WorldWideScience

Sample records for hybrid training approach

  1. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew

    2017-12-06

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  2. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew; McCabe, Matthew

    2017-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  3. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    Science.gov (United States)

    Houborg, Rasmus; McCabe, Matthew F.

    2018-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory 'predictor' variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association with

  4. Model-based design validation for advanced energy management strategies for electrified hybrid power trains using innovative vehicle hardware in the loop (VHIL) approach

    International Nuclear Information System (INIS)

    Mayyas, Abdel Ra'ouf; Kumar, Sushil; Pisu, Pierluigi; Rios, Jacqueline; Jethani, Puneet

    2017-01-01

    Highlights: •Vehicle hardware In-the-loop VHiL testing and validation is implemented in vehicle test bed. •Torque at the roller bench test is used to control the torque at wheels to reflect vehicle electrification symptoms. •Electrified powertrain with Equivalent Consumption Minimization Strategy is tested and validated using VHiL. •Fuel economy and power train performance is measured using high precision fuel measurement device. -- Abstract: Hybridization of automotive powertrains by using more than one type of energy converter is considered as an important step towards reducing fuel consumption and air pollutants. Specifically, the development of energy efficient, highly complex, alternative drive-train systems, in which the interactions of different energy converters play an important role, requires new design methods and processes. This paper discusses the inclusion of an alternative hybrid power train into an existing vehicle platform for maximum energy efficiency. The new proposed integrated Vehicle Hardware In-the-loop (VHiL) and Model Based Design (MBD) approach is utilized to evaluate the energy efficiency of electrified powertrain. In VHiL, a complete chassis system becomes an integrated part of the vehicle test bed. A complete conventional Internal Combustion Engine (ICE) powered vehicle is tested in roller bench test for the integration of energy efficient hybrid electric power train modules in closed-loop, real-time, feedback configuration. A model that is a replica of the test vehicle is executed – in real-time- where all hybrid power train modules are included. While the VHiL platform is controlling the signal exchange between the test bed automation software and the vehicle on-board controller, the road load exerted on the driving wheels is manipulated in closed –loop real-time manner in order to reflect all hybrid driving modes including: All Electric Range (AER), Electric Power Assist (EPA) and blended Modes (BM). Upon successful

  5. A globally networked hybrid approach to public health capacity training for maternal health professionals in low and middle income countries.

    Science.gov (United States)

    McIntosh, Scott; Pérez-Ramos, José G; David, Tamala; Demment, Margaret M; Avendaño, Esteban; Ossip, Deborah J; De Ver Dye, Timothy

    2017-01-01

    MundoComm is a current NIH-funded project for sustainable public health capacity building in community engagement and technological advances aimed at improving maternal health issues. Two to four teams are selected annually, each consisting of three healthcare professionals and one technical person from specific low and middle income countries (LMICs) including Costa Rica, Dominican Republic, Honduras, and other LMICs. MundoComm is a course with three parts: in-person workshops, online modules, and mentored community engagement development. Two annual 1-week on-site "short courses" convened in Costa Rica are supplemented with six monthly online training modules using the Moodle® online platform for e-learning, and mentored project development. The year-long course comprises over 20 topics divided into the six modules - each module further segmented into 4 week-long assignments, with readings and assigned tasks covering different aspects of community-engaged interventions. The content is peer reviewed by experts in the respective fields from University of Rochester, UCIMED in Costa Rica, and faculty from Costa Rica and the Dominican Republic who maintain regular contact with the trainees to mentor learning and project progress. The purpose of this paper is to report the first year results of the MundoComm project. Both quantitative and qualitative feedback (using online data capturing forms) assess baseline and post-training knowledge and skills in public health project strategies. The course currently has one team each in Costa Rica, the Dominican Republic, and Honduras for a total of 12 trainees. The course and modules include best practices in information and communication technologies (ICTs), ethical reviews, community engagement, evidence-based community interventions, and e-Health strategies. To maximize successful and culturally appropriate training approaches, the multi-media didactic presentations, flexible distance learning strategies, and the use of

  6. NEW APPROACHES: Toppling trains

    Science.gov (United States)

    Parry, Malcolm

    1998-03-01

    This article explains a novel way of approaching centripetal force: theory is used to predict an orbital period at which a toy train will topple from a circular track. The demonstration has proved useful in A-level, GNVQ and undergraduate Physics and Engineering schemes.

  7. A study of the talent training project management for semiconductor industry in Taiwan: the application of a hybrid data envelopment analysis approach.

    Science.gov (United States)

    Kao, Ling-Jing; Chiu, Shu-Yu; Ko, Hsien-Tang

    2014-01-01

    The purpose of this study is to evaluate the training institution performance and to improve the management of the Manpower Training Project (MTP) administered by the Semiconductor Institute in Taiwan. Much literature assesses the efficiency of an internal training program initiated by a firm, but only little literature studies the efficiency of an external training program led by government. In the study, a hybrid solution of ICA-DEA and ICA-MPI is developed for measuring the efficiency and the productivity growth of each training institution over the period. The technical efficiency change, the technological change, pure technical efficiency change, scale efficiency change, and the total factor productivity change were evaluated according to five inputs and two outputs. According to the results of the study, the training institutions can be classified by their efficiency successfully and the guidelines for the optimal level of input resources can be obtained for each inefficient training institution. The Semiconductor Institute in Taiwan can allocate budget more appropriately and establish withdrawal mechanisms for inefficient training institutions.

  8. Approach to team skills training

    International Nuclear Information System (INIS)

    Koontz, J.L.; Roe, M.L.; Gaddy, C.D.

    1987-01-01

    The US commercial nuclear power industry has recognized the importance of team skills in control room operation. The desire to combine training of team interaction skills, like communications, with technical knowledge of reactor operations requires a unique approach to training. An NRC-sponsored study identified a five-phase approach to team skills training designed to be consistent with the systems approach to training currently endorsed by the NRC Policy Statement on Training and Qualification. This paper describes an approach to team skills training with emphasis on the nuclear power plant control room crew. An approach to team skills training

  9. Evaporator modeling - A hybrid approach

    International Nuclear Information System (INIS)

    Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun

    2009-01-01

    In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis

  10. A Hybrid Approach to Teaching Managerial Economics

    Science.gov (United States)

    Metzgar, Matthew

    2014-01-01

    Many institutions in higher education are experimenting with hybrid teaching approaches to undergraduate courses. Online resources may provide a number of advantages to students as compared to in-class approaches. Research regarding the effectiveness of hybrid approaches is mixed and still accumulating. This paper discusses the use of a hybrid…

  11. Improved Hybrid Opponent System for Professional Military Training

    Directory of Open Access Journals (Sweden)

    Michael Pelosi

    2017-10-01

    Full Text Available Described herein is a general-purpose software engineering architecture for autonomous, computer controlled opponent implementation in modern maneuver warfare simulation and training. The implementation has been developed, refined, and tested in the user crucible for several years. The approach represents a hybrid application of various well-known AI techniques, including domain modeling, agent modeling, and object-oriented programming. Inspired by computer chess approaches, the methodology combines this theoretical foundation with a hybrid and scalable portfolio of additional techniques. The result remains simple enough to be maintainable, comprehensible for the code writers as well as the end-users, and robust enough to handle a wide spectrum of possible mission scenarios and circumstances without modification.

  12. Hybrid soft computing approaches research and applications

    CERN Document Server

    Dutta, Paramartha; Chakraborty, Susanta

    2016-01-01

    The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

  13. A Hybrid Approach to Protect Palmprint Templates

    Directory of Open Access Journals (Sweden)

    Hailun Liu

    2014-01-01

    Full Text Available Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach.

  14. THE APPROACHING TRAIN DETECTION ALGORITHM

    OpenAIRE

    S. V. Bibikov

    2015-01-01

    The paper deals with detection algorithm for rail vibroacoustic waves caused by approaching train on the background of increased noise. The urgency of algorithm development for train detection in view of increased rail noise, when railway lines are close to roads or road intersections is justified. The algorithm is based on the method of weak signals detection in a noisy environment. The information statistics ultimate expression is adjusted. We present the results of algorithm research and t...

  15. Alternative systematic approaches to training

    Energy Technology Data Exchange (ETDEWEB)

    1995-01-01

    This handbook is approved for use by all DOE Components and contractors. The handbook was prepared primarily for DOE nuclear facilities, but the information can be effectively used by any other type of facility. DOE nuclear, DOE non-nuclear, commercial nuclear reactor, fuel fabrication, chemical processing, or other types of facilities may also apply the principles of this approach and find it useful and applicable to local needs. The handbook provides DOE and contractor operating organizations with concepts and guidance regarding the use of alternative techniques to implement a systematic approach to training (SAT). The techniques described in this handbook are endorsed by DOE and use of the guidance in this handbook is appropriate for establishment of technical training programs at DOE nuclear facilities. The use of guidance on selection and implementation of appropriate training approaches after consideration of job complexity, the consequences of error based on risk/hazard potential, and available training media should result in effective and efficient training programs. The information presented in this handbook can be used to grade the level of effort and formality used in developing training programs.

  16. Detection of cardiovascular anomalies: Hybrid systems approach

    KAUST Repository

    Ledezma, Fernando

    2012-06-06

    In this paper, we propose a hybrid interpretation of the cardiovascular system. Based on a model proposed by Simaan et al. (2009), we study the problem of detecting cardiovascular anomalies that can be caused by variations in some physiological parameters, using an observerbased approach. We present the first numerical results obtained. © 2012 IFAC.

  17. A HYBRID APPROACH FOR RURAL FEEDER DESIGN

    Directory of Open Access Journals (Sweden)

    DAMANJEET KAUR

    2012-08-01

    Full Text Available In this paper, a population based approach for conductor size selection in rural radial distribution system is presented. The proposed hybrid approach implies a particle swarm optimization (PSO approach in combination with mutant property of differential evolution (DE for conductor size selection in radial distribution system. The conductor size for each feeder segment is selected such that the total cost of capital investment and capitalized cost of energy losses is minimized while constraints of voltage at each node and current carrying capacity of conductor is within the limits. The applicability and effectiveness of the proposed method is demonstrated with the help of 32-node test system.

  18. A hybrid approach for biobjective optimization

    DEFF Research Database (Denmark)

    Stidsen, Thomas Jacob Riis; Andersen, Kim Allan

    2018-01-01

    to singleobjective problems is that no standard multiobjective solvers exist and specialized algorithms need to be programmed from scratch.In this article we will present a hybrid approach, which operates both in decision space and in objective space. The approach enables massive efficient parallelization and can...... be used to a wide variety of biobjective Mixed Integer Programming models. We test the approach on the biobjective extension of the classic traveling salesman problem, on the standard datasets, and determine the full set of nondominated points. This has only been done once before (Florios and Mavrotas...

  19. Hybrid drive train technologies for vehicles

    NARCIS (Netherlands)

    Hofman, T.; Folkson, R.

    This chapter provides a classification of electric hybrid systems for cars and describes the conflicting design challenges involved in designing advanced vehicle propulsion systems. In addition, the chapter provides an analysis of the solution methods currently provided in literature on the coupled

  20. Hybrid biasing approaches for global variance reduction

    International Nuclear Information System (INIS)

    Wu, Zeyun; Abdel-Khalik, Hany S.

    2013-01-01

    A new variant of Monte Carlo—deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses. - Highlights: ► Hybrid Monte Carlo Deterministic Method based on Gaussian Process Model is introduced. ► Method employs deterministic model to calculate responses correlations. ► Method employs correlations to bias Monte Carlo transport. ► Method compared to FW-CADIS methodology in SCALE code. ► An order of magnitude speed up is achieved for a PWR core model.

  1. Hybrid simulation using mixed reality for interventional ultrasound imaging training.

    Science.gov (United States)

    Freschi, C; Parrini, S; Dinelli, N; Ferrari, M; Ferrari, V

    2015-07-01

    Ultrasound (US) imaging offers advantages over other imaging modalities and has become the most widespread modality for many diagnostic and interventional procedures. However, traditional 2D US requires a long training period, especially to learn how to manipulate the probe. A hybrid interactive system based on mixed reality was designed, implemented and tested for hand-eye coordination training in diagnostic and interventional US. A hybrid simulator was developed integrating a physical US phantom and a software application with a 3D virtual scene. In this scene, a 3D model of the probe with its relative scan plane is coherently displayed with a 3D representation of the phantom internal structures. An evaluation study of the diagnostic module was performed by recruiting thirty-six novices and four experts. The performances of the hybrid (HG) versus physical (PG) simulator were compared. After the training session, each novice was required to visualize a particular target structure. The four experts completed a 5-point Likert scale questionnaire. Seventy-eight percentage of the HG novices successfully visualized the target structure, whereas only 45% of the PG reached this goal. The mean scores from the questionnaires were 5.00 for usefulness, 4.25 for ease of use, 4.75 for 3D perception, and 3.25 for phantom realism. The hybrid US training simulator provides ease of use and is effective as a hand-eye coordination teaching tool. Mixed reality can improve US probe manipulation training.

  2. A Hybrid Approach on Tourism Demand Forecasting

    Science.gov (United States)

    Nor, M. E.; Nurul, A. I. M.; Rusiman, M. S.

    2018-04-01

    Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is challenging to produce an accurate forecast since economic data such as the tourism data is affected by social, economic and environmental factors. In this study, an equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was assessed by taking the each individual method as a benchmark. The results showed that this hybrid approach outperformed the other two models

  3. Heuristic approach to train rescheduling

    Directory of Open Access Journals (Sweden)

    Mladenović Snežana

    2007-01-01

    Full Text Available Starting from the defined network topology and the timetable assigned beforehand, the paper considers a train rescheduling in respond to disturbances that have occurred. Assuming that the train trips are jobs, which require the elements of infrastructure - resources, it was done by the mapping of the initial problem into a special case of job shop scheduling problem. In order to solve the given problem, a constraint programming approach has been used. A support to fast finding "enough good" schedules is offered by original separation, bound and search heuristic algorithms. In addition, to improve the time performance, instead of the actual objective function with a large domain, a surrogate objective function is used with a smaller domain, if there is such. .

  4. A hybrid approach for global sensitivity analysis

    International Nuclear Information System (INIS)

    Chakraborty, Souvik; Chowdhury, Rajib

    2017-01-01

    Distribution based sensitivity analysis (DSA) computes sensitivity of the input random variables with respect to the change in distribution of output response. Although DSA is widely appreciated as the best tool for sensitivity analysis, the computational issue associated with this method prohibits its use for complex structures involving costly finite element analysis. For addressing this issue, this paper presents a method that couples polynomial correlated function expansion (PCFE) with DSA. PCFE is a fully equivalent operational model which integrates the concepts of analysis of variance decomposition, extended bases and homotopy algorithm. By integrating PCFE into DSA, it is possible to considerably alleviate the computational burden. Three examples are presented to demonstrate the performance of the proposed approach for sensitivity analysis. For all the problems, proposed approach yields excellent results with significantly reduced computational effort. The results obtained, to some extent, indicate that proposed approach can be utilized for sensitivity analysis of large scale structures. - Highlights: • A hybrid approach for global sensitivity analysis is proposed. • Proposed approach integrates PCFE within distribution based sensitivity analysis. • Proposed approach is highly efficient.

  5. Opportunistic beam training with hybrid analog/digital codebooks for mmWave systems

    KAUST Repository

    Eltayeb, Mohammed E.

    2016-02-25

    © 2015 IEEE. Millimeter wave (mmWave) communication is one solution to provide more spectrum than available at lower carrier frequencies. To provide sufficient link budget, mmWave systems will use beamforming with large antenna arrays at both the transmitter and receiver. Training these large arrays using conventional approaches taken at lower carrier frequencies, however, results in high overhead. In this paper, we propose a beam training algorithm that efficiently designs the beamforming vectors with low training overhead. Exploiting mmWave channel reciprocity, the proposed algorithm relaxes the need for an explicit feedback channel, and opportunistically terminates the training process when a desired quality of service is achieved. To construct the training beamforming vectors, a new multi-resolution codebook is developed for hybrid analog/digital architectures. Simulation results show that the proposed algorithm achieves a comparable rate to that obtained by exhaustive search solutions while requiring lower training overhead when compared to prior work.

  6. Opportunistic beam training with hybrid analog/digital codebooks for mmWave systems

    KAUST Repository

    Eltayeb, Mohammed E.; Alkhateeb, Ahmed; Heath, Robert W.; Al-Naffouri, Tareq Y.

    2016-01-01

    © 2015 IEEE. Millimeter wave (mmWave) communication is one solution to provide more spectrum than available at lower carrier frequencies. To provide sufficient link budget, mmWave systems will use beamforming with large antenna arrays at both the transmitter and receiver. Training these large arrays using conventional approaches taken at lower carrier frequencies, however, results in high overhead. In this paper, we propose a beam training algorithm that efficiently designs the beamforming vectors with low training overhead. Exploiting mmWave channel reciprocity, the proposed algorithm relaxes the need for an explicit feedback channel, and opportunistically terminates the training process when a desired quality of service is achieved. To construct the training beamforming vectors, a new multi-resolution codebook is developed for hybrid analog/digital architectures. Simulation results show that the proposed algorithm achieves a comparable rate to that obtained by exhaustive search solutions while requiring lower training overhead when compared to prior work.

  7. Comprehensive Approach Training Toolkit: Training Needs Analysis

    Science.gov (United States)

    2013-03-01

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  8. A hybrid personalized data recommendation approach for geoscience data sharing

    Science.gov (United States)

    WANG, M.; Wang, J.

    2016-12-01

    Recommender systems are effective tools helping Internet users overcome information overloading. The two most widely used recommendation algorithms are collaborating filtering (CF) and content-based filtering (CBF). A number of recommender systems based on those two algorithms were developed for multimedia, online sells, and other domains. Each of the two algorithms has its advantages and shortcomings. Hybrid approaches that combine these two algorithms are better choices in many cases. In geoscience data sharing domain, where the items (datasets) are more informative (in space and time) and domain-specific, no recommender system is specialized for data users. This paper reports a dynamic weighted hybrid recommendation algorithm that combines CF and CBF for geoscience data sharing portal. We first derive users' ratings on items with their historical visiting time by Jenks Natural Break. In the CBF part, we incorporate the space, time, and subject information of geoscience datasets to compute item similarity. Predicted ratings were computed with k-NN method separately using CBF and CF, and then combined with weights. With training dataset we attempted to find the best model describing ideal weights and users' co-rating numbers. A logarithmic function was confirmed to be the best model. The model was then used to tune the weights of CF and CBF on user-item basis with test dataset. Evaluation results show that the dynamic weighted approach outperforms either solo CF or CBF approach in terms of Precision and Recall.

  9. Stock selection using a hybrid MCDM approach

    Directory of Open Access Journals (Sweden)

    Tea Poklepović

    2014-12-01

    Full Text Available The problem of selecting the right stocks to invest in is of immense interest for investors on both emerging and developed capital markets. Moreover, an investor should take into account all available data regarding stocks on the particular market. This includes fundamental and stock market indicators. The decision making process includes several stocks to invest in and more than one criterion. Therefore, the task of selecting the stocks to invest in can be viewed as a multiple criteria decision making (MCDM problem. Using several MCDM methods often leads to divergent rankings. The goal of this paper is to resolve these possible divergent results obtained from different MCDM methods using a hybrid MCDM approach based on Spearman’s rank correlation coefficient. Five MCDM methods are selected: COPRAS, linear assignment, PROMETHEE, SAW and TOPSIS. The weights for all criteria are obtained by using the AHP method. Data for this study includes information on stock returns and traded volumes from March 2012 to March 2014 for 19 stocks on the Croatian capital market. It also includes the most important fundamental and stock market indicators for selected stocks. Rankings using five selected MCDM methods in the stock selection problem yield divergent results. However, after applying the proposed approach the final hybrid rankings are obtained. The results show that the worse stocks to invest in happen to be the same when the industry is taken into consideration or when not. However, when the industry is taken into account, the best stocks to invest in are slightly different, because some industries are more profitable than the others.

  10. Training Package Implementation: Innovative and Flexible Approaches.

    Science.gov (United States)

    Meyers, Dave; Blom, Kaaren

    The implementation of training packages (TPs) in Australian workplaces was examined through case studies of the use of TPs in nontraditional trade areas by six innovative registered training organizations (RTOs) across Australia. The study focused on the extent to which new and flexible approaches to learning, training delivery, and assessment…

  11. Multilayer Approach for Advanced Hybrid Lithium Battery

    KAUST Repository

    Ming, Jun

    2016-06-06

    Conventional intercalated rechargeable batteries have shown their capacity limit, and the development of an alternative battery system with higher capacity is strongly needed for sustainable electrical vehicles and hand-held devices. Herein, we introduce a feasible and scalable multilayer approach to fabricate a promising hybrid lithium battery with superior capacity and multivoltage plateaus. A sulfur-rich electrode (90 wt % S) is covered by a dual layer of graphite/Li4Ti5O12, where the active materials S and Li4Ti5O12 can both take part in redox reactions and thus deliver a high capacity of 572 mAh gcathode -1 (vs the total mass of electrode) or 1866 mAh gs -1 (vs the mass of sulfur) at 0.1C (with the definition of 1C = 1675 mA gs -1). The battery shows unique voltage platforms at 2.35 and 2.1 V, contributed from S, and 1.55 V from Li4Ti5O12. A high rate capability of 566 mAh gcathode -1 at 0.25C and 376 mAh gcathode -1 at 1C with durable cycle ability over 100 cycles can be achieved. Operando Raman and electron microscope analysis confirm that the graphite/Li4Ti5O12 layer slows the dissolution/migration of polysulfides, thereby giving rise to a higher sulfur utilization and a slower capacity decay. This advanced hybrid battery with a multilayer concept for marrying different voltage plateaus from various electrode materials opens a way of providing tunable capacity and multiple voltage platforms for energy device applications. © 2016 American Chemical Society.

  12. The Business Approach to Training.

    Science.gov (United States)

    Williams, Teresa; Green, Adrian

    This self-study book concentrates on enabling trainers to talk and think in a business-related way, use business concepts and terminology, and translate training and development ideas into a business setting. Each part contains activities to enable users to study their training and development function and organization and consider how to use the…

  13. Training Program Handbook: A systematic approach to training

    Energy Technology Data Exchange (ETDEWEB)

    1994-08-01

    This DOE handbook describes a systematic method for establishing and maintaining training programs that meet the requirements and expectations of DOE Orders 5480.18B and 5480.20. The systematic approach to training includes 5 phases: Analysis, design, development, implementation, and evaluation.

  14. A systematic approach to training: A training needs assessment

    Science.gov (United States)

    Manning, Margaret H.

    1989-01-01

    In an effort to determine the gap between the actual performance and the necessary performance of employees for the effective and efficient accomplishment of an organization's mission and goals, an organization-wide Training Needs Assessment must be conducted. The purpose of this work was to conduct a training needs analysis and prepare a NASA Langley Catalog of On-Site Training programs. The work included developing a Training Needs Assessment Survey, implementing the survey, analyzing and researching the training needs, identifying the courses to meet the needs, and preparing and designing an On-Site Training Catalog. This needs analysis attempted to identify performance weaknesses and deficits; seek out and provide opportunities for improved performance; anticipate and avoid future problems; enhance and create new strengths. The end product is a user-friendly catalog of on-site training available. The results include: top-down approach to needs assessment; improved communication with training coordinators; 98 percent return rate of the Training Needs Assessment survey; complete, newly designed, user-friendly catalog; 167 catalog descriptions advertised; 82 new courses advertised; training logo; and request for the training application form.

  15. A hybrid modeling approach for option pricing

    Science.gov (United States)

    Hajizadeh, Ehsan; Seifi, Abbas

    2011-11-01

    The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.

  16. Approaches to training in companies

    Directory of Open Access Journals (Sweden)

    Magnoler Patrizia

    2016-12-01

    Full Text Available The need to address generational change and the challenges of a global market in terms of maintaining productivity require small and medium enterprises, mainly of an artisanal nature, to rethink training. The challenges mainly concern production capacity, which is increasingly problematic given that demand does not allow for long-term schedules and enhancement of human resources. There are many tensions and just as many needs for improvement, and training is therefore the space in which to collect and rework in order to restore a new perspective of sustainable and quality change.

  17. Detection of cardiovascular anomalies: Hybrid systems approach

    KAUST Repository

    Ledezma, Fernando; Laleg-Kirati, Taous-Meriem

    2012-01-01

    In this paper, we propose a hybrid interpretation of the cardiovascular system. Based on a model proposed by Simaan et al. (2009), we study the problem of detecting cardiovascular anomalies that can be caused by variations in some physiological

  18. Inductive Reasoning: A Training Approach

    Science.gov (United States)

    Klauer, Karl Josef; Phye, Gary D.

    2008-01-01

    Researchers have examined inductive reasoning to identify different cognitive processes when participants deal with inductive problems. This article presents a prescriptive theory of inductive reasoning that identifies cognitive processing using a procedural strategy for making comparisons. It is hypothesized that training in the use of the…

  19. A hybrid ensemble learning approach to star-galaxy classification

    Science.gov (United States)

    Kim, Edward J.; Brunner, Robert J.; Carrasco Kind, Matias

    2015-10-01

    There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template-fitting method. Using data from the CFHTLenS survey (Canada-France-Hawaii Telescope Lensing Survey), we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2 (Deep Extragalactic Evolutionary Probe Phase 2 ), SDSS (Sloan Digital Sky Survey), VIPERS (VIMOS Public Extragalactic Redshift Survey), and VVDS (VIMOS VLT Deep Survey), and when the demographics of sources in a low-quality training set do not match the demographics of objects in the test data set. We demonstrate that our Bayesian combination technique improves the overall performance over any individual classification method in these scenarios. Thus, strategies that combine the predictions of different classifiers may prove to be optimal in currently ongoing and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

  20. A "Hybrid" Approach for Synthesizing Optimal Controllers of Hybrid Systems

    DEFF Research Database (Denmark)

    Zhao, Hengjun; Zhan, Naijun; Kapur, Deepak

    2012-01-01

    to discretization manageable and within bounds. A major advantage of our approach is not only that it avoids errors due to numerical computation, but it also gives a better optimal controller. In order to illustrate our approach, we use the real industrial example of an oil pump provided by the German company HYDAC...

