Time of Use VTES

  14. Data driven model generation based on computational intelligence

    Science.gov (United States)

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

    2010-05-01

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

  15. Comparison of two intelligent models to estimate the instantaneous ...

    Indian Academy of Sciences (India)

    Mostafa Zamani Mohiabadi

    2017-07-25

    Jul 25, 2017 ... help of fuzzy systems and neural networks, two models have been .... tions of six cities in semi-arid regions of Iran. ... specified problem solving algorithm (as is the case ... analysis and structural developments as well as in.

  16. Advances in Games Technology: Software, Models, and Intelligence

    Science.gov (United States)

    Prakash, Edmond; Brindle, Geoff; Jones, Kevin; Zhou, Suiping; Chaudhari, Narendra S.; Wong, Kok-Wai

    2009-01-01

    Games technology has undergone tremendous development. In this article, the authors report the rapid advancement that has been observed in the way games software is being developed, as well as in the development of games content using game engines. One area that has gained special attention is modeling the game environment such as terrain and…

  17. Model-based state estimator for an intelligent tire

    NARCIS (Netherlands)

    Goos, J.; Teerhuis, A. P.; Schmeitz, A. J.C.; Besselink, I.; Nijmeijer, H.

    2017-01-01

    In this work a Tire State Estimator (TSE) is developed and validated using data from a tri-axial accelerometer, installed at the inner liner of the tire. The Flexible Ring Tire (FRT) model is proposed to calculate the tire deformation. For a rolling tire, this deformation is transformed into

  18. Model-based State Estimator for an Intelligent Tire

    NARCIS (Netherlands)

    Goos, J.; Teerhuis, A.P.; Schmeitz, A.J.C.; Besselink, I.J.M.; Nijmeijer, H.

    2016-01-01

    In this work a Tire State Estimator (TSE) is developed and validated using data from a tri-axial accelerometer, installed at the inner liner of the tire. The Flexible Ring Tire (FRT) model is proposed to calculate the tire deformation. For a rolling tire, this deformation is transformed into

  19. An artificial intelligence tool for complex age-depth models

    Science.gov (United States)

    Bradley, E.; Anderson, K. A.; de Vesine, L. R.; Lai, V.; Thomas, M.; Nelson, T. H.; Weiss, I.; White, J. W. C.

    2017-12-01

    CSciBox is an integrated software system for age modeling of paleoenvironmental records. It incorporates an array of data-processing and visualization facilities, ranging from 14C calibrations to sophisticated interpolation tools. Using CSciBox's GUI, a scientist can build custom analysis pipelines by composing these built-in components or adding new ones. Alternatively, she can employ CSciBox's automated reasoning engine, Hobbes, which uses AI techniques to perform an in-depth, autonomous exploration of the space of possible age-depth models and presents the results—both the models and the reasoning that was used in constructing and evaluating them—to the user for her inspection. Hobbes accomplishes this using a rulebase that captures the knowledge of expert geoscientists, which was collected over the course of more than 100 hours of interviews. It works by using these rules to generate arguments for and against different age-depth model choices for a given core. Given a marine-sediment record containing uncalibrated 14C dates, for instance, Hobbes tries CALIB-style calibrations using a choice of IntCal curves, with reservoir age correction values chosen from the 14CHRONO database using the lat/long information provided with the core, and finally composes the resulting age points into a full age model using different interpolation methods. It evaluates each model—e.g., looking for outliers or reversals—and uses that information to guide the next steps of its exploration, and presents the results to the user in human-readable form. The most powerful of CSciBox's built-in interpolation methods is BACON, a Bayesian sedimentation-rate algorithm—a powerful but complex tool that can be difficult to use. Hobbes adjusts BACON's many parameters autonomously to match the age model to the expectations of expert geoscientists, as captured in its rulebase. It then checks the model against the data and iteratively re-calculates until it is a good fit to the data.

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

    Energy Technology Data Exchange (ETDEWEB)

    Galloway, P.

    1983-12-01

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

  1. 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.

  2. 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...

  3. Intelligent harmonic load model based on neural networks

    Science.gov (United States)

    Ji, Pyeong-Shik; Lee, Dae-Jong; Lee, Jong-Pil; Park, Jae-Won; Lim, Jae-Yoon

    2007-12-01

    In this study, we developed a RBFNs(Radial Basis Function Networks) based load modeling method with harmonic components. The developed method implemented by using harmonic information as well as fundamental frequency and voltage which are essential input factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. The RBFNs have certain advantage such as simple structure and rapid computation ability compared with multilayer perceptron which is extensively applied for load modeling. To show the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with conventional methods such as polynominal 2nd equation method, MLP and RBF without considering harmonic components.

  4. Product models for the Construction industry

    DEFF Research Database (Denmark)

    Sørensen, Lars Schiøtt

    1996-01-01

    Different types of product models for the building sector was elaborated and grouped. Some discussion on the different models was given. The "definition" of Product models was given.......Different types of product models for the building sector was elaborated and grouped. Some discussion on the different models was given. The "definition" of Product models was given....

  5. 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...... 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...

  6. 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. 

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

    International Nuclear Information System (INIS)

    Choi, Seong Hoon; Park, Tae Won; Lee, Soo Ho; Jung, Sung Pil; Jun, Kab Jin; Yoon, J. W.

    2010-01-01

    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

  8. Estimation of zero-intelligence models by L1 data

    Czech Academy of Sciences Publication Activity Database

    Šmíd, Martin

    2016-01-01

    Roč. 16, č. 9 (2016), s. 1423-1444 ISSN 1469-7688 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional support: RVO:67985556 Keywords : Limit Order Market * Stochastic Models * Econometric Methods Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.960, year: 2016 http://library.utia.cas.cz/separaty/2016/E/smid-0458944.pdf

  9. Fast substation service restoration using intelligent petri-nets models

    Energy Technology Data Exchange (ETDEWEB)

    Yang, H.T.; Peng, P.C.; Jiang, H.L. [Chung Yuan Christian Univ., Chung Li, Taiwan (China)

    2006-07-01

    Service restoration of a substation is a stressful and immediate task that must be conducted by system operators following a blackout. Operators, including those of Taiwan Power Company (TPC), normally restore power loads on the basis of their past experiences and engineering heuristics. Due to the significant number of switching operations to be evaluated, a computer-aided decision support system can be quite valuable. In distribution system automation, installation of unmanned substations requires an automated restoration computer system to rapidly devise a switching plan after a fault event. The modeling technique of Petri Nets (PNs) encompasses fault diagnosis of distribution systems, protective scheming of relays, and generic restoration schedule of power transmission systems. Knowledge or configuration about the system concerned can be expressed systematically through a structured model with parallelism and synchronization. This paper proposed a new PNs knowledge representation scheme to achieve a fast, on-line service restoration plan of a substation. The paper described the task of service restoration in a substation as well as the heuristic rules adopted by the dispatchers of the TPC distribution systems. The paper also introduced the topic of Typical PN properties and the proposed matrix operations for PNs reasoning. The proposed basic PNs model for service restoration on the basis of the engineering heuristics were also identified. It was concluded that the proposed approach not only facilitated software programming, but was highly adaptive to the extension or maintenance of the developed programs, arising from the changes of the substation configuration. 18 refs., 1 tab., 8 figs.

  10. 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...... is used for checking the consistency of a design with respect to the availablity of services and resources. In the second application, a tool for automatically implementing the communication infrastructure of a process network application, the Service Relation Model is used for analyzing the capabilities...

  11. 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

  12. 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

  13. A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting

    International Nuclear Information System (INIS)

    Su, Zhongyue; Wang, Jianzhou; Lu, Haiyan; Zhao, Ge

    2014-01-01

    Highlights: • A new hybrid model is developed for wind speed forecasting. • The model is based on the Kalman filter and the ARIMA. • An intelligent optimization method is employed in the hybrid model. • The new hybrid model has good performance in western China. - Abstract: Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily

  14. 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...

  15. 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.

  16. 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.

  17. Use of artificial intelligence to identify cardiovascular compromise in a model of hemorrhagic shock.

    Science.gov (United States)

    Glass, Todd F; Knapp, Jason; Amburn, Philip; Clay, Bruce A; Kabrisky, Matt; Rogers, Steven K; Garcia, Victor F

    2004-02-01

    To determine whether a prototype artificial intelligence system can identify volume of hemorrhage in a porcine model of controlled hemorrhagic shock. Prospective in vivo animal model of hemorrhagic shock. Research foundation animal surgical suite; computer laboratories of collaborating industry partner. Nineteen, juvenile, 25- to 35-kg, male and female swine. Anesthetized animals were instrumented for arterial and systemic venous pressure monitoring and blood sampling, and a splenectomy was performed. Following a 1-hr stabilization period, animals were hemorrhaged in aliquots to 10, 20, 30, 35, 40, 45, and 50% of total blood volume with a 10-min recovery between each aliquot. Data were downloaded directly from a commercial monitoring system into a proprietary PC-based software package for analysis. Arterial and venous blood gas values, glucose, and cardiac output were collected at specified intervals. Electrocardiogram, electroencephalogram, mixed venous oxygen saturation, temperature (core and blood), mean arterial pressure, pulmonary artery pressure, central venous pressure, pulse oximetry, and end-tidal CO(2) were continuously monitored and downloaded. Seventeen of 19 animals (89%) died as a direct result of hemorrhage. Stored data streams were analyzed by the prototype artificial intelligence system. For this project, the artificial intelligence system identified and compared three electrocardiographic features (R-R interval, QRS amplitude, and R-S interval) from each of nine unknown samples of the QRS complex. We found that the artificial intelligence system, trained on only three electrocardiographic features, identified hemorrhage volume with an average accuracy of 91% (95% confidence interval, 84-96%). These experiments demonstrate that an artificial intelligence system, based solely on the analysis of QRS amplitude, R-R interval, and R-S interval of an electrocardiogram, is able to accurately identify hemorrhage volume in a porcine model of lethal

  18. 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.

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

    DEFF Research Database (Denmark)

    Jørgensen, Søren

    of modulation frequency selectivity in the auditory processing of sound with a decision metric for intelligibility that is based on the signal-to-noise envelope power ratio (SNRenv). The proposed speech-based envelope power spectrum model (sEPSM) is demonstrated to account for the effects of stationary...... 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...

  20. Reflection on robotic intelligence

    NARCIS (Netherlands)

    Bartneck, C.

    2006-01-01

    This paper reflects on the development or robots, both their physical shape as well as their intelligence. The later strongly depends on the progress made in the artificial intelligence (AI) community which does not yet provide the models and tools necessary to create intelligent robots. It is time

  1. Big cats as a model system for the study of the evolution of intelligence.

    Science.gov (United States)

    Borrego, Natalia

    2017-08-01

    Currently, carnivores, and felids in particular, are vastly underrepresented in cognitive literature, despite being an ideal model system for tests of social and ecological intelligence hypotheses. Within Felidae, big cats (Panthera) are uniquely suited to studies investigating the evolutionary links between social, ecological, and cognitive complexity. Intelligence likely did not evolve in a unitary way but instead evolved as the result of mutually reinforcing feedback loops within the physical and social environments. The domain-specific social intelligence hypothesis proposes that social complexity drives only the evolution of cognitive abilities adapted only to social domains. The domain-general hypothesis proposes that the unique demands of social life serve as a bootstrap for the evolution of superior general cognition. Big cats are one of the few systems in which we can directly address conflicting predictions of the domain-general and domain-specific hypothesis by comparing cognition among closely related species that face roughly equivalent ecological complexity but vary considerably in social complexity. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2009-01-01

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

  3. Forecasting the natural gas demand in China using a self-adapting intelligent grey model

    International Nuclear Information System (INIS)

    Zeng, Bo; Li, Chuan

    2016-01-01

    Reasonably forecasting demands of natural gas in China is of significance as it could aid Chinese government in formulating energy policies and adjusting industrial structures. To this end, a self-adapting intelligent grey prediction model is proposed in this paper. Compared with conventional grey models which have the inherent drawbacks of fixed structure and poor adaptability, the proposed new model can automatically optimize model parameters according to the real data characteristics of modeling sequence. In this study, the proposed new model, discrete grey model, even difference grey model and classical grey model were employed, respectively, to simulate China's natural gas demands during 2002–2010 and forecast demands during 2011–2014. The results show the new model has the best simulative and predictive precision. Finally, the new model is used to forecast China's natural gas demand during 2015–2020. The forecast shows the demand will grow rapidly over the next six years. Therefore, in order to maintain the balance between the supplies and the demands for the natural gas in the future, Chinese government needs to take some measures, such as importing huge amounts of natural gas from abroad, increasing the domestic yield, using more alternative energy, and reducing the industrial reliance on natural gas. - Highlights: • A self-adapting intelligent grey prediction model (SIGM) is proposed in this paper. • The SIGM has the advantage of working with exponential functions and linear functions. • The SIGM solves the drawbacks of fixed structure and poor adaptability of grey models. • The demand of natural gas in China is successfully forecasted using the SIGM model. • The study findings can help Chinese government reasonably formulate energy policies.

  4. A review on the integration of artificial intelligence into coastal modeling.

    Science.gov (United States)

    Chau, Kwokwing

    2006-07-01

    With the development of computing technology, mechanistic models are often employed to simulate processes in coastal environments. However, these predictive tools are inevitably highly specialized, involving certain assumptions and/or limitations, and can be manipulated only by experienced engineers who have a thorough understanding of the underlying theories. This results in significant constraints on their manipulation as well as large gaps in understanding and expectations between the developers and practitioners of a model. The recent advancements in artificial intelligence (AI) technologies are making it possible to integrate machine learning capabilities into numerical modeling systems in order to bridge the gaps and lessen the demands on human experts. The objective of this paper is to review the state-of-the-art in the integration of different AI technologies into coastal modeling. The algorithms and methods studied include knowledge-based systems, genetic algorithms, artificial neural networks, and fuzzy inference systems. More focus is given to knowledge-based systems, which have apparent advantages over the others in allowing more transparent transfers of knowledge in the use of models and in furnishing the intelligent manipulation of calibration parameters. Of course, the other AI methods also have their individual contributions towards accurate and reliable predictions of coastal processes. The integrated model might be very powerful, since the advantages of each technique can be combined.