  1. A Systematic Approach to Terminal Training.

    Science.gov (United States)

    Sheffield, John

    1980-01-01

    Describes the systematic approach used by the training department of the Canada Trust Company to develop a training program for operators of the new terminals for the online banking system to which the bank was converting, the Canadian On-Line Financial Information System (COFIS). (JD)

  2. Institutionalizing the Ecohealth Approach : Training and Awards ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    The program will comprise three elements: a region-wide training and awards ... of the Ecohealth approach within INSP's graduate program; and a co-financing strategy to ... New funding opportunity for gender equality and climate change.

  3. Hybrid perovskites: Approaches towards light-emitting devices

    KAUST Repository

    Alias, Mohd Sharizal

    2016-10-06

    The high optical gain and absorption of organic-inorganic hybrid perovskites have attracted extensive research for photonic device applications. Using the bromide halide as an example, we present key approaches of our work towards realizing efficient perovskites based light-emitters. The approaches involved determination of optical constants for the hybrid perovskites thin films, fabrication of photonic nanostructures in the form of subwavelength grating reflector patterned directly on the hybrid perovskites as light manipulation layer, and enhancing the emission property of the hybrid perovskites by using microcavity structure. Our results provide a platform for realization of hybrid perovskites based light-emitting devices for solid-state lighting and display applications. © 2016 IEEE.

  4. Hybrid perovskites: Approaches towards light-emitting devices

    KAUST Repository

    Alias, Mohd Sharizal; Dursun, Ibrahim; Priante, Davide; Saidaminov, Makhsud I.; Ng, Tien Khee; Bakr, Osman; Ooi, Boon S.

    2016-01-01

    The high optical gain and absorption of organic-inorganic hybrid perovskites have attracted extensive research for photonic device applications. Using the bromide halide as an example, we present key approaches of our work towards realizing efficient perovskites based light-emitters. The approaches involved determination of optical constants for the hybrid perovskites thin films, fabrication of photonic nanostructures in the form of subwavelength grating reflector patterned directly on the hybrid perovskites as light manipulation layer, and enhancing the emission property of the hybrid perovskites by using microcavity structure. Our results provide a platform for realization of hybrid perovskites based light-emitting devices for solid-state lighting and display applications. © 2016 IEEE.

  5. Intraprocedural arterial perforation during neuroendovascular therapy: Preliminary result of a dual-trained endovascular neurosurgeon in the neurosurgical hybrid operating room

    Directory of Open Access Journals (Sweden)

    Yuang-Seng Tsuei

    2018-01-01

    Conclusion: IPAP can be rescued successfully with an aggressive approach and quick conversion to backup surgery by a dual-trained endovascular neurosurgeon in the hybrid OR. The value of the hybrid OR in neuroendovascular therapy should be further investigated in the future.

  6. Scalar field dark matter in hybrid approach

    NARCIS (Netherlands)

    Friedrich, Pavel; Prokopec, Tomislav

    2017-01-01

    We develop a hybrid formalism suitable for modeling scalar field dark matter, in which the phase-space distribution associated to the real scalar field is modeled by statistical equal-time two-point functions and gravity is treated by two stochastic gravitational fields in the longitudinal gauge (in

  7. HYBRID EDUCATION: THE ESTIMATION IN THE CATEGORIES OF INFORMATION-AXIOLOGICAL APPROACH

    Directory of Open Access Journals (Sweden)

    A. S. Kizilova

    2018-01-01

    Full Text Available Introduction: a hybrid assessment of reality is a new information-axiological level of communication between people. The term "hybrid (hybrid training" has been used as a result of the integration of digital and communication technologies in the form of online courses.Materials and methods: the main Russian forms of education are analyzed. The evaluation of the forms of education in the categories of the information-axiological approach is made on the basis of the following idea: everything is interchangeable, since everything has value. The mixing principles and models used in the process of hybrid formation are considered. Due to the fact that any mixed training requires planning, the analysis of the project and the target group, content analysis and financial analysis in this process is carried out.Results: specific educational methods are studied at the Bauman MSTU, subject to a hybrid assessment in the categories of the information-axiological approach. The analysis showed that the above explanation of the term "hybrid formation" is extremely narrow and one-sided. In particular, the search for information on volunteer education and the search for a socially-based education was conducted not only in the Bauman MSTU, but in Russia as a whole. However, the result was the portals of international student organizations with their own projects. Another example of a different interpretation of the "hybrid education" may be the assumption of quite axiologically new duties.Discussion and Conclusions: hybrid education is not limited to any temporal and territorial framework. It can manifest itself not only in the Internet-sphere, but also in the most diverse spheres of everyday life, with the interaction of various people and entire societies.

  8. Locomotion training of legged robots using hybrid machine learning techniques

    Science.gov (United States)

    Simon, William E.; Doerschuk, Peggy I.; Zhang, Wen-Ran; Li, Andrew L.

    1995-01-01

    In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible

  9. Manifold absolute pressure estimation using neural network with hybrid training algorithm.

    Directory of Open Access Journals (Sweden)

    Mohd Taufiq Muslim

    Full Text Available In a modern small gasoline engine fuel injection system, the load of the engine is estimated based on the measurement of the manifold absolute pressure (MAP sensor, which took place in the intake manifold. This paper present a more economical approach on estimating the MAP by using only the measurements of the throttle position and engine speed, resulting in lower implementation cost. The estimation was done via two-stage multilayer feed-forward neural network by combining Levenberg-Marquardt (LM algorithm, Bayesian Regularization (BR algorithm and Particle Swarm Optimization (PSO algorithm. Based on the results found in 20 runs, the second variant of the hybrid algorithm yields a better network performance than the first variant of hybrid algorithm, LM, LM with BR and PSO by estimating the MAP closely to the simulated MAP values. By using a valid experimental training data, the estimator network that trained with the second variant of the hybrid algorithm showed the best performance among other algorithms when used in an actual retrofit fuel injection system (RFIS. The performance of the estimator was also validated in steady-state and transient condition by showing a closer MAP estimation to the actual value.

  10. Manifold absolute pressure estimation using neural network with hybrid training algorithm.

    Science.gov (United States)

    Muslim, Mohd Taufiq; Selamat, Hazlina; Alimin, Ahmad Jais; Haniff, Mohamad Fadzli

    2017-01-01

    In a modern small gasoline engine fuel injection system, the load of the engine is estimated based on the measurement of the manifold absolute pressure (MAP) sensor, which took place in the intake manifold. This paper present a more economical approach on estimating the MAP by using only the measurements of the throttle position and engine speed, resulting in lower implementation cost. The estimation was done via two-stage multilayer feed-forward neural network by combining Levenberg-Marquardt (LM) algorithm, Bayesian Regularization (BR) algorithm and Particle Swarm Optimization (PSO) algorithm. Based on the results found in 20 runs, the second variant of the hybrid algorithm yields a better network performance than the first variant of hybrid algorithm, LM, LM with BR and PSO by estimating the MAP closely to the simulated MAP values. By using a valid experimental training data, the estimator network that trained with the second variant of the hybrid algorithm showed the best performance among other algorithms when used in an actual retrofit fuel injection system (RFIS). The performance of the estimator was also validated in steady-state and transient condition by showing a closer MAP estimation to the actual value.

  11. Infectious disease modeling a hybrid system approach

    CERN Document Server

    Liu, Xinzhi

    2017-01-01

    This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.

  12. E-Learning Approach in Teacher Training

    Science.gov (United States)

    Yucel, Seda A.

    2006-01-01

    There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational…

  13. A Hybrid Approach to the Optimization of Multiechelon Systems

    Directory of Open Access Journals (Sweden)

    Paweł Sitek

    2015-01-01

    Full Text Available In freight transportation there are two main distribution strategies: direct shipping and multiechelon distribution. In the direct shipping, vehicles, starting from a depot, bring their freight directly to the destination, while in the multiechelon systems, freight is delivered from the depot to the customers through an intermediate points. Multiechelon systems are particularly useful for logistic issues in a competitive environment. The paper presents a concept and application of a hybrid approach to modeling and optimization of the Multi-Echelon Capacitated Vehicle Routing Problem. Two ways of mathematical programming (MP and constraint logic programming (CLP are integrated in one environment. The strengths of MP and CLP in which constraints are treated in a different way and different methods are implemented and combined to use the strengths of both. The proposed approach is particularly important for the discrete decision models with an objective function and many discrete decision variables added up in multiple constraints. An implementation of hybrid approach in the ECLiPSe system using Eplex library is presented. The Two-Echelon Capacitated Vehicle Routing Problem (2E-CVRP and its variants are shown as an illustrative example of the hybrid approach. The presented hybrid approach will be compared with classical mathematical programming on the same benchmark data sets.

  14. Using hybrid expert system approaches for engineering applications

    Science.gov (United States)

    Allen, R. H.; Boarnet, M. G.; Culbert, C. J.; Savely, R. T.

    1987-01-01

    In this paper, the use of hybrid expert system shells and hybrid (i.e., algorithmic and heuristic) approaches for solving engineering problems is reported. Aspects of various engineering problem domains are reviewed for a number of examples with specific applications made to recently developed prototype expert systems. Based on this prototyping experience, critical evaluations of and comparisons between commercially available tools, and some research tools, in the United States and Australia, and their underlying problem-solving paradigms are made. Characteristics of the implementation tool and the engineering domain are compared and practical software engineering issues are discussed with respect to hybrid tools and approaches. Finally, guidelines are offered with the hope that expert system development will be less time consuming, more effective, and more cost-effective than it has been in the past.

  15. A novel Monte Carlo approach to hybrid local volatility models

    NARCIS (Netherlands)

    A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

  16. A hybrid approach to designing inbound-resupply strategies

    NARCIS (Netherlands)

    Dullaert, Wout; Vernimmen, Bert; Raa, Birger; Witlox, Frank

    A new hybrid approach was developed to determine the optimal inbound-resupply strategy when suppliers ship goods to receivers. The optimal reorder level was calculated on the basis of a simulation of the distribution of demand and the lead time of the various sourcing alternatives. An evolutionary

  17. A hybrid generative-discriminative approach to speaker diarization

    NARCIS (Netherlands)

    Noulas, A.K.; van Kasteren, T.; Kröse, B.J.A.

    2008-01-01

    In this paper we present a sound probabilistic approach to speaker diarization. We use a hybrid framework where a distribution over the number of speakers at each point of a multimodal stream is estimated with a discriminative model. The output of this process is used as input in a generative model

  18. A hybrid agent-based approach for modeling microbiological systems.

    Science.gov (United States)

    Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

    2008-11-21

    Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

  19. Sled Tests Using the Hybrid III Rail Safety ATD and Workstation Tables for Passenger Trains

    Science.gov (United States)

    2017-08-01

    The Hybrid III Rail Safety (H3-RS) anthropomorphic test device (ATD) is a crash test dummy developed in the United Kingdom to evaluate abdomen and lower thorax injuries that occur when passengers impact workstation tables during train accidents. The ...

  20. Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2014-01-01

    Full Text Available Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone’s health. Although there are several ways to measure the body fat percentage (BFP, the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR, artificial neural network (ANN, multivariate adaptive regression splines (MARS, and support vector regression (SVR techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models.

  1. Solving University Scheduling Problem Using Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Aftab Ahmed Shaikh

    2011-10-01

    Full Text Available In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.

  2. Hybrid methodological approach to context-dependent speech recognition

    Directory of Open Access Journals (Sweden)

    Dragiša Mišković

    2017-01-01

    Full Text Available Although the importance of contextual information in speech recognition has been acknowledged for a long time now, it has remained clearly underutilized even in state-of-the-art speech recognition systems. This article introduces a novel, methodologically hybrid approach to the research question of context-dependent speech recognition in human–machine interaction. To the extent that it is hybrid, the approach integrates aspects of both statistical and representational paradigms. We extend the standard statistical pattern-matching approach with a cognitively inspired and analytically tractable model with explanatory power. This methodological extension allows for accounting for contextual information which is otherwise unavailable in speech recognition systems, and using it to improve post-processing of recognition hypotheses. The article introduces an algorithm for evaluation of recognition hypotheses, illustrates it for concrete interaction domains, and discusses its implementation within two prototype conversational agents.

  3. Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

    Science.gov (United States)

    Wallace, Byron C; Noel-Storr, Anna; Marshall, Iain J; Cohen, Aaron M; Smalheiser, Neil R; Thomas, James

    2017-11-01

    Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML. We trained a classifier to discriminate between citations that describe RCTs and those that do not. We then adopted a simple strategy of automatically excluding citations deemed very unlikely to be RCTs by the classifier and deferring to crowdworkers otherwise. Combining ML and crowdsourcing provides a highly sensitive RCT identification strategy (our estimates suggest 95%-99% recall) with substantially less effort (we observed a reduction of around 60%-80%) than relying on manual screening alone. Hybrid crowd-ML strategies warrant further exploration for biomedical curation/annotation tasks. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  4. E-Learning Approach in Teacher Training

    Directory of Open Access Journals (Sweden)

    A. Seda YUCEL

    2006-10-01

    Full Text Available There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational system on platform with Internet, Intranet or computer access. The concept of e-learning has two main subtitles as synchronized (where a group of students and an instructor actualize an online conference meeting in a computer environment an asynchronized (where individuals actualize self-training in computer environments. Students have access to the course contents whenever they want and communicate with their peers or teachers via communication tools such as e-mail and forums. In order the distance learning system to succeed in e-learning, the program should be planned as both synchronized and asynchronized.

  5. Hybrid modeling approach to improve the forecasting capability for the gaseous radionuclide in a nuclear site

    International Nuclear Information System (INIS)

    Jeong, Hyojoon; Hwang, Wontae; Kim, Eunhan; Han, Moonhee

    2012-01-01

    Highlights: ► This study is to improve the reliability of air dispersion modeling. ► Tracer experiments assumed gaseous radionuclides were conducted at a nuclear site. ► The performance of a hybrid modeling combined ISC with ANFIS was investigated.. ► Hybrid modeling approach shows better performance rather than a single ISC model. - Abstract: Predicted air concentrations of radioactive materials are important for an environmental impact assessment for the public health. In this study, the performance of a hybrid modeling combined with the industrial source complex (ISC) model and an adaptive neuro-fuzzy inference system (ANFIS) for predicting tracer concentrations was investigated. Tracer dispersion experiments were performed to produce the field data assuming the accidental release of radioactive material. ANFIS was trained in order that the outputs of the ISC model are similar to the measured data. Judging from the higher correlation coefficients between the measured and the calculated ones, the hybrid modeling approach could be an appropriate technique for an improvement of the modeling capability to predict the air concentrations for radioactive materials.

  6. NEW APPROACHES TO TEACHER PHILOLOGIST TRAINING

    Directory of Open Access Journals (Sweden)

    Margarita Igorevna Postnikova

    2015-03-01

    Full Text Available The article explores the theory of teacher training in the field of Humanities and Pedagogy and the problem of devising academic syllabus for the Bachelor’s Degree in Philology and its compliance to present day requirements.Goa. Devising theoretical grounding to the course content in the academic discipline applying the principle of cross-subject communications, pragmatism and integral approach.Methods. Study of literature, modelling general and specific hypothesis, forecasting the results and processes at various stages of research, study of international documents, genera-lization and synthesis, simulation method.Results. The study presents theoretical grounding to the courses content ‘Language and Literature as Factors in Developing Tolerance’ and ‘Psychology of Interpersonal Relations in the Language Environment’ of the academic module ‘Communication in Modern Multicultural Environment’ within the syllabus ‘Pedagogical Education (philologists’. The study presents new approach to practical training of a language teacher in the context of cross-subject communications and integrated and practical approaches.Scope of application: higher professional education

  7. Upgrading NPP personnel. Competence and training through the systematic approach to training

    International Nuclear Information System (INIS)

    Mautner Markhof, F.

    1998-01-01

    This paper presents the reasons for acceptance of SAT (Systematic Approach to Training) as the best international practice in respect to training of NPP personnel and the differences in comparison to traditional approaches to training. The identification and evaluation of the new training needs, resources and other requirements for implementing SAT are discussed as well as new approaches and existing training capabilities and involvement of Regulatory body in training of NPP personnel. The IAEA Guidebook on NPP Personnel Training (TRS-380) was used a a basis for discussion of the mentioned topics with the emphasis on achieving the best possible training programmes for NPP personnel

  8. E-Learning Approach in Teacher Training

    OpenAIRE

    YUCEL, A. Seda

    2015-01-01

    There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational system on platform with Internet, Intranet or computer access. The concept of e-learning has two main subtitles as synchronized (where a group of stu...

  9. Modular modeling and simulation of hybrid power trains; Modulare Modellbildung und Simulation von hybriden Antriebstraengen

    Energy Technology Data Exchange (ETDEWEB)

    Kelz, Gerald; Hirschberg, Wolfgang [Inst. fuer Fahrzeugtechnik, Technische Univ. Graz (Austria)

    2009-07-01

    The power train of a hybrid vehicle is considerably more complex than that of conventional vehicles. Whilst the topology of a conventional vehicle is normally fixed, the arrangement of the power train components for innovative propulsion systems is a flexible one. The aim is to find those topologies and configurations which are optimal for the intended use. Fuel consumption potentials can be derived with the aid of vehicle longitudinal dynamics simulation. Mostly these simulations are carried out using commercial software which is optimized for the standard topology and do not offer the flexibility to calculate arbitrary topologies. This article covers the modular modeling and the fuel consumption simulation of complex hybrid power trains for topology analysis. A component library for the development of arbitrary hybrid propulsion systems is introduced. The focus lies on an efficient and fast modeling which provides exact simulation results. Several models of power train components are introduced. (orig.)

  10. Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

    Directory of Open Access Journals (Sweden)

    Jui-Yu Wu

    2013-01-01

    Full Text Available Stochastic global optimization (SGO algorithms such as the particle swarm optimization (PSO approach have become popular for solving unconstrained global optimization (UGO problems. The PSO approach, which belongs to the swarm intelligence domain, does not require gradient information, enabling it to overcome this limitation of traditional nonlinear programming methods. Unfortunately, PSO algorithm implementation and performance depend on several parameters, such as cognitive parameter, social parameter, and constriction coefficient. These parameters are tuned by using trial and error. To reduce the parametrization of a PSO method, this work presents two efficient hybrid SGO approaches, namely, a real-coded genetic algorithm-based PSO (RGA-PSO method and an artificial immune algorithm-based PSO (AIA-PSO method. The specific parameters of the internal PSO algorithm are optimized using the external RGA and AIA approaches, and then the internal PSO algorithm is applied to solve UGO problems. The performances of the proposed RGA-PSO and AIA-PSO algorithms are then evaluated using a set of benchmark UGO problems. Numerical results indicate that, besides their ability to converge to a global minimum for each test UGO problem, the proposed RGA-PSO and AIA-PSO algorithms outperform many hybrid SGO algorithms. Thus, the RGA-PSO and AIA-PSO approaches can be considered alternative SGO approaches for solving standard-dimensional UGO problems.

  11. A study on optimization of hybrid drive train using Advanced Vehicle Simulator (ADVISOR)

    Energy Technology Data Exchange (ETDEWEB)

    Same, Adam; Stipe, Alex; Grossman, David; Park, Jae Wan [Department of Mechanical and Aeronautical Engineering, University of California, Davis, One Shields Ave, Davis, CA 95616 (United States)

    2010-10-01

    This study investigates the advantages and disadvantages of three hybrid drive train configurations: series, parallel, and ''through-the-ground'' parallel. Power flow simulations are conducted with the MATLAB/Simulink-based software ADVISOR. These simulations are then applied in an application for the UC Davis SAE Formula Hybrid vehicle. ADVISOR performs simulation calculations for vehicle position using a combined backward/forward method. These simulations are used to study how efficiency and agility are affected by the motor, fuel converter, and hybrid configuration. Three different vehicle models are developed to optimize the drive train of a vehicle for three stages of the SAE Formula Hybrid competition: autocross, endurance, and acceleration. Input cycles are created based on rough estimates of track geometry. The output from these ADVISOR simulations is a series of plots of velocity profile and energy storage State of Charge that provide a good estimate of how the Formula Hybrid vehicle will perform on the given course. The most noticeable discrepancy between the input cycle and the actual velocity profile of the vehicle occurs during deceleration. A weighted ranking system is developed to organize the simulation results and to determine the best drive train configuration for the Formula Hybrid vehicle. Results show that the through-the-ground parallel configuration with front-mounted motors achieves an optimal balance of efficiency, simplicity, and cost. ADVISOR is proven to be a useful tool for vehicle power train design for the SAE Formula Hybrid competition. This vehicle model based on ADVISOR simulation is applicable to various studies concerning performance and efficiency of hybrid drive trains. (author)

  12. A novel hybridization approach for detection of citrus viroids.

    Science.gov (United States)

    Murcia, N; Serra, P; Olmos, A; Duran-Vila, N

    2009-04-01

    Citrus plants are natural hosts of several viroid species all belonging to the family Pospiviroidae. Previous attempts to detect viroids from field-grown species and cultivars yielded erratic results unless analyses were performed using Etrog citron a secondary bio-amplification host. To overcome the use of Etrog citron a number of RT-PCR approaches have been proposed with different degrees of success. Here we report the suitability of an easy to handle northern hybridization protocol for viroid detection of samples collected from field-grown citrus species and cultivars. The protocol involves: (i) Nucleic acid preparations from bark tissue samples collected from field-grown trees regardless of the growing season and storage conditions; (ii) Separation in 5% PAGE or 1% agarose, blotting to membrane and fixing; (iii) Hybridization with viroid-specific DIG-labelled probes and detection with anti-DIG-alkaline phosphatase conjugate and autoradiography with the CSPD substrate. The method has been tested with viroid-infected trees of sweet orange, lemon, mandarin, grapefruit, sour orange, Swingle citrumello, Tahiti lime and Mexican lime. This novel hybridization approach is extremely sensitive, easy to handle and shortens the time needed for reliable viroid indexing tests. The suitability of PCR generated DIG-labelled probes and the sensitivity achieved when the samples are separated and blotted from non-denaturing gels are discussed.

  13. Neuro-Fuzzy Prediction of Cooperation Interaction Profile of Flexible Road Train Based on Hybrid Automaton Modeling

    Directory of Open Access Journals (Sweden)

    Banjanovic-Mehmedovic Lejla

    2016-01-01

    Full Text Available Accurate prediction of traffic information is important in many applications in relation to Intelligent Transport systems (ITS, since it reduces the uncertainty of future traffic states and improves traffic mobility. There is a lot of research done in the field of traffic information predictions such as speed, flow and travel time. The most important research was done in the domain of cooperative intelligent transport system (C-ITS. The goal of this paper is to introduce the novel cooperation behaviour profile prediction through the example of flexible Road Trains useful road cooperation parameter, which contributes to the improvement of traffic mobility in Intelligent Transportation Systems. This paper presents an approach towards the control and cooperation behaviour modelling of vehicles in the flexible Road Train based on hybrid automaton and neuro-fuzzy (ANFIS prediction of cooperation profile of the flexible Road Train. Hybrid automaton takes into account complex dynamics of each vehicle as well as discrete cooperation approach. The ANFIS is a particular class of the ANN family with attractive estimation and learning potentials. In order to provide statistical analysis, RMSE (root mean square error, coefficient of determination (R2 and Pearson coefficient (r, were utilized. The study results suggest that ANFIS would be an efficient soft computing methodology, which could offer precise predictions of cooperative interactions between vehicles in Road Train, which is useful for prediction mobility in Intelligent Transport systems.

  14. Forecasting conditional climate-change using a hybrid approach

    Science.gov (United States)

    Esfahani, Akbar Akbari; Friedel, Michael J.

    2014-01-01

    A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.

  15. A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction

    Science.gov (United States)

    Benvenuto, Federico; Piana, Michele; Campi, Cristina; Massone, Anna Maria

    2018-01-01

    This paper introduces a novel method for flare forecasting, combining prediction accuracy with the ability to identify the most relevant predictive variables. This result is obtained by means of a two-step approach: first, a supervised regularization method for regression, namely, LASSO is applied, where a sparsity-enhancing penalty term allows the identification of the significance with which each data feature contributes to the prediction; then, an unsupervised fuzzy clustering technique for classification, namely, Fuzzy C-Means, is applied, where the regression outcome is partitioned through the minimization of a cost function and without focusing on the optimization of a specific skill score. This approach is therefore hybrid, since it combines supervised and unsupervised learning; realizes classification in an automatic, skill-score-independent way; and provides effective prediction performances even in the case of imbalanced data sets. Its prediction power is verified against NOAA Space Weather Prediction Center data, using as a test set, data in the range between 1996 August and 2010 December and as training set, data in the range between 1988 December and 1996 June. To validate the method, we computed several skill scores typically utilized in flare prediction and compared the values provided by the hybrid approach with the ones provided by several standard (non-hybrid) machine learning methods. The results showed that the hybrid approach performs classification better than all other supervised methods and with an effectiveness comparable to the one of clustering methods; but, in addition, it provides a reliable ranking of the weights with which the data properties contribute to the forecast.

  16. Parameter Design and Energy Control of the Power Train in a Hybrid Electric Boat

    Directory of Open Access Journals (Sweden)

    Diju Gao

    2017-07-01

    Full Text Available With the continuous development worldwide of the inland shipping industry, emissions to the atmosphere have become a serious threat in terms of pollution. Hybrid power technology is an important means for reducing pollution due to emissions from ships. This paper considers a power train series in a hybrid electric inland waterway boat. From the analysis of the structure and principle of the power train, the parameter design for its key devices is presented, and a novel energy control strategy is proposed. Navigation experience shows that the proposed design method and control strategy are useful and satisfactory.

  17. A hybrid approach for efficient anomaly detection using metaheuristic methods

    Directory of Open Access Journals (Sweden)

    Tamer F. Ghanem

    2015-07-01

    Full Text Available Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

  18. Approaches to Low Fuel Regression Rate in Hybrid Rocket Engines

    Directory of Open Access Journals (Sweden)

    Dario Pastrone

    2012-01-01

    Full Text Available Hybrid rocket engines are promising propulsion systems which present appealing features such as safety, low cost, and environmental friendliness. On the other hand, certain issues hamper the development hoped for. The present paper discusses approaches addressing improvements to one of the most important among these issues: low fuel regression rate. To highlight the consequence of such an issue and to better understand the concepts proposed, fundamentals are summarized. Two approaches are presented (multiport grain and high mixture ratio which aim at reducing negative effects without enhancing regression rate. Furthermore, fuel material changes and nonconventional geometries of grain and/or injector are presented as methods to increase fuel regression rate. Although most of these approaches are still at the laboratory or concept scale, many of them are promising.

  19. Hybrid Decision-making Method for Emergency Response System of Unattended Train Operation Metro

    Directory of Open Access Journals (Sweden)

    Bobo Zhao

    2016-04-01

    Full Text Available Suitable selection of the emergency alternatives is a critical issue in emergency response system of Unattended Train Operation (UTO metro system of China. However, there is no available method for dispatcher group in Operating Control Center (OCC to evaluate the decision under emergency situation. It was found that the emergency decision making in UTO metro system is relative with the preferences and the importance of multi-dispatcher in emergency. Regarding these factors, this paper presents a hybrid method to determinate the priority weights of emergency alternatives, which aggregates the preference matrix by constructing the emergency response task model based on the Weighted Ordered Weighted Averaging (WOWA operator. This calculation approach derives the importance weights depending on the dispatcher emergency tasks and integrates it into the Ordered Weighted Averaging (OWA operator weights based on a fuzzy membership relation. A case from train fire is given to demonstrate the feasibility and practicability of the proposed methods for Group Multi-Criteria Decision Making (GMCDM in emergency management of UTO metro system. The innovation of this research is paving the way for a systematic emergency decision-making solution which connects the automatic metro emergency response system with the GMCDM theory.

  20. A hybrid approach for minimizing makespan in permutation flowshop scheduling

    DEFF Research Database (Denmark)

    Govindan, Kannan; Balasundaram, R.; Baskar, N.

    2017-01-01

    This work proposes a hybrid approach for solving traditional flowshop scheduling problems to reduce the makespan (total completion time). To solve scheduling problems, a combination of Decision Tree (DT) and Scatter Search (SS) algorithms are used. Initially, the DT is used to generate a seed...... solution which is then given input to the SS to obtain optimal / near optimal solutions of makespan. The DT used the entropy function to convert the given problem into a tree structured format / set of rules. The SS provides an extensive investigation of the search space through diversification...

  1. Hybrid closure of atrial septal defect: A modified approach

    Directory of Open Access Journals (Sweden)

    Kshitij Sheth

    2015-01-01

    Full Text Available A 3.5-year-old girl underwent transcatheter closure of patent ductus arteriosus in early infancy during which time her secundum atrial septal defect (ASD was left alone. When she came for elective closure of ASD, she was found to have bilaterally blocked femoral veins. The defect was successfully closed with an Amplatzer septal occluder (ASO; St. Jude Medical, Plymouth, MN, USA using a hybrid approach via a sub-mammary mini-thoracotomy incision without using cardiopulmonary bypass. At the end of 1-year follow-up, the child is asymptomatic with device in a stable position without any residual shunt.

  2. A hybrid simulation approach for integrating safety behavior into construction planning: An earthmoving case study.

    Science.gov (United States)

    Goh, Yang Miang; Askar Ali, Mohamed Jawad

    2016-08-01

    One of the key challenges in improving construction safety and health is the management of safety behavior. From a system point of view, workers work unsafely due to system level issues such as poor safety culture, excessive production pressure, inadequate allocation of resources and time and lack of training. These systemic issues should be eradicated or minimized during planning. However, there is a lack of detailed planning tools to help managers assess the impact of their upstream decisions on worker safety behavior. Even though simulation had been used in construction planning, the review conducted in this study showed that construction safety management research had not been exploiting the potential of simulation techniques. Thus, a hybrid simulation framework is proposed to facilitate integration of safety management considerations into construction activity simulation. The hybrid framework consists of discrete event simulation (DES) as the core, but heterogeneous, interactive and intelligent (able to make decisions) agents replace traditional entities and resources. In addition, some of the cognitive processes and physiological aspects of agents are captured using system dynamics (SD) approach. The combination of DES, agent-based simulation (ABS) and SD allows a more "natural" representation of the complex dynamics in construction activities. The proposed hybrid framework was demonstrated using a hypothetical case study. In addition, due to the lack of application of factorial experiment approach in safety management simulation, the case study demonstrated sensitivity analysis and factorial experiment to guide future research. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. THE ARCHITECTURE OF MULTI-COMPONENT DISTRIBUTED HYBRID EXPERT TRAINING SYSTEM

    Directory of Open Access Journals (Sweden)

    Оleh Shevchuk

    2016-09-01

    Full Text Available The paper reports on the design of a multi-component architecture of distributed hybrid expert training system that can be used for the study of knowledge base of both internal and external expert systems and artificial intelligence systems that are distributed on Internet servers and other computer networks. Expert training system is based on three groups of basic principles: cybernetic, reflecting experience of previous research of systems of artificial intelligence, expert training systems; pedagogical, determining the principles, on which pedagogical design and use of expert training systems are based; psychological, determining preconditious and understanding of pupils psychics, on which the processes of design and use of expert training systems in professional training of future specialists are based.It accounts for the efficient training through the distributed knowledge via the Internet, which greatly increases the didactic capabilities of the system.

  4. Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach.

    Directory of Open Access Journals (Sweden)

    Kristen Feher

    Full Text Available Heterosis, the greater vigor of hybrids compared to their parents, has been exploited in maize breeding for more than 100 years to produce ever better performing elite hybrids of increased yield. Despite extensive research, the underlying mechanisms shaping the extent of heterosis are not well understood, rendering the process of selecting an optimal set of parental lines tedious. This study is based on a dataset consisting of 112 metabolite levels in young roots of four parental maize inbred lines and their corresponding twelve hybrids, along with the roots' biomass as a heterotic trait. Because the parental biomass is a poor predictor for hybrid biomass, we established a model framework to deduce the biomass of the hybrid from metabolite profiles of its parental lines. In the proposed framework, the hybrid metabolite levels are expressed relative to the parental levels by incorporating the standard concept of additivity/dominance, which we name the Combined Relative Level (CRL. Our modeling strategy includes a feature selection step on the parental levels which are demonstrated to be predictive of CRL across many hybrid metabolites. We demonstrate that these selected parental metabolites are further predictive of hybrid biomass. Our approach directly employs the diallel structure in a multivariate fashion, whereby we attempt to not only predict macroscopic phenotype (biomass, but also molecular phenotype (metabolite profiles. Therefore, our study provides the first steps for further investigations of the genetic determinants to metabolism and, ultimately, growth. Finally, our success on the small-scale experiments implies a valid strategy for large-scale experiments, where parental metabolite profiles may be used together with profiles of selected hybrids as a training set to predict biomass of all possible hybrids.

  5. An Innovative Solution for Suburban Railroad Transportation: The Gas Turbine-Hybrid Train

    OpenAIRE

    Capata, Roberto; Sciubba, Enrico

    2010-01-01

    The paper reports the latest results of a study conducted on a hybrid train in which a gas turbine, operating in several alternative control modes (fixed point, on-off or load-following), generates the electrical energy for recharging a battery package and for driving the electric motors of a suburban train. The model, originally developed for automotive applications, has been validated by experimental tests performed on an ELLIOTT TA-45 GT group in the ENEA-Casaccia Research Center....

  6. Hybrid simulation: bringing motivation to the art of teamwork training in the operating room.

    Science.gov (United States)

    Kjellin, A; Hedman, L; Escher, C; Felländer-Tsai, L

    2014-12-01

    Crew resource management-based operating room team training will be an evident part of future surgical training. Hybrid simulation in the operating room enables the opportunity for trainees to perform higher fidelity training of technical and non-technical skills in a realistic context. We focus on situational motivation and self-efficacy, two important factors for optimal learning in light of a prototype course for teams of residents in surgery and anesthesiology and nurses. Authentic operating room teams consisting of residents in anesthesia (n = 2), anesthesia nurses (n = 3), residents in surgery (n = 2), and scrub nurses (n = 6) were, during a one-day course, exposed to four different scenarios. Their situational motivation was self-assessed (ranging from 1 = does not correspond at all to 7 = corresponds exactly) immediately after training, and their self-efficacy (graded from 1 to 7) before and after training. Training was performed in a mock-up operating theater equipped with a hybrid patient simulator (SimMan 3G; Laerdal) and a laparoscopic simulator (Lap Mentor Express; Simbionix). The functionality of the systematic hybrid procedure simulation scenario was evaluated by an exit questionnaire (graded from 1 = disagree entirely to 5 = agree completely). The trainees were mostly intrinsically motivated, engaged for their own sake, and had a rather great degree of self-determination toward the training situation. Self-efficacy among the team members improved significantly from 4 to 6 (median). Overall evaluation showed very good result with a median grading of 5. We conclude that hybrid simulation is feasible and has the possibility to train an authentic operating team in order to improve individual motivation and confidence. © The Finnish Surgical Society 2014.

  7. An Adaptive and Hybrid Approach for Revisiting the Visibility Pipeline

    Directory of Open Access Journals (Sweden)

    Ícaro Lins Leitão da Cunha

    2016-04-01

    Full Text Available We revisit the visibility problem, which is traditionally known in Computer Graphics and Vision fields as the process of computing a (potentially visible set of primitives in the computational model of a scene. We propose a hybrid solution that uses a dry structure (in the sense of data reduction, a triangulation of the type J1a, to accelerate the task of searching for visible primitives. We came up with a solution that is useful for real-time, on-line, interactive applications as 3D visualization. In such applications the main goal is to load the minimum amount of primitives from the scene during the rendering stage, as possible. For this purpose, our algorithm executes the culling by using a hybrid paradigm based on viewing-frustum, back-face culling and occlusion models. Results have shown substantial improvement over these traditional approaches if applied separately. This novel approach can be used in devices with no dedicated processors or with low processing power, as cell phones or embedded displays, or to visualize data through the Internet, as in virtual museums applications.

  8. A Hybrid Genetic Algorithm Approach for Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Sydulu Maheswarapu

    2011-08-01

    Full Text Available This paper puts forward a reformed hybrid genetic algorithm (GA based approach to the optimal power flow. In the approach followed here, continuous variables are designed using real-coded GA and discrete variables are processed as binary strings. The outcomes are compared with many other methods like simple genetic algorithm (GA, adaptive genetic algorithm (AGA, differential evolution (DE, particle swarm optimization (PSO and music based harmony search (MBHS on a IEEE30 bus test bed, with a total load of 283.4 MW. Its found that the proposed algorithm is found to offer lowest fuel cost. The proposed method is found to be computationally faster, robust, superior and promising form its convergence characteristics.

  9. Development of a hybrid strength training technique for paretic lower-limb muscles

    NARCIS (Netherlands)

    Bennett, T. L.; Glaser, R. M.; Janssen, T. W J; Couch, W. P.; Herr, C. J.; Almeyda, J. W.; Petrofsky, S. H.; Akuthota, P.

    1996-01-01

    A hybrid resistance exercise technique for strength training of patients with lower-limb paresis was developed. It consists of electrical stimulation-induced contractions (ESIC) superimposed on voluntary contractions to increase recruitment of motor units and the functional load capability of

  10. Training versus Education: eLearning, Hybrid, and Face-to-Face Modalities - a Participatory Debate

    Directory of Open Access Journals (Sweden)

    Risa Blair

    2016-10-01

    Full Text Available Is training education or is education training? Universities and organizations treat training and education synonymously, but it is worth exploring the differences. Universities are scrambling to standardize a preferred delivery method of education and training. With the blended modalities of eLearning, face-to-face, and hybrid learning, the educational delivery seems to be equalizing. The disruptive shift with technology in education or training is complicated by the expectations of our millennial, Gen Y, and Gen Z students. As an added pressure at the university level, even more importantly, the expectation of the administration and the accrediting bodies keep changing the 'play book' on requirements. Given the ever changing complexities of today's paradigm-shift in education and learning, we explored the complexities of navigating the delivery methods to achieve educational goals in higher education or training goals in corporate America.

  11. Development of a power train for the hybrid automobile - the Civic IMA

    Energy Technology Data Exchange (ETDEWEB)

    Matsuki, Masato; Sato, Toshiyuki; Wakashiro, Teruo; Kaku, Toshiaki; Kamiyama, Toshihiro; Kanda, Masahiro [Tochigi R and D Center (Japan); Brachmann, T. [Tochigi Offenbach R und D Center (Germany)

    2003-07-01

    The Civic Hybrid was developed as a compact passenger hybrid car that achieves both low fuel consumption and cleaner operation from the viewpoints of preserving the global environment and conserving resources. The engine has been improved for Hybrid applications, which were added to the base i-DSI, 4-cylinder, 1.3-liter SOHC, 2-ignition plugs/cylinder engine mounted in the Honda 'Jazz'. In addition, the cylinder idling system has been adopted to increase the regenerated energy during deceleration. The hybrid system is based on the Honda IMA system, and the maximum regenerative torque has been increased by approximately 30% by improving the magnetic circuits of an ultra-thin DC brushless motor and adopting a new rotor manufacturing method. Fuel economy is improved by a new hybrid power train, thus achieving low fuel consumption of 4.9 1/100 km in the European UDC+EUCD combined mode by at the same time meeting EURO IV standards. The power control unit, which is the IMA system control unit, was downsized and located behind the rear seat, thus ensuring comparable trunk capacity to the base vehicle of the Civic 4-Door. Hybrid vehicles have a lot to offer. This paper introduces evolutionary developments of Hybrid vehicles within the Honda Motor Company. (orig.)

  12. Genetic algorithm and neural network hybrid approach for job-shop scheduling

    OpenAIRE

    Zhao, Kai; Yang, Shengxiang; Wang, Dingwei

    1998-01-01

    Copyright @ 1998 ACTA Press This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach for job-shop scheduling with respect to the quality of solutions and ...

  13. Systematic Approach to Research Training: Benefits for Counseling Practice.

    Science.gov (United States)

    Loughead, Teri A.; And Others

    1991-01-01

    Synthesizes developments concerning research training in graduate counselor education and presents a systematic approach for training master's and doctoral students in mental health counseling to assimilate, use, and perform research. Suggests diversity of research training strategies for implementation in counselor preparation programs.…

  14. Radiation protection training programmes Spanish approach

    International Nuclear Information System (INIS)

    Arboli, M. Marco; Suarez, M. Rodriguez; Cabrera, S. Falcon

    2002-01-01

    Radiation Protection Programmes are being considered the best way to promote safety culture and to spread and propagate European basic safety standards. It is widely accepted that training is an important tool to upgrade competence for radiation exposed workers. The Spanish Radiation Protection Education and Training Programmes provide a solid and integrated educational model, which takes into account the variety of applied fields, the different levels of responsibilities, the technological and methodological advances, as well as the international tendencies. The needs for a specialised training on Radiation Protection (RP) for exposed workers appears into the Spanish regulation in 1964. National initial training programmes are well established since 1972. Individual certifications, based on personal licences are required for exposed workers. The Spanish regulation also includes continuous and on the job RP training. The educational programmes are being continuously updating and improving. CIEMAT plays an important role in RP Spanish training, improving and modifying the previous RP courses and developing new programmes in order to complete the RP training levels. To achieve Radiation Protection objectives, new technological media for educational methods and material are taking into account. Nevertheless, Spanish RP education and training model has to be improved in some aspects. The purpose of this paper is to analyse the situation and the future needs to be considered in order to complete the RP training processes

  15. Bias modification training can alter approach bias and chocolate consumption.

    Science.gov (United States)

    Schumacher, Sophie E; Kemps, Eva; Tiggemann, Marika

    2016-01-01

    Recent evidence has demonstrated that bias modification training has potential to reduce cognitive biases for attractive targets and affect health behaviours. The present study investigated whether cognitive bias modification training could be applied to reduce approach bias for chocolate and affect subsequent chocolate consumption. A sample of 120 women (18-27 years) were randomly assigned to an approach-chocolate condition or avoid-chocolate condition, in which they were trained to approach or avoid pictorial chocolate stimuli, respectively. Training had the predicted effect on approach bias, such that participants trained to approach chocolate demonstrated an increased approach bias to chocolate stimuli whereas participants trained to avoid such stimuli showed a reduced bias. Further, participants trained to avoid chocolate ate significantly less of a chocolate muffin in a subsequent taste test than participants trained to approach chocolate. Theoretically, results provide support for the dual process model's conceptualisation of consumption as being driven by implicit processes such as approach bias. In practice, approach bias modification may be a useful component of interventions designed to curb the consumption of unhealthy foods. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. A Hybrid Satellite-Terrestrial Approach to Aeronautical Communication Networks

    Science.gov (United States)

    Kerczewski, Robert J.; Chomos, Gerald J.; Griner, James H.; Mainger, Steven W.; Martzaklis, Konstantinos S.; Kachmar, Brian A.

    2000-01-01

    Rapid growth in air travel has been projected to continue for the foreseeable future. To maintain a safe and efficient national and global aviation system, significant advances in communications systems supporting aviation are required. Satellites will increasingly play a critical role in the aeronautical communications network. At the same time, current ground-based communications links, primarily very high frequency (VHF), will continue to be employed due to cost advantages and legacy issues. Hence a hybrid satellite-terrestrial network, or group of networks, will emerge. The increased complexity of future aeronautical communications networks dictates that system-level modeling be employed to obtain an optimal system fulfilling a majority of user needs. The NASA Glenn Research Center is investigating the current and potential future state of aeronautical communications, and is developing a simulation and modeling program to research future communications architectures for national and global aeronautical needs. This paper describes the primary requirements, the current infrastructure, and emerging trends of aeronautical communications, including a growing role for satellite communications. The need for a hybrid communications system architecture approach including both satellite and ground-based communications links is explained. Future aeronautical communication network topologies and key issues in simulation and modeling of future aeronautical communications systems are described.

  17. A Hybrid Soft Computing Approach for Subset Problems

    Directory of Open Access Journals (Sweden)

    Broderick Crawford

    2013-01-01

    Full Text Available Subset problems (set partitioning, packing, and covering are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S can be partitioned into smaller subsets. All items in S must be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions and set covering (all items must be contained in at least one partition. Here, we present a hybrid solver based on ant colony optimization (ACO combined with arc consistency for solving this kind of problems. ACO is a swarm intelligence metaheuristic inspired on ants behavior when they search for food. It allows to solve complex combinatorial problems for which traditional mathematical techniques may fail. By other side, in constraint programming, the solving process of Constraint Satisfaction Problems can dramatically reduce the search space by means of arc consistency enforcing constraint consistencies either prior to or during search. Our hybrid approach was tested with set covering and set partitioning dataset benchmarks. It was observed that the performance of ACO had been improved embedding this filtering technique in its constructive phase.

  18. A hybrid data compression approach for online backup service

    Science.gov (United States)

    Wang, Hua; Zhou, Ke; Qin, MingKang

    2009-08-01

    With the popularity of Saas (Software as a service), backup service has becoming a hot topic of storage application. Due to the numerous backup users, how to reduce the massive data load is a key problem for system designer. Data compression provides a good solution. Traditional data compression application used to adopt a single method, which has limitations in some respects. For example data stream compression can only realize intra-file compression, de-duplication is used to eliminate inter-file redundant data, compression efficiency cannot meet the need of backup service software. This paper proposes a novel hybrid compression approach, which includes two levels: global compression and block compression. The former can eliminate redundant inter-file copies across different users, the latter adopts data stream compression technology to realize intra-file de-duplication. Several compressing algorithms were adopted to measure the compression ratio and CPU time. Adaptability using different algorithm in certain situation is also analyzed. The performance analysis shows that great improvement is made through the hybrid compression policy.

  19. ADHD in Preschool: Approaches and Teacher Training

    Science.gov (United States)

    Singh, Ajay; Squires, Jane

    2014-01-01

    Due to the prevalence of ADHD, there is a need for early intervention at the preschool level to improve children's chance of academic success in later years. Yet few preschool teachers are trained to meet the challenges children with ADHD present. This paper gives a rationale and curriculum for teacher training in ADHD, with an emphasis on Social…

  20. Innovative Approaches in the Training of Lexicographers

    African Journals Online (AJOL)

    What kind of in-service training should the trainee lexicographer undergo if he or she ... In answer to the question which qualities a good definer should have, Landau ... valuable practical training, but I know of none that offer such opportunities.

  1. An Instructional Systems Approach or FAA Student Centered Training.

    Science.gov (United States)

    Federal Aviation Administration (DOT), Washington, DC.

    The Federal Aviation Administration (FAA) Academy has been using a systems approach as part of its training program since 1969. This booklet describes the general characteristics of an instructional system and explains the steps the FAA goes through in implementing the approach. These steps are: 1) recognize a need for training, 2) specify the…

  2. Dry Port Location Problem: A Hybrid Multi-Criteria Approach

    Directory of Open Access Journals (Sweden)

    BENTALEB Fatimazahra

    2016-03-01

    Full Text Available Choosing a location for a dry port is a problem which becomes more essential and crucial. This study deals with the problem of locating dry ports. On this matter, a model combining multi-criteria (MACBETH and mono-criteria (BARYCENTER methods to find a solution to dry port location problem has been proposed. In the first phase, a systematic literature review was carried out on dry port location problem and then a methodological classification was presented for this research. In the second phase, a hybrid multi-criteria approach was developed in order to determine the best dry port location taking different criteria into account. A Computational practice and a qualitative analysis from a case study in the Moroccan context have been provided. The results show that the optimal location is very convenient with the geographical region and the government policies.

  3. Attention-level transitory response: a novel hybrid BCI approach

    Science.gov (United States)

    Diez, Pablo F.; Garcés Correa, Agustina; Orosco, Lorena; Laciar, Eric; Mut, Vicente

    2015-10-01

    Objective. People with disabilities may control devices such as a computer or a wheelchair by means of a brain-computer interface (BCI). BCI based on steady-state visual evoked potentials (SSVEP) requires visual stimulation of the user. However, this SSVEP-based BCI suffers from the ‘Midas touch effect’, i.e., the BCI can detect an SSVEP even when the user is not gazing at the stimulus. Then, these incorrect detections deteriorate the performance of the system, especially in asynchronous BCI because ongoing EEG is classified. In this paper, a novel transitory response of the attention-level of the user is reported. It was used to develop a hybrid BCI (hBCI). Approach. Three methods are proposed to detect the attention-level of the user. They are based on the alpha rhythm and theta/beta rate. The proposed hBCI scheme is presented along with these methods. Hence, the hBCI sends a command only when the user is at a high-level of attention, or in other words, when the user is really focused on the task being performed. The hBCI was tested over two different EEG datasets. Main results. The performance of the hybrid approach is superior to the standard one. Improvements of 20% in accuracy and 10 bits min-1 are reported. Moreover, the attention-level is extracted from the same EEG channels used in SSVEP detection and this way, no extra hardware is needed. Significance. A transitory response of EEG signal is used to develop the attention-SSVEP hBCI which is capable of reducing the Midas touch effect.

  4. Hybrid x-space: a new approach for MPI reconstruction.

    Science.gov (United States)

    Tateo, A; Iurino, A; Settanni, G; Andrisani, A; Stifanelli, P F; Larizza, P; Mazzia, F; Mininni, R M; Tangaro, S; Bellotti, R

    2016-06-07

    Magnetic particle imaging (MPI) is a new medical imaging technique capable of recovering the distribution of superparamagnetic particles from their measured induced signals. In literature there are two main MPI reconstruction techniques: measurement-based (MB) and x-space (XS). The MB method is expensive because it requires a long calibration procedure as well as a reconstruction phase that can be numerically costly. On the other side, the XS method is simpler than MB but the exact knowledge of the field free point (FFP) motion is essential for its implementation. Our simulation work focuses on the implementation of a new approach for MPI reconstruction: it is called hybrid x-space (HXS), representing a combination of the previous methods. Specifically, our approach is based on XS reconstruction because it requires the knowledge of the FFP position and velocity at each time instant. The difference with respect to the original XS formulation is how the FFP velocity is computed: we estimate it from the experimental measurements of the calibration scans, typical of the MB approach. Moreover, a compressive sensing technique is applied in order to reduce the calibration time, setting a fewer number of sampling positions. Simulations highlight that HXS and XS methods give similar results. Furthermore, an appropriate use of compressive sensing is crucial for obtaining a good balance between time reduction and reconstructed image quality. Our proposal is suitable for open geometry configurations of human size devices, where incidental factors could make the currents, the fields and the FFP trajectory irregular.

  5. HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.

    Science.gov (United States)

    Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

    2017-12-01

    For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm. HAMDA took not only network structure and information propagation but also node attribution into consideration, resulting in a satisfactory prediction performance. Specifically, HAMDA obtained AUCs of 0.9035 and 0.8395 in the frameworks of global and local leave-one-out cross validation, respectively. Meanwhile, HAMDA also achieved good performance with AUC of 0.8965 ± 0.0012 in 5-fold cross validation. Additionally, we conducted case studies about three important human cancers for performance evaluation of HAMDA. As a result, 90% (Lymphoma), 86% (Prostate Cancer) and 92% (Kidney Cancer) of top 50 predicted miRNAs were confirmed by recent experiment literature, which showed the reliable prediction ability of HAMDA. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

    Science.gov (United States)

    Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

    2016-01-01

    Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

  7. An energy management approach of hybrid vehicles using traffic preview information for energy saving

    International Nuclear Information System (INIS)

    Zheng, Chunhua; Xu, Guoqing; Xu, Kun; Pan, Zhongming; Liang, Quan

    2015-01-01

    Highlights: • Energy management approach of hybrid vehicles using traffic preview information. • Vehicle velocity profile and fuel consumption are optimized at the same time. • It is proved that a further energy saving is achieved by the proposed approach. • The proposed approach is useful especially for autonomous hybrid vehicles. - Abstract: The traffic preview information is very helpful for hybrid vehicles when distributing the power requirement of the vehicle to power sources and when determining the next driving route of the vehicle. In this research, an energy management approach for hybrid vehicles is proposed, which optimizes the vehicle velocity profile while minimizing the fuel consumption with the help of the traffic preview information, so that a further energy saving for hybrid vehicles can be achieved. The Pontryagin’s Minimum Principle (PMP) is adopted on the proposed approach. A fuel cell hybrid vehicle (FCHV) is selected as an example, and the proposed energy management approach is applied to the FCHV in a computer simulation environment for the offline and online cases respectively. Simulation results show that the fuel economy of the FCHV is improved by the proposed energy management approach compared to a benchmark case where the driving cycle is fixed and only the hybrid power split (allocation) ratio is optimized. The proposed energy management approach is useful especially for the autonomous hybrid vehicles.