  5. Role of theory of mind and executive function in explaining social intelligence: a structural equation modeling approach.

    Science.gov (United States)

    Yeh, Zai-Ting

    2013-01-01

    Social intelligence is the ability to understand others and the social context effectively and thus to interact with people successfully. Research has suggested that the theory of mind (ToM) and executive function may play important roles in explaining social intelligence. The specific aim of the present study was to test with structural equation modeling (SEM) the hypothesis that performance on ToM tasks is more associated with social intelligence in the elderly than is performance on executive functions. One hundred and seventy-seven participants (age 56-96) completed ToM, executive function, and other basic cognition tasks, and were rated with social intelligence scales. The SEM results showed that ToM and executive function were strongly correlated (0.54); however, only the path coefficient from ToM to social intelligence, and not from executive function, was significant (0.37). ToM performance, but not executive function, was strongly correlated with social intelligence among elderly individuals. ToM and executive function might play different roles in social behavior during normal aging; however, based on the present results, it is possible that ToM might play an important role in social intelligence.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy.

    Science.gov (United States)

    Zhang, Libo; Zhu, Junjie; Ren, Hao; Liu, Dongdong; Meng, Dan; Wu, Yanjun; Luo, Tiejian

    2017-10-14

    Intelligent robots are part of a new generation of robots that are able to sense the surrounding environment, plan their own actions and eventually reach their targets. In recent years, reliance upon robots in both daily life and industry has increased. The protocol proposed in this paper describes the design and production of a handling robot with an intelligent search algorithm and an autonomous identification function. First, the various working modules are mechanically assembled to complete the construction of the work platform and the installation of the robotic manipulator. Then, we design a closed-loop control system and a four-quadrant motor control strategy, with the aid of debugging software, as well as set steering gear identity (ID), baud rate and other working parameters to ensure that the robot achieves the desired dynamic performance and low energy consumption. Next, we debug the sensor to achieve multi-sensor fusion to accurately acquire environmental information. Finally, we implement the relevant algorithm, which can recognize the success of the robot's function for a given application. The advantage of this approach is its reliability and flexibility, as the users can develop a variety of hardware construction programs and utilize the comprehensive debugger to implement an intelligent control strategy. This allows users to set personalized requirements based on their needs with high efficiency and robustness.

  11. 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.

  12. Production Variability and Single Word Intelligibility in Aphasia and Apraxia of Speech

    Science.gov (United States)

    Haley, Katarina L.; Martin, Gwenyth

    2011-01-01

    This study was designed to estimate test-retest reliability of orthographic speech intelligibility testing in speakers with aphasia and AOS and to examine its relationship to the consistency of speaker and listener responses. Monosyllabic single word speech samples were recorded from 13 speakers with coexisting aphasia and AOS. These words were…

  13. On the Relationship between Fluid Intelligence, Gesture Production, and Brain Structure

    Science.gov (United States)

    Wartenburger, Isabell; Kuhn, Esther; Sassenberg, Uta; Foth, Manja; Franz, Elizabeth A.; van der Meer, Elke

    2010-01-01

    Individuals scoring high in fluid intelligence tasks generally perform very efficiently in problem solving tasks and analogical reasoning tasks presumably because they are able to select the task-relevant information very quickly and focus on a limited set of task-relevant cognitive operations. Moreover, individuals with high fluid intelligence…

  14. A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

    Science.gov (United States)

    Huang, Darong; Bai, Xing-Rong

    Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

  15. Methods and Technologies of XML Data Modeling for IP Mode Intelligent Measuring and Controlling System

    International Nuclear Information System (INIS)

    Liu, G X; Hong, X B; Liu, J G

    2006-01-01

    This paper presents the IP mode intelligent measuring and controlling system (IMIMCS). Based on object-oriented modeling technology of UML and XML Schema, the innovative methods and technologies of some key problems for XML data modeling in the IMIMCS were especially discussed, including refinement for systemic business by means of use-case diagram of UML, the confirmation of the content of XML data model and logic relationship of the objects of XML Schema with the aid of class diagram of UML, the mapping rules from the UML object model to XML Schema. Finally, the application of the IMIMCS based on XML for a modern greenhouse was presented. The results show that the modeling methods of the measuring and controlling data in the IMIMCS involving the multi-layer structure and many operating systems process strong reliability and flexibility, guarantee uniformity of complex XML documents and meet the requirement of data communication across platform

  16. 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.

  17. Goleman-Boyatzis Model of Emotional Intelligence for Dealing with Problems in Project Management

    Directory of Open Access Journals (Sweden)

    Peter Vincent Livesey

    2017-03-01

    Full Text Available As projects grow in size and complexity the sizes of teams needed to manage them also increases. This places greater emphasis on the need for the project manager to develop people management skills, commonly called soft skills, of which emotional intelligence (EI has been recognised as an important component. The objective of this research was to investigate the relevance of the Goleman-Boyatzis model of EI in dealing with the problems in large projects identified via a literature review. To achieve this end, a Delphi study using project managers who had been involved in the management of projects in excess of $500 million was used. The responses from the Delphi panel were analysed and the results showed that the competencies contained in the Goleman-Boyatzis model had a relevance of 95% or greater to the problems presented to the panel. A ranking of the various competencies contained within the model was also developed, some competencies being found to be more important than others. By confirming the importance of emotional intelligence, as described by the model, this research adds to the understanding of the necessary skills needed by a project manager to successfully manage large projects.

  18. Optimizing bi-objective, multi-echelon supply chain model using particle swarm intelligence algorithm

    Science.gov (United States)

    Sathish Kumar, V. R.; Anbuudayasankar, S. P.; Rameshkumar, K.

    2018-02-01

    In the current globalized scenario, business organizations are more dependent on cost effective supply chain to enhance profitability and better handle competition. Demand uncertainty is an important factor in success or failure of a supply chain. An efficient supply chain limits the stock held at all echelons to the extent of avoiding a stock-out situation. In this paper, a three echelon supply chain model consisting of supplier, manufacturing plant and market is developed and the same is optimized using particle swarm intelligence algorithm.

  19. 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...

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

    Directory of Open Access Journals (Sweden)

    Kazemi P

    2017-01-01

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

  1. 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.

  2. 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.

  3. Modeling an Optical and Infrared Search for Extraterrestrial Intelligence Survey with Exoplanet Direct Imaging

    Science.gov (United States)

    Vides, Christina; Macintosh, Bruce; Ruffio, Jean-Baptiste; Nielsen, Eric; Povich, Matthew Samuel

    2018-01-01

    Gemini Planet Imager (GPI) is a direct high contrast imaging instrument coupled to the Gemini South Telescope. Its purpose is to image extrasolar planets around young (~Intelligence), we modeled GPI’s capabilities to detect an extraterrestrial continuous wave (CW) laser broadcasted within the H-band have been modeled. By using sensitivity evaluated for actual GPI observations of young target stars, we produced models of the CW laser power as a function of distance from the star that could be detected if GPI were to observe nearby (~ 3-5 pc) planet-hosting G-type stars. We took a variety of transmitters into consideration in producing these modeled values. GPI is known to be sensitive to both pulsed and CW coherent electromagnetic radiation. The results were compared to similar studies and it was found that these values are competitive to other optical and infrared observations.

  4. 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.

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

    Science.gov (United States)

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

    2018-06-01

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

  6. Study on intelligent processing system of man-machine interactive garment frame model

    Science.gov (United States)

    Chen, Shuwang; Yin, Xiaowei; Chang, Ruijiang; Pan, Peiyun; Wang, Xuedi; Shi, Shuze; Wei, Zhongqian

    2018-05-01

    A man-machine interactive garment frame model intelligent processing system is studied in this paper. The system consists of several sensor device, voice processing module, mechanical parts and data centralized acquisition devices. The sensor device is used to collect information on the environment changes brought by the body near the clothes frame model, the data collection device is used to collect the information of the environment change induced by the sensor device, voice processing module is used for speech recognition of nonspecific person to achieve human-machine interaction, mechanical moving parts are used to make corresponding mechanical responses to the information processed by data collection device.it is connected with data acquisition device by a means of one-way connection. There is a one-way connection between sensor device and data collection device, two-way connection between data acquisition device and voice processing module. The data collection device is one-way connection with mechanical movement parts. The intelligent processing system can judge whether it needs to interact with the customer, realize the man-machine interaction instead of the current rigid frame model.

  7. Artificial intelligence-based modeling and control of fluidized bed combustion

    Energy Technology Data Exchange (ETDEWEB)

    Ikonen, E.; Leppaekoski, K. (Univ. of Oulu, Dept. of Process and Environmental Engineering (Finland)). email: enso.ikonen@oulu.fi

    2009-07-01

    AI-inspired techniques have a lot to offer when developing methods for advanced identification, monitoring, control and optimization of industrial processes, such as power plants. Advanced control methods have been extensively examined in the research of the Power Plant Automation group at the Systems Engineering Laboratory, e.g., in fuel inventory modelling, combustion power control, modelling and control of flue gas oxygen, drum control, modelling and control of superheaters, or in optimization of flue-gas emissions. Most engineering approaches to artificial intelligence (AI) are characterized by two fundamental properties: the ability to learn from various sources and the ability to deal with plant complexity. Learning systems that are able to operate in uncertain environments based on incomplete information are commonly referred to as being intelligent. A number of other approaches exist, characterized by these properties, but not easily categorized as AI-systems. Advanced control methods (adaptive, predictive, multivariable, robust, etc.) are based on the availability of a model of the process to be controlled. Hence identification of processes becomes a key issue, leading to the use of adaptation and learning techniques. A typical learning control system concerns a selection of learning techniques applied for updating a process model, which in turn is used for the controller design. When design of learning control systems is complemented with concerns for dealing with uncertainties or vaguenesses in models, measurements, or even objectives, particularly close connections exist between advanced process control and methods of artificial intelligence and machine learning. Needs for advanced techniques are typically characterized by the desire to properly handle plant non-linearities, the multivariable nature of the dynamic problems, and the necessity to adapt to changing plant conditions. In the field of fluidized bed combustion (FBC) control, the many promising

  8. A model for optimizing the production of pharmaceutical products

    Directory of Open Access Journals (Sweden)

    Nevena Gospodinova

    2017-05-01

    Full Text Available The problem associated with the optimal production planning is especially relevant in modern industrial enterprises. The most commonly used optimality criteria in this context are: maximizing the total profit; minimizing the cost per unit of production; maximizing the capacity utilization; minimizing the total production costs. This article aims to explore the possibility for optimizing the production of pharmaceutical products through the construction of a mathematical model that can be viewed in two ways – as a single-product model and a multi-product model. As an optimality criterion it is set the minimization of the cost per unit of production for a given planning period. The author proposes an analytical method for solving the nonlinear optimization problem. An optimal production plan of Tylosin tartrate is found using the single-product model.

  9. State and Local Intelligence Fusion Centers: An Evaluative Approach in Modeling a State Fusion Center

    National Research Council Canada - National Science Library

    Forsyth, William A

    2005-01-01

    .... Effective terrorism prevention, however, requires information and intelligence fusion as a cooperative process at all levels of government so that the flow of intelligence can be managed to support...

  10. Artificial Intelligence and Moral intelligence

    Directory of Open Access Journals (Sweden)

    Laura Pana

    2008-07-01

    means for supplementing the objective decision with a subjective one. Machine ethics can/will be of the highest quality because it will be derived from the sciences, modelled by techniques and accomplished by technologies. If our theoretical hypothesis about a specific moral intelligence, necessary for the implementation of an artificial moral conduct, is correct, then some theoretical and technical issues appear, but the following working hypotheses are possible: structural, functional and behavioural. The future of human and/or artificial morality is to be anticipated.

  11. Product Family Modelling for Manufacturing Planning

    DEFF Research Database (Denmark)

    Jørgensen, Kaj Asbjørn; Petersen, Thomas Ditlev; Nielsen, Kjeld

    2011-01-01

    To enable product configuration of a product family, it is important to develop a model of the selected product family. From such a model, an often performed practice is to make a product configurator from which customers can specify individual products from the family. To get further utilisation...

  12. Artificial intelligence for Space Station automation: Crew safety, productivity, autonomy, augmented capability

    Science.gov (United States)

    Firschein, O.; Georgeff, M. P.; Park, W.; Cheeseman, P. C.; Geldberg, J.

    1986-01-01

    Artificial intelligence (AI) R&D projects for the successful and efficient operation of the Space Station are described. The book explores the most advanced AI-based technologies, reviews the results of concept design studies to determine required AI capabilities, details demonstrations that would indicate the existence of these capabilities, and develops an R&D plan leading to such demonstrations. Particular attention is given to teleoperation and robotics, sensors, expert systems, computers, planning, and man-machine interface.

  13. Decay of Iconic Memory Traces Is Related to Psychometric Intelligence: A Fixed-Links Modeling Approach

    Science.gov (United States)

    Miller, Robert; Rammsayer, Thomas H.; Schweizer, Karl; Troche, Stefan J.

    2010-01-01

    Several memory processes have been examined regarding their relation to psychometric intelligence with the exception of sensory memory. This study examined the relation between decay of iconic memory traces, measured with a partial-report task, and psychometric intelligence, assessed with the Berlin Intelligence Structure test, in 111…

  14. Transformational leadership and organizational citizenship behavior: Modeling emotional intelligence as mediator

    Directory of Open Access Journals (Sweden)

    Majeed Nauman

    2017-12-01

    Full Text Available Leadership and organizational citizenship behavior (OCB stayed at pinnacle in the arena of organizational behavior research since decades and has attained significant consideration of scholars pursuing to define multifaceted dynamics of leadership and their influence on follower’s behavior at work. The voluntary behavior of Organizational citizenship improves organizational effectiveness, and it goes beyond formal job duties. This study attempts to explore the association amongst transformational leadership and organizational citizenship behavior of teachers in public sector higher education institutions in Pakistan. Study of organizational citizenship behavior in educational organizations and academicians is of high value that definitely requires attention. This study examines the direct and indirect influence of transformational leadership through exploring the mediating role of emotional intelligence. The model was tested by employing structural equation modelling technique on survey responses collected from academicians. Results from 220 responses indicated that relationship between transformational leadership and Organizational Citizenship Behavior is statistically significant where Emotional Intelligence plays an important role as a mediator. The results support and add to the positive effects of transformational leadership style interconnected with extra role behavior at work making it more meaningful. The findings make a significant contribution to leadership and organizational behavior literature in higher education sector and propose that organizations should implement practices that help in enhancing the level of organizational citizenship behavior in organizations.

  15. A Dynamic Intelligent Decision Approach to Dependency Modeling of Project Tasks in Complex Engineering System Optimization

    Directory of Open Access Journals (Sweden)

    Tinggui Chen

    2013-01-01

    Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.

  16. Production economic models of fisheries

    DEFF Research Database (Denmark)

    Andersen, Jesper Levring

    The overall purpose of this PhD thesis is to investigate different aspects of fishermen’s behaviour using production economic models at the individual and industry levels. Three parts make up this thesis. The first part provides an overview of the thesis. The second part consists of four papers......, including all relevant factors in specific analyses is impossible, and it is therefore important to be aware of the most essential ones. As demonstrated in the literature review of Paper 1, a large number of factors may significantly influence fishermen’s short run behaviour, i.e. choice of gear type...

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

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2011-01-01

    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......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...... observed for the different interferers. None of the standardized models successfully describe these data....

  18. 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.

  19. Towards An Intelligent Model-Based Decision Support System For An Integrated Oil Company (EGPC)

    International Nuclear Information System (INIS)

    Khorshid, M.; Hassan, H.; Abdel Latife, M.A.

    2004-01-01

    Decision Support System (DSS) is an interactive, flexible and adaptable computer-based support system specially developed for supporting the solution of unstructured management problems [31] DSS has become widespread for oil industry domain in recent years. The computer-based DSS, which were developed and implemented in oil industry, are used to address the complex short-term planning and operational issues associated with downstream industry. Most of these applications concentrate on the data-centered tools, while the model-centered applications of DSS are still very limited up till now [20]. This study develops an Intelligent Model-Based DSS for an integrated oil company, to help policy makers and petroleum planner in improving the effectiveness of the strategic planning in oil sector. This domain basically imposes semi-structured or unstructured decisions and involves a very complex modeling process

  20. 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...

  1. Machine listening intelligence

    Science.gov (United States)

    Cella, C. E.

    2017-05-01

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

  2. STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

    Science.gov (United States)

    ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

  3. 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.

  4. Temperature-based modeling of reference evapotranspiration using several artificial intelligence models: application of different modeling scenarios

    Science.gov (United States)

    Sanikhani, Hadi; Kisi, Ozgur; Maroufpoor, Eisa; Yaseen, Zaher Mundher

    2018-02-01

    The establishment of an accurate computational model for predicting reference evapotranspiration (ET0) process is highly essential for several agricultural and hydrological applications, especially for the rural water resource systems, water use allocations, utilization and demand assessments, and the management of irrigation systems. In this research, six artificial intelligence (AI) models were investigated for modeling ET0 using a small number of climatic data generated from the minimum and maximum temperatures of the air and extraterrestrial radiation. The investigated models were multilayer perceptron (MLP), generalized regression neural networks (GRNN), radial basis neural networks (RBNN), integrated adaptive neuro-fuzzy inference systems with grid partitioning and subtractive clustering (ANFIS-GP and ANFIS-SC), and gene expression programming (GEP). The implemented monthly time scale data set was collected at the Antalya and Isparta stations which are located in the Mediterranean Region of Turkey. The Hargreaves-Samani (HS) equation and its calibrated version (CHS) were used to perform a verification analysis of the established AI models. The accuracy of validation was focused on multiple quantitative metrics, including root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (R 2), coefficient of residual mass (CRM), and Nash-Sutcliffe efficiency coefficient (NS). The results of the conducted models were highly practical and reliable for the investigated case studies. At the Antalya station, the performance of the GEP and GRNN models was better than the other investigated models, while the performance of the RBNN and ANFIS-SC models was best compared to the other models at the Isparta station. Except for the MLP model, all the other investigated models presented a better performance accuracy compared to the HS and CHS empirical models when applied in a cross-station scenario. A cross-station scenario examination implies the

  5. Swarm intelligence for multi-objective optimization of synthesis gas production

    Science.gov (United States)

    Ganesan, T.; Vasant, P.; Elamvazuthi, I.; Ku Shaari, Ku Zilati

    2012-11-01

    In the chemical industry, the production of methanol, ammonia, hydrogen and higher hydrocarbons require synthesis gas (or syn gas). The main three syn gas production methods are carbon dioxide reforming (CRM), steam reforming (SRM) and partial-oxidation of methane (POM). In this work, multi-objective (MO) optimization of the combined CRM and POM was carried out. The empirical model and the MO problem formulation for this combined process were obtained from previous works. The central objectives considered in this problem are methane conversion, carbon monoxide selectivity and the hydrogen to carbon monoxide ratio. The MO nature of the problem was tackled using the Normal Boundary Intersection (NBI) method. Two techniques (Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO)) were then applied in conjunction with the NBI method. The performance of the two algorithms and the quality of the solutions were gauged by using two performance metrics. Comparative studies and results analysis were then carried out on the optimization results.

  6. Leadership vs. Management From Competitive Intelligence Perspective

    Directory of Open Access Journals (Sweden)

    Valeriu Ivan

    2015-05-01

    Full Text Available This paper brings into attention a less studies topic: the analysis and intelligence productionspecificity – as competitive intelligence process stage – given that the beneficiary is practicing classic management or leadership. The contextualization of the issue imposed us to separate the two concepts from the current debates perspective regarding the relationship between management and leadership. We did this in respect of the competition and competitiveness. Although that report is not clearly and definitively established, we tried to identify the main characteristics and essential differences in the approach of the actionable information needs. The obtained results were correlated with the competitive intelligence cycle stages, in order to identify the approach similarities and differences for each stage. Subsequently, we suggested models of possible approaches in the information analysis and intelligence production activity in order for the resulted informational product to fulfil their role as decision support in competitiveness augmenting.

  7. The Consciousness-Intelligence-Knowledge Pyramid: An 8x8 Layer Model

    Directory of Open Access Journals (Sweden)

    Athanasios S. Drigas

    2017-10-01

    Full Text Available Cognitive and metacognitive skills are recognized and studied since antiquity. From the theory of Aristotle, according to which knowledge is product of the human mind and Platonic gnosiology and the theory of true knowledge, to the modern cognitive science, the question of how people acquire knowledge, has occupied a multitude of scientists. In this article we present a cognitive-based approach to the process of acquiring knowledge, we analyze the dominant theories of knowledge, theories of intelligence, as well as learning theories, and thus we propose an eight-layer pyramid of knowledge. We also analyze the cognitive processes and metacognitive skills required to get an individual to the highest layer of the knowledge pyramid.

  8. 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.

  9. Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools

    Science.gov (United States)

    Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu

    2018-03-01

    Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.

  10. Plant intelligence

    Science.gov (United States)

    Lipavská, Helena; Žárský, Viktor

    2009-01-01

    The concept of plant intelligence, as proposed by Anthony Trewavas, has raised considerable discussion. However, plant intelligence remains loosely defined; often it is either perceived as practically synonymous to Darwinian fitness, or reduced to a mere decorative metaphor. A more strict view can be taken, emphasizing necessary prerequisites such as memory and learning, which requires clarifying the definition of memory itself. To qualify as memories, traces of past events have to be not only stored, but also actively accessed. We propose a criterion for eliminating false candidates of possible plant intelligence phenomena in this stricter sense: an “intelligent” behavior must involve a component that can be approximated by a plausible algorithmic model involving recourse to stored information about past states of the individual or its environment. Re-evaluation of previously presented examples of plant intelligence shows that only some of them pass our test. “You were hurt?” Kumiko said, looking at the scar. Sally looked down. “Yeah.” “Why didn't you have it removed?” “Sometimes it's good to remember.” “Being hurt?” “Being stupid.”—(W. Gibson: Mona Lisa Overdrive) PMID:19816094

  11. Implementation of Business Intelligence in An IT Organization - The Concept of An Evaluation Model

    Directory of Open Access Journals (Sweden)

    Sitek Tomasz

    2014-08-01

    Full Text Available This paper presents the issue of assessing the validity and effectiveness of implementing a Business Intelligence system in an IT Support Organization. This entity provides IT services to external clients involving, in particular, the storage and processing of large amounts of data. The vast amount of realized projects and also incidents reported in connection with those projects prevented effective decisions from being made without the support of dedicated technologies. The authors present the problems encountered by the studied entity and describe the tool that was selected to improve the situation. The aim of this study is to measure and describe the key processes in the organization on the basis of prepared aggregated measures, first prior to the implementation of the BI system and then a year after its implementation. The evaluation model developed by the authors allowed the assessment of the key aspects of the company’s operation over 2 years. It thus helped decision makers to establish whether the decision to implement the Business Intelligence system was correct or not.

  12. 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.

  13. Forensic intelligence applied to questioned document analysis: A model and its application against organized crime.

    Science.gov (United States)

    De Alcaraz-Fossoul, Josep; Roberts, Katherine A

    2017-07-01

    The capability of forensic sciences to fight crime, especially against organized criminal groups, becomes relevant in the recent economic downturn and the war on terrorism. In view of these societal challenges, the methods of combating crime should experience critical changes in order to improve the effectiveness and efficiency of the current resources available. It is obvious that authorities have serious difficulties combating criminal groups of transnational nature. These are characterized as well structured organizations with international connections, abundant financial resources and comprised of members with significant and diverse expertise. One common practice among organized criminal groups is the use of forged documents that allow for the commission of illegal cross-border activities. Law enforcement can target these movements to identify counterfeits and establish links between these groups. Information on document falsification can become relevant to generate forensic intelligence and to design new strategies against criminal activities of this nature and magnitude. This article discusses a methodology for improving the development of forensic intelligence in the discipline of questioned document analysis. More specifically, it focuses on document forgeries and falsification types used by criminal groups. It also describes the structure of international criminal organizations that use document counterfeits as means to conduct unlawful activities. The model presented is partially based on practical applications of the system that have resulted in satisfactory outcomes in our laboratory. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

  14. Historical milk production performance in São Paulo State municipalities between 2005 and 2015 using Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Patrícia de Freitas Pelozo

    2016-12-01

    Full Text Available This study analyzes the use of Artificial Intelligence on milk production chain, aiming at identifying patterns of their characteristics in 645 municipalities of the State of São Paulo taking into account produced milk categories. Using information from secondary sources, it was used the Optimum-Path Forest method (OPF to identify milk production characteristics clusters. The analyzed data were the amount of milk produced in the rural properties according to their categories regarding quality making possible to suggest training adequacies and public bodies actions regarding rural producers, more focused on the reality of each municipality and secondarily, it was possible to test the OPF use as a decision-making tool at the agroindustrial sector.

  15. A Production Model for Deteriorating Inventory Items with Production Disruptions

    OpenAIRE

    Yong He; Ju He

    2010-01-01

    Disruption management has recently become an active area of research. In this study, an extension is made to consider the fact that some products may deteriorate during storage. A production-inventory model for deteriorating items with production disruptions is developed. Then the optimal production and inventory plans are provided, so that the manufacturer can reduce the loss caused by disruptions. Finally, a numerical example is used to illustrate the model.

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

    International Nuclear Information System (INIS)

    Isa, Nor Ashidi Mat

    2015-01-01

    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

  17. 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

  18. 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

  19. Extending product modeling methods for integrated product development

    DEFF Research Database (Denmark)

    Bonev, Martin; Wörösch, Michael; Hauksdóttir, Dagný

    2013-01-01

    Despite great efforts within the modeling domain, the majority of methods often address the uncommon design situation of an original product development. However, studies illustrate that development tasks are predominantly related to redesigning, improving, and extending already existing products...... and PVM methods, in a presented Product Requirement Development model some of the individual drawbacks of each method could be overcome. Based on the UML standard, the model enables the representation of complex hierarchical relationships in a generic product model. At the same time it uses matrix....... Updated design requirements have then to be made explicit and mapped against the existing product architecture. In this paper, existing methods are adapted and extended through linking updated requirements to suitable product models. By combining several established modeling techniques, such as the DSM...

  20. Predicting adsorptive removal of chlorophenol from aqueous solution using artificial intelligence based modeling approaches.