  8. The hybrid thermography approach applied to architectural structures

    Science.gov (United States)

    Sfarra, S.; Ambrosini, D.; Paoletti, D.; Nardi, I.; Pasqualoni, G.

    2017-07-01

    This work contains an overview of infrared thermography (IRT) method and its applications relating to the investigation of architectural structures. In this method, the passive approach is usually used in civil engineering, since it provides a panoramic view of the thermal anomalies to be interpreted also thanks to the use of photographs focused on the region of interest (ROI). The active approach, is more suitable for laboratory or indoor inspections, as well as for objects having a small size. The external stress to be applied is thermal, coming from non-natural apparatus such as lamps or hot / cold air jets. In addition, the latter permits to obtain quantitative information related to defects not detectable to the naked eyes. Very recently, the hybrid thermography (HIRT) approach has been introduced to the attention of the scientific panorama. It can be applied when the radiation coming from the sun, directly arrives (i.e., possibly without the shadow cast effect) on a surface exposed to the air. A large number of thermograms must be collected and a post-processing analysis is subsequently applied via advanced algorithms. Therefore, an appraisal of the defect depth can be obtained passing through the calculation of the combined thermal diffusivity of the materials above the defect. The approach is validated herein by working, in a first stage, on a mosaic sample having known defects while, in a second stage, on a Church built in L'Aquila (Italy) and covered with a particular masonry structure called apparecchio aquilano. The results obtained appear promising.

  9. Ping-Pong Beam Training with Hybrid Digital-Analog Antenna Arrays

    DEFF Research Database (Denmark)

    Manchón, Carles Navarro; Carvalho, Elisabeth De; Andersen, Jørgen Bach

    2017-01-01

    In this article we propose an iterative training scheme that approximates optimal beamforming between two transceivers equipped with hybrid digital-analog antenna arrays. Inspired by methods proposed for digital arrays that exploit algebraic power iterations, the proposed training procedure...... is based on a series of alternate (ping-pong) transmissions between the two devices over a reciprocal channel. During the transmissions, the devices updates their digital beamformers by conjugation and normalization operations on the received digital signal, while the analog beamformers are progressively...

  10. Hybrid Force Control Based on ICMAC for an Astronaut Rehabilitative Training Robot

    OpenAIRE

    Lixun Zhang; Yupeng Zou; Lan Wang; Xinping Pei

    2012-01-01

    A novel Astronaut Rehabilitative Training Robot (ART) based on a cable‐driven mechanism is represented in this paper. ART, a typical passive force servo system, can help astronauts to bench press in a microgravity environment. The purpose of this paper is to design controllers to eliminate the surplus force caused by an astronaut’s active movements. Based on the dynamics modelling of the cable‐driven unit, a hybrid force controller based on improved credit assignment CMAC (ICMAC) is presented...

  11. Informatics Approach to Improving Surgical Skills Training

    Science.gov (United States)

    Islam, Gazi

    2013-01-01

    Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of…

  12. Housekeeping. An Approach to Housekeeping Training.

    Science.gov (United States)

    Hotel and Catering Industry Training Board, Wembley (England).

    This booklet examines the training required by staff employed in housekeeping departments in the hotel and catering industry. It details specifications of particular tasks--baths/cloakrooms; service pantries and utility rooms; beds; furniture/fittings; floors/walls and ceilings; carpets/upholstery/soft furnishings; linen handling; linen room work;…

  13. Living with a systematic approach to training. A personal experience

    International Nuclear Information System (INIS)

    Duarte, R.F.

    2002-01-01

    The Systematic Approach to Training (SAT) plays an important role in the safe operation of a nuclear power plant. It can often be seen as the answer to all training needs but it can sometimes fall victim to its own rigidity and inertia. This paper outlines the personal experiences and conceptual models of a former Human Resources Manager with responsibility for both pre operational and operational training. (author)

  14. A Simulation-Based Approach to Training Operational Cultural Competence

    Science.gov (United States)

    Johnson, W. Lewis

    2010-01-01

    Cultural knowledge and skills are critically important for military operations, emergency response, or any job that involves interaction with a culturally diverse population. However, it is not obvious what cultural knowledge and skills need to be trained, and how to integrate that training with the other training that trainees must undergo. Cultural training needs to be broad enough to encompass both regional (culture-specific) and cross-cultural (culture-general) competencies, yet be focused enough to result in targeted improvements in on-the-job performance. This paper describes a comprehensive instructional development methodology and training technology framework that focuses cultural training on operational needs. It supports knowledge acquisition, skill acquisition, and skill transfer. It supports both training and assessment, and integrates with other aspects of operational skills training. Two training systems will be used to illustrate this approach: the Virtual Cultural Awareness Trainer (VCAT) and the Tactical Dari language and culture training system. The paper also discusses new and emerging capabilities that are integrating cultural competence training more strongly with other aspects of training and mission rehearsal.

  15. Common modelling approaches for training simulators for nuclear power plants

    International Nuclear Information System (INIS)

    1990-02-01

    Training simulators for nuclear power plant operating staff have gained increasing importance over the last twenty years. One of the recommendations of the 1983 IAEA Specialists' Meeting on Nuclear Power Plant Training Simulators in Helsinki was to organize a Co-ordinated Research Programme (CRP) on some aspects of training simulators. The goal statement was: ''To establish and maintain a common approach to modelling for nuclear training simulators based on defined training requirements''. Before adapting this goal statement, the participants considered many alternatives for defining the common aspects of training simulator models, such as the programming language used, the nature of the simulator computer system, the size of the simulation computers, the scope of simulation. The participants agreed that it was the training requirements that defined the need for a simulator, the scope of models and hence the type of computer complex that was required, the criteria for fidelity and verification, and was therefore the most appropriate basis for the commonality of modelling approaches. It should be noted that the Co-ordinated Research Programme was restricted, for a variety of reasons, to consider only a few aspects of training simulators. This report reflects these limitations, and covers only the topics considered within the scope of the programme. The information in this document is intended as an aid for operating organizations to identify possible modelling approaches for training simulators for nuclear power plants. 33 refs

  16. A Comparison of HPT and Traditional Training Approaches.

    Science.gov (United States)

    Kretz, Richard

    2002-01-01

    Focuses on the comparative use of training from human performance technology (HPT) and traditional training perspectives, based on taxonomy. Concludes that the primary difference is a holistic systems performance improvement approach by eliminating barriers with HPT versus reaction or response to a set of business objectives in traditional…

  17. A hybrid stochastic approach for self-location of wireless sensors in indoor environments.

    Science.gov (United States)

    Lloret, Jaime; Tomas, Jesus; Garcia, Miguel; Canovas, Alejandro

    2009-01-01

    Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS) in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

  18. A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments

    Directory of Open Access Journals (Sweden)

    Alejandro Canovas

    2009-05-01

    Full Text Available Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

  19. Strategic planning approach to nuclear training

    International Nuclear Information System (INIS)

    Mills, R.J.

    1985-01-01

    Detroit Edison Company's Nuclear Training group used an organizational planning process that yielded significant results in 1984. At the heart of the process was a concept called the Driving Force which served as the basis for the development of goals, objectives, and action plants. A key ingredient of the success of the planning process was the total, voluntary participation by all members of the organization

  20. Mobile phone use while driving: a hybrid modeling approach.

    Science.gov (United States)

    Márquez, Luis; Cantillo, Víctor; Arellana, Julián

    2015-05-01

    The analysis of the effects that mobile phone use produces while driving is a topic of great interest for the scientific community. There is consensus that using a mobile phone while driving increases the risk of exposure to traffic accidents. The purpose of this research is to evaluate the drivers' behavior when they decide whether or not to use a mobile phone while driving. For that, a hybrid modeling approach that integrates a choice model with the latent variable "risk perception" was used. It was found that workers and individuals with the highest education level are more prone to use a mobile phone while driving than others. Also, "risk perception" is higher among individuals who have been previously fined and people who have been in an accident or almost been in an accident. It was also found that the tendency to use mobile phones while driving increases when the traffic speed reduces, but it decreases when the fine increases. Even though the urgency of the phone call is the most important explanatory variable in the choice model, the cost of the fine is an important attribute in order to control mobile phone use while driving. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Agricultural Tractor Selection: A Hybrid and Multi-Attribute Approach

    Directory of Open Access Journals (Sweden)

    Jorge L. García-Alcaraz

    2016-02-01

    Full Text Available Usually, agricultural tractor investments are assessed using traditional economic techniques that only involve financial attributes, resulting in reductionist evaluations. However, tractors have qualitative and quantitative attributes that must be simultaneously integrated into the evaluation process. This article reports a hybrid and multi-attribute approach to assessing a set of agricultural tractors based on AHP-TOPSIS. To identify the attributes in the model, a survey including eighteen attributes was given to agricultural machinery salesmen and farmers for determining their importance. The list of attributes was presented to a decision group for a case of study, and their importance was estimated using AHP and integrated into the TOPSIS technique. In this case, one tractor was selected from a set of six alternatives, integrating six attributes in the model: initial cost, annual maintenance cost, liters of diesel per hour, safety of the operator, maintainability and after-sale customer service offered by the supplier. Based on the results obtained, the model can be considered easy to apply and to have good acceptance among farmers and salesmen, as there are no special software requirements for the application.

  2. Learning from the application of the systematic approach to training

    International Nuclear Information System (INIS)

    Haber, S.B.; Yoder, J.A.

    1998-01-01

    The paper describes the objectives, lessons learned, key accomplishments and related activities of the application of the systematic approach to training initiated by DOE in Russia and Ukraine in 1992 focused on single facility in each country

  3. A New Hybrid Approach for Wind Speed Prediction Using Fast Block Least Mean Square Algorithm and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Ummuhan Basaran Filik

    2016-01-01

    Full Text Available A new hybrid wind speed prediction approach, which uses fast block least mean square (FBLMS algorithm and artificial neural network (ANN method, is proposed. FBLMS is an adaptive algorithm which has reduced complexity with a very fast convergence rate. A hybrid approach is proposed which uses two powerful methods: FBLMS and ANN method. In order to show the efficiency and accuracy of the proposed approach, seven-year real hourly collected wind speed data sets belonging to Turkish State Meteorological Service of Bozcaada and Eskisehir regions are used. Two different ANN structures are used to compare with this approach. The first six-year data is handled as a train set; the remaining one-year hourly data is handled as test data. Mean absolute error (MAE and root mean square error (RMSE are used for performance evaluations. It is shown for various cases that the performance of the new hybrid approach gives better results than the different conventional ANN structure.

  4. Systematic approach to training. Experiences from the training activities of regulatory body personnel in STUK

    International Nuclear Information System (INIS)

    Aro, I.

    1998-04-01

    The report describes the experiences obtained of a training programme for nuclear power plant inspectors arranged in the 90's by the Radiation and Nuclear Safety Authority of Finland (STUK). In the implementation of the programme, a systematic method was used to analyse the training needs, to plan, develop and implement the training programme as well as to assess the programme's implementation and results. The method used, 'SAT Ae Systematic Approach to Training', is presented in 'Nuclear Power Plant Personnel Training and its Evaluation, A Guidebook', IAEA Technical Report Series No. 380, which is a publication of the International Atomic Energy Agency. It is recommended that this method be applied in the planning and implementation of nuclear power plant personnel training. The application of the method as a tool for developing the qualifications of nuclear power plant inspectors shows that the method is well suited for use in Finland. Until the 90's, STUK had no systematic approach to training activities. Some training was arranged internally, but training in most respects meant participation in external training events and international seminars. A more systematic approach was adopted in the early 90's. The main goal was to define basic competence profiles for inspectors working in different fields and to provide an internal basic training programme not available externally. The development of the training activities called for a profound renewal of the training function to ensure a systematic approach and high quality. The experiences gained in STUK are useful in co-operation with Eastern and Central European regulatory bodies; they can be utilized when the qualifications of personnel who carry out inspections are developed. This will extensively contribute to the safety of nuclear power plants. (orig.)

  5. Systematic approach to training. Experiences from the training activities of regulatory body personnel in STUK

    Energy Technology Data Exchange (ETDEWEB)

    Aro, I.

    1998-04-01

    The report describes the experiences obtained of a training programme for nuclear power plant inspectors arranged in the 90`s by the Radiation and Nuclear Safety Authority of Finland (STUK). In the implementation of the programme, a systematic method was used to analyse the training needs, to plan, develop and implement the training programme as well as to assess the programme`s implementation and results. The method used, `SAT Ae Systematic Approach to Training`, is presented in `Nuclear Power Plant Personnel Training and its Evaluation, A Guidebook`, IAEA Technical Report Series No. 380, which is a publication of the International Atomic Energy Agency. It is recommended that this method be applied in the planning and implementation of nuclear power plant personnel training. The application of the method as a tool for developing the qualifications of nuclear power plant inspectors shows that the method is well suited for use in Finland. Until the 90`s, STUK had no systematic approach to training activities. Some training was arranged internally, but training in most respects meant participation in external training events and international seminars. A more systematic approach was adopted in the early 90`s. The main goal was to define basic competence profiles for inspectors working in different fields and to provide an internal basic training programme not available externally. The development of the training activities called for a profound renewal of the training function to ensure a systematic approach and high quality. The experiences gained in STUK are useful in co-operation with Eastern and Central European regulatory bodies; they can be utilized when the qualifications of personnel who carry out inspections are developed. This will extensively contribute to the safety of nuclear power plants. (orig.). 2 refs.

  6. ACTIVITY APPROACH IN THE ORGANIZATION OF TRAINING OF TEACHERS

    Directory of Open Access Journals (Sweden)

    Elena Sidenko

    2015-09-01

    Full Text Available The article contains the results of research in the field of pedagogy. The author develops a model of teacher’s training course that focuses on self-determination of participants with respect to teachers’ personal sense of participation in training courses; organization of system-activity approach to professional development; subject-subject approach to skills development. The novelty is the development of a mechanism of transformation of the teachers’ motivation of avoiding failure into motivation to succeed.

  7. A hybrid approach to automatic de-identification of psychiatric notes.

    Science.gov (United States)

    Lee, Hee-Jin; Wu, Yonghui; Zhang, Yaoyun; Xu, Jun; Xu, Hua; Roberts, Kirk

    2017-11-01

    De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing system for automatic de-identification of psychiatric notes, which was designed to participate in the 2016 CEGS N-GRID shared task Track 1. The system has a hybrid structure that combines machine leaning techniques and rule-based approaches. The rule-based components exploit the structure of the psychiatric notes as well as characteristic surface patterns of PHI mentions. The machine learning components utilize supervised learning with rich features. In addition, the system performance was boosted with integration of additional data to the training set through domain adaptation. The hybrid system showed overall micro-averaged F-score 90.74 on the test set, second-best among all the participants of the CEGS N-GRID task. Copyright © 2017. Published by Elsevier Inc.

  8. Hybrid Type II fuzzy system & data mining approach for surface finish

    Directory of Open Access Journals (Sweden)

    Tzu-Liang (Bill Tseng

    2015-07-01

    Full Text Available In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

  9. Mass Optimization of Battery/Supercapacitors Hybrid Systems Based on a Linear Programming Approach

    Science.gov (United States)

    Fleury, Benoit; Labbe, Julien

    2014-08-01

    The objective of this paper is to show that, on a specific launcher-type mission profile, a 40% gain of mass is expected using a battery/supercapacitors active hybridization instead of a single battery solution. This result is based on the use of a linear programming optimization approach to perform the mass optimization of the hybrid power supply solution.

  10. TRX Suspension Training: A New Functional Training Approach for Older Adults - Development, Training Control and Feasibility.

    Science.gov (United States)

    Gaedtke, Angus; Morat, Tobias

    Because of its proximity to daily activities functional training becomes more important for older adults. Sling training, a form of functional training, was primarily developed for therapy and rehabilitation. Due to its effects (core muscle activation, strength and balance improvements), sling training may be relevant for older adults. However, to our knowledge no recent sling training program for healthy older adults included a detailed training control which is indeed an essential component in designing and implementing this type of training to reach positive effects. The purpose of this study was to develop a TRX Suspension Training for healthy older adults (TRX-OldAge) and to evaluate its feasibility. Eleven participants finished the 12 week intervention study. All participants trained in the TRX-OldAge whole-body workout which consists of seven exercises including 3-4 progressively advancing stages of difficulty for every exercise. At each stage, intensity could be increased through changes in position. Feasibility data was evaluated in terms of training compliance and a self-developed questionnaire for rating TRX-OldAge. The training compliance was 85 %. After study period, 91 % of the participants were motivated to continue with the program. The training intensity, duration and frequency were rated as optimal. All participants noted positive effects whereas strength gains were the most. On the basis of the detailed information about training control, TRX-OldAge can be individually adapted for each older adult appropriate to its precondition, demands and preference.

  11. Script Templates: A Practical Approach to Script Training in Aphasia

    Science.gov (United States)

    Kaye, Rosalind C.; Cherney, Leora R.

    2016-01-01

    Purpose: Script training for aphasia involves repeated practice of relevant phrases and sentences that, when mastered, can potentially be used in other communicative situations. Although an increasingly popular approach, script development can be time-consuming. We provide a detailed summary of the evidence supporting this approach. We then…

  12. Implementing an Holistic Approach in Vocational Education and Training

    Science.gov (United States)

    McGrath, Donna-Louise

    2007-01-01

    Although the phrase "holistic approach" is increasingly used in reference to vocational education and training (VET) in Australia, there appears to be a paucity of literature which extensively conceptualises or details its practical application. Existing references to an "holistic approach" appear indicative of an integrated…

  13. A HYBRID GENETIC ALGORITHM-NEURAL NETWORK APPROACH FOR PRICING CORES AND REMANUFACTURED CORES

    Directory of Open Access Journals (Sweden)

    M. Seidi

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT:Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. Remanufacturing is an industrial process that makes used products reusable. One of the important aspects in both reverse logistics and remanufacturing is the pricing of returned and remanufactured products (called cores. In this paper, we focus on pricing the cores and remanufactured cores. First we present a mathematical model for this purpose. Since this model does not satisfy our requirements, we propose a simulation optimisation approach. This approach consists of a hybrid genetic algorithm based on a neural network employed as the fitness function. We use automata learning theory to obtain the learning rate required for training the neural network. Numerical results demonstrate that the optimal value of the acquisition price of cores and price of remanufactured cores is obtained by this approach.

    AFRIKAANSE OPSOMMING: Volhoubaarheid het ‘n belangrike saak geword in die meeste ekonomieë, wat verskeie maatskappye genoop het om produkherwinning en omgekeerde logistiek te onder oë te neem. Hervervaardiging is ‘n industriële proses wat gebruikte produkte weer bruikbaar maak. Een van die belangrike aspekte in beide omgekeerde logistiek en hervervaardiging is die prysbepaling van herwinne en hervervaardigde produkte. Hierdie artikel fokus op die prysbepalingsaspekte by wyse van ‘n wiskundige model.

  14. Implementation of systematic training approach in Kozloduy Training Centre - Current situation. Presentation of Bulgaria

    International Nuclear Information System (INIS)

    Kosturkov, L.

    1993-01-01

    To identify the needs in implementation of the systematic training approach, a relation between the number of trainees, duration of the training and the type of training should be made. In other hand, as it was stated in the TWG-T(93) Status Report, in order to be better identified outstanding training needs, the existing capabilities and other related projects should be taken into account. This report is pointed to give more details for the current situation in Bulgaria and to clarify the needs of international assistance. 3 refs, 3 tabs

  15. A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Fernando Sánchez Lasheras

    2015-03-01

    Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

  16. When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

    KAUST Repository

    Liu, Xiao; Liu, An; Zhang, Xiangliang; Li, Zhixu; Liu, Guanfeng; Zhao, Lei; Zhou, Xiaofang

    2017-01-01

    result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP

  17. Conduct of operations training - An innovative approach to team building

    International Nuclear Information System (INIS)

    Widen, W.C.; Kurth, W.; Broccolo, A.

    1987-01-01

    The conduct of nuclear power plant operations is a key parameter for station management and regulators alike. Indeed, the basic methods and demeanor in which operating crews approach overall plant operations is perhaps the principal factor leading to safe and efficient operations. Hence, Commonwealth Edison's Zion Station has initiated an innovative and positive training program designed to increase operator awareness of conducting station operations in an attentive, diligent, and conscientious manner. This Conduct of Operations Training Program is a collaborative joint effort between Commonwealth Edison and the Westinghouse Nuclear Training Center. In particular, the key managers of Zion's operating department brainstormed various philosophies and strategies with senior training staff members of the Westinghouse Nuclear Training Center. The outcome of these sessions has formed the skeleton of an intensified, one-day Conduct of Operations course. Several unique aspects of this innovative course are described

  18. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    Energy Technology Data Exchange (ETDEWEB)

    Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

    2011-02-15

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  19. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    International Nuclear Information System (INIS)

    Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.

    2011-01-01

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  20. Critical safety parameters: The logical approach to refresher training

    International Nuclear Information System (INIS)

    Johnson, A.R.; Pilkington, W.; Turner, S.

    1991-01-01

    Nuclear power plant managers must ensure that control room staff are able to perform effectively. This is of particular importance through the longer term after initial authorization. Traditionally refresher training has been based on delivery of fragmented training packages typically derived from the initial authorization training programs. Various approaches have been taken to provide a more integrated refresher training program. However, methods such as job and task analysis and subject matter expert derived training have tended to develop without a focused clear overall training objective. The primary objective of all control room staff training is to ensure a proper and safe response to all plant transients. At the Point Lepreau Nuclear Plant, this has defined the Critical Safety Parameter based refresher training program. The overall objective of the Critical Safety Parameter training program is to ensure that control room staff can monitor and control a discrete set of plant parameters. Maintenance of the selected parameters within defined boundaries assures adequate cooling of the fuel and containment of radioactivity. Control room staff need to be able to reliably respond correctly to plant transients under potentially high stress conditions,. utilizing the essential knowledge and skills to deal with such transients. The inference is that the knowledge and skills must be limited to that which can be reliably recalled. This paper describes how the Point Lepreau Nuclear Plant has developed a refresher training program on the basis of a limited number of Critical Safety Parameters. Through this approach, it has been possible to define the essential set of knowledge and skills which ensures a correct response to plant transients

  1. Training in ionizing radiation metrology: a systematic approach

    International Nuclear Information System (INIS)

    Peixoto, J.G.P.; Sales, E.; Wieland, P.

    2001-01-01

    This paper presents the systematic approach to training applied to the determination of backscattering factor of the mammography radiation qualities implemented at LNMRI/IRD/CNEN. The strategy for training includes the procedures described at the IAEA Safety Reports Series 201, i.e. analysis, design, implementation and evaluation with feedback . The training included theoretical and practical classes on dosimetry tools, interaction of radiation with matter, radiation protection, laboratory rules, and measurements and uncertainty analysis. At the end the trainee presents a seminar to show the competency acquired and to improve the scientific communication skills. (author)

  2. A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries

    Directory of Open Access Journals (Sweden)

    Wen-An Yang

    2016-01-01

    Full Text Available Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles and its failure can lead to reduced capability, downtime, and even catastrophic breakdowns. Remaining useful life (RUL prediction of lithium-ion batteries before the future failure event is extremely crucial for proactive maintenance/safety actions. This study proposes a hybrid prognostic approach that can predict the RUL of degraded lithium-ion batteries using physical laws and data-driven modeling simultaneously. In this hybrid prognostic approach, the relevant vectors obtained with the selective kernel ensemble-based relevance vector machine (RVM learning algorithm are fitted to the physical degradation model, which is then extrapolated to failure threshold for estimating the RUL of the lithium-ion battery of interest. The experimental results indicated that the proposed hybrid prognostic approach can accurately predict the RUL of degraded lithium-ion batteries. Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs like the conventional backpropagation (BP algorithm and support vector machines (SVMs. In addition, an investigation is also conducted to identify the effects of RVM learning algorithm on the proposed hybrid prognostic approach.

  3. Hybridization success is largely limited to homoploid Prunus hybrids: a multidisciplinary approach

    Czech Academy of Sciences Publication Activity Database

    Macková, L.; Vít, Petr; Ďurišová, Ľ.; Eliáš, P. Jr.; Urfus, T.

    2017-01-01

    Roč. 303, č. 4 (2017), s. 481-495 ISSN 0378-2697 Institutional support: RVO:67985939 Keywords : absolute genome size * interspecific hybridization * embryology Subject RIV: EF - Botanics OBOR OECD: Plant sciences, botany Impact factor: 1.239, year: 2016

  4. A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid Wind Turbine Rotors

    DEFF Research Database (Denmark)

    Herbert-Acero, José F.; Martínez-Lauranchet, Jaime; Probst, Oliver

    2014-01-01

    of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize...

  5. Hybrid Engine Powered City Car: Fuzzy Controlled Approach

    Science.gov (United States)

    Rahman, Ataur; Mohiuddin, AKM; Hawlader, MNA; Ihsan, Sany

    2017-03-01

    This study describes a fuzzy controlled hybrid engine powered car. The car is powered by the lithium ion battery capacity of 1000 Wh is charged by the 50 cc hybrid engine and power regenerative mode. The engine is operated with lean mixture at 3000 rpm to charge the battery. The regenerative mode that connects with the engine generates electrical power of 500-600 W for the deceleration of car from 90 km/h to 20 km/h. The regenerated electrical power has been used to power the air-conditioning system and to meet the other electrical power. The battery power only used to propel the car. The regenerative power also found charging the battery for longer operation about 40 minutes and more. The design flexibility of this vehicle starts with whole-vehicle integration based on radical light weighting, drag reduction, and accessory efficiency. The energy efficient hybrid engine cut carbon dioxide (CO2) and nitrogen oxides (N2O) emission about 70-80% as the loads on the crankshaft such as cam-follower and its associated rotating components are replaced by electromagnetic systems, and the flywheel, alternator and starter motor are replaced by a motor generator. The vehicle was tested and found that it was able to travel 70 km/litre with the power of hybrid engine.