    Science.gov (United States)

    Singh, Kunwar P; Gupta, Shikha; Ojha, Priyanka; Rai, Premanjali

    2013-04-01

    The research aims to develop artificial intelligence (AI)-based model to predict the adsorptive removal of 2-chlorophenol (CP) in aqueous solution by coconut shell carbon (CSC) using four operational variables (pH of solution, adsorbate concentration, temperature, and contact time), and to investigate their effects on the adsorption process. Accordingly, based on a factorial design, 640 batch experiments were conducted. Nonlinearities in experimental data were checked using Brock-Dechert-Scheimkman (BDS) statistics. Five nonlinear models were constructed to predict the adsorptive removal of CP in aqueous solution by CSC using four variables as input. Performances of the constructed models were evaluated and compared using statistical criteria. BDS statistics revealed strong nonlinearity in experimental data. Performance of all the models constructed here was satisfactory. Radial basis function network (RBFN) and multilayer perceptron network (MLPN) models performed better than generalized regression neural network, support vector machines, and gene expression programming models. Sensitivity analysis revealed that the contact time had highest effect on adsorption followed by the solution pH, temperature, and CP concentration. The study concluded that all the models constructed here were capable of capturing the nonlinearity in data. A better generalization and predictive performance of RBFN and MLPN models suggested that these can be used to predict the adsorption of CP in aqueous solution using CSC.

  1. Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

    Science.gov (United States)

    Krishnan, Govindarajapuram Subramaniam

    1997-12-01

    The National Aeronautics & Space Administration (NASA), the European Space Agency (ESA), and the Canadian Space Agency (CSA) missions involve the performance of scientific experiments in Space. Instruments used in such experiments are fabricated using electronic parts such as microcircuits, inductors, capacitors, diodes, transistors, etc. For instruments to perform reliably the selection of commercial parts must be monitored and strictly controlled. The process used to achieve this goal is by a manual review and approval of every part used to build the instrument. The present system to select and approve parts for space applications is manual, inefficient, inconsistent, slow and tedious, and very costly. In this dissertation a computer based decision support model is developed for implementing this process using artificial intelligence concepts based on the current information (expert sources). Such a model would result in a greater consistency, accuracy, and timeliness of evaluation. This study presents the methodology of development and features of the model, and the analysis of the data pertaining to the performance of the model in the field. The model was evaluated for three different part types by experts from three different space agencies. The results show that the model was more consistent than the manual evaluation for all part types considered. The study concludes with the cost and benefits analysis of implementing the models and shows that implementation of the model will result in significant cost savings. Other implementation details are highlighted.

  2. The relationship between employees’ emotional intelligence and their job satisfaction using structural equation model in one of the oil industries in Tehran

    Directory of Open Access Journals (Sweden)

    S. Dodangeh

    2016-04-01

      Conclusion: Emotional intelligence, as a psychological variable, affects the worker's job satisfaction. Considering the direct relationship between these two variables, by training and increasing the emotional intelligence of employees, job satisfaction and consequently their efficiency and productivity can be improved in the workplaces.

  3. Modelling of virtual production networks

    Directory of Open Access Journals (Sweden)

    2011-03-01

    Full Text Available Nowadays many companies, especially small and medium-sized enterprises (SMEs, specialize in a limited field of production. It requires forming virtual production networks of cooperating enterprises to manufacture better, faster and cheaper. Apart from that, some production orders cannot be realized, because there is not a company of sufficient production potential. In this case the virtual production networks of cooperating companies can realize these production orders. These networks have larger production capacity and many different resources. Therefore it can realize many more production orders together than each of them separately. Such organization allows for executing high quality product. The maintenance costs of production capacity and used resources are not so high. In this paper a methodology of rapid prototyping of virtual production networks is proposed. It allows to execute production orders on time considered existing logistic constraints.

  4. Recent Advances in Intelligent Engineering Systems

    CERN Document Server

    Klempous, Ryszard; Araujo, Carmen

    2012-01-01

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

  5. The contribution of competitive intelligence to the development of local productive settlements: case Jaú-SP

    Directory of Open Access Journals (Sweden)

    Wanda A. M. Hoffmann

    2004-01-01

    Full Text Available The current economical context has been provoking the largest exhibition of the Brazilian companies to the international competition, imposing challenges and opportunities. The Brazilian small and medium enterprises, SME’s, they are the most vulnerable given the shortage of resources and production costs, among other aspects. The local productive settlements or clusters are important manners of organization of the production of SMEs. Those production manners are considered vital in the employment generation and income to the country. The characteristics of those settlements that measure your dynamics and growth are important themes of research in several areas and countries, for the economical and social importance, thoroughly spread the last years for researchers and entities. The present study approaches the contribution of the competitive intelligence for the clusters improvements. In that context the dynamics of local productive settlements and your technological difficulties and of administration they are identified focalizing the segment of foot-wears and leathers of Jaú in the State of São Paulo. Several aspects are approached in relation to dynamics of that local productive settlement, through your comparative analysis with international settlements, especially Italian. Indicating signs of a typical strategy of industrial clusters, shown by the synergy obtained by the interactivity of change of information intra-cluster and the effort in increasing your competitive capacity.

  6. Intelligent Tutor

    Science.gov (United States)

    1990-01-01

    NASA also seeks to advance American education by employing the technology utilization process to develop a computerized, artificial intelligence-based Intelligent Tutoring System (ITS) to help high school and college physics students. The tutoring system is designed for use with the lecture and laboratory portions of a typical physics instructional program. Its importance lies in its ability to observe continually as a student develops problem solutions and to intervene when appropriate with assistance specifically directed at the student's difficulty and tailored to his skill level and learning style. ITS originated as a project of the Johnson Space Center (JSC). It is being developed by JSC's Software Technology Branch in cooperation with Dr. R. Bowen Loftin at the University of Houston-Downtown. Program is jointly sponsored by NASA and ACOT (Apple Classrooms of Tomorrow). Other organizations providing support include Texas Higher Education Coordinating Board, the National Research Council, Pennzoil Products Company and the George R. Brown Foundation. The Physics I class of Clear Creek High School, League City, Texas are providing the classroom environment for test and evaluation of the system. The ITS is a spinoff product developed earlier to integrate artificial intelligence into training/tutoring systems for NASA astronauts flight controllers and engineers.

  7. A procedure for Building Product Models

    DEFF Research Database (Denmark)

    Hvam, Lars

    1999-01-01

    , easily adaptable concepts and methods from data modeling (object oriented analysis) and domain modeling (product modeling). The concepts are general and can be used for modeling all types of specifications in the different phases in the product life cycle. The modeling techniques presented have been......The application of product modeling in manufacturing companies raises the important question of how to model product knowledge in a comprehensible and efficient way. An important challenge is to qualify engineers to model and specify IT-systems (product models) to support their specification...... activities. A basic assumption is that engineers have to take the responsability for building product models to be used in their domain. To do that they must be able to carry out the modeling task on their own without any need for support from computer science experts. This paper presents a set of simple...

  8. A Quasiphysics Intelligent Model for a Long Range Fast Tool Servo

    Science.gov (United States)

    Liu, Qiang; Zhou, Xiaoqin; Lin, Jieqiong; Xu, Pengzi; Zhu, Zhiwei

    2013-01-01

    Accurately modeling the dynamic behaviors of fast tool servo (FTS) is one of the key issues in the ultraprecision positioning of the cutting tool. Herein, a quasiphysics intelligent model (QPIM) integrating a linear physics model (LPM) and a radial basis function (RBF) based neural model (NM) is developed to accurately describe the dynamic behaviors of a voice coil motor (VCM) actuated long range fast tool servo (LFTS). To identify the parameters of the LPM, a novel Opposition-based Self-adaptive Replacement Differential Evolution (OSaRDE) algorithm is proposed which has been proved to have a faster convergence mechanism without compromising with the quality of solution and outperform than similar evolution algorithms taken for consideration. The modeling errors of the LPM and the QPIM are investigated by experiments. The modeling error of the LPM presents an obvious trend component which is about ±1.15% of the full span range verifying the efficiency of the proposed OSaRDE algorithm for system identification. As for the QPIM, the trend component in the residual error of LPM can be well suppressed, and the error of the QPIM maintains noise level. All the results verify the efficiency and superiority of the proposed modeling and identification approaches. PMID:24163627

  9. A Causal Model of Faculty Research Productivity.

    Science.gov (United States)

    Bean, John P.

    A causal model of faculty research productivity was developed through a survey of the literature. Models of organizational behavior, organizational effectiveness, and motivation were synthesized into a causal model of productivity. Two general types of variables were assumed to affect individual research productivity: institutional variables and…

  10. Efficient drilling problem detection. Early fault detection by the combination of physical models and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Nyboe, Roar

    2009-09-15

    The drilling of an oil or gas well is an expensive undertaking. Hence, it is not surprising that mistakes and accidents during drilling incur a high cost. Accidents could result in the loss of expensive equipment and subsequent delays setting back the operation for days or weeks and thus running up large bills on rig-time and personnel hours. Some types of accidents also pose a risk to the personnel or the environment. In this dissertation we study alarm systems which could give the driller an early warning of upcoming problems, and thus provide time to avoid these accidents. We explore alarm systems which combine advanced physical models of the well and drilling process with artificial intelligence and time series analysis. Finally, we determine the advantages as well as the challenges of this approach. It is our hope that this dissertation is accessible to both practitioners in machine learning and control engineering, as well as to petroleum engineers with a passing familiarity with machine learning. Hence this dissertation starts with a quick introduction to drilling problems and some terms from time series analysis and machine learning. We then briefly describe the theory of observer-based fault detection and isolation. Theories of supervisory control systems are also introduced, as these concern both the choice of algorithms and how AI-based alarm systems integrate with the rest of the operation. From chapter 6 and onward, the challenges to fault detection in drilling are discussed. We focus on clarifying what restrictions the available training data put on our choice of machine learning methods. In chapter 8 and 9, we propose ways to combine machine learning and observer-based fault detection. Experimental results are presented in chapter 10, before we end with concluding remarks in chapter 11. Our main conclusion, reflected in our experimental results, is that physical models and artificial intelligence can be combined to produce hybrid alarm systems that

  11. 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.

  12. 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

  13. Improving the All-Hazards Homeland Security Enterprise Through the Use of an Emergency Management Intelligence Model

    Science.gov (United States)

    2013-09-01

    OSINT Open Source Intelligence PPD Presidential Policy Directive SIGINT Signals Intelligence SLFC State/Local Fusion...Geospatial Intelligence (GEOINT) from Geographic Information Systems (GIS), and Open Source Intelligence ( OSINT ) from Social Media. GIS is widely...Central Intelligence Agency is the federal agency most often associated with HUMINT collection. • Open - Source Intelligence ( OSINT )– OSINT

  14. Alignment of Product Models and Product State Models - Integration of the Product Lifecycle Phases

    DEFF Research Database (Denmark)

    Larsen, Michael Holm; Kirkby, Lars Phillip; Vesterager, Johan

    1999-01-01

    The purpose of this paper is to discuss the integration of the Product Model (PM) and the Product State Model (PCM). Focus is on information exchange from the PSM to the PM within the manufacturing of a single ship. The paper distinguishes between information and knowledge integration. The paper ...... provides some overall strategies for integrating PM and PSM. The context of this discussion is a development project at Odense Steel Shipyard....

  15. Intelligent Production Monitoring and Control based on Three Main Modules for Automated Manufacturing Cells in the Automotive Industry

    International Nuclear Information System (INIS)

    Berger, Ulrich; Kretzschmann, Ralf; Algebra, A. Vargas Veronica

    2008-01-01

    The automotive industry is distinguished by regionalization and customization of products. As consequence, the diversity of products will increase while the lot sizes will decrease. Thus, more product types will be handled along the process chain and common production paradigms will fail. Although Rapid Manufacturing (RM) methodology will be used for producing small individual lot sizes, new solution for joining and assembling these components are needed. On the other hand, the non-availability of existing operational knowledge and the absence of dynamic and explicit knowledge retrieval minimize the achievement of on-demand capabilities. Thus, in this paper, an approach for an Intelligent Production System will be introduced. The concept is based on three interlinked main modules: a Technology Data Catalogue (TDC) based on an ontology system, an Automated Scheduling Processor (ASP) based on graph theory and a central Programmable Automation Controller (PAC) for real-time sensor/actor communication. The concept is being implemented in a laboratory set-up with several assembly and joining processes and will be experimentally validated in some research and development projects

  16. 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

  17. Strategic Management Model with Lens of Knowledge Management and Competitive Intelligence: A Review Approach

    OpenAIRE

    Shujahat, Muhammad; Hussain, Saddam; Javed, Sammar; Muhammad, Imran Malik; Thursamy, Ramayah; Ali, Junaid

    2017-01-01

    Purpose:\\ud First purpose of this study is to discuss the synergic and separate use of knowledge and\\ud intelligence, via knowledge management and competitive intelligence, in each stage of strategic\\ud management process. Second purpose is to discuss the implications of each stage of strategic\\ud management process for knowledge management and competitive intelligence and vice versa.\\ud Methodology/Design/Approach:\\ud A systematic literature review was performed within timeframe of 2000 to 2...

  18. Application of Structural Equations Modeling to assess relationship among Emotional Intelligence, General Health and Occupational Accidents

    OpenAIRE

    MOAMMAD KHANDAN; AMIR KAVOUSI; ALIREZA KOOHPAEI

    2015-01-01

    ORIGINAL ARTICLEEmotional intelligence (EI) has been subject of significant amounts of literature over the past two decades. However, little has been contributed to how emotional intelligence may be practically applied to enhance both accident prevention program and general health in workplaces. Purpose of this paper is to survey relationship among these variables in working society of Iran in 2014. As well as identify practical approaches to application of emotional intelligence skills to ma...