  6. A promising hybrid approach to SPECT attenuation correction

    International Nuclear Information System (INIS)

    Lewis, N.H.; Faber, T.L.; Corbett, J.R.; Stokely, E.M.

    1984-01-01

    Most methods for attenuation compensation in SPECT either rely on the assumption of uniform attenuation, or use slow iteration to achieve accuracy. However, hybrid methods that combine iteration with simple multiplicative correction can accommodate nonuniform attenuation, and such methods converge faster than other iterative techniques. The authors evaluated two such methods, which differ in use of a damping factor to control convergence. Both uniform and nonuniform attenuation were modeled, using simulated and phantom data for a rotating gamma camera. For simulations done with 360 0 data and the correct attenuation map, activity levels were reconstructed to within 5% of the correct values after one iteration. Using 180 0 data, reconstructed levels in regions representing lesion and background were within 5% of the correct values in three iterations; however, further iterations were needed to eliminate the characteristic streak artifacts. The damping factor had little effect on 360 0 reconstruction, but was needed for convergence with 180 0 data. For both cold- and hot-lesion models, image contrast was better from the hybrid methods than from the simpler geometric-mean corrector. Results from the hybrid methods were comparable to those obtained using the conjugate-gradient iterative method, but required 50-100% less reconstruction time. The relative speed of the hybrid methods, and their accuracy in reconstructing photon activity in the presence of nonuniform attenuation, make them promising tools for quantitative SPECT reconstruction

  7. Using a Hybrid Approach for a Leadership Cohort Program

    Science.gov (United States)

    Norman, Maxine A.

    2013-01-01

    Because information technology continues to change rapidly, Extension is challenged with learning and using technology appropriately. We assert Extension cannot shy away from the challenges but must embrace technology because audiences and external forces demand it. A hybrid, or blended, format of a leadership cohort program was offered to public…

  8. Hybrid Force Control Based on ICMAC for an Astronaut Rehabilitative Training Robot

    Directory of Open Access Journals (Sweden)

    Lixun Zhang

    2012-08-01

    Full Text Available A novel Astronaut Rehabilitative Training Robot (ART based on a cable-driven mechanism is represented in this paper. ART, a typical passive force servo system, can help astronauts to bench press in a microgravity environment. The purpose of this paper is to design controllers to eliminate the surplus force caused by an astronaut's active movements. Based on the dynamics modelling of the cable-driven unit, a hybrid force controller based on improved credit assignment CMAC (ICMAC is presented. A planning method for the cable tension is proposed so that the dynamic load produced by the ART can realistically simulate the gravity and inertial force of the barbell in a gravity environment. Finally, MATLAB simulation results of the man-machine cooperation system are provided in order to verify the effectiveness of the proposed control strategy. The simulation results show that the hybrid control method based on the structure invariance principle can inhibit the surplus force and that ICMAC can improve the dynamic performance of the passive force servo system. Furthermore, the hybrid force controller based on ICMAC can ensure the stability of the system.

  9. Clinical application of the Hybrid Assistive Limb (HAL) for gait training-a systematic review.

    Science.gov (United States)

    Wall, Anneli; Borg, Jörgen; Palmcrantz, Susanne

    2015-01-01

    The aim of this study was to review the literature on clinical applications of the Hybrid Assistive Limb system for gait training. A systematic literature search was conducted using Web of Science, PubMed, CINAHL and clinicaltrials.gov and additional search was made using reference lists in identified reports. Abstracts were screened, relevant articles were reviewed and subject to quality assessment. Out of 37 studies, 7 studies fulfilled inclusion criteria. Six studies were single group studies and 1 was an explorative randomized controlled trial. In total, these studies involved 140 participants of whom 118 completed the interventions and 107 used HAL for gait training. Five studies concerned gait training after stroke, 1 after spinal cord injury (SCI) and 1 study after stroke, SCI or other diseases affecting walking ability. Minor and transient side effects occurred but no serious adverse events were reported in the studies. Beneficial effects on gait function variables and independence in walking were observed. The accumulated findings demonstrate that the HAL system is feasible when used for gait training of patients with lower extremity paresis in a professional setting. Beneficial effects on gait function and independence in walking were observed but data do not allow conclusions. Further controlled studies are recommended.

  10. Facile approach to prepare Pt decorated SWNT/graphene hybrid catalytic ink

    Energy Technology Data Exchange (ETDEWEB)

    Mayavan, Sundar, E-mail: sundarmayavan@cecri.res.in [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Mandalam, Aditya; Balasubramanian, M. [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Sim, Jun-Bo [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Choi, Sung-Min, E-mail: sungmin@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of)

    2015-07-15

    Highlights: • Pt NPs were in situ synthesized onto CNT–graphene support in aqueous solution. • The as-prepared material was used directly as a catalyst ink without further treatment. • Catalyst ink is active toward methanol oxidation. • This approach realizes both scalable and greener production of hybrid catalysts. - Abstract: Platinum nanoparticles were in situ synthesized onto hybrid support involving graphene and single walled carbon nanotube in aqueous solution. We investigate the reduction of graphene oxide, and platinum nanoparticle functionalization on hybrid support by X-ray photoelectron spectroscopy, Raman spectroscopy, X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The as-prepared platinum on hybrid support was used directly as a catalyst ink without further treatment and is active toward methanol oxidation. This work realizes both scalable and greener production of highly efficient hybrid catalysts, and would be valuable for practical applications of graphene based fuel cell catalysts.

  11. Gait training using a hybrid assistive limb (HAL) attenuates head drop: A case report.

    Science.gov (United States)

    Miura, Kousei; Koda, Masao; Kadone, Hideki; Kubota, Shigeki; Shimizu, Yukiyo; Kumagai, Hiroshi; Nagashima, Katsuya; Mataki, Kentaro; Fujii, Kengo; Noguchi, Hiroshi; Funayama, Toru; Abe, Tetsuya; Sankai, Yoshiyuki; Yamazaki, Masashi

    2018-03-31

    Dropped head syndrome (DHS) is characterized by a chin-on-chest deformity, which can severely interfere with forward vision and impair activities of daily living. A standardized treatment strategy for DHS has not been established. To our knowledge, this is the first case report describing the efficacy of gait training using a hybrid assistive limb (HAL) for DHS. A 75-year-old man showed apparent head drop in a standing position, resulting in passively reducible chin-on-chest deformity. A radiograph image showed apparent cervical kyphosis. Center of gravity of the head (CGH)-C7 SVA was +115 mm, CL was -40°, and T1S 39°. The patient underwent a treatment program using HAL, in which gait training was mainly performed, 60 min a day, 5 days a week for 2 weeks (10 sessions). After 2-3 sessions, dropped head started to attenuate. At the end of 10 sessions, the patient was able to walk with normal posture and radiograph images showed cervical kyphosis dramatically decreased because of HAL training. CGH-C7 SVA was 42 mm, CL was -1.7°, and T1S was 30°. Three months' outpatient follow-up revealed a slight deterioration of cervical alignment. However, the patient was able to maintain a better cervical alignment than before HAL training and keep walking with forward vision. There were no complications in any HAL treatment session. In conclusion, gait training using HAL is an option for treatment of DHS in addition to previously reported neck extensor muscle training. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. COMPETENCE APPROACH TO TRAINING OF EXPERTS IN RADIATION HYGIENE

    Directory of Open Access Journals (Sweden)

    T. B. Baltrukova

    2015-01-01

    Full Text Available Modification of attitude to labor in the society, in professional communities and among people is necessary for further development of society and national economy. This goal may be achieved if the system of professional training is modified: switched to competence approach which should include training of experts, including those in radiation hygiene, with a set of general cultural and professional competences. The system of future experts training should be based on traditions of domestic and international education; it should use modern forms of active and interactive education (computer simulations, business games and role-playing, analysis of concrete situations, portfolio, psychological and other trainings, remote education, etc. It should consider actuality of knowledge and skills and develop independence and responsibility that will enable the young expert to be competitive at the modern labor market and to meet employers’ expectations. Under the new federal educational standard on radiation hygiene accepted in 2014 at present primary specialization in radiation hygiene takes place in internship. At training of experts the new standard provides great use of on-the-job training, independent work, scientific and practical work. Employers should play an important role in training of experts.

  13. A Hybrid Approach for Thread Recommendation in MOOC Forums

    OpenAIRE

    Ahmad. A. Kardan; Amir Narimani; Foozhan Ataiefard

    2017-01-01

    Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC ...

  14. Interactive Digital Storytelling: Towards a Hybrid Conceptual Approach

    OpenAIRE

    Spierling, Ulrike

    2005-01-01

    1 Introduction In this contribution, Interactive Digital Storytelling is viewed as a hybrid form of game design and cinematic storytelling for the understanding and making of future learning and entertainment applications. The paper shall present formal design models that provide a conceptual bridge between both traditional linear narrative techniques as well as agent-based emergent conversations with virtual characters. In summary, a theoretical classification of thinking models for authors ...

  15. Increasing the effectiveness of instrumentation and control training programs using integrated training settings and a systematic approach to training

    International Nuclear Information System (INIS)

    McMahon, J.F.; Rakos, N.

    1992-01-01

    The performance of plant maintenance-related tasks assigned to instrumentation and control (I ampersand C) technicians can be broken down into physical skills required to do the task; resident knowledge of how to do the task; effect of maintenance on plant operating conditions; interactions with other plant organizations such as operations, radiation protection, and quality control; and knowledge of consequences of miss-action. A technician who has learned about the task in formal classroom presentations has not had the advantage of integrating that knowledge with the requisite physical and communication skills; hence, the first time these distinct and vital parts of the task equation are put together is on the job, during initial task performance. On-the-job training provides for the integration of skills and knowledge; however, this form of training is limited by plant conditions, availability of supporting players, and training experience levels of the personnel conducting the exercise. For licensed operations personnel, most nuclear utilities use formal classroom and a full-scope control room simulator to achieve the integration of skills and knowledge in a controlled training environment. TU Electric has taken that same approach into maintenance areas by including identical plant equipment in a laboratory setting for the large portion of training received by maintenance personnel at its Comanche Peak steam electric station. The policy of determining training needs and defining the scope of training by using the systematic approach to training has been highly effective and provided training at a reasonable cost (approximately $18.00/student contact hour)

  16. Control and fault diagnosis based sliding mode observer of a multicellular converter: Hybrid approach

    KAUST Repository

    Benzineb, Omar

    2013-01-01

    In this article, the diagnosis of a three cell converter is developed. The hybrid nature of the system represented by the presence of continuous and discrete dynamics is taken into account in the control design. The idea is based on using a hybrid control and an observer-type sliding mode to generate residuals from the observation errors of the system. The simulation results are presented at the end to illustrate the performance of the proposed approach. © 2013 FEI STU.

  17. An Approach to Management of Health Care and Medical Diagnosis Using of a Hybrid Disease Diagnosis System

    Directory of Open Access Journals (Sweden)

    Hodjat Hamidi

    2017-02-01

    Full Text Available Introduction: In order to simplify the information exchange within the medical diagnosis process, a collaborative software agent’s framework is presented. The purpose of the framework is to allow the automated information exchange between different medicine specialists. Methods: This study presented architecture of a hybrid disease diagnosis system. The architecture employed a learning algorithm and used soft computing to build a medical knowledge base. These machine intelligences are combined in a complementary approach to overcome the weakness of each other. To evaluate the hybrid learning algorithm and compare it with other methods, 699 samples were used in each experiment, where 60% was for training, 20% was for cross validation, and 20% for testing. Results: The results were obtained from the experiments on the breast cancer dataset. Different methods of soft computing system were merged to create diagnostic software functionality. As it is shown in the structure, the system has the ability to learn and collect knowledge that can be used in the detection of new images. Currently, the system is at the design stage. The system is to evaluate the performance of hybrid learning algorithm. The preliminary results showed a better performance of this system than other methods. However, the results can be tested with hybrid system on larger data sets to improve hybrid learning algorithm. Conclusion: The purpose of this paper was to simplify the diagnosis process of a patient by splitting the medical domain concepts (e.g., causes, effects, symptoms, tests in human body systems (e.g., respiratory, cardiovascular, though maintaining the holistic perspective through the links between common concepts.

  18. Hybrid Electric Power Train and Control Strategies Automotive Technology Education (GATE) Program

    Energy Technology Data Exchange (ETDEWEB)

    Andrew Frank

    2006-05-31

    Plug-in hybrid electric vehicles (PHEV) offer societal benefits through their ability to displace the use of petroleum fuels. Petroleum fuels represent a polluting and politically destabilizing energy carrier. PHEV technologies can move transportation away from petroleum fuel sources by enabling domestically generated electricity and liquids bio-fuels to serve as a carrier for transportation energy. Additionally, the All-Electric-Range (AER) offered by PHEVs can significantly reduce demand for expensive and polluting liquid fuels. The GATE funding received during the 1998 through 2004 funding cycle by the UC Davis Hybrid Electric Vehicle Center (HEVC) was used to advance and train researchers in PHEV technologies. GATE funding was used to construct a rigorous PHEV curriculum, provide financial support for HEVC researchers, and provide material support for research efforts. A rigorous curriculum was developed through the UC Davis Mechanical and Aeronautical Engineering Department to train HEVC researchers. Students' research benefited from this course work by advancing the graduate student researchers' understanding of key PHEV design considerations. GATE support assisted HEVC researchers in authoring technical articles and producing patents. By supporting HEVC researchers multiple Master's theses were written as well as journal articles and publications. The topics from these publications include Continuously Variable Transmission control strategies and PHEV cross platform controls software development. The GATE funding has been well used to advance PHEV systems. The UC Davis Hybrid Electric Vehicle Center is greatly appreciative for the opportunities GATE funding provided. The goals and objectives for the HEVC GATE funding were to nourish engineering research in PHEV technologies. The funding supplied equipment needed to allow researchers to investigate PHEV design sensitivities and to further optimize system components. Over a dozen PHEV

  19. Training programs for the systems approach to nuclear security

    International Nuclear Information System (INIS)

    Ellis, D.

    2005-01-01

    Full text: In support of United States Government (USG) and International Atomic Energy Agency (IAEA) nuclear security programs, Sandia National Laboratories (SNL) has advocated and practiced a risk-based, systematic approach to nuclear security. The risk equation has been developed and implemented as the basis for a performance-based methodology for the design and evaluation of physical protection systems against a design basis threat (DBT) for theft and sabotage of nuclear and/or radiological materials. Integrated systems must include technology, people, and the man-machine interface. A critical aspect of the human element is training on the systems-approach for all the stakeholders in nuclear security. Current training courses and workshops have been very beneficial but are still rather limited in scope. SNL has developed two primary international classes - the international training course on the physical protection of nuclear facilities and materials, and the design basis threat methodology workshop. SNL is also completing the development of three new courses that will be offered and presented in the near term. They are vital area identification methodology focused on nuclear power plants to aid in their protection against radiological sabotage, insider threat analysis methodology and protection schemes, and security foundations for competent authority and facility operator stakeholders who are not security professionals. In the long term, we envision a comprehensive nuclear security curriculum that spans policy and technology, regulators and operators, introductory and expert levels, classroom and laboratory/field, and local and offsite training options. This training curriculum will be developed in concert with a nuclear security series of guidance documents that is expected to be forthcoming from the IAEA. It is important to note that while appropriate implementation of systems based on such training and documentation can improve the risk reduction, such a

  20. Task-based neurofeedback training: A novel approach toward training executive functions.

    Science.gov (United States)

    Hosseini, S M Hadi; Pritchard-Berman, Mika; Sosa, Natasha; Ceja, Angelica; Kesler, Shelli R

    2016-07-01

    Cognitive training is an emergent approach to improve cognitive functions in various neurodevelopmental and neurodegenerative diseases. However, current training programs can be relatively lengthy, making adherence potentially difficult for patients with cognitive difficulties. Previous studies suggest that providing individuals with real-time feedback about the level of brain activity (neurofeedback) can potentially help them learn to control the activation of specific brain regions. In the present study, we developed a novel task-based neurofeedback training paradigm that benefits from the effects of neurofeedback in parallel with computerized training. We focused on executive function training given its core involvement in various developmental and neurodegenerative diseases. Near-infrared spectroscopy (NIRS) was employed for providing neurofeedback by measuring changes in oxygenated hemoglobin in the prefrontal cortex. Of the twenty healthy adult participants, ten received real neurofeedback (NFB) on prefrontal activity during cognitive training, and ten were presented with sham feedback (SHAM). Compared with SHAM, the NFB group showed significantly improved executive function performance including measures of working memory after four sessions of training (100min total). The NFB group also showed significantly reduced training-related brain activity in the executive function network including right middle frontal and inferior frontal regions compared with SHAM. Our data suggest that providing neurofeedback along with cognitive training can enhance executive function after a relatively short period of training. Similar designs could potentially be used for patient populations with known neuropathology, potentially helping them to boost/recover the activity in the affected brain regions. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. An hybrid and non-modern approach to urban studies

    Directory of Open Access Journals (Sweden)

    Marc Grau i Solés

    2012-03-01

    Full Text Available This article draws upon the so-called Forat de la Vergonya urban controversy and the urban transformation process of a neighborhood in Barcelona: el Casc Antic. Drawing on inputs from Actor-Network Theory (ANT, the city is explored as a multiple urban assemblage. Besides, we analyze the dichotomous nature of the modern notion of politics. Especially, the role of object-subject dichotomy is explored. Through the analysis of citizen participation opportunities we propose a new hybrid notion of citizen participation and urban policy.

  2. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and fault...... can be used as a test signal for sanity check at the commissioning or for detection of faults hidden by regulatory actions of the controller. The method is tested on the two tank benchmark example. ©2009 IEEE....

  3. A Hybrid Approach for Reliability Analysis Based on Analytic Hierarchy Process and Bayesian Network

    International Nuclear Information System (INIS)

    Zubair, Muhammad

    2014-01-01

    By using analytic hierarchy process (AHP) and Bayesian Network (BN) the present research signifies the technical and non-technical issues of nuclear accidents. The study exposed that the technical faults was one major reason of these accidents. Keep an eye on other point of view it becomes clearer that human behavior like dishonesty, insufficient training, and selfishness are also play a key role to cause these accidents. In this study, a hybrid approach for reliability analysis based on AHP and BN to increase nuclear power plant (NPP) safety has been developed. By using AHP, best alternative to improve safety, design, operation, and to allocate budget for all technical and non-technical factors related with nuclear safety has been investigated. We use a special structure of BN based on the method AHP. The graphs of the BN and the probabilities associated with nodes are designed to translate the knowledge of experts on the selection of best alternative. The results show that the improvement in regulatory authorities will decrease failure probabilities and increase safety and reliability in industrial area.

  4. A novel approach for fire recognition using hybrid features and manifold learning-based classifier

    Science.gov (United States)

    Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

    2018-03-01

    Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

  5. An augmented reality home-training system based on the mirror training and imagery approach.

    Science.gov (United States)

    Trojan, Jörg; Diers, Martin; Fuchs, Xaver; Bach, Felix; Bekrater-Bodmann, Robin; Foell, Jens; Kamping, Sandra; Rance, Mariela; Maaß, Heiko; Flor, Herta

    2014-09-01

    Mirror training and movement imagery have been demonstrated to be effective in treating several clinical conditions, such as phantom limb pain, stroke-induced hemiparesis, and complex regional pain syndrome. This article presents an augmented reality home-training system based on the mirror and imagery treatment approaches for hand training. A head-mounted display equipped with cameras captures one hand held in front of the body, mirrors this hand, and displays it in real time in a set of four different training tasks: (1) flexing fingers in a predefined sequence, (2) moving the hand into a posture fitting into a silhouette template, (3) driving a "Snake" video game with the index finger, and (4) grasping and moving a virtual ball. The system records task performance and transfers these data to a central server via the Internet, allowing monitoring of training progress. We evaluated the system by having 7 healthy participants train with it over the course of ten sessions of 15-min duration. No technical problems emerged during this time. Performance indicators showed that the system achieves a good balance between relatively easy and more challenging tasks and that participants improved significantly over the training sessions. This suggests that the system is well suited to maintain motivation in patients, especially when it is used for a prolonged period of time.

  6. Modeling level change in Lake Urmia using hybrid artificial intelligence approaches

    Science.gov (United States)

    Esbati, M.; Ahmadieh Khanesar, M.; Shahzadi, Ali

    2017-06-01

    The investigation of water level fluctuations in lakes for protecting them regarding the importance of these water complexes in national and regional scales has found a special place among countries in recent years. The importance of the prediction of water level balance in Lake Urmia is necessary due to several-meter fluctuations in the last decade which help the prevention from possible future losses. For this purpose, in this paper, the performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the lake water level balance has been studied. In addition, for the training of the adaptive neuro-fuzzy inference system, particle swarm optimization (PSO) and hybrid backpropagation-recursive least square method algorithm have been used. Moreover, a hybrid method based on particle swarm optimization and recursive least square (PSO-RLS) training algorithm for the training of ANFIS structure is introduced. In order to have a more fare comparison, hybrid particle swarm optimization and gradient descent are also applied. The models have been trained, tested, and validated based on lake level data between 1991 and 2014. For performance evaluation, a comparison is made between these methods. Numerical results obtained show that the proposed methods with a reasonable error have a good performance in water level balance prediction. It is also clear that with continuing the current trend, Lake Urmia will experience more drop in the water level balance in the upcoming years.

  7. Why should nuclear power plant management support the systematic approach to training?

    International Nuclear Information System (INIS)

    Haber, S.B.; Yoder, J.A.

    1998-01-01

    The presentation shows the role of management in training of NPP personnel especially in training for technology transfer and training for transfer of the training capabilities. Systematic approach to training should be used to achieve standard among different industries; consistent, effective and efficient training

  8. The pulling power of chocolate: Effects of approach-avoidance training on approach bias and consumption.

    Science.gov (United States)

    Dickson, Hugh; Kavanagh, David J; MacLeod, Colin

    2016-04-01

    Previous research has shown that action tendencies to approach alcohol may be modified using computerized Approach-Avoidance Task (AAT), and that this impacted on subsequent consumption. A recent paper in this journal (Becker, Jostman, Wiers, & Holland, 2015) failed to show significant training effects for food in three studies: Nor did it find effects on subsequent consumption. However, avoidance training to high calorie foods was tested against a control rather than Approach training. The present study used a more comparable paradigm to the alcohol studies. It randomly assigned 90 participants to 'approach' or 'avoid' chocolate images on the AAT, and then asked them to taste and rate chocolates. A significant interaction of condition and time showed that training to avoid chocolate resulted in faster avoidance responses to chocolate images, compared with training to approach it. Consistent with Becker et al.'s Study 3, no effect was found on amounts of chocolate consumed, although a newly published study in this journal (Schumacher, Kemps, & Tiggemann, 2016) did do so. The collective evidence does not as yet provide solid basis for the application of AAT training to reduction of problematic food consumption, although clinical trials have yet to be conducted. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. The graded approach to SAT: A cost effective use of the systematic approach to training

    International Nuclear Information System (INIS)

    Coe, R.P.; Bruno, R.J.

    2002-01-01

    The Systematic Approach to Training (SAT) has become the internationally accepted standard for the identification, organization, development and delivery of performance - based training. The SAT methodology has been defined and endorsed by the National Academy for Nuclear Training (NANT) and the International Atomic Energy Agency (IAEA). Through the routine use of the SAT process organizations, including non-nuclear industries, have been provided with a consistent methodology to determine the level of knowledge and skills that are required to successfully perform job related tasks. However, due to the complexity of each NPP job position and those in other highly technical organizations an enormous volume of data is required to develop, deliver and maintain a performance - based training program. This burden most often falls on the Training Department and requires proficient information management to ensure that all aspects of job performance are incorporated into position specific training programs. Traditionally the SAT process has been a costly and labor- intensive endeavor that many organizations are beginning to challenge as 'too expensive'. Organizations in the US are spending 60+ billion dollars annually on training and the number is growing rapidly. These organizations are also demanding that training: Develop shorter timeframes for learning; Bring physically disconnected employees together in a virtual learning environment; Optimize training by leveraging technology; Be diverse enough to support employee careers; More clearly demonstrate training's ROI; Accommodate cultural diversity and learning differences. (author)

  10. Gait quality is improved by locomotor training in individuals with SCI regardless of training approach

    NARCIS (Netherlands)

    Nooijen, C.F.J.; ter Hoeve, N.; Field-Fote, E.C.

    2009-01-01

    Background: While various body weight supported locomotor training (BWSLT) approaches are reported in the literature for individuals with spinal cord injury (SCI), none have evaluated outcomes in terms of gait quality. The purpose of this study was to compare changes in measures of gait quality

  11. Measurement and analysis of electromagnetic fields from trams, trains and hybrid cars

    International Nuclear Information System (INIS)

    Halgamuge, M. N.; Abeyrathne, C. D.; Mendis, P.

    2010-01-01

    Electricity is used substantially and sources of electric and magnetic fields are, unavoidably, everywhere. The transportation system is a source of these fields, to which a large proportion of the population is exposed. Hence, investigation of the effects of long-term exposure of the general public to low-frequency electromagnetic fields caused by the transportation system is critically important. In this study, measurements of electric and magnetic fields emitted from Australian trams, trains and hybrid cars were investigated. These measurements were carried out under different conditions, locations, and are summarised in this article. A few of the measured electric and magnetic field strengths were significantly lower than those found in prior studies. These results seem to be compatible with the evidence of the laboratory studies on the biological effects that are found in the literature, although they are far lower than international levels, such as those set up in the International Commission on Non-Ionising Radiation Protection guidelines. (authors)

  12. Measurement and analysis of electromagnetic fields from trams, trains and hybrid cars.

    Science.gov (United States)

    Halgamuge, Malka N; Abeyrathne, Chathurika D; Mendis, Priyan

    2010-10-01

    Electricity is used substantially and sources of electric and magnetic fields are, unavoidably, everywhere. The transportation system is a source of these fields, to which a large proportion of the population is exposed. Hence, investigation of the effects of long-term exposure of the general public to low-frequency electromagnetic fields caused by the transportation system is critically important. In this study, measurements of electric and magnetic fields emitted from Australian trams, trains and hybrid cars were investigated. These measurements were carried out under different conditions, locations, and are summarised in this article. A few of the measured electric and magnetic field strengths were significantly lower than those found in prior studies. These results seem to be compatible with the evidence of the laboratory studies on the biological effects that are found in the literature, although they are far lower than international levels, such as those set up in the International Commission on Non-Ionising Radiation Protection guidelines.

  13. A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-25

    This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

  14. A hybrid approach for probabilistic forecasting of electricity price

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Wang, Yelei

    2014-01-01

    to the nonstationarities involved in market clearing prices (MCPs), it is rather difficult to accurately predict MCPs in advance. The challenge is getting intensified as more and more renewable energy and other new technologies emerged in smart grids. Therefore transformation from traditional point forecasts...... electricity price forecasting is proposed in this paper. The effectiveness of the proposed hybrid method has been validated through comprehensive tests using real price data from Australian electricity market.......The electricity market plays a key role in realizing the economic prophecy of smart grids. Accurate and reliable electricity market price forecasting is essential to facilitate various decision making activities of market participants in the future smart grid environment. However, due...

  15. A Hybrid ACO Approach to the Matrix Bandwidth Minimization Problem

    Science.gov (United States)

    Pintea, Camelia-M.; Crişan, Gloria-Cerasela; Chira, Camelia

    The evolution of the human society raises more and more difficult endeavors. For some of the real-life problems, the computing time-restriction enhances their complexity. The Matrix Bandwidth Minimization Problem (MBMP) seeks for a simultaneous permutation of the rows and the columns of a square matrix in order to keep its nonzero entries close to the main diagonal. The MBMP is a highly investigated {NP}-complete problem, as it has broad applications in industry, logistics, artificial intelligence or information recovery. This paper describes a new attempt to use the Ant Colony Optimization framework in tackling MBMP. The introduced model is based on the hybridization of the Ant Colony System technique with new local search mechanisms. Computational experiments confirm a good performance of the proposed algorithm for the considered set of MBMP instances.

  16. Hybrid Quantum-Classical Approach to Quantum Optimal Control.

    Science.gov (United States)

    Li, Jun; Yang, Xiaodong; Peng, Xinhua; Sun, Chang-Pu

    2017-04-14

    A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely, computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving answers from the quantum simulator, classical computing devices update the control parameters until an optimal control solution is found. To demonstrate the quantum-classical scheme in experiment, we use a seven-qubit nuclear magnetic resonance system, on which we have succeeded in optimizing state preparation without involving classical computation of the large Hilbert space evolution.

  17. Hybrid simulation of reactor kinetics in CANDU reactors using a modal approach

    International Nuclear Information System (INIS)

    Monaghan, B.M.; McDonnell, F.N.; Hinds, H.W.T.; m.

    1980-01-01

    A hybrid computer model for simulating the behaviour of large CANDU (Canada Deuterium Uranium) reactor cores is presented. The main dynamic variables are expressed in terms of weighted sums of a base set of spatial natural-mode functions with time-varying co-efficients. This technique, known as the modal or synthesis approach, permits good three-dimensional representation of reactor dynamics and is well suited to hybrid simulation. The hybrid model provides improved man-machine interaction and real-time capability. The model was used in two applications. The first studies the transient that follows a loss of primary coolant and reactor shutdown; the second is a simulation of the dynamics of xenon, a fission product which has a high absorption cross-section for neutrons and thus has an important effect on reactor behaviour. Comparison of the results of the hybrid computer simulation with those of an all-digital one is good, within 1% to 2%

  18. Salutogenetic approach to professional training of future teachers

    Directory of Open Access Journals (Sweden)

    Ionova O.M.

    2015-02-01

    Full Text Available Purpose: disclosure of a nature and characteristics of the Movement for the renewal of adult education (New Adult Learning Movement - NALM as salutogenetic approach to the training of future teachers. Results: to analyze the nature and characteristics of salutogenetic approach to training of future teachers, which is based on anthroposophical methodological foundations and practically realized in the world as Movement for the renewal of adult education. Described the theoretical basis and direction of training (academic training, learning experiences, inner spiritual development, that allow to activate the internal intention of the person, arouse will of students to learn throughout life and contributes to the healthy development of the whole structure of the individual. Conclusions: were reported health saving forms and methods of education of future teachers: the organization of health-improving educational space, development of integrated programs (integration of educational elements - lectures, discussions, group work, project work, art classes, social exercises, etc., the rhythmic organization of educational process taking into account the human biorhythms, work with the biography of a man, pedagogical diagnostics and etc.

  19. Innovative approach to training radiation safety regulatory professionals

    International Nuclear Information System (INIS)

    Gilley, Debbie Bray

    2008-01-01

    Full text: The supply of human resources required to adequately manage a radiation safety regulatory program has diminished in the last five years. Competing professional opportunities and a reduction in the number of health physics secondary schools have made it necessary to look at alternative methods of training. There are limited educational programs in the US that prepare our professionals for careers in the Radiation Regulatory Programs. The state of Florida's radiation control program embraced a new methodology using a combination of didactic and work experience using qualification journals, subject matter experts, and formalized training to develop a qualified pool of employees to perform the regulatory functions and emergency response requirements of a state radiation control program. This program uses a task-based approach to identify training needs and draws upon current staff to develop and implement the training. This has led to a task-oriented staff capable of responding to basic regulatory and emergency response activities within one year of employment. Florida's program lends itself to other states or countries with limited resources that have experienced staff attrition due to retirement or competing employment opportunities. Information on establishing a 'task-based' pool of employees that can perform basic regulatory functions and emergency response after one year of employment will be described. Initial task analysis of core functions and methodology is used to determine the appropriate training methodology for these functions. Instructions will be provided on the methodology used to 'mentor' new employees and then incorporate the new employees into the established core functions and be a useful employee at the completion of the first year of employment. New training philosophy and regime may be useful in assisting in the development of programs in countries and states with limited resources for training radiation protection personnel. (author)

  20. Hybrid Qualifications

    DEFF Research Database (Denmark)

    Against the background of increasing qualification needs there is a growing awareness of the challenge to widen participation in processes of skill formation and competence development. At the same time, the issue of permeability between vocational education and training (VET) and general education...... has turned out as a major focus of European education and training policies and certainly is a crucial principle underlying the European Qualifications Framework (EQF). In this context, «hybrid qualifications» (HQ) may be seen as an interesting approach to tackle these challenges as they serve «two...

  1. A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran

    Directory of Open Access Journals (Sweden)

    Shakiba Khademolqorani

    2015-01-01

    Full Text Available Bankruptcy prediction is an important problem facing financial decision support for stakeholders of firms, including auditors, managers, shareholders, debt-holders, and potential investors, as well as academic researchers. Popular discourse on financial distress forecasting focuses on developing the discrete models to improve the prediction. The aim of this paper is to develop a novel hybrid financial distress model based on combining various statistical and machine learning methods. Then multiple attribute decision making method is exploited to choose the optimized model from the implemented ones. Proposed approaches have also been applied in Iranian companies that performed previous models and it can be consolidated with the help of the hybrid approach.

  2. Hybrid energy system evaluation in water supply system energy production: neural network approach

    Energy Technology Data Exchange (ETDEWEB)

    Goncalves, Fabio V.; Ramos, Helena M. [Civil Engineering Department, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal); Reis, Luisa Fernanda R. [Universidade de Sao Paulo, EESC/USP, Departamento de Hidraulica e Saneamento., Avenida do Trabalhador Saocarlense, 400, Sao Carlos-SP (Brazil)

    2010-07-01

    Water supply systems are large consumers of energy and the use of hybrid systems for green energy production is this new proposal. This work presents a computational model based on neural networks to determine the best configuration of a hybrid system to generate energy in water supply systems. In this study the energy sources to make this hybrid system can be the national power grid, micro-hydro and wind turbines. The artificial neural network is composed of six layers, trained to use data generated by a model of hybrid configuration and an economic simulator - CES. The reason for the development of an advanced model of forecasting based on neural networks is to allow rapid simulation and proper interaction with hydraulic and power model simulator - HPS. The results show that this computational model is useful as advanced decision support system in the design of configurations of hybrid power systems applied to water supply systems, improving the solutions in the development of its global energy efficiency.

  3. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng

    2016-07-06

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  4. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

    Directory of Open Access Journals (Sweden)

    Guozheng Liu

    Full Text Available Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1 examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2 explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3 investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L. and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs, but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  5. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  6. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    Science.gov (United States)

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population. PMID:27383841

  7. A hybrid approach to simulate multiple photon scattering in X-ray imaging

    International Nuclear Information System (INIS)

    Freud, N.; Letang, J.-M.; Babot, D.

    2005-01-01

    A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or γ-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results

  8. A hybrid approach to simulate multiple photon scattering in X-ray imaging

    Energy Technology Data Exchange (ETDEWEB)

    Freud, N. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)]. E-mail: nicolas.freud@insa-lyon.fr; Letang, J.-M. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France); Babot, D. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)

    2005-01-01

    A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or {gamma}-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results.

  9. A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid Wind Turbine Rotors

    Directory of Open Access Journals (Sweden)

    José F. Herbert-Acero

    2014-01-01

    Full Text Available This work presents a novel framework for the aerodynamic design and optimization of blades for small horizontal axis wind turbines (WT. The framework is based on a state-of-the-art blade element momentum model, which is complemented with the XFOIL 6.96 software in order to provide an estimate of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize the aerodynamic efficiency of small WT (SWT rotors for a wide range of operational conditions. The design variables are (1 the airfoil shape at the different blade span positions and the radial variation of the geometrical variables of (2 chord length, (3 twist angle, and (4 thickness along the blade span. A wind tunnel validation study of optimized rotors based on the NACA 4-digit airfoil series is presented. Based on the experimental data, improvements in terms of the aerodynamic efficiency, the cut-in wind speed, and the amount of material used during the manufacturing process were achieved. Recommendations for the aerodynamic design of SWT rotors are provided based on field experience.

  10. A Low Cost, Hybrid Approach to Data Mining, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed effort will combine a low cost physical modeling approach with inductive, data-centered modeling in an aerosopace relevant context to demonstrate...

  11. Hybrid Metaheuristic Approach for Nonlocal Optimization of Molecular Systems.

    Science.gov (United States)

    Dresselhaus, Thomas; Yang, Jack; Kumbhar, Sadhana; Waller, Mark P

    2013-04-09

    Accurate modeling of molecular systems requires a good knowledge of the structure; therefore, conformation searching/optimization is a routine necessity in computational chemistry. Here we present a hybrid metaheuristic optimization (HMO) algorithm, which combines ant colony optimization (ACO) and particle swarm optimization (PSO) for the optimization of molecular systems. The HMO implementation meta-optimizes the parameters of the ACO algorithm on-the-fly by the coupled PSO algorithm. The ACO parameters were optimized on a set of small difluorinated polyenes where the parameters exhibited small variance as the size of the molecule increased. The HMO algorithm was validated by searching for the closed form of around 100 molecular balances. Compared to the gradient-based optimized molecular balance structures, the HMO algorithm was able to find low-energy conformations with a 87% success rate. Finally, the computational effort for generating low-energy conformation(s) for the phenylalanyl-glycyl-glycine tripeptide was approximately 60 CPU hours with the ACO algorithm, in comparison to 4 CPU years required for an exhaustive brute-force calculation.

  12. A Hybrid Approach to Spatial Multiplexing in Multiuser MIMO Downlinks

    Directory of Open Access Journals (Sweden)

    Spencer Quentin H

    2004-01-01

    Full Text Available In the downlink of a multiuser multiple-input multiple-output (MIMO communication system, simultaneous transmission to several users requires joint optimization of the transmitted signals. Allowing all users to have multiple antennas adds an additional degree of complexity to the problem. In this paper, we examine the case where a single base station transmits to multiple users using linear processing (beamforming at each of the antenna arrays. We propose generalizations of several previous iterative algorithms for multiuser transmit beamforming that allow multiple antennas and multiple data streams for each user, and that take into account imperfect channel estimates at the transmitter. We then present a new hybrid algorithm that is based on coordinated transmit-receive beamforming, and combines the strengths of nonorthogonal iterative solutions with zero-forcing solutions. The problem of distributing power among the subchannels is solved by using standard bit-loading algorithms combined with the subchannel gains resulting from the zero-forcing solution. The result is a significant performance improvement over equal power distribution. At the same time, the number of iterations required to compute the final solution is reduced.

  13. Multi-level and hybrid modelling approaches for systems biology.

    Science.gov (United States)

    Bardini, R; Politano, G; Benso, A; Di Carlo, S

    2017-01-01

    During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

  14. A new approach to flow simulation using hybrid models

    Science.gov (United States)

    Solgi, Abazar; Zarei, Heidar; Nourani, Vahid; Bahmani, Ramin

    2017-11-01

    The necessity of flow prediction in rivers, for proper management of water resource, and the need for determining the inflow to the dam reservoir, designing efficient flood warning systems and so forth, have always led water researchers to think about models with high-speed response and low error. In the recent years, the development of Artificial Neural Networks and Wavelet theory and using the combination of models help researchers to estimate the river flow better and better. In this study, daily and monthly scales were used for simulating the flow of Gamasiyab River, Nahavand, Iran. The first simulation was done using two types of ANN and ANFIS models. Then, using wavelet theory and decomposing input signals of the used parameters, sub-signals were obtained and were fed into the ANN and ANFIS to obtain hybrid models of WANN and WANFIS. In this study, in addition to the parameters of precipitation and flow, parameters of temperature and evaporation were used to analyze their effects on the simulation. The results showed that using wavelet transform improved the performance of the models in both monthly and daily scale. However, it had a better effect on the monthly scale and the WANFIS was the best model.

  15. Hybrid Enhanced Epidermal SpaceSuit Design Approaches

    Science.gov (United States)

    Jessup, Joseph M.

    A Space suit that does not rely on gas pressurization is a multi-faceted problem that requires major stability controls to be incorporated during design and construction. The concept of Hybrid Epidermal Enhancement space suit integrates evolved human anthropomorphic and physiological adaptations into its functionality, using commercially available bio-medical technologies to address shortcomings of conventional gas pressure suits, and the impracticalities of MCP suits. The prototype HEE Space Suit explored integumentary homeostasis, thermal control and mobility using advanced bio-medical materials technology and construction concepts. The goal was a space suit that functions as an enhanced, multi-functional bio-mimic of the human epidermal layer that works in attunement with the wearer rather than as a separate system. In addressing human physiological requirements for design and construction of the HEE suit, testing regimes were devised and integrated into the prototype which was then subject to a series of detailed tests using both anatomical reproduction methods and human subject.

  16. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Science.gov (United States)

    Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin; Choo, Kim-Kwang Raymond

    2016-01-01

    To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO).

  17. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Directory of Open Access Journals (Sweden)

    Firdaus Afifi

    Full Text Available To deal with the large number of malicious mobile applications (e.g. mobile malware, a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS and particle swarm optimization (PSO. Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE and ant colony optimization (ANFIS-ACO.

  18. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware

    Science.gov (United States)

    Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin

    2016-01-01

    To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO). PMID:27611312

  19. A hybrid clustering approach to recognition of protein families in 114 microbial genomes

    Directory of Open Access Journals (Sweden)

    Gogarten J Peter

    2004-04-01

    Full Text Available Abstract Background Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function. Standard clustering methods such as single-linkage clustering capture a history of cluster topologies as a function of threshold, but in practice their usefulness is limited because unrelated sequences join clusters before biologically meaningful families are fully constituted, e.g. as the result of matches to so-called promiscuous domains. Use of the Markov Cluster algorithm avoids this non-specificity, but does not preserve topological or threshold information about protein families. Results We describe a hybrid approach to sequence-based clustering of proteins that combines the advantages of standard and Markov clustering. We have implemented this hybrid approach over a relational database environment, and describe its application to clustering a large subset of PDB, and to 328577 proteins from 114 fully sequenced microbial genomes. To demonstrate utility with difficult problems, we show that hybrid clustering allows us to constitute the paralogous family of ATP synthase F1 rotary motor subunits into a single, biologically interpretable hierarchical grouping that was not accessible using either single-linkage or Markov clustering alone. We describe validation of this method by hybrid clustering of PDB and mapping SCOP families and domains onto the resulting clusters. Conclusion Hybrid (Markov followed by single-linkage clustering combines the advantages of the Markov Cluster algorithm (avoidance of non-specific clusters resulting from matches to promiscuous domains and single-linkage clustering (preservation of topological information as a function of threshold. Within the individual Markov clusters, single-linkage clustering is a more-precise instrument, discerning sub-clusters of biological relevance. Our hybrid approach thus provides a computationally efficient

  20. Domain Adaptation for Opinion Classification: A Self-Training Approach

    Directory of Open Access Journals (Sweden)

    Yu, Ning

    2013-03-01

    Full Text Available Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.

  1. Inspector training for VIFM equipment - An integrated approach

    International Nuclear Information System (INIS)

    Truong, Q.S. Bob; Keeffe, R.; Ellacott, T.; Desson, K.; Herber, N.

    2001-01-01

    Full text: The VXI Integrated Fuel Monitor (VIFM) was developed by the Canadian Safeguards Support Program (CSSP) as a generic radiation monitor for safeguards applications. The VIFM equipment features a modular design, where a single cabinet can house several instruments such as bundle counters, core discharge monitors, Yes/No monitors, and other devices. VIFM can also be used in a stand-alone, transportable mode, with a detector connected to a single VIFM module linked to a laptop computer. VIFM equipment is currently in use at CANDU nuclear generating stations in several countries. Because each facility may have a different combination of detectors, the training program has been designed to reflect the modular nature of VIFM. Introductory material is generic and applies to any facility. More advanced material is carefully compartmentalized to allow IAEA Inspectors to concentrate their efforts in areas that concern them. Advanced material is available in a just-in-time reference format that simplifies rapid access to detailed information. A number of training resources have been developed, including multimedia and video material on CD-ROMs. This material has been designed to operate on a laptop computer, allowing inspectors to review and refresh their knowledge at any time - for example, during inspection trips. Although each of these resources is useful in its own right, the CSSP is developing an integrated approach to inspector training that combines all of these elements in a new way calculated to produce better training results than in the past. This new training approach features a two-day workshop preceded by a period of CD-ROM-based self-paced study. After the workshop, participants are able to make use of printed and CD-ROM-based reference materials for just-in-time 'refreshers'. Each step in this integrated approach to training will be described in the presentation. Briefly, the steps are as follows. A multimedia computer-based training package is made

  2. Shakeout: A New Approach to Regularized Deep Neural Network Training.

    Science.gov (United States)

    Kang, Guoliang; Li, Jun; Tao, Dacheng

    2018-05-01

    Recent years have witnessed the success of deep neural networks in dealing with a plenty of practical problems. Dropout has played an essential role in many successful deep neural networks, by inducing regularization in the model training. In this paper, we present a new regularized training approach: Shakeout. Instead of randomly discarding units as Dropout does at the training stage, Shakeout randomly chooses to enhance or reverse each unit's contribution to the next layer. This minor modification of Dropout has the statistical trait: the regularizer induced by Shakeout adaptively combines , and regularization terms. Our classification experiments with representative deep architectures on image datasets MNIST, CIFAR-10 and ImageNet show that Shakeout deals with over-fitting effectively and outperforms Dropout. We empirically demonstrate that Shakeout leads to sparser weights under both unsupervised and supervised settings. Shakeout also leads to the grouping effect of the input units in a layer. Considering the weights in reflecting the importance of connections, Shakeout is superior to Dropout, which is valuable for the deep model compression. Moreover, we demonstrate that Shakeout can effectively reduce the instability of the training process of the deep architecture.

  3. Building national capacity for research mentor training: an evidence-based approach to training the trainers.

    Science.gov (United States)

    Pfund, Christine; Spencer, Kimberly C; Asquith, Pamela; House, Stephanie C; Miller, Sarah; Sorkness, Christine A

    2015-01-01

    Research mentor training (RMT), based on the published Entering Mentoring curricula series, has been shown to improve the knowledge and skills of research mentors across career stages, as self-reported by both the mentors engaged in training and their mentees. To promote widespread dissemination and empower others to implement this evidence-based training at their home institutions, we developed an extensive, interactive, multifaceted train-the-trainer workshop. The specific goals of these workshops are to 1) increase facilitator knowledge of an RMT curriculum, 2) increase facilitator confidence in implementing the curriculum, 3) provide a safe environment to practice facilitation of curricular activities, and 4) review implementation strategies and evaluation tools. Data indicate that our approach results in high satisfaction and significant confidence gains among attendees. Of the 195 diverse attendees trained in our workshops since Fall 2010, 44% report implementation at 39 different institutions, collectively training more than 500 mentors. Further, mentors who participated in the RMT sessions led by our trained facilitators report high facilitator effectiveness in guiding discussion. Implications and challenges to building the national capacity needed for improved research mentoring relationships are discussed. © 2015 C. Pfund, K. C. Spencer, et al. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  4. Molecular and morphological approaches for species delimitation and hybridization investigations of two Cichla species

    Directory of Open Access Journals (Sweden)

    Andrea A. F. Mourão

    Full Text Available ABSTRACT The hybridization is a widely-discussed issue in several studies with fish species. For some authors, hybridization may be related with diversification and speciation of several groups, or also with the extinction of populations or species. Difficulties to differentiate species and hybrids may be a problem to correctly apply a management of wild species, because hybrid lineages, especially the advanced ones, may resemble the parental species. The genus Cichla Bloch & Schneider, 1801 constitutes an interesting experimental model, considering that hybridization and taxonomic uncertainties hinder a correct identification. Considering these problems, in this study, we developed genetic methodologies and applied meristic and morphometric approaches in wild samples in order to identify species and for test a possible hybridization between Cichla kelberi Kullander & Ferreira, 2006 and Cichla piquiti Kullander & Ferreira, 2006. For this, C. kelberi, C. piquiti and potential hybrid ( carijó individuals were collected in Paraná and Tietê rivers (SP, Brazil. For meristic and morphometric methods, the individuals were analyzed using the statistical software Pcord 5:31, while for molecular methods, primers for PCR-multiplex were designed and enzyme for PCR-RFLP were selected, under the species-specific nucleotide. All results indicated that the carijó is not an interspecific hybrid, because it presented identical genetic pattern and morphology closed to C. piquiti. Thus, we propose that carijó is a C. piquiti morphotype. In addition, this study promotes a new molecular tool that could be used in future research, monitoring and management programs of the genus Cichla.

  5. Training programs for the systems approach to nuclear security

    International Nuclear Information System (INIS)

    Ellis, Doris E.

    2005-01-01

    In support of the US Government and the International Atomic Energy Agency (IAEA) Nuclear Security Programmes, Sandia National Laboratories (SNL) has advocated and practiced a risk-based, systematic approach to nuclear security. The risk equation has been implemented as the basis for a performance methodology for the design and evaluation of Physical Protection Systems against a Design Basis Threat (DBT) for theft or sabotage of nuclear and/or radiological materials. Since integrated systems must include people as well as technology and the man-machine interface, a critical aspect of the human element is to train all stakeholders in nuclear security on the systems approach. Current training courses have been beneficial but are still limited in scope. SNL has developed two primary international courses and is completing development of three new courses that will be offered and presented in the near term. In the long-term, SNL envisions establishing a comprehensive nuclear security training curriculum that will be developed along with a series of forthcoming IAEA Nuclear Security Series guidance documents.

  6. A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

    Science.gov (United States)

    Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

    2017-12-01

    Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

  7. Bioenergy II. Biomass Valorisation by a Hybrid Thermochemical Fractionation Approach

    Energy Technology Data Exchange (ETDEWEB)

    De Wild, P.J.; Den Uil, H.; Reith, J.H. [ECN Biomass, Coal and Environmental Research, Petten (Netherlands); Lunshof, A.; Hendriks, C.; Van Eck, E. [Radboud University, Nijmegen (Netherlands); Heeres, E. [University of Groningen, Groningen (Netherlands)

    2009-11-15

    The need for green renewable sources is adamant because of the adverse effects of the increasing use of fossil fuels on our society. Biomass has been considered as a very attractive candidate for green energy carriers, chemicals and materials. The development of cheap and efficient fractionation technology to separate biomass into its main constituents is highly desirable. It enables treatment of each constituent separately, using dedicated conversion technologies to get specific target chemicals. The synergistic combination of aquathermolysis (hot pressurised water treatment) and pyrolysis (thermal degradation in the absence of oxygen) is a promising thermolysis option, integrating fractionation of biomass with production of valuable chemicals. Batch aquathermolysis in an autoclave and subsequent pyrolysis using bubbling fluidised bed reactor technology with beech, poplar, spruce and straw indicate the potential of this hybrid concept to valorise lignocellulosic biomass. Hemicellulose-derived furfural was obtained in yields that ranged from 2 wt% for spruce to 8 wt% for straw. Hydroxymethylfurfural from hemicellulose was obtained in yields from 0.3 wt% for poplar to 3 wt% for spruce. Pyrolysis of the aquathermolised biomass types resulted in 8 wt% (straw) to 11 wt% (spruce) of cellulose-derived levoglucosan. Next to the furfurals and levoglucosan, appreciable amounts of acetic acid were obtained as well from the aquathermolysis step, ranging from 1 wt% for spruce to 5 wt% for straw. To elucidate relations between the chemical changes occurring in the biomass during the integrated process and type and amount of the chemical products formed, a 13C-solid state NMR study has been conducted. Main conclusions are that aquathermolysis results in hemicellulose degradation to lower molecular weight components. Lignin ether bonds are broken, but apart from that, lignin is hardly affected by the aquathermolysis. Cellulose is also retained, although it seems to become more

  8. Hybrid gait training with an overground robot for people with incomplete spinal cord injury: a pilot study

    Directory of Open Access Journals (Sweden)

    Antonio J del-Ama

    2014-05-01

    Full Text Available Locomotor training has proved to provide beneficial effect in terms of mobility in incomplete paraplegic patients. Neuroprosthetic technology can contribute to increase the efficacy of a training paradigm in the promotion of a locomotor pattern. Robotic exoskeletons can be used to manage the unavoidable loss of performance of artificially-driven muscles. Hybrid exoskeletons blend complementary robotic and neuro-prosthetic technologies. The aim of this pilot study was to determine the effects of hybrid gait training in three case studies with persons with incomplete spinal cord injury in terms of locomotion performance during assisted gait, patient-robot adaptations, impact on ambulation and assessment of lower limb muscle strength and spasticity. Participants with incomplete Spinal Cord Injury (SCI received interventions with a hybrid bilateral exoskeleton for 4 days. Assessment of gait function revealed that patients improved the 6 minutes and 10 meters walking tests after the intervention, and further improvements were observed one week after the intervention. Muscle examination revealed improvements in knee and hip sagittal muscle balance scores and decreased score in ankle extensor balance. It is concluded that improvements in biomechanical function of the knee joint after the tested overground hybrid gait trainer are coherent with improvements in gait performance.