  19. Social intelligence, human intelligence and niche construction.

    Science.gov (United States)

    Sterelny, Kim

    2007-04-29

    This paper is about the evolution of hominin intelligence. I agree with defenders of the social intelligence hypothesis in thinking that externalist models of hominin intelligence are not plausible: such models cannot explain the unique cognition and cooperation explosion in our lineage, for changes in the external environment (e.g. increasing environmental unpredictability) affect many lineages. Both the social intelligence hypothesis and the social intelligence-ecological complexity hybrid I outline here are niche construction models. Hominin evolution is hominin response to selective environments that earlier hominins have made. In contrast to social intelligence models, I argue that hominins have both created and responded to a unique foraging mode; a mode that is both social in itself and which has further effects on hominin social environments. In contrast to some social intelligence models, on this view, hominin encounters with their ecological environments continue to have profound selective effects. However, though the ecological environment selects, it does not select on its own. Accidents and their consequences, differential success and failure, result from the combination of the ecological environment an agent faces and the social features that enhance some opportunities and suppress others and that exacerbate some dangers and lessen others. Individuals do not face the ecological filters on their environment alone, but with others, and with the technology, information and misinformation that their social world provides.

  20. 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. © 2016 by the Society for Personality and Social Psychology, Inc.

  1. 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.

  2. Learning How to Construct Models of Dynamic Systems: An Initial Evaluation of the Dragoon Intelligent Tutoring System

    Science.gov (United States)

    VanLehn, Kurt; Wetzel, Jon; Grover, Sachin; van de Sande, Brett

    2017-01-01

    Constructing models of dynamic systems is an important skill in both mathematics and science instruction. However, it has proved difficult to teach. Dragoon is an intelligent tutoring system intended to quickly and effectively teach this important skill. This paper describes Dragoon and an evaluation of it. The evaluation randomly assigned…

  3. 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…

  4. Intelligible genders in scene: the cinema and the truth production about bodies

    Directory of Open Access Journals (Sweden)

    Luciene Galvão

    2014-06-01

    Full Text Available This paper aims to discuss how cinematographic language produces truths about men and women. Throughout the text, we have used to illustrate some iconic films that bring notions of masculinity and femininity. The film we have chosen are works that have a distinct esthetic and markets, they are able to raise issues related to gender and sexuality in discussions against romantic love, identity, homosexuality, violence and techniques confession of truths, among others. We analyze the films from Michel Foucault perspective concern sexuality and power relations and Judith Butler about gender intelligible. The plots of the films show that such truths are constantly negotiated and further indicate that norms about sex, desire, pleasure, masculinity and femininity are not only reproduced as its effects on private plots do not end with the end of the film.

  5. 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.

  6. Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

    International Nuclear Information System (INIS)

    Ahmadi, Rouhollah; Khamehchi, Ehsan

    2013-01-01

    Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks and fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data

  7. Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models.

    Science.gov (United States)

    Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Abdullah, Sharifah Mastura Syed; El-Shafie, Ahmed

    2018-05-01

    Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.

  8. Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

    Energy Technology Data Exchange (ETDEWEB)

    Ahmadi, Rouhollah, E-mail: rouhollahahmadi@yahoo.com [Amirkabir University of Technology, PhD Student at Reservoir Engineering, Department of Petroleum Engineering (Iran, Islamic Republic of); Khamehchi, Ehsan [Amirkabir University of Technology, Faculty of Petroleum Engineering (Iran, Islamic Republic of)

    2013-12-15

    Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks and fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data.

  9. 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.

  10. The Impact of Contextual Background Fusion on Perceived Value and Quality of Unclassified Terrorism Intelligence

    National Research Council Canada - National Science Library

    Eaneff, Charles

    2007-01-01

    ...). Simply pushing intelligence products to NTR is not enough, NTR must possess adequate contextual background in order to effectively utilize intelligence provided by the Intelligence Community (IC...

  11. Calculating the Contribution Rate of Intelligent Transportation System in Improving Urban Traffic Smooth Based on Advanced DID Model

    Directory of Open Access Journals (Sweden)

    Ming-wei Li

    2015-01-01

    Full Text Available Recent years have witnessed the rapid development of intelligent transportation system around the world, which helps to relieve urban traffic congestion problems. For instance, many mega-cities in China have devoted a large amount of money and resources to the development of intelligent transportation system. This poses an intriguing and important issue: how to measure and quantify the contribution of intelligent transportation system to the urban city, which is still a puzzle. This paper proposes a matching difference-in-difference model to calculate the contribution rate of intelligent transportation system on traffic smoothness. Within the model, the main effect indicators of traffic smoothness are first identified, and then the evaluation index system is built, and finally the ideas of the matching pool are introduced. The proposed model is illustrated in Guangzhou, China (capital city of Guangdong province. The results show that introduction of ITS contributes 9.25% to the improvement of traffic smooth in Guangzhou. Also, the research explains the working mechanism of how ITS improves urban traffic smooth. Eventually, some strategy recommendations are put forward to improve urban traffic smooth.

  12. Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: methodology and preliminary report.

    Science.gov (United States)

    Fu, Jicheng; Jones, Maria; Jan, Yih-Kuen

    2014-01-01

    Wheelchair tilt and recline functions are two of the most desirable features for relieving seating pressure to decrease the risk of pressure ulcers. The effective guidance on wheelchair tilt and recline usage is therefore critical to pressure ulcer prevention. The aim of this study was to demonstrate the feasibility of using machine learning techniques to construct an intelligent model to provide personalized guidance to individuals with spinal cord injury (SCI). The motivation stems from the clinical evidence that the requirements of individuals vary greatly and that no universal guidance on tilt and recline usage could possibly satisfy all individuals with SCI. We explored all aspects involved in constructing the intelligent model and proposed approaches tailored to suit the characteristics of this preliminary study, such as the way of modeling research participants, using machine learning techniques to construct the intelligent model, and evaluating the performance of the intelligent model. We further improved the intelligent model's prediction accuracy by developing a two-phase feature selection algorithm to identify important attributes. Experimental results demonstrated that our approaches held the promise: they could effectively construct the intelligent model, evaluate its performance, and refine the participant model so that the intelligent model's prediction accuracy was significantly improved.

  13. A procedure for building product models

    DEFF Research Database (Denmark)

    Hvam, Lars; Riis, Jesper; Malis, Martin

    2001-01-01

    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, which are to be supported...... with 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 using object oriented modelling. The procedure is developed in order to ensure that the product models constructed are fit...... for the business processes they support, and properly structured and documented, in order to facilitate that the systems can be maintained continually and further developed. The research has been carried out at the Centre for Industrialisation of Engineering, Department of Manufacturing Engineering, Technical...

  14. The prediction of intelligence in preschool children using alternative models to regression.

    Science.gov (United States)

    Finch, W Holmes; Chang, Mei; Davis, Andrew S; Holden, Jocelyn E; Rothlisberg, Barbara A; McIntosh, David E

    2011-12-01

    Statistical prediction of an outcome variable using multiple independent variables is a common practice in the social and behavioral sciences. For example, neuropsychologists are sometimes called upon to provide predictions of preinjury cognitive functioning for individuals who have suffered a traumatic brain injury. Typically, these predictions are made using standard multiple linear regression models with several demographic variables (e.g., gender, ethnicity, education level) as predictors. Prior research has shown conflicting evidence regarding the ability of such models to provide accurate predictions of outcome variables such as full-scale intelligence (FSIQ) test scores. The present study had two goals: (1) to demonstrate the utility of a set of alternative prediction methods that have been applied extensively in the natural sciences and business but have not been frequently explored in the social sciences and (2) to develop models that can be used to predict premorbid cognitive functioning in preschool children. Predictions of Stanford-Binet 5 FSIQ scores for preschool-aged children is used to compare the performance of a multiple regression model with several of these alternative methods. Results demonstrate that classification and regression trees provided more accurate predictions of FSIQ scores than does the more traditional regression approach. Implications of these results are discussed.

  15. 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…

  16. On production costs in vertical differentiation models

    OpenAIRE

    Dorothée Brécard

    2009-01-01

    In this paper, we analyse the effects of the introduction of a unit production cost beside a fixed cost of quality improvement in a duopoly model of vertical product differentiation. Thanks to an original methodology, we show that a low unit cost tends to reduce product differentiation and thus prices, whereas a high unit cost leads to widen product differentiation and to increase prices

  17. An Optimization Model for Product Placement on Product Listing Pages

    Directory of Open Access Journals (Sweden)

    Yan-Kwang Chen

    2014-01-01

    Full Text Available The design of product listing pages is a key component of Website design because it has significant influence on the sales volume on a Website. This study focuses on product placement in designing product listing pages. Product placement concerns how venders of online stores place their products over the product listing pages for maximization of profit. This problem is very similar to the offline shelf management problem. Since product information sources on a Web page are typically communicated through the text and image, visual stimuli such as color, shape, size, and spatial arrangement often have an effect on the visual attention of online shoppers and, in turn, influence their eventual purchase decisions. In view of the above, this study synthesizes the visual attention literature and theory of shelf-space allocation to develop a mathematical programming model with genetic algorithms for finding optimal solutions to the focused issue. The validity of the model is illustrated with example problems.

  18. Proactive Modeling of Market, Product and Production Architectures

    DEFF Research Database (Denmark)

    Mortensen, Niels Henrik; Hansen, Christian Lindschou; Hvam, Lars

    2011-01-01

    This paper presents an operational model that allows description of market, products and production architectures. The main feature of this model is the ability to describe both structural and functional aspect of architectures. The structural aspect is an answer to the question: What constitutes...... the architecture, e.g. standard designs, design units and interfaces? The functional aspect is an answer to the question: What is the behaviour or the architecture, what is it able to do, i.e. which products at which performance levels can be derived from the architecture? Among the most important benefits...... of this model is the explicit ability to describe what the architecture is prepared for, and what it is not prepared for - concerning development of future derivative products. The model has been applied in a large scale global product development project. Among the most important benefits is contribution to...

  19. 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

  20. MASS CUSTOMIZATION and PRODUCT MODELS

    DEFF Research Database (Denmark)

    Svensson, Carsten; Malis, Martin

    2003-01-01

    to the product. Through the application of a mass customization strategy, companies have a unique opportunity to create increased customer satisfaction. In a customized production, knowledge and information have to be easily accessible since every product is a unique combination of information. If the dream...... of a customized alternative instead of a uniform mass-produced product shall become a reality, then the cross-organizational efficiency must be kept at a competitive level. This is the real challenge for mass customization. A radical restructuring of both the internal and the external knowledge management systems...

  1. Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

    International Nuclear Information System (INIS)

    Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; Tagina, M

    2017-01-01

    Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach. (paper)

  2. An ecosystem of products and systems for ambient intelligence - the AAL4ALL users perspective.

    Science.gov (United States)

    Sousa, Filipe; Viola, Lara; Ferreira, Liliana; Trevisan, Gabriela; Cunha, David; Alves, José; Simões, Ricardo

    2012-01-01

    Developed societies are currently facing severe demographic changes: the world is getting older at an unprecedented rate. In 2000, about 420 million people, or approximately 7 percent of the world population, were aged 65 or older. By 2050, that number will be nearly 1.5 billion people, about 16 percent of the world population. This demographic trend will be also followed by an increase of people with physical limitations. The traditional health care systems, not only in Portugal, but also in all other European states, will be faced with new challenges. There is an urgent need to find solutions that allow extending the time people can live in their preferred environment by increasing their autonomy, self-confidence and mobility. AAL4ALL presents an idea for an answer through the development of an ecosystem of products and services for Ambient Assisted Living (AAL) associated to a business model and validated through large scale trial. This paper presents the results of the first survey developed within the AAL4ALL project: the users' survey targeted at the Portuguese seniors and pre-seniors. In this way, this paper addresses the lives of the Portuguese population aged 50 and over.

  3. Intelligent uranium fission converter for neutron production on the periphery of the nuclear reactor core (MARIA reactor in Swierk - Poland)

    Energy Technology Data Exchange (ETDEWEB)

    Gryzinski, M.A.; Wielgosz, M. [National Centre for Nuclear Research, Andrzeja Soltana 7, 05-400 Otwock-Swierk (Poland)

    2015-07-01

    The multipurpose, high flux research reactor MARIA in Otwock - Swierk is an open-pool type, water and beryllium moderated and graphite reflected. There are two not occupied experimental H1 and H2 horizontal channels with complex of empty rooms beside them. Making use of these two channels is not in conflict with other research or commercial employing channels. They can work simultaneously, moreover commercial channels covers the cost of reactor working. Such conditions give beneficial possibility of creating epithermal neutron stand for researches in various field at the horizontal channel H2 of MARIA reactor (co-organization of research at H1 channel is additionally planned). At the front of experimental channels the neutron flux is strongly thermalized - neutrons with energies above 0.625 eV constitute only ∼2% of the total flux. This thermalized neutron flux will be used to achieve high flux of epithermal neutrons at the level of 2x10{sup 9} n cm{sup -2}s{sup -1} by uranium neutron converter (fast neutron production - conversion of reactor core thermal neutrons to fast neutrons - and then filtering, moderating and finally cutting of unwanted gamma radiation). The intelligent converter will be placed in the reactor pool, near the front of the H2 channel. It will replace one graphite block at the periphery of MARIA graphite reflector. The converter will consist of 20 fuel elements - low enriched uranium plates. A fuel plate will be a part which will measure 110 mm wide by 380 mm long and will consist of a thin layer of uranium sealed between two aluminium plates. These plates, once assembled, form the fuel element used in converter. The plates will be positioned vertically. There are several important requirements which should be taken into account at the converter design stage: -maximum efficiency of the converter for neutrons conversion, -cooling of the converter need to be integrated with the cooling circuit of the reactor pool and if needed equipped with

  4. Modeling dependencies in product families with COVAMOF

    NARCIS (Netherlands)

    Sinnema, Marco; Deelstra, Sybren; Nijhuis, Jos; Bosch, Jan; Riebisch, M; Tabeling, P; Zorn, W

    2006-01-01

    Many variability modeling approaches consider only formalized dependencies, i.e. in- or exclude relations between variants. However, in real industrial product families, dependencies are often much more complicated. In this paper, we discuss the product derivation problems associated with

  5. BOREAS TE-17 Production Efficiency Model Images

    Data.gov (United States)

    National Aeronautics and Space Administration — A BOREAS version of the Global Production Efficiency Model(www.inform.umd.edu/glopem) was developed by TE-17 to generate maps of gross and net primary production,...