  9. Hybrid gait training with an overground robot for people with incomplete spinal cord injury: a pilot study.

    Science.gov (United States)

    Del-Ama, Antonio J; Gil-Agudo, Angel; Pons, José L; Moreno, Juan C

    2014-01-01

    Locomotor training has proved to provide beneficial effect in terms of mobility in incomplete paraplegic patients. Neuroprosthetic technology can contribute to increase the efficacy of a training paradigm in the promotion of a locomotor pattern. Robotic exoskeletons can be used to manage the unavoidable loss of performance of artificially driven muscles. Hybrid exoskeletons blend complementary robotic and neuro-prosthetic technologies. The aim of this pilot study was to determine the effects of hybrid gait training in three case studies with persons with incomplete spinal cord injury (iSCI) in terms of locomotion performance during assisted gait, patient-robot adaptations, impact on ambulation and assessment of lower limb muscle strength and spasticity. Participants with iSCI received interventions with a hybrid bilateral exoskeleton for 4 days. Assessment of gait function revealed that patients improved the 6 min and 10 m walking tests after the intervention, and further improvements were observed 1 week after the intervention. Muscle examination revealed improvements in knee and hip sagittal muscle balance scores and decreased score in ankle extensor balance. It is concluded that improvements in biomechanical function of the knee joint after the tested overground hybrid gait trainer are coherent with improvements in gait performance.

  10. Application of systematic approach to training at TVO Nuclear Power Plant

    International Nuclear Information System (INIS)

    Piirto, A.; Latva, T.-M.; Yli-Antola, K.

    2002-01-01

    Systematic Approach to Training has been used at TVO as the basic principle directing training activity especially in the training of operating personnel. This paper presents how training in general has been planned to be developed. Special attention has been paid on the more systematic realization of the training program of maintenance personnel

  11. Statistical comparison of a hybrid approach with approximate and exact inference models for Fusion 2+

    Science.gov (United States)

    Lee, K. David; Wiesenfeld, Eric; Gelfand, Andrew

    2007-04-01

    One of the greatest challenges in modern combat is maintaining a high level of timely Situational Awareness (SA). In many situations, computational complexity and accuracy considerations make the development and deployment of real-time, high-level inference tools very difficult. An innovative hybrid framework that combines Bayesian inference, in the form of Bayesian Networks, and Possibility Theory, in the form of Fuzzy Logic systems, has recently been introduced to provide a rigorous framework for high-level inference. In previous research, the theoretical basis and benefits of the hybrid approach have been developed. However, lacking is a concrete experimental comparison of the hybrid framework with traditional fusion methods, to demonstrate and quantify this benefit. The goal of this research, therefore, is to provide a statistical analysis on the comparison of the accuracy and performance of hybrid network theory, with pure Bayesian and Fuzzy systems and an inexact Bayesian system approximated using Particle Filtering. To accomplish this task, domain specific models will be developed under these different theoretical approaches and then evaluated, via Monte Carlo Simulation, in comparison to situational ground truth to measure accuracy and fidelity. Following this, a rigorous statistical analysis of the performance results will be performed, to quantify the benefit of hybrid inference to other fusion tools.

  12. The business case for condition-based maintenance: a hybrid (non-) financial approach

    NARCIS (Netherlands)

    Tiddens, W.W.; Tinga, T.; Braaksma, A.J.J.; Brouwer, O.; Cepin, Marko; Bris, Radim

    2017-01-01

    Although developing business cases is key for evaluating project success, the costs and benefits of condition-based maintenance (CBM) implementations are often not explicitly defined and evaluated. Using the design science methodology, we developed a hybrid business case approach to help managers

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

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

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

  14. Students' Game Performance Improvements during a Hybrid Sport Education-Step-Game-Approach Volleyball Unit

    Science.gov (United States)

    Araújo, Rui; Mesquita, Isabel; Hastie, Peter; Pereira, Cristiana

    2016-01-01

    The purpose of this study was to examine a hybrid combination of sport education and the step-game-approach (SGA) on students' gameplay performance in volleyball, taking into account their sex and skill-level. Seventeen seventh-grade students (seven girls, 10 boys, average age 11.8) participated in a 25-lesson volleyball season, in which the…

  15. A hybrid approach to decision making and information fusion: Combining humans and artificial agents

    NARCIS (Netherlands)

    Groen, Frans C.A.; Pavlin, Gregor; Winterboer, Andi; Evers, Vanessa

    This paper argues that hybrid human–agent systems can support powerful solutions to relevant problems such as Environmental Crisis management. However, it shows that such solutions require comprehensive approaches covering different aspects of data processing, model construction and the usage. In

  16. TwitterNEED: a hybrid approach for named entity extraction and disambiguation for tweets

    NARCIS (Netherlands)

    Habib, Mena Badieh; van Keulen, Maurice

    Twitter is a rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing tasks. In this paper, we present TwitterNEED, a hybrid approach for Named Entity Extraction and Named Entity Disambiguation for tweets. We

  17. A hybrid system approach to airspeed, angle of attack and sideslip estimation in Unmanned Aerial Vehicles

    KAUST Repository

    Shaqura, Mohammad; Claudel, Christian

    2015-01-01

    , low power autopilots in real-time. The computational method is based on a hybrid decomposition of the modes of operation of the UAV. A Bayesian approach is considered for estimation, in which the estimated airspeed, angle of attack and sideslip

  18. A Hybrid Approach to Processing Big Data Graphs on Memory-Restricted Systems

    KAUST Repository

    Harshvardhan,; West, Brandon; Fidel, Adam; Amato, Nancy M.; Rauchwerger, Lawrence

    2015-01-01

    that sacrifice performance. In this work, we propose a novel RAM-Disk hybrid approach to graph processing that can scale well from a single shared-memory node to large distributed-memory systems. It works by partitioning the graph into sub graphs that fit in RAM

  19. A training approach for the transition of repeatable collaboration processes to practitioners

    NARCIS (Netherlands)

    Kolfschoten, G.L.; De Vreede, G.J.; Pietron, L.R.

    2011-01-01

    This paper presents a training approach to support the deployment of collaboration process support according to the Collaboration Engineering approach. In Collaboration Engineering, practitioners in an organization are trained to facilitate a specific collaborative work practice on a recurring

  20. A hybrid linked data approach to support asset management

    NARCIS (Netherlands)

    Luiten, G.T.; Bohms, H.M.; O'Keeffe, A.; Nederveen, S. van; Bakker, J.; Wikstrom, L.

    2016-01-01

    This paper evaluates experiences with applying a linked data approach for coping with the many challenges for information management in asset management from the perspective of National Road Authorities (NRAs). As influential players, NRAs are often the initiators of innovation in the civil

  1. Systematic approach to training for competence building in radiation safety

    International Nuclear Information System (INIS)

    Asiamah, S.D.; Schandorf, C.; Darko, E.O.

    2003-01-01

    Competence building involves four main attributes, namely, knowledge, skills, operating experience and attitude to radiation safety. These multi-attribute requirements demand a systematic approach to education and training of regulatory staff, licensees/registrants and service providers to ensure commensurate competence in performance of responsibilities and duties to specified standards. In order to address issues of competencies required in radiation safety a national programme for qualification and certification has been initiated for regulatory staff, operators, radiation safety officers and qualified experts. Since the inception of this programme in 1993, 40 training events have been organized involving 423 individuals. This programme is at various levels of implementation due to financial and human resource constraints. A department for Human Resource Development and Research was established in 2000 to enhance and ensure the sustainability of the effectiveness of capacity building in radiation safety. (author)

  2. Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

    Science.gov (United States)

    Chiadamrong, N.; Piyathanavong, V.

    2017-12-01

    Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

  3. Restraining approach for the spurious kinematic modes in hybrid equilibrium element

    Science.gov (United States)

    Parrinello, F.

    2013-10-01

    The present paper proposes a rigorous approach for the elimination of spurious kinematic modes in hybrid equilibrium elements, for three well known mesh patches. The approach is based on the identification of the dependent equations in the set of inter-element and boundary equilibrium equations of the sides involved in the spurious kinematic mode. Then the kinematic variables related to the dependent equations are reciprocally constrained and, by application of master slave elimination method, the set of inter-element equilibrium equations is reduced to full rank. The elastic solutions produced by means of the proposed approach verify the homogeneous, the inter-element and the boundary equilibrium equations. Hybrid stress formulation is developed in a rigorous mathematical setting. The results of linear elastic analysis obtained by the proposed approach and by classical displacement based method are compared for some structural examples.

  4. FUTURE TEACHERS TRAINING TO INNOVATIVE PEDAGOGICAL ACTIVITY: CONTEXT APPROACH

    Directory of Open Access Journals (Sweden)

    Shevchenko L.

    2017-03-01

    Full Text Available The innovative processes in education arose in different historical periods and determined its development. The analysis of theoretical and experimental studies showed that now the teachers have difficulty in developing and implementing innovative technologies, choosing the most appropriate pedagogical methods and assets. The widespread innovations lead to changes in future teachers’ training to the professional activity. The leading objective of higher pedagogical education is to train teacher who has the developed personal and professional skills, able to perform innovative teaching activity. The achievement of this strategic objective requires the organization of targeted training of future teachers to innovative pedagogical activity in terms of higher education system, promoting their professional and personal growth, the formation of innovative capacity and innovative culture. In this regard, there is a need to find approaches to education that are focused on the future content of professional activity. In our opinion, these requirements fully meet the contextual approach that provides consistent, continuous and systematic formation of future teachers’ readiness to innovative pedagogical activity. The this article we analyzed the features of the training of future teachers to innovative pedagogical activity; identified the possibilities of contextual education application in pedagogical institutions; considered the survey results of the beginning teachers of secondary and vocational schools; defined a number of innovative forms, methods and technologies for implementing the contextual education system thet allow combining educational, quasi professional and educational-professional activity, such as: design and usage of electronic educational resources, electronic teaching methods; engaging students into self-educational activity by means of Web services; fulfillment of individual and group projects based on Web and Blog-quests in which

  5. A Hybrid approach for aeroacoustic analysis of the engine exhaust system

    OpenAIRE

    Sathyanarayana, Y; Munjal, ML

    2000-01-01

    This paper presents a new hybrid approach for prediction of noise radiation from engine exhaust systems. It couples the time domain analysis of the engine and the frequency domain analysis of the muffler, and has the advantages of both. In this approach, cylinder/cavity is analyzed in the time domain to calculate the exhaust mass flux history at the exhaust valve by means of the method of characteristics, avoiding the tedious procedure of interpolation at every mesh point and solving a number...

  6. Unilateral robotic hybrid mini-maze: a novel experimental approach.

    Science.gov (United States)

    Moslemi, Mohammad; Rawashdeh, Badi; Meyer, Mark; Nguyen, Duy; Poston, Robert; Gharagozloo, Farid

    2016-03-01

    A complete Cox maze IV procedure is difficult to accomplish using current endoscopic and minimally invasive techniques. These techniques are hampered by inability to adequately dissect the posterior structures of the heart and place all necessary lesions. We present a novel approach, using robotic technology, that achieves placement of all the lesions of the complete maze procedure. In three cadaveric human models, the technical feasibility of using robotic instruments through the right chest to dissect the posterior structures of the heart and place all Cox maze lesions was performed. The entire posterior aspect of the heart was dissected in the cadaveric model facilitating successful placement of all Cox maze IV lesions with robotic assistance through minimally invasive incisions. The robotic Cox maze IV procedure through the novel right thoracic approach is feasible. This obviates the need for sternotomy and avoids the associated morbidity of the conventional Cox-maze procedure. Copyright © 2015 John Wiley & Sons, Ltd.

  7. The evolution of green jobs in Scotland: A hybrid approach

    International Nuclear Information System (INIS)

    Connolly, Kevin; Allan, Grant J; McIntyre, Stuart G

    2016-01-01

    In support of its ambitious target to reduce CO_2 emissions the Scottish Government is aiming to have the equivalent of 100% of Scottish electricity consumption generated from renewable sources by 2020. This is, at least in part, motivated by an expectation of subsequent employment growth in low carbon and renewable energy technologies; however there is no official data source to track employment in these areas. This has led to a variety of definitions, methodologies and alternative estimates being produced. Building on a recent study (Bishop and Brand, 2013) we develop a “hybrid” approach which combines the detail of “bottom-up” surveys with “top-down” trend data to produce estimates on employment in Low Carbon Environmental Goods and Services (LCEGS). We demonstrate this methodology to produce estimates for such employment in Scotland between 2004 and 2012. Our approach shows how survey and official sources can combine to produce a more timely measure of employment in LCEGS activities, assisting policymakers in tracking, consistently, developments. Applying our approach, we find that over this period employment in LCEGS in Scotland grew, but that this was more volatile than aggregate employment, and in particular that employment in this sector was particularly badly hit during the great recession. - Highlights: • A “hybrid” approach estimates green jobs from bottom-up detail and top-down data. • Illustrative results show the evolution of such jobs in Scotland from 2004 to 2012. • Method provides policymakers a timely measure of the jobs success of energy policy.

  8. Hybrid approaches to nanometer-scale patterning: Exploiting tailored intermolecular interactions

    International Nuclear Information System (INIS)

    Mullen, Thomas J.; Srinivasan, Charan; Shuster, Mitchell J.; Horn, Mark W.; Andrews, Anne M.; Weiss, Paul S.

    2008-01-01

    In this perspective, we explore hybrid approaches to nanometer-scale patterning, where the precision of molecular self-assembly is combined with the sophistication and fidelity of lithography. Two areas - improving existing lithographic techniques through self-assembly and fabricating chemically patterned surfaces - will be discussed in terms of their advantages, limitations, applications, and future outlook. The creation of such chemical patterns enables new capabilities, including the assembly of biospecific surfaces to be recognized by, and to capture analytes from, complex mixtures. Finally, we speculate on the potential impact and upcoming challenges of these hybrid strategies.

  9. A Hybrid FEM-ANN Approach for Slope Instability Prediction

    Science.gov (United States)

    Verma, A. K.; Singh, T. N.; Chauhan, Nikhil Kumar; Sarkar, K.

    2016-09-01

    Assessment of slope stability is one of the most critical aspects for the life of a slope. In any slope vulnerability appraisal, Factor Of Safety (FOS) is the widely accepted index to understand, how close or far a slope from the failure. In this work, an attempt has been made to simulate a road cut slope in a landslide prone area in Rudrapryag, Uttarakhand, India which lies near Himalayan geodynamic mountain belt. A combination of Finite Element Method (FEM) and Artificial Neural Network (ANN) has been adopted to predict FOS of the slope. In ANN, a three layer, feed- forward back-propagation neural network with one input layer and one hidden layer with three neurons and one output layer has been considered and trained using datasets generated from numerical analysis of the slope and validated with new set of field slope data. Mean absolute percentage error estimated as 1.04 with coefficient of correlation between the FOS of FEM and ANN as 0.973, which indicates that the system is very vigorous and fast to predict FOS for any slope.

  10. On application of the systematic approach to training in Qinshan NPP

    International Nuclear Information System (INIS)

    Wang Riqing

    1997-01-01

    The author describes the feature of systematic approach to training and introduces the situation about using the approach for training operation and maintenance personnel in Qinshan NPP. The final part of paper shows that there are still some problems worthy of serious consideration in application of the systematic approach to training in nuclear power plant

  11. A hybrid, coupled approach for modeling charged fluids from the nano to the mesoscale

    Science.gov (United States)

    Cheung, James; Frischknecht, Amalie L.; Perego, Mauro; Bochev, Pavel

    2017-11-01

    We develop and demonstrate a new, hybrid simulation approach for charged fluids, which combines the accuracy of the nonlocal, classical density functional theory (cDFT) with the efficiency of the Poisson-Nernst-Planck (PNP) equations. The approach is motivated by the fact that the more accurate description of the physics in the cDFT model is required only near the charged surfaces, while away from these regions the PNP equations provide an acceptable representation of the ionic system. We formulate the hybrid approach in two stages. The first stage defines a coupled hybrid model in which the PNP and cDFT equations act independently on two overlapping domains, subject to suitable interface coupling conditions. At the second stage we apply the principles of the alternating Schwarz method to the hybrid model by using the interface conditions to define the appropriate boundary conditions and volume constraints exchanged between the PNP and the cDFT subdomains. Numerical examples with two representative examples of ionic systems demonstrate the numerical properties of the method and its potential to reduce the computational cost of a full cDFT calculation, while retaining the accuracy of the latter near the charged surfaces.

  12. Numerical schemes for the hybrid modeling approach of gas-particle turbulent flows

    International Nuclear Information System (INIS)

    Dorogan, K.

    2012-01-01

    Hybrid Moments/PDF methods have shown to be well suitable for the description of poly-dispersed turbulent two-phase flows in non-equilibrium which are encountered in some industrial situations involving chemical reactions, combustion or sprays. They allow to obtain a fine enough physical description of the poly-dispersity, non-linear source terms and convection phenomena. However, their approximations are noised with the statistical error, which in several situations may be a source of a bias. An alternative hybrid Moments-Moments/PDF approach examined in this work consists in coupling the Moments and the PDF descriptions, within the description of the dispersed phase itself. This hybrid method could reduce the statistical error and remove the bias. However, such a coupling is not straightforward in practice and requires the development of accurate and stable numerical schemes. The approaches introduced in this work rely on the combined use of the up-winding and relaxation-type techniques. They allow to obtain stable unsteady approximations for a system of partial differential equations containing non-smooth external data which are provided by the PDF part of the model. A comparison of the results obtained using the present method with those of the 'classical' hybrid approach is presented in terms of the numerical errors for a case of a co-current gas-particle wall jet. (author)

  13. A novel hybrid approach for predicting wind farm power production based on wavelet transform, hybrid neural networks and imperialist competitive algorithm

    International Nuclear Information System (INIS)

    Aghajani, Afshin; Kazemzadeh, Rasool; Ebrahimi, Afshin

    2016-01-01

    Highlights: • Proposing a novel hybrid method for short-term prediction of wind farms with high accuracy. • Investigating the prediction accuracy for proposed method in comparison with other methods. • Investigating the effect of six types of parameters as input data on predictions. • Comparing results for 6 & 4 types of the input parameters – addition of pressure and air humidity. - Abstract: This paper proposes a novel hybrid approach to forecast electric power production in wind farms. Wavelet transform (WT) is employed to filter input data of wind power, while radial basis function (RBF) neural network is utilized for primary prediction. For better predictions the main forecasting engine is comprised of three multilayer perceptron (MLP) neural networks by different learning algorithms of Levenberg–Marquardt (LM), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and Bayesian regularization (BR). Meta-heuristic technique Imperialist Competitive Algorithm (ICA) is used to optimize neural networks’ weightings in order to escape from local minima. In the forecast process, the real data of wind farms located in the southern part of Alberta, Canada, are used to train and test the proposed model. The data are a complete set of six meteorological and technical characteristics, including wind speed, wind power, wind direction, temperature, pressure, and air humidity. In order to demonstrate the efficiency of the proposed method, it is compared with several other wind power forecast techniques. Results of optimizations indicate the superiority of the proposed method over the other mentioned techniques; and, forecasting error is remarkably reduced. For instance, the average normalized root mean square error (NRMSE) and average mean absolute percentage error (MAPE) are respectively 11% and 14% lower for the proposed method in 1-h-ahead forecasts over a 24-h period with six types of input than those for the best of the compared models.

  14. Entity recognition in the biomedical domain using a hybrid approach.

    Science.gov (United States)

    Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

    2017-11-09

    This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

  15. Approach to team skills training of nuclear power plant control room crews

    International Nuclear Information System (INIS)

    Davis, L.T.; Gaddy, C.D.; Turney, J.R.

    1985-07-01

    An investigation of current team skills training practices and research was conducted by General Physics Corporation for the Office of Nuclear Reactor Regulation. The methodology used included a review of relevant team skills training literature and a workshop to collect inputs from team training practitioners and researchers from the public and private sectors. The workshop was attended by representatives from nuclear utility training organizations, the commercial airline industry, federal agencies, and defense training and research commands. The literature reviews and workshop results provided the input for a suggested approach to team skills training that can be integrated into existing training programs for control room operating crews. The approach includes five phases: (1) team skills objectives development, (2) basic team skills training, (3) team task training, (4) team skills evaluation, and (5) team training program evaluation. Supporting background information and a user-oriented description of the approach to team skills training are provided. 47 refs

  16. A bottom-up approach for the synthesis of highly ordered fullerene-intercalated graphene hybrids

    Directory of Open Access Journals (Sweden)

    Dimitrios eGournis

    2015-02-01

    Full Text Available Much of the research effort on graphene focuses on its use as a building block for the development of new hybrid nanostructures with well-defined dimensions and properties suitable for applications such as gas storage, heterogeneous catalysis, gas/liquid separations, nanosensing and biomedicine. Towards this aim, here we describe a new bottom-up approach, which combines self-assembly with the Langmuir Schaefer deposition technique to synthesize graphene-based layered hybrid materials hosting fullerene molecules within the interlayer space. Our film preparation consists in a bottom-up layer-by-layer process that proceeds via the formation of a hybrid organo-graphene oxide Langmuir film. The structure and composition of these hybrid fullerene-containing thin multilayers deposited on hydrophobic substrates were characterized by a combination of X-ray diffraction, Raman and X-ray photoelectron spectroscopies, atomic force microscopy and conductivity measurements. The latter revealed that the presence of C60 within the interlayer spacing leads to an increase in electrical conductivity of the hybrid material as compared to the organo-graphene matrix alone.

  17. A hybrid approach to device integration on a genetic analysis platform

    International Nuclear Information System (INIS)

    Brennan, Des; Justice, John; Aherne, Margaret; Galvin, Paul; Jary, Dorothee; Kurg, Ants; Berik, Evgeny; Macek, Milan

    2012-01-01

    Point-of-care (POC) systems require significant component integration to implement biochemical protocols associated with molecular diagnostic assays. Hybrid platforms where discrete components are combined in a single platform are a suitable approach to integration, where combining multiple device fabrication steps on a single substrate is not possible due to incompatible or costly fabrication steps. We integrate three devices each with a specific system functionality: (i) a silicon electro-wetting-on-dielectric (EWOD) device to move and mix sample and reagent droplets in an oil phase, (ii) a polymer microfluidic chip containing channels and reservoirs and (iii) an aqueous phase glass microarray for fluorescence microarray hybridization detection. The EWOD device offers the possibility of fully integrating on-chip sample preparation using nanolitre sample and reagent volumes. A key challenge is sample transfer from the oil phase EWOD device to the aqueous phase microarray for hybridization detection. The EWOD device, waveguide performance and functionality are maintained during the integration process. An on-chip biochemical protocol for arrayed primer extension (APEX) was implemented for single nucleotide polymorphism (SNiP) analysis. The prepared sample is aspirated from the EWOD oil phase to the aqueous phase microarray for hybridization. A bench-top instrumentation system was also developed around the integrated platform to drive the EWOD electrodes, implement APEX sample heating and image the microarray after hybridization. (paper)

  18. New MPPT algorithm for PV applications based on hybrid dynamical approach

    KAUST Repository

    Elmetennani, Shahrazed

    2016-10-24

    This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

  19. Mixed H∞ and passive control for linear switched systems via hybrid control approach

    Science.gov (United States)

    Zheng, Qunxian; Ling, Youzhu; Wei, Lisheng; Zhang, Hongbin

    2018-03-01

    This paper investigates the mixed H∞ and passive control problem for linear switched systems based on a hybrid control strategy. To solve this problem, first, a new performance index is proposed. This performance index can be viewed as the mixed weighted H∞ and passivity performance. Then, the hybrid controllers are used to stabilise the switched systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. The design of state updating controllers not only depends on the pre-switching subsystem and the post-switching subsystem, but also depends on the measurable output signal. The hybrid controllers proposed in this paper can include some existing ones as special cases. Combine the multiple Lyapunov functions approach with the average dwell time technique, new sufficient conditions are obtained. Under the new conditions, the closed-loop linear switched systems are globally uniformly asymptotically stable with a mixed H∞ and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example and a practical example are given.

  20. Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach

    Directory of Open Access Journals (Sweden)

    Oliveira Rui

    2010-09-01

    Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.

  1. New MPPT algorithm for PV applications based on hybrid dynamical approach

    KAUST Repository

    Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem; Djemai, M.; Tadjine, M.

    2016-01-01

    This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

  2. An effective secondary decomposition approach for wind power forecasting using extreme learning machine trained by crisscross optimization

    International Nuclear Information System (INIS)

    Yin, Hao; Dong, Zhen; Chen, Yunlong; Ge, Jiafei; Lai, Loi Lei; Vaccaro, Alfredo; Meng, Anbo

    2017-01-01

    Highlights: • A secondary decomposition approach is applied in the data pre-processing. • The empirical mode decomposition is used to decompose the original time series. • IMF1 continues to be decomposed by applying wavelet packet decomposition. • Crisscross optimization algorithm is applied to train extreme learning machine. • The proposed SHD-CSO-ELM outperforms other pervious methods in the literature. - Abstract: Large-scale integration of wind energy into electric grid is restricted by its inherent intermittence and volatility. So the increased utilization of wind power necessitates its accurate prediction. The contribution of this study is to develop a new hybrid forecasting model for the short-term wind power prediction by using a secondary hybrid decomposition approach. In the data pre-processing phase, the empirical mode decomposition is used to decompose the original time series into several intrinsic mode functions (IMFs). A unique feature is that the generated IMF1 continues to be decomposed into appropriate and detailed components by applying wavelet packet decomposition. In the training phase, all the transformed sub-series are forecasted with extreme learning machine trained by our recently developed crisscross optimization algorithm (CSO). The final predicted values are obtained from aggregation. The results show that: (a) The performance of empirical mode decomposition can be significantly improved with its IMF1 decomposed by wavelet packet decomposition. (b) The CSO algorithm has satisfactory performance in addressing the premature convergence problem when applied to optimize extreme learning machine. (c) The proposed approach has great advantage over other previous hybrid models in terms of prediction accuracy.