  6. 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

  7. 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.

  8. Modelling Product Families for Product Configuration Systems with Product Variant Master

    DEFF Research Database (Denmark)

    Mortensen, Niels Henrik; Hvam, Lars; Haug, Anders

    2010-01-01

    This article presents an evaluation of applying a suggested method for modelling product families for product configuration based on theory for modelling mechanical products,systems theory and object-oriented modelling. The modelling technique includes a so-called product variant master and CRC-cards...... the three views. Modelling of characteristics of the product variants in a product family Modelling of constraints between parts in the product family Visualisation of the entire product family on a poster e.g. 1x2 meters The product variant master and CRC-cards are means to bridge the gap between domain...... experts and IT-developers, thus making it possible for the domain experts (e.g. engineers from product development) to express their knowledge in a form that is understandable both for the domain experts and the IT-developers. The product variant master and CRC-cards have currently been tested and further...

  9. The Comparison of Think Talk Write and Think Pair Share Model with Realistic Mathematics Education Approach Viewed from Mathematical-Logical Intelligence

    Directory of Open Access Journals (Sweden)

    Himmatul Afthina

    2017-12-01

    Full Text Available The aims of this research to determine the effect of Think Talk Write (TTW and Think Pair Share (TPS model with Realistic Mathematics Education (RME approach viewed from mathematical-logical intelligence. This research employed the quasi experimental research. The population of research was all students of the eight graders of junior high school in Karangamyar Regency in academic year 2016/2017. The result of this research shows that (1 TTW with RME approach gave better mathematics achievement than TPS with RME approach, (2 Students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one, (3 In TTW model with RME approach, students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low, whereas students with average and low mathematical-logical intelligence gave same mathematics achievement, and  in TPS model with RME approach students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one (4 In each category of  mathematical-logical intelligence, TTW with RME approach and TPS with RME approach gave same mathematics achievement.

  10. CRC-cards for Product Modelling

    DEFF Research Database (Denmark)

    Hvam, Lars; Riis, Jesper; Hansen, Benjamin Loer

    2003-01-01

    , transportation, service and decommissioning. A main challenge when building product models is to collect and document the product related data, information and knowledge in a structured way. CRC cards are index cards (or computerized versions of these) which are used to record proposed classes, the behavior......This paper describes the CRC (class, responsibility, collaboration) modelling process for building product models. A product model is normally represented in an IT system which contains data, information and knowledge on industrial products and their life cycle properties e.g. manufacturing...... of the classes, their responsibilities, and their relationship to other classes (collaboration). CRC modelling gives an effective, low-tech method for domain-experts, programmers and users to work closely together to identify, structure, understand and document a product model. CRC cards were originally...

  11. Description, Modelling and Design of Production Systems

    DEFF Research Database (Denmark)

    Jacobsen, Peter; Rudolph, Carsten

    1997-01-01

    Design of production systems are rarely an activity in which decision makers in most production companies have much experience. In future, this activity is to be more recurrent due to more and more frequent changes in the production task. Consequently, the decision makers are in need of better...... management tools and methods for description and modelling of production systems supporting the decisions. In this article a structural framework to describe and model production systems will be introduced, and it is shown how the production system of a minor Danish manufacturer of electromechanical...

  12. Roadmap for a Smart Factory: A Modular, Intelligent Concept for the Production of Specialty Chemicals.

    Science.gov (United States)

    Reitze, Arnulf; Jürgensmeyer, Nikolas; Lier, Stefan; Kohnke, Marco; Riese, Julia; Grünewald, Marcus

    2018-04-09

    Digitalization and increasing the flexibility of production concepts offer the possibility to react to market challenges in the field of specialty chemicals. Shorter product lifetimes, increasing product individualization, and the resulting market volatility impose new requirements on plant operators. Novel concepts such as modular production plants and developments in digitalization (Industry 4.0) are able to assist the implementation of smart factories in specialty chemicals. These essential concepts will be presented in this Minireview. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. A review of forecasting models for new products

    Directory of Open Access Journals (Sweden)

    Marta Mas-Machuca

    2014-02-01

    Full Text Available Purpose. The main objective of this article is to present an up-to-date review of new product forecasting techniques. Design/methodology/approach: A systematic review of forecasting journals was carried out using the ISI-Web of Knowledge database. Several articles were retrieved and examined, and forecasting techniques relevant to this study were selected and assessed. Findings: The strengths, weaknesses and applications of the main forecasting models are discussed to examine trends and set future challenges. Research limitations/implications: A theoretical reference framework for forecasting techniques classified into judgmental, consumer/market research, cause-effect and artificial intelligence is proposed. Future research can assess these models qualitatively. Practical implications: Companies are currently motivated to launch new products and thus attract new customers to expand their market share.  In order to reduce uncertainty and risk, many companies go to extra lengths to forecast sales accurately using several techniques. Originality/value: This article outlines new lines of research on the improvement of new product performance which will aid managers in decision making and allow companies to sustain their competitive advantages in this challenging world.

  14. Multiple Intelligences in Action.

    Science.gov (United States)

    Campbell, Bruce

    1992-01-01

    Describes the investigation of the effects of a four-step model program used with third through fifth grade students to implement Gardener's concepts of seven human intelligences--linguistic, logical/mathematical, visual/spatial, musical, kinesthetic, intrapersonal, and interpersonal intelligence--into daily learning. (BB)

  15. NEPHRUS: model of intelligent multilayers expert system for evaluation of the renal system based on scintigraphic images analysis

    International Nuclear Information System (INIS)

    Silva, Jose W.E. da; Schirru, Roberto; Boasquevisque, Edson M.

    1997-01-01

    This work develops a prototype for the system model based on Artificial Intelligence devices able to perform functions related to scintigraphic image analysis of the urinary system. Criteria used by medical experts for analysis images obtained with 99m Tc+DTPA and/or 99m Tc+DMSA were modeled and a multi resolution diagnosis technique was implemented. Special attention was given to the programs user interface design. Human Factor Engineering techniques were considered so as to ally friendliness and robustness. Results obtained using Artificial Neural Networks for the qualitative image analysis and the knowledge model constructed shows the feasibility of Artificial Intelligence implementation that use 'inherent' abilities of each technique in the resolution of diagnosis image analysis problems. (author). 12 refs., 2 figs., 2 tabs

  16. Artificial Intelligence and Moral intelligence

    OpenAIRE

    Laura Pana

    2008-01-01

    We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

  17. 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.

  18. A grand model for chemical product design

    DEFF Research Database (Denmark)

    Fung, Ka Y.; Ng, Ka M.; Zhang, Lei

    2016-01-01

    , a pricing model, an economic model as well as factors such as company strategy, government policies and regulations. This article introduces the model and highlights selected aspects of the model with two case studies. One is a die attach adhesive that illustrates how pricing affects profitability, and how...... product composition changes with market conditions. Another is a hand lotion that illustrates how product quality affects the profit.(C) 2016 Elsevier Ltd. All rights reserved....

  19. 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)

  20. 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.

  1. 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.

  2. Domestic Intelligence in the United Kingdom: Applicability of the MI-5 Model to the United States

    National Research Council Canada - National Science Library

    Masse, Todd

    2003-01-01

    .... One potential remedy that has been suggested in response to the events of September 11, 2001 is the establishment of a domestic intelligence agency akin to the British Security Service, also known as MI5...

  3. Classification hierarchies for product data modelling

    NARCIS (Netherlands)

    Pels, H.J.

    2006-01-01

    Abstraction is an essential element in data modelling that appears mainly in one of the following forms: generalisation, classification or aggregation. In the design of complex products classification hierarchies can be found product families that are viewed as classes of product types, while

  4. 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....

  5. Marketing Modeling for New Products

    NARCIS (Netherlands)

    C. Hernández-Mireles (Carlos)

    2010-01-01

    textabstractThis thesis addresses the analysis of new or very recent marketing data and the introduction of new marketing models. We present a collection of models that are useful to analyze (1) the optimal launch time of new and dominant technologies, (2) the triggers, speed and timing of new

  6. Structural equation modeling in the genetically informative study of the covariation of intelligence, working memory and planning

    Directory of Open Access Journals (Sweden)

    Voronin I.

    2016-01-01

    Full Text Available Structural equation modelling (SEM has become an important tool in behaviour genetic research. The application of SEM for multivariate twin analysis allows revealing the structure of genetic and environmental factors underlying individual differences in human traits. We outline the framework of twin method and SEM, describe SEM implementation of a multivariate twin model and provide an example of a multivariate twin study. The study included 901 adolescent twin pairs from Russia. We measured general cognitive ability and characteristics of working memory and planning. The individual differences in working memory and planning were explained mostly by person-specific environment. The variability of intelligence is related to genes, family environment, and person specific environment. Moderate and weak associations between intelligence, working memory, and planning were entirely explained by shared environmental effects.

  7. Sustainable Technology Analysis of Artificial Intelligence Using Bayesian and Social Network Models

    Directory of Open Access Journals (Sweden)

    Juhwan Kim

    2018-01-01

    Full Text Available Recent developments in artificial intelligence (AI have led to a significant increase in the use of AI technologies. Many experts are researching and developing AI technologies in their respective fields, often submitting papers and patent applications as a result. In particular, owing to the characteristics of the patent system that is used to protect the exclusive rights to registered technology, patent documents contain detailed information on the developed technology. Therefore, in this study, we propose a statistical method for analyzing patent data on AI technology to improve our understanding of sustainable technology in the field of AI. We collect patent documents that are related to AI technology, and then analyze the patent data to identify sustainable AI technology. In our analysis, we develop a statistical method that combines social network analysis and Bayesian modeling. Based on the results of the proposed method, we provide a technological structure that can be applied to understand the sustainability of AI technology. To show how the proposed method can be applied to a practical problem, we apply the technological structure to a case study in order to analyze sustainable AI technology.

  8. The Fusion Model of Intelligent Transportation Systems Based on the Urban Traffic Ontology

    Science.gov (United States)

    Yang, Wang-Dong; Wang, Tao

    On these issues unified representation of urban transport information using urban transport ontology, it defines the statute and the algebraic operations of semantic fusion in ontology level in order to achieve the fusion of urban traffic information in the semantic completeness and consistency. Thus this paper takes advantage of the semantic completeness of the ontology to build urban traffic ontology model with which we resolve the problems as ontology mergence and equivalence verification in semantic fusion of traffic information integration. Information integration in urban transport can increase the function of semantic fusion, and reduce the amount of data integration of urban traffic information as well enhance the efficiency and integrity of traffic information query for the help, through the practical application of intelligent traffic information integration platform of Changde city, the paper has practically proved that the semantic fusion based on ontology increases the effect and efficiency of the urban traffic information integration, reduces the storage quantity, and improve query efficiency and information completeness.

  9. Do narcissism and emotional intelligence win us friends? : modeling dynamics of peer popularity using inferential network analysis

    OpenAIRE

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

    2016-01-01

    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...

  10. An Integral Model to Provide Reactive and Proactive Services in an Academic CSIRT Based on Business Intelligence

    OpenAIRE

    Walter Fuertes; Francisco Reyes; Paúl Valladares; Freddy Tapia; Theofilos Toulkeridis; Ernesto Pérez

    2017-01-01

    Cyber-attacks have increased in severity and complexity. That requires, that the CERT/CSIRT research and develops new security tools. Therefore, our study focuses on the design of an integral model based on Business Intelligence (BI), which provides reactive and proactive services in a CSIRT, in order to alert and reduce any suspicious or malicious activity on information systems and data networks. To achieve this purpose, a solution has been assembled, that generates information stores, bein...

  11. The intelligent customer: considerations around build-own-operate business and licensing models for small modular reactors in Canada

    International Nuclear Information System (INIS)

    Jones, K.

    2014-01-01

    An organization planning a proposal for a build-own-operate business model needs to address expanded licensee responsibilities under this model, associated regulatory impacts and how this affects their role as an 'intelligent customer'. This is particularly important for cases where builder-owner-operators plan to manufacture factory-fuelled designs and ship them to a site for installation and operation. The primary responsibility for safe conduct of licensed activities rests with the licensee. A build-own-operate model expands the scope of licensed activities to include design, manufacturing, transport, construction, and operation. The licensee must be able to demonstrate they are qualified to conduct all licensed activities including sufficient competent resources within the licensee's organization to oversee('Intelligent Customer') any work it commissions externally and the subsequent flow down through of the supply chain. This paper examines aspects that organizations need to assess the suitability of approaches that it may take to maintain in-house expertise for the control and oversight of licensed activities at all times. It considers the approach to identification of: core capabilities the licensee would need to understand its safety case under a build-own-operate model to manage licensed activities in accordance with requirements under the Nuclear Safety and Control Acta licensee's 'intelligent customer' capabilities in particular around understanding, specifying, overseeing and accepting work undertaken on its behalf by contractors. While this paper is focused on small modular reactors, being an intelligent customer applies to large commercial or research reactors equally; the size of reactor is immaterial.