  3. A Hybrid Harmony Search Algorithm Approach for Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Mimoun YOUNES

    2012-08-01

    Full Text Available Optimal Power Flow (OPF is one of the main functions of Power system operation. It determines the optimal settings of generating units, bus voltage, transformer tap and shunt elements in Power System with the objective of minimizing total production costs or losses while the system is operating within its security limits. The aim of this paper is to propose a novel methodology (BCGAs-HSA that solves OPF including both active and reactive power dispatch It is based on combining the binary-coded genetic algorithm (BCGAs and the harmony search algorithm (HSA to determine the optimal global solution. This method was tested on the modified IEEE 30 bus test system. The results obtained by this method are compared with those obtained with BCGAs or HSA separately. The results show that the BCGAs-HSA approach can converge to the optimum solution with accuracy compared to those reported recently in the literature.

  4. Training digital divide seniors to use a telehealth system: a remote training approach.

    Science.gov (United States)

    Lai, Albert M; Kaufman, David R; Starren, Justin

    2006-01-01

    As the use of health information technologies continues to proliferate amongst seniors, many of whom lack computer experience, there is a need to develop effective training approaches to foster basic competencies. This paper describes the REmote Patient Education in a Telemedicine Environment (REPETE) system, a component of the IDEATel telemedicine architecture. The REPETE architecture supports simultaneous visual and audio teaching modes over low bandwidth connections. This paper presents an in-depth qualitative analysis of two patients being trained to use the IDEATel patient web portal. The results indicate that this method of instruction was useful in facilitating patients' use of the web application. However, the observations suggest that there is learning curve for the trainer to use the resources effectively to establish common ground and foster competencies in the patient.

  5. A Multimedia Approach to ODL for Agricultural Training in Cambodia

    Directory of Open Access Journals (Sweden)

    Helena Grunfeld

    2013-03-01

    Full Text Available Open distance learning (ODL has long been an important option for formal and non-formal education (NFE in most developed and developing countries, but less so in post-conflict countries, including Cambodia. However, in Cambodia there is now greater awareness that ODL can complement traditional face-to-face educational approaches, particularly as there is a shortage of teachers in the country. Thus, understanding how ODL can achieve learning and other objectives has important implications for both formal education and NFE. If it can be found to be effective, ODL has the potential of reaching a large number of people at comparatively lower average costs. This paper reports on a project where the same content was taught to farmers in Cambodia via traditional face-to-face and via ODL and compares outcomes between the different training methods. Exploring the extent to which farmers had adopted new farm practices taught in the course, our results indicate that the outcomes did not vary considerably between those trained using the different approaches.

  6. NBI - plasma vaporization hybrid approach in bladder cancer endoscopic management.

    Science.gov (United States)

    Stănescu, F; Geavlete, B; Georgescu, D; Jecu, M; Moldoveanu, C; Adou, L; Bulai, C; Ene, C; Geavlete, P

    2014-06-15

    A prospective study was performed aiming to evaluate the surgical efficacy, perioperative safety profile, diagnostic accuracy and medium term results of a multi-modal approach consisting in narrow band imaging (NBI) cystoscopy and bipolar plasma vaporization (BPV) when compared to the standard protocol represented by white light cystoscopy (WLC) and transurethral resection of bladder tumors (TURBT). A total of 260 patients with apparently at least one bladder tumor over 3 cm were included in the trial. In the first group, 130 patients underwent conventional and NBI cystoscopy followed by BPV, while in a similar number of cases of the second arm, classical WLC and TURBT were applied. In all non-muscle invasive bladder tumors' (NMIBT) pathologically confirmed cases, standard monopolar Re-TUR was performed at 4-6 weeks after the initial intervention, followed by one year' BCG immunotherapy. The follow-up protocol included abdominal ultrasound, urinary cytology and WLC, performed every 3 months for a period of 2 years. The obturator nerve stimulation, bladder wall perforation, mean hemoglobin level drop, postoperative bleeding, catheterization period and hospital stay were significantly reduced for the plasma vaporization technique by comparison to conventional resection. Concerning tumoral detection, the present data confirmed the NBI superiority when compared to standard WLC regardless of tumor stage (95.3% vs. 65.1% for CIS, 93.3% vs. 82.2% for pTa, 97.4% vs. 94% for pT1, 95% vs. 84.2% overall). During standard Re-TUR the overall (6.3% versus 17.4%) and primary site (3.6% versus 12.8%) residual tumors' rates were significantly lower for the NBI-BPV group. The 1 (7.2% versus 18.3%) and 2 (11.5% versus 25.8%) years' recurrence rates were substantially lower for the combined approach. NBI cystoscopy significantly improved diagnostic accuracy, while bipolar technology showed a higher surgical efficiency, lower morbidity and faster postoperative recovery. The combined

  7. Hybrid empirical--theoretical approach to modeling uranium adsorption

    International Nuclear Information System (INIS)

    Hull, Larry C.; Grossman, Christopher; Fjeld, Robert A.; Coates, John T.; Elzerman, Alan W.

    2004-01-01

    An estimated 330 metric tons of U are buried in the radioactive waste Subsurface Disposal Area (SDA) at the Idaho National Engineering and Environmental Laboratory (INEEL). An assessment of U transport parameters is being performed to decrease the uncertainty in risk and dose predictions derived from computer simulations of U fate and transport to the underlying Snake River Plain Aquifer. Uranium adsorption isotherms were measured for 14 sediment samples collected from sedimentary interbeds underlying the SDA. The adsorption data were fit with a Freundlich isotherm. The Freundlich n parameter is statistically identical for all 14 sediment samples and the Freundlich K f parameter is correlated to sediment surface area (r 2 =0.80). These findings suggest an efficient approach to material characterization and implementation of a spatially variable reactive transport model that requires only the measurement of sediment surface area. To expand the potential applicability of the measured isotherms, a model is derived from the empirical observations by incorporating concepts from surface complexation theory to account for the effects of solution chemistry. The resulting model is then used to predict the range of adsorption conditions to be expected in the vadose zone at the SDA based on the range in measured pore water chemistry. Adsorption in the deep vadose zone is predicted to be stronger than in near-surface sediments because the total dissolved carbonate decreases with depth

  8. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    International Nuclear Information System (INIS)

    Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

    2011-01-01

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

  9. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

    2011-01-15

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

  10. Advanced control approach for hybrid systems based on solid oxide fuel cells

    International Nuclear Information System (INIS)

    Ferrari, Mario L.

    2015-01-01

    Highlights: • Advanced new control system for SOFC based hybrid plants. • Proportional–Integral approach with feed-forward technology. • Good control of fuel cell temperature. • All critical properties maintained inside safe conditions. - Abstract: This paper shows a new advanced control approach for operations in hybrid systems equipped with solid oxide fuel cell technology. This new tool, which combines feed-forward and standard proportional–integral techniques, controls the system during load changes avoiding failures and stress conditions detrimental to component life. This approach was selected to combine simplicity and good control performance. Moreover, the new approach presented in this paper eliminates the need for mass flow rate meters and other expensive probes, as usually required for a commercial plant. Compared to previous works, better performance is achieved in controlling fuel cell temperature (maximum gradient significantly lower than 3 K/min), reducing the pressure gap between cathode and anode sides (at least a 30% decrease during transient operations), and generating a higher safe margin (at least a 10% increase) for the Steam-to-Carbon Ratio. This new control system was developed and optimized using a hybrid system transient model implemented, validated and tested within previous works. The plant, comprising the coupling of a tubular solid oxide fuel cell stack with a microturbine, is equipped with a bypass valve able to connect the compressor outlet with the turbine inlet duct for rotational speed control. Following model development and tuning activities, several operative conditions were considered to show the new control system increased performance compared to previous tools (the same hybrid system model was used with the new control approach). Special attention was devoted to electrical load steps and ramps considering significant changes in ambient conditions

  11. Hybrid Approach of Aortic Diseases: Zone 1 Delivery and Volumetric Analysis on the Descending Aorta

    Directory of Open Access Journals (Sweden)

    José Augusto Duncan

    Full Text Available Abstract Introduction: Conventional techniques of surgical correction of arch and descending aortic diseases remains as high-risk procedures. Endovascular treatments of abdominal and descending thoracic aorta have lower surgical risk. Evolution of both techniques - open debranching of the arch and endovascular approach of the descending aorta - may extend a less invasive endovascular treatment for a more extensive disease with necessity of proximal landing zone in the arch. Objective: To evaluate descending thoracic aortic remodeling by means of volumetric analysis after hybrid approach of aortic arch debranching and stenting the descending aorta. Methods: Retrospective review of seven consecutive patients treated between September 2014 and August 2016 for diseases of proximal descending aorta (aneurysms and dissections by hybrid approach to deliver the endograft at zone 1. Computed tomography angiography were analyzed using a specific software to calculate descending thoracic aorta volumes pre- and postoperatively. Results: Follow-up was done in 100% of patients with a median time of 321 days (range, 41-625 days. No deaths or permanent neurological complications were observed. There were no endoleaks or stent migrations. Freedom from reintervention was 100% at 300 days and 66% at 600 days. Median volume reduction was of 45.5 cm3, representing a median volume shrinkage by 9.3%. Conclusion: Hybrid approach of arch and descending thoracic aorta diseases is feasible and leads to a favorable aortic remodeling with significant volume reduction.

  12. Does the acceptance of hybrid learning affect learning approaches in France?

    Science.gov (United States)

    Marco, Lionel Di; Venot, Alain; Gillois, Pierre

    2017-01-01

    Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (Paffected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.

  13. Hourly forecasting of global solar radiation based on multiscale decomposition methods: A hybrid approach

    International Nuclear Information System (INIS)

    Monjoly, Stéphanie; André, Maïna; Calif, Rudy; Soubdhan, Ted

    2017-01-01

    This paper introduces a new approach for the forecasting of solar radiation series at 1 h ahead. We investigated on several techniques of multiscale decomposition of clear sky index K_c data such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) and Wavelet Decomposition. From these differents methods, we built 11 decomposition components and 1 residu signal presenting different time scales. We performed classic forecasting models based on linear method (Autoregressive process AR) and a non linear method (Neural Network model). The choice of forecasting method is adaptative on the characteristic of each component. Hence, we proposed a modeling process which is built from a hybrid structure according to the defined flowchart. An analysis of predictive performances for solar forecasting from the different multiscale decompositions and forecast models is presented. From multiscale decomposition, the solar forecast accuracy is significantly improved, particularly using the wavelet decomposition method. Moreover, multistep forecasting with the proposed hybrid method resulted in additional improvement. For example, in terms of RMSE error, the obtained forecasting with the classical NN model is about 25.86%, this error decrease to 16.91% with the EMD-Hybrid Model, 14.06% with the EEMD-Hybid model and to 7.86% with the WD-Hybrid Model. - Highlights: • Hourly forecasting of GHI in tropical climate with many cloud formation processes. • Clear sky Index decomposition using three multiscale decomposition methods. • Combination of multiscale decomposition methods with AR-NN models to predict GHI. • Comparison of the proposed hybrid model with the classical models (AR, NN). • Best results using Wavelet-Hybrid model in comparison with classical models.

  14. Integrated approach for fusion multi-physics coupled analyses based on hybrid CAD and mesh geometries

    Energy Technology Data Exchange (ETDEWEB)

    Qiu, Yuefeng, E-mail: yuefeng.qiu@kit.edu; Lu, Lei; Fischer, Ulrich

    2015-10-15

    Highlights: • Integrated approach for neutronics, thermal and structural analyses was developed. • MCNP5/6, TRIPOLI-4 were coupled with CFX, Fluent and ANSYS Workbench. • A novel meshing approach has been proposed for describing MC geometry. - Abstract: Coupled multi-physics analyses on fusion reactor devices require high-fidelity neutronic models, and flexible, accurate data exchanging between various calculation codes. An integrated coupling approach has been developed to enable the conversion of CAD, mesh, or hybrid geometries for Monte Carlo (MC) codes MCNP5/6, TRIPOLI-4, and translation of nuclear heating data for CFD codes Fluent, CFX and structural mechanical software ANSYS Workbench. The coupling approach has been implemented based on SALOME platform with CAD modeling, mesh generation and data visualization capabilities. A novel meshing approach has been developed for generating suitable meshes for MC geometry descriptions. The coupling approach has been concluded to be reliable and efficient after verification calculations of several application cases.

  15. A decision support system based on hybrid knowledge approach for nuclear power plant operation

    International Nuclear Information System (INIS)

    Yang, J.O.; Chang, S.H.

    1991-01-01

    This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. Frames and rules are adopted to represent the various knowledge types. Rule-based deduction and abduction are used for shallow and deep knowledge based reasoning respectively. The event-based operational guidelines are provided to the operator according to the diagnosed results

  16. A diagnostic expert system for NPP based on hybrid knowledge approach

    International Nuclear Information System (INIS)

    Yang, Joon On; Chang, Soon Heung

    1989-01-01

    This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem solving behavior modeled in HYPOSS. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies showed a good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

  17. A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

    Science.gov (United States)

    Marzban, Hamid Reza

    2018-05-01

    In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.

  18. A Study on a Hybrid Approach for Diagnosing Faults in Nuclear Power Plant

    International Nuclear Information System (INIS)

    Yang, M.; Zhang, Z.J.; Peng, M.J.; Yan, S.Y.; Wang, H.; Ouyang, J.

    2006-01-01

    Proper and rapid identification of malfunctions is of premier importance for the safe operation of Nuclear Power Plants (NPP). Many monitoring or/and diagnosis methodologies based on artificial and computational intelligence have been proposed to aid operator to understand system problems, perform trouble-shooting action and reduce human error under serious pressure. However, because no single method is adequate to handle all requirements for diagnostic system, hybrid approaches where different methods work in conjunction to solve parts of the problem interest researchers greatly. In this study, Multilevel Flow Models (MFM) and Artificial Neural Network (ANN) are proposed and employed to develop a fault diagnosis system with the intention of improving the success rate of recognition on the one hand, and improving the understandability of diagnostic process and results on the other hand. Several simulation cases were conducted for evaluating the performance of the proposed diagnosis system. The simulation results validated the effectiveness of the proposed hybrid approach. (authors)

  19. Neuro-genetic hybrid approach for the solution of non-convex economic dispatch problem

    International Nuclear Information System (INIS)

    Malik, T.N.; Asar, A.U.

    2009-01-01

    ED (Economic Dispatch) is non-convex constrained optimization problem, and is used for both on line and offline studies in power system operation. Conventionally, it is solved as convex problem using optimization techniques by approximating generator input/output characteristic. Curves of monotonically increasing nature thus resulting in an inaccurate dispatch. The GA (Genetic Algorithm) has been used for the solution of this problem owing to its inherent ability to address the convex and non-convex problems equally. This approach brings the solution to the global minimum region of search space in a short time and then takes longer time to converge to near optimal results. GA based hybrid approaches are used to fine tune the near optimal results produced by GA. This paper proposes NGH (Neuro Genetic Hybrid) approach to solve the economic dispatch with valve point effect. The proposed approach combines the GA with the ANN (Artificial Neural Network) using SI (Swarm Intelligence) learning rule. The GA acts as a global optimizer and the neural network fine tunes the GA results to the desired targets. Three machines standard test system has been tested for validation of the approach. Comparing the results with GA and NGH model based on back-propagation learning, the proposed approach gives contrast improvements showing the promise of the approach. (author)

  20. Training Second-Career Teachers: A Different Student Profile, A Different Training Approach?

    Directory of Open Access Journals (Sweden)

    Marlies Baeten

    2016-08-01

    Full Text Available Second-career teachers are career changers who leave their current jobs to become teachers. This study conducts a narrative literature review which explores the student profiles of these teachers, asking how they differ from school leavers entering teacher education. The literature review also explores the characteristics of training approaches that are most suitable for second-career teachers based on their general student profile. Results show that second-career teachers are older, have strong intrinsic motivation, possess a wide range of knowledge and skills, have a self-directed and application-oriented approach to learning and teaching, and appreciate peer support. They benefit from teacher education programs that are flexible and include a preparatory period, that transfer their expertise into the teaching profession, provide opportunities for self-directed learning and peer support, integrate coursework and field experience, offer a significant amount of field experience and provide intensive mentoring support.

  1. A hybrid MCDM approach for ranking suppliers by considering ethical factors

    OpenAIRE

    Azadfallah, Mohammad

    2016-01-01

    One of the negative effects of cooperating with un-ethically behaving suppliers is that it may devastate the companies' credibility among employees, customers and the public. In this paper, a hybrid Multiple Criteria Decision Making (MCDM) approach (Disjunctive-WPM method) is proposed to resolve this limitation. The proposed methods consist of the following steps: 1. drop unethical solutions and 2. rank the remaining solutions. Therefore, the aim of t...

  2. Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

    OpenAIRE

    Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

    2015-01-01

    Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

  3. 49 CFR 214.329 - Train approach warning provided by watchmen/lookouts.

    Science.gov (United States)

    2010-10-01

    ... Protection § 214.329 Train approach warning provided by watchmen/lookouts. Roadway workers in a roadway work group who foul any track outside of working limits shall be given warning of approaching trains by one... shall clearly signify to all recipients of the warning that a train or other on-track equipment is...

  4. A Novel Combined Hybrid Approach to Enable Revascularisation of a Trauma-Induced Subclavian Artery Injury

    Directory of Open Access Journals (Sweden)

    C.N. Sabbagh

    Full Text Available : Introduction: This case highlights the complexity of upper limb revascularization after a subclavian artery traumatic injury and strengthens the role of a hybrid/multi-disciplinary approach to such injuries. Report: A 45-year-old male patient presented with an acute right upper limb following a traumatic injury to the right subclavian artery due to a motor vehicle accident (MVA. Associated injuries included an unstable cervical spine injury, a large open right clavicular injury, and a brain injury, which limited the potential revascularisation options available. The arm was revascularised using a hybrid endovascular/open surgical approach, namely embolization of the proximal subclavian artery (just distal to vertebral artery and a right common femoral artery to distal axillary artery bypass using prosthetic material. Discussion: Blunt injuries to the subclavian artery are often high impact, complex and associated with multiple injuries to surrounding structures, which limit the role of standard procedures used in the elective setting. This case highlights the role of multidisciplinary team involvement, using a hybrid approach and a novel distal inflow site to restore upper limb perfusion. Keywords: Upper limb, Ischemia, Trauma, Revascularization

  5. A MOOC approach for training researchers in developing countries

    Directory of Open Access Journals (Sweden)

    Ravi Murugesan

    2017-03-01

    Full Text Available We report on an online course in research writing offered in a massive open online course (MOOC format for developing country researchers. The concepts of cognitive presence, teacher presence, and social presence informed the design of the course, with a philosophy of strong social interaction supported by guest facilitators. The course was developed with low-bandwidth elements and hosted on a Moodle site. It was offered twice as a MOOC and 2830 learners from more than 90 countries, mainly in the developing world, took part. The average completion rate was 53%. Female learners and learners who were active in the forums were more likely to complete the course. Our MOOC approach may be a useful model for continuing professional development training in the developing world.

  6. Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

    Science.gov (United States)

    Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

    2016-01-01

    Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

  7. Hybrid ANN–PLS approach to scroll compressor thermodynamic performance prediction

    International Nuclear Information System (INIS)

    Tian, Z.; Gu, B.; Yang, L.; Lu, Y.

    2015-01-01

    In this paper, a scroll compressor thermodynamic performance prediction was carried out by applying a hybrid ANN–PLS model. Firstly, an experimental platform with second-refrigeration calorimeter was set up and steady-state scroll compressor data sets were collected from experiments. Then totally 148 data sets were introduced to train and verify the validity of the ANN–PLS model for predicting the scroll compressor parameters such as volumetric efficiency, refrigerant mass flow rate, discharge temperature and power consumption. The ANN–PLS model was determined with 5 hidden neurons and 7 latent variables through the training process. Ultimately, the ANN–PLS model showed better performance than the ANN model and the PLS model working separately. ANN–PLS predictions agree well with the experimental values with mean relative errors (MREs) in the range of 0.34–1.96%, correlation coefficients (R 2 ) in the range of 0.9703–0.9999 and very low root mean square errors (RMSEs). - Highlights: • Hybrid ANN–PLS is utilized to predict the thermodynamic performance of scroll compressor. • ANN–PLS model is determined with 5 hidden neurons and 7 latent variables. • ANN–PLS model demonstrates better performance than ANN and PLS working separately. • The values of MRE and RMSE are in the range of 0.34–1.96% and 0.9703–0.9999, respectively

  8. Developing the Mental Health Workforce: Review and Application of Training Approaches from Multiple Disciplines

    OpenAIRE

    Lyon, Aaron R.; Stirman, Shannon Wiltsey; Kerns, Suzanne E. U.; Bruns, Eric J.

    2011-01-01

    Strategies specifically designed to facilitate the training of mental health practitioners in evidence-based practices (EBPs) have lagged behind the development of the interventions themselves. The current paper draws from an interdisciplinary literature (including medical training, adult education, and teacher training) to identify useful training and support approaches as well as important conceptual frameworks that may be applied to training in mental health. Theory and research findings a...

  9. A Hybrid Approach to Cognitive Engineering: Supporting Development of a Revolutionary Warfighter-Centered Command and Control System

    National Research Council Canada - National Science Library

    Ockerman, Jennifer; McKneely, Jennifer A; Koterba, Nathan

    2005-01-01

    ...) for the requirements analysis and design of revolutionary command and control systems and domains. This hybrid approach uses knowledge elicitation and representation techniques from several current cognitive engineering methodologies...

  10. A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

    Science.gov (United States)

    Oh, Yoo Rhee; Kim, Hong Kook

    In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

  11. A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

    Science.gov (United States)

    Dickman, Christopher T D; Moehring, Amanda J

    2013-01-01

    When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW) sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56%) of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

  12. A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

    Directory of Open Access Journals (Sweden)

    Christopher T D Dickman

    Full Text Available When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56% of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

  13. A Gaussian process regression based hybrid approach for short-term wind speed prediction

    International Nuclear Information System (INIS)

    Zhang, Chi; Wei, Haikun; Zhao, Xin; Liu, Tianhong; Zhang, Kanjian

    2016-01-01

    Highlights: • A novel hybrid approach is proposed for short-term wind speed prediction. • This method combines the parametric AR model with the non-parametric GPR model. • The relative importance of different inputs is considered. • Different types of covariance functions are considered and combined. • It can provide both accurate point forecasts and satisfactory prediction intervals. - Abstract: This paper proposes a hybrid model based on autoregressive (AR) model and Gaussian process regression (GPR) for probabilistic wind speed forecasting. In the proposed approach, the AR model is employed to capture the overall structure from wind speed series, and the GPR is adopted to extract the local structure. Additionally, automatic relevance determination (ARD) is used to take into account the relative importance of different inputs, and different types of covariance functions are combined to capture the characteristics of the data. The proposed hybrid model is compared with the persistence model, artificial neural network (ANN), and support vector machine (SVM) for one-step ahead forecasting, using wind speed data collected from three wind farms in China. The forecasting results indicate that the proposed method can not only improve point forecasts compared with other methods, but also generate satisfactory prediction intervals.

  14. Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

    Science.gov (United States)

    Koeppen, W. C.; Pilger, E.; Wright, R.

    2011-07-01

    We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

  15. A Hybrid Column Generation approach for an Industrial Waste Collection Routing Problem

    DEFF Research Database (Denmark)

    Hauge, Kristian; Larsen, Jesper; Lusby, Richard Martin

    2014-01-01

    , while empty containers must be returned to the depot to await further assignments. Unlike, the traditional ROROR problem, where vehicles may transport one skip container at a time regardless of whether it is full or not, we consider cases in which a vehicle can transport up to eight containers, at most...... two of which can be full. We propose a Generalized Set Partitioning formulation of the problem and describe a hybrid column generation procedure to solve it. A fast Tabu Search heuristic is used to generate new columns. The proposed methodology is tested on nine data sets, four of which are actual......, real-world problem instances. Results indicate that the hybrid column generation outperforms a purely heuristic approach in terms of both running time and solution quality. High quality solutions to problems containing up to 100 orders can be solved in approximately 15 minutes....

  16. A hybrid least squares support vector machines and GMDH approach for river flow forecasting

    Science.gov (United States)

    Samsudin, R.; Saad, P.; Shabri, A.

    2010-06-01

    This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

  17. A frequency domain approach to analyzing passive battery-ultracapacitor hybrids supplying periodic pulsed current loads

    International Nuclear Information System (INIS)

    Kuperman, Alon; Aharon, Ilan; Kara, Avi; Malki, Shalev

    2011-01-01

    Highlights: → Passive battery-ultracapacitor hybrids are examined. → Frequency domain analysis is employed. → The ultracapacitor branch operates as a low-pass filter for the battery. → The battery supplies the average load demand. → Design requirements are discussed. - Abstract: A Fourier-based analysis of passive battery-ultracapacitor hybrid sources is introduced in the manuscript. The approach is first introduced for a general load, and then is followed by a study for a case of periodic pulsed current load. It is shown that the ultracapacitor branch is perceived by the battery as a low-pass filter, which absorbs the majority of the high frequency harmonic current and letting the battery to supply the average load demand in addition to the small part of dynamic current. Design requirements influence on the ultracapacitor capacitance and internal resistance choice are quantitatively discussed. The theory is enforced by simulation and experimental results, showing an excellent agreement.

  18. A hybrid approach to solving the problem of design of nuclear fuel cells

    International Nuclear Information System (INIS)

    Montes T, J. L.; Perusquia del C, R.; Ortiz S, J. J.; Castillo, A.

    2015-09-01

    An approach to solving the problem of fuel cell design for BWR power reactor is presented. For this purpose the hybridization of a method based in heuristic knowledge rules called S15 and the advantages