  12. The intelligent customer: considerations around build-own-operate business and licensing models for small modular reactors in Canada

    Energy Technology Data Exchange (ETDEWEB)

    Jones, K., E-mail: kenneth.jones@cnsc-ccsn.gc.ca [Canadian Nuclear Safety Commission, Ottawa, Ontario (Canada)

    2014-07-01

    An organization planning a proposal for a build-own-operate business model needs to address expanded licensee responsibilities under this model, associated regulatory impacts and how this affects their role as an 'intelligent customer'. This is particularly important for cases where builder-owner-operators plan to manufacture factory-fuelled designs and ship them to a site for installation and operation. The primary responsibility for safe conduct of licensed activities rests with the licensee. A build-own-operate model expands the scope of licensed activities to include design, manufacturing, transport, construction, and operation. The licensee must be able to demonstrate they are qualified to conduct all licensed activities including sufficient competent resources within the licensee's organization to oversee('Intelligent Customer') any work it commissions externally and the subsequent flow down through of the supply chain. This paper examines aspects that organizations need to assess the suitability of approaches that it may take to maintain in-house expertise for the control and oversight of licensed activities at all times. It considers the approach to identification of: core capabilities the licensee would need to understand its safety case under a build-own-operate model to manage licensed activities in accordance with requirements under the Nuclear Safety and Control Acta licensee's 'intelligent customer' capabilities in particular around understanding, specifying, overseeing and accepting work undertaken on its behalf by contractors. While this paper is focused on small modular reactors, being an intelligent customer applies to large commercial or research reactors equally; the size of reactor is immaterial.

  13. Intelligent optimization models based on hard-ridge penalty and RBF for forecasting global solar radiation

    International Nuclear Information System (INIS)

    Jiang, He; Dong, Yao; Wang, Jianzhou; Li, Yuqin

    2015-01-01

    Highlights: • CS-hard-ridge-RBF and DE-hard-ridge-RBF are proposed to forecast solar radiation. • Pearson and Apriori algorithm are used to analyze correlations between the data. • Hard-ridge penalty is added to reduce the number of nodes in the hidden layer. • CS algorithm and DE algorithm are used to determine the optimal parameters. • Proposed two models have higher forecasting accuracy than RBF and hard-ridge-RBF. - Abstract: Due to the scarcity of equipment and the high costs of maintenance, far fewer observations of solar radiation are made than observations of temperature, precipitation and other weather factors. Therefore, it is increasingly important to study several relevant meteorological factors to accurately forecast solar radiation. For this research, monthly average global solar radiation and 12 meteorological parameters from 1998 to 2010 at four sites in the United States were collected. Pearson correlation coefficients and Apriori association rules were successfully used to analyze correlations between the data, which provided a basis for these relative parameters as input variables. Two effective and innovative methods were developed to forecast monthly average global solar radiation by converting a RBF neural network into a multiple linear regression problem, adding a hard-ridge penalty to reduce the number of nodes in the hidden layer, and applying intelligent optimization algorithms, such as the cuckoo search algorithm (CS) and differential evolution (DE), to determine the optimal center and scale parameters. The experimental results show that the proposed models produce much more accurate forecasts than other models

  14. Artificial intelligence in a technological production system of the set quality

    Directory of Open Access Journals (Sweden)

    V. I. Karpov

    2017-01-01

    Full Text Available This  article considers the expert system (ES as a subsystem of management information system technology of sausage products of a given quality. Given the typical structure of an automated expert system, upgraded under a set of interrelated operations of the technological process of production of cooked sausages. Describes the development of two main blocks of this expert system – a database and knowledge base, creating an information space. The work of ES is a sequence of steps, each of which is selected from the database for a rule that applies to the current contents of the working set. The cycle ends when withdrawn or denied the target claim. In our case, the system is designed as a system with direct output, in which the known facts is found the conclusion which from these facts follows. If such a conclusion is found, it is entered into working memory. The knowledge base of an expert system is created as a set of separate entities. The set of these entities allows you to generate objects of study, rules that they can conform, and recommendations for meeting these rules. A set of such entities with their attributes and relationships can be represented as a set of tuples. For the implementation of this approach developed an automated expert system of control of technological process of production of meat and sausage products – the program complex (PC “MulTimit Expert”. The effectiveness of using the developed expert system to control the technology of sausage products of a given quality are considered in one of the examples of the identification of technology defects in the formulation of cooked sausages "Capital", containing large amounts of fatty raw materials. The results of the research as a whole showed that the recommendations of the developed expert system make it possible to improve the quality of the ready-to-eat meat product, increase the water retention coefficient characterizing the moisture retention capacity of the

  15. Real-time intelligent production monitoring of a North Sea asset

    NARCIS (Netherlands)

    Linden, R.J.P. van der; Reijn, H.; Muñoz, E.; Wolff, F. de; Renes, W.

    2010-01-01

    The increasing complexity of natural gas extraction because of reducing reserves, complex behavior and more intricate contractual rules (due to liberalization of the West European energy markets) creates a need for more effective production efficiency. In order to deal with these challenges

  16. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

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

  17. Competitive Intelligence.

    Science.gov (United States)

    Bergeron, Pierrette; Hiller, Christine A.

    2002-01-01

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

  18. Driver's various information process and multi-ruled decision-making mechanism: a fundamental of intelligent driving shaping model

    Directory of Open Access Journals (Sweden)

    Wuhong Wang

    2011-05-01

    Full Text Available The most difficult but important problem in advance driver assistance system development is how to measure and model the behavioral response of drivers with focusing on the cognition process. This paper describes driver's deceleration and acceleration behavior based on driving situation awareness in the car-following process, and then presents several driving models for analysis of driver's safety approaching behavior in traffic operation. The emphasis of our work is placed on the research of driver's various information process and multi-ruled decisionmaking mechanism by considering the complicated control process of driving; the results will be able to provide a theoretical basis for intelligent driving shaping model.

  19. The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri Vocational School students

    Science.gov (United States)

    Antinah; Kusmayadi, T. A.; Husodo, B.

    2018-03-01

    This study aimed to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students’ mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

  20. The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri vocational school students

    Science.gov (United States)

    Antinah; Kusmayadi, T. A.; Husodo, B.

    2018-05-01

    This study aims to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students' mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

  1. Intelligence analysis – the royal discipline of Competitive Intelligence

    Directory of Open Access Journals (Sweden)

    František Bartes

    2011-01-01

    Full Text Available The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in business practice, is the “forecasting of the future”. That is forecasting about the future, which forms the basis for strategic decisions made by the company’s top management. To implement that requirement in corporate practice, the author perceives Competitive Intelligence as a systemic application discipline. This approach allows him to propose a “Work Plan” for Competitive Intelligence as a fundamental standardized document to steer Competitive Intelligence team activities. The author divides the Competitive Intelligence team work plan into five basic parts. Those parts are derived from the five-stage model of the intelligence cycle, which, in the author’s opinion, is more appropriate for complicated cases of Competitive Intelligence.

  2. A physiological production model for cacao : results of model simulations

    NARCIS (Netherlands)

    Zuidema, P.A.; Leffelaar, P.A.

    2002-01-01

    CASE2 is a physiological model for cocoa (Theobroma cacao L.) growth and yield. This report introduces the CAcao Simulation Engine for water-limited production in a non-technical way and presents simulation results obtained with the model.

  3. Modelling Configuration Knowledge in Heterogeneous Product Families

    DEFF Research Database (Denmark)

    Queva, Matthieu Stéphane Benoit; Männistö, Tomi; Ricci, Laurent

    2011-01-01

    Product configuration systems play an important role in the development of Mass Customisation. The configuration of complex product families may nowadays involve multiple design disciplines, e.g. hardware, software and services. In this paper, we present a conceptual approach for modelling...... the variability in such heterogeneous product families. Our approach is based on a framework that aims to cater for the different stakeholders involved in the modelling and management of the product family. The modelling approach is centred around the concepts of views, types and constraints and is illustrated...... by a motivation example. Furthermore, as a proof of concept, a prototype has been implemented for configuring a non-trivial heterogeneous product family....

  4. Business Intelligence Integrated Solutions

    Directory of Open Access Journals (Sweden)

    Cristescu Marian Pompiliu

    2017-01-01

    Full Text Available This paper shows how businesses make decisions better and faster in terms of customers, partners and operations by turning data into valuable business information. The paper describes how to bring together people's and business intelligence information to achieve successful business strategies. There is the possibility of developing business intelligence projects in large and medium-sized organizations only with the Microsoft product described in the paper, and possible alternatives can be discussed according to the required features.

  5. Speech perception, production and intelligibility in French-speaking children with profound hearing loss and early cochlear implantation after congenital cytomegalovirus infection.

    Science.gov (United States)

    Laccourreye, L; Ettienne, V; Prang, I; Couloigner, V; Garabedian, E-N; Loundon, N

    2015-12-01

    To analyze speech in children with profound hearing loss following congenital cytomegalovirus (cCMV) infection with cochlear implantation (CI) before the age of 3 years. In a cohort of 15 children with profound hearing loss, speech perception, production and intelligibility were assessed before and 3 years after CI; variables impacting results were explored. Post-CI, median word recognition was 74% on closed-list and 48% on open-list testing; 80% of children acquired speech production; and 60% were intelligible for all listeners or listeners attentive to lip-reading and/or aware of the child's hearing loss. Univariate analysis identified 3 variables (mean post-CI hearing threshold, bilateral vestibular areflexia, and brain abnormality on MRI) with significant negative impact on the development of speech perception, production and intelligibility. CI showed positive impact on hearing and speech in children with post-cCMV profound hearing loss. Our study demonstrated the key role of maximizing post-CI hearing gain. A few children had insufficient progress, especially in case of bilateral vestibular areflexia and/or brain abnormality on MRI. This led us to suggest that balance rehabilitation and speech therapy should be intensified in such cases. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  6. 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...

  7. A conceptual model for worksite intelligent physical exercise training - IPET - intervention for decreasing life style health risk indicators among employees: a randomized controlled trial

    Science.gov (United States)

    2014-01-01

    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 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 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 indicators, 2) Improve muscle strength and decrease musculoskeletal disorders, 3) Succeed in regular adherence to worksite and leisure physical activity training, and 3) Reduce sickness absence and productivity losses (presenteeism) in office workers. The present RCT study enrolled almost 400 employees with sedentary jobs in the private as well as public sectors. The training interventions last 2 years with measures at baseline as well as one and two years follow-up. Discussion If proven effective, the intelligent physical exercise training scheduled as well as the information for its practical implementation can provide meaningful scientifically based information for public health policy. Trial Registration ClinicalTrials.gov, number: NCT01366950. PMID:24964869

  8. A conceptual model for worksite intelligent physical exercise training--IPET--intervention for decreasing life style health risk indicators among employees: a randomized controlled trial.

    Science.gov (United States)

    Sjøgaard, Gisela; Justesen, Just Bendix; Murray, Mike; Dalager, Tina; Søgaard, Karen

    2014-06-26

    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. The aim of this paper is to present a study protocol 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 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 indicators, 2) Improve muscle strength and decrease musculoskeletal disorders, 3) Succeed in regular adherence to worksite and leisure physical activity training, and 3) Reduce sickness absence and productivity losses (presenteeism) in office workers. The present RCT study enrolled almost 400 employees with sedentary jobs in the private as well as public sectors. The training interventions last 2 years with measures at baseline as well as one and two years follow-up. If proven effective, the intelligent physical exercise training scheduled as well as the information for its practical implementation can provide meaningful scientifically based information for public health policy. ClinicalTrials.gov, number: NCT01366950.

  9. 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

  10. Hybrid simulation models of production networks

    CERN Document Server

    Kouikoglou, Vassilis S

    2001-01-01

    This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.

  11. REVIEW OF AQUACULTURAL PRODUCTION SYSTEM MODELS

    African Journals Online (AJOL)

    user

    models of aquacultural production systems with the aim of adopting a suitable one for ... of predicting the environmental condition, so as to determine point of diminishing returns and optimize yield in an ..... sale of fish are also tracked.

  12. Framework for product knowledge and product related knowledge which supports product modelling for mass customization

    DEFF Research Database (Denmark)

    Riis, Jesper; Hansen, Benjamin Loer; Hvam, Lars

    2003-01-01

    on experience from product modelling projects in several companies. Among them for example companies manufacturing electronic switchboards, spray dryer systems and air conditioning equipment. The framework is divided into three views: the product knowledge view, the life phase system view and the transformation...... and personalization. The framework for product knowledge and product related knowledge is based on the following theories: axiomatic design, technical systems, theory of domains, theory of structuring, theory of properties and the framework for the content of product and product related models. The framework is built......The article presents a framework for product knowledge and product related knowledge which can be used to support the product modelling process which is needed for developing IT systems. These IT systems are important tools for many companies when they aim at achieving mass customization...

  13. Statistical Model Checking for Product Lines

    DEFF Research Database (Denmark)

    ter Beek, Maurice H.; Legay, Axel; Lluch Lafuente, Alberto

    2016-01-01

    average cost of products (in terms of the attributes of the products’ features) and the probability of features to be (un)installed at runtime. The product lines must be modelled in QFLan, which extends the probabilistic feature-oriented language PFLan with novel quantitative constraints among features...

  14. A model for persistency of egg production

    NARCIS (Netherlands)

    Grossman, M.; Gossman, T.N.; Koops, W.J.

    2000-01-01

    The objectives of our study were to propose a new definition for persistency of egg production and to develop a mathematical model to describe the egg production curve, one that includes a new measure for persistency, based on the proposed definition, for use as a selection criterion to improve

  15. Modeling oil production based on symbolic regression

    International Nuclear Information System (INIS)

    Yang, Guangfei; Li, Xianneng; Wang, Jianliang; Lian, Lian; Ma, Tieju

    2015-01-01

    Numerous models have been proposed to forecast the future trends of oil production and almost all of them are based on some predefined assumptions with various uncertainties. In this study, we propose a novel data-driven approach that uses symbolic regression to model oil production. We validate our approach on both synthetic and real data, and the results prove that symbolic regression could effectively identify the true models beneath the oil production data and also make reliable predictions. Symbolic regression indicates that world oil production will peak in 2021, which broadly agrees with other techniques used by researchers. Our results also show that the rate of decline after the peak is almost half the rate of increase before the peak, and it takes nearly 12 years to drop 4% from the peak. These predictions are more optimistic than those in several other reports, and the smoother decline will provide the world, especially the developing countries, with more time to orchestrate mitigation plans. -- Highlights: •A data-driven approach has been shown to be effective at modeling the oil production. •The Hubbert model could be discovered automatically from data. •The peak of world oil production is predicted to appear in 2021. •The decline rate after peak is half of the increase rate before peak. •Oil production projected to decline 4% post-peak

  16. Modeling Fission Product Sorption in Graphite Structures

    International Nuclear Information System (INIS)

    Szlufarska, Izabela; Morgan, Dane; Allen, Todd

    2013-01-01

    The goal of this project is to determine changes in adsorption and desorption of fission products to/from nuclear-grade graphite in response to a changing chemical environment. First, the project team will employ principle calculations and thermodynamic analysis to predict stability of fission products on graphite in the presence of structural defects commonly observed in very high-temperature reactor (VHTR) graphites. Desorption rates will be determined as a function of partial pressure of oxygen and iodine, relative humidity, and temperature. They will then carry out experimental characterization to determine the statistical distribution of structural features. This structural information will yield distributions of binding sites to be used as an input for a sorption model. Sorption isotherms calculated under this project will contribute to understanding of the physical bases of the source terms that are used in higher-level codes that model fission product transport and retention in graphite. The project will include the following tasks: Perform structural characterization of the VHTR graphite to determine crystallographic phases, defect structures and their distribution, volume fraction of coke, and amount of sp2 versus sp3 bonding. This information will be used as guidance for ab initio modeling and as input for sorptivity models; Perform ab initio calculations of binding energies to determine stability of fission products on the different sorption sites present in nuclear graphite microstructures. The project will use density functional theory (DFT) methods to calculate binding energies in vacuum and in oxidizing environments. The team will also calculate stability of iodine complexes with fission products on graphite sorption sites; Model graphite sorption isotherms to quantify concentration of fission products in graphite. The binding energies will be combined with a Langmuir isotherm statistical model to predict the sorbed concentration of fission products

  17. A mathematical model to forecast uranium production

    International Nuclear Information System (INIS)

    Camisani-Calzolari, F.A.G.M.

    1987-01-01

    The uranium production forecasting program described in this paper projects production from reasonably assured, estimated additional and speculative resources in the cost categories of less than $130/kg U. Originally designed to handle South African production, it has been expanded and redimensioned using available published information to forecast production for countries of the Western World. The program forecasts production from up to 400 plants over a period of fifty years and has built-in production models derived from documented historical data of the more important uranium provinces. It is particularly suitable to assess production capabilities on a national and global scale where variations in outputs for the individual plants tend to even out. The program is aimed at putting the uranium potential of any one country into a realistic perspective, and it could thus be useful for planning purposes and marketing strategies

  18. 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.

  19. Intelligence Naturelle et Intelligence Artificielle

    OpenAIRE

    Dubois, Daniel

    2011-01-01

    Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...

  20. A model predictive control approach combined unscented Kalman filter vehicle state estimation in intelligent vehicle trajectory tracking

    Directory of Open Access Journals (Sweden)

    Hongxiao Yu

    2015-05-01

    Full Text Available Trajectory tracking and state estimation are significant in the motion planning and intelligent vehicle control. This article focuses on the model predictive control approach for the trajectory tracking of the intelligent vehicles and state estimation of the nonlinear vehicle system. The constraints of the system states are considered when applying the model predictive control method to the practical problem, while 4-degree-of-freedom vehicle model and unscented Kalman filter are proposed to estimate the vehicle states. The estimated states of the vehicle are used to provide model predictive control with real-time control and judge vehicle stability. Furthermore, in order to decrease the cost of solving the nonlinear optimization, the linear time-varying model predictive control is used at each time step. The effectiveness of the proposed vehicle state estimation and model predictive control method is tested by driving simulator. The results of simulations and experiments show that great and robust performance is achieved for trajectory tracking and state estimation in different scenarios.

  1. Methods and models for quantative assessment of speech intelligibility in cross-language communication

    NARCIS (Netherlands)

    Wijngaarden, S.J. van; Steeneken, H.J.M.; Houtgast, T.

    2001-01-01

    To deal with the effects of nonnative speech communication on speech intelligibility, one must know the magnitude of these effects. To measure this magnitude, suitable test methods must be available. Many of the methods used in cross-language speech communication research are not very suitable for

  2. An Ambient Intelligent Agent Model for Relapse and Recurrence Monitoring in Unipolar Depression

    NARCIS (Netherlands)

    Aziz, A.A.; Klein, M.C.A.; Treur, J.; Combi, C.; Shahar, Y.; Abu-Hanna, A.

    2009-01-01

    Mental healthcare is a prospective area for applying AI techniques. For example, a computerized system could support individuals with a history of depression in maintaining their well-being throughout their lifetime. In this paper, the design of an ambient intelligent agent to support these

  3. Methods for Model-Based Reasoning within Agent-Based Ambient Intelligence Applications

    NARCIS (Netherlands)

    Bosse, T.; Both, F.; Gerritsen, C.; Hoogendoorn, M.; Treur, J.

    2012-01-01

    Within agent-based Ambient Intelligence applications agents react to humans based on information obtained by sensoring and their knowledge about human functioning. Appropriate types of reactions depend on the extent to which an agent understands the human and is able to interpret the available

  4. 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...

  5. Convergent and Divergent Validity of Integrative versus Mixed Model Measures of Emotional Intelligence

    Science.gov (United States)

    Webb, Christian A.; Schwab, Zachary J.; Weber, Mareen; DelDonno, Sophie; Kipman, Maia; Weiner, Melissa R.; Killgore, William D. S.

    2013-01-01

    The construct of emotional intelligence (EI) has garnered increased attention in the popular media and scientific literature. Several competing measures of EI have been developed, including self-report and performance-based instruments. The current study replicates and expands on previous research by examining three competing EI measures…

  6. 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…

  7. 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…

  8. 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

  9. 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…

  10. 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

  11. The U.S. Marine Corps Leadership Model: Can the Central Intelligence Agency Model After It?

    Science.gov (United States)

    2010-04-26

    Daft , Richard L. Leadership Theory and Practice. The Dryden Press. Fort Worth, TX, 1999. Faddis, Charles S. Beyond Repair,· The Decline and Fall...Military Studies Research Paper September 2009 - April 2010 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER The U.S. Marine Corps Leadership Model: can the...protecting our nation against foreign threats. Over the last few years, former CIA officers argue that the Agency’s organizational leadership structure needs

  12. Optimization of surface condensate production from natural gases using artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Al-Farhan, Farhan A.; Ayala, Luis F. [Petroleum and Natural Gas Engineering Program, The Pennsylvania State University 122 Hosler Building, University Park, PA 16802-5001 (United States)

    2006-08-15

    The selection of operating pressures in surface separators can have a remarkable impact on the quantity and quality of the oil produced at the stock tank. In the case of a three-stage separation process, where the operating pressures of the first and third stage (stock tank) are usually set by process considerations, the middle-stage separator pressure becomes the natural variable that lends itself to optimization. Middle-stage pressure is said to be optimum when it maximizes liquid yield in the production facility (i.e., CGR value reaches a maximum) while enhancing the quality of the produced oil condensate (i.e., API is maximized). Accurate thermodynamic and phase equilibrium calculations, albeit elaborate and computer-intensive, represent the more rigorous and reliable way of approaching this optimization problem. Nevertheless, empirical and quasi-empirical approaches are typically the norm when it comes to the selection of the middle-stage surface separation pressure in field operations. In this study, we propose the implementation of Artificial Neural Network (ANN) technology for the establishment of an expert system capable of learning the complex relationship between the input parameters and the output response of the middle-stage optimization problems via neuro-simulation. During the neuro-simulation process, parametric studies are conducted to identify the most influential variables in the thermodynamic optimization protocol. This study presents a powerful optimization tool for the selection of the optimum middle-stage separation pressure, for a variety of natural gas fluid mixtures. The developed ANN is able to predict operating conditions for optimum surface condensate recovery from typical natural gases with condensate contents between 10

  13. A deterministic aggregate production planning model considering quality of products

    International Nuclear Information System (INIS)

    Madadi, Najmeh; Wong, Kuan Yew

    2013-01-01

    Aggregate Production Planning (APP) is a medium-term planning which is concerned with the lowest-cost method of production planning to meet customers' requirements and to satisfy fluctuating demand over a planning time horizon. APP problem has been studied widely since it was introduced and formulated in 1950s. However, in several conducted studies in the APP area, most of the researchers have concentrated on some common objectives such as minimization of cost, fluctuation in the number of workers, and inventory level. Specifically, maintaining quality at the desirable level as an objective while minimizing cost has not been considered in previous studies. In this study, an attempt has been made to develop a multi-objective mixed integer linear programming model that serves those companies aiming to incur the minimum level of operational cost while maintaining quality at an acceptable level. In order to obtain the solution to the multi-objective model, the Fuzzy Goal Programming approach and max-min operator of Bellman-Zadeh were applied to the model. At the final step, IBM ILOG CPLEX Optimization Studio software was used to obtain the experimental results based on the data collected from an automotive parts manufacturing company. The results show that incorporating quality in the model imposes some costs, however a trade-off should be done between the cost resulting from producing products with higher quality and the cost that the firm may incur due to customer dissatisfaction and sale losses.

  14. Nephrus: expert system model in intelligent multilayers for evaluation of urinary system based on scintigraphic image analysis

    International Nuclear Information System (INIS)

    Silva, Jorge Wagner Esteves da; Schirru, Roberto; Boasquevisque, Edson Mendes

    1999-01-01

    Renal function can be measured noninvasively with radionuclides in a extremely safe way compared to other diagnosis techniques. Nevertheless, due to the fact that radioactive materials are used in this procedure, it is necessary to maximize its benefits, therefore all efforts are justifiable in the development of data analysis support tools for this diagnosis modality. The objective of this work is to develop a prototype for a system model based on Artificial Intelligence devices able to perform functions related to cintilographic image analysis of the urinary system. Rules used by medical experts in the analysis of images obtained with 99m Tc+DTPA and /or 99m Tc+DMSA were modeled and a Neural Network diagnosis technique was implemented. Special attention was given for designing programs user-interface. Human Factor Engineering techniques were taking in account allowing friendliness and robustness. The image segmentation adopts a model based on Ideal ROIs, which represent the normal anatomic concept for urinary system organs. Results obtained using Artificial Neural Networks for qualitative image analysis and knowledge model constructed show the feasibility of Artificial Neural Networks for qualitative image analysis and knowledge model constructed show feasibility of Artificial Intelligence implementation that uses inherent abilities of each technique in the medical diagnosis image analysis. (author)

  15. Revised Reynolds Stress and Triple Product Models

    Science.gov (United States)

    Olsen, Michael E.; Lillard, Randolph P.

    2017-01-01

    Revised versions of Lag methodology Reynolds-stress and triple product models are applied to accepted test cases to assess the improvement, or lack thereof, in the prediction capability of the models. The Bachalo-Johnson bump flow is shown as an example for this abstract submission.

  16. Intelligent nesting system

    Directory of Open Access Journals (Sweden)

    Đuričić Zoran

    2003-01-01

    Full Text Available The economy of the process for the manufacture of parts from sheet metal plates depends on successful solution of the process of cutting various parts from sheet metal plates. Essentially, the problem is to arrange contours within a defined space so that they take up minimal surface. When taken in this way, the considered problem assumes a more general nature; it refers to the utilization of a flat surface, and it can represent a general principle of arranging 2D contours on a certain surface. The paper presents a conceptual solution and a prototypal intelligent nesting system for optimal cutting. The problem of nesting can generally be divided into two intellectual phases: recognition and classification of shapes, and arrangement of recognized shapes on a given surface. In solving these problems, methods of artificial intelligence are applied. In the paper, trained neural network is used for recognition of shapes; on the basis of raster record of a part's drawing, it recognizes the part's shape and which class it belongs to. By means of the expert system, based on rules defined on the basis of acquisition of knowledge from manufacturing sections, as well as on the basis of certain mathematical algorithms, parts are arranged on the arrangement surface. Both systems can also work independently, having been built on the modular principle. The system uses various product models as elements of integration for the entire system. .

  17. 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...

  18. 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.

  19. The Prediction of Mental Quality of Life Based on Defectiveness/Shame Schema with Mediating Role of Emotional Intelligence and Coping Strategies by Means of Structural Equations Modeling

    Directory of Open Access Journals (Sweden)

    S. Dehghani

    2014-06-01

    Full Text Available Early maladaptive schema is assumed to be a disrupting factor for quality of life. Yet, the mechanism of this vulnerability is not well known. The purpose of this study was to investigate the characteristic of emotional intelligence and coping strategy with stress as a mediator between early maladaptive defectiveness/ shame and mental quality of life. Participants were 245 men and women in Isfahan who were selected as the sample by availability sampling method. They completed the Petrides and Furnham's Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF, Coping Inventory for stressful situation (CISS and WHO Quality of Life-BREF (WHOQOL-BREF and Young Schema Questionnaire-Short Form (YSQ-SF. Data was analyzed by means of structural equation modeling. The results indicated that the suggested model of study needs modification and only emotional intelligence was the mediator. Standard path coefficient of defectiveness/shame schema to emotional intelligence was -0.55 and emotional intelligence to problem focused coping, emotion focused coping and mental quality of life were 0.49, -0.59 and 0.78 (p<0.05. Based on results, emotional intelligence training can improve mental quality of life and coping strategies in people who have early defectiveness/shame maladaptive schema.

  20. 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...... settings to meet an optimization objective such as minimum cost and minimum reference temperature error. It demonstrates that this MPC strategy can realize load shifting, and maximize the PV self-consumption in the residential sector. With this demand side control study, it is expected that MPC strategy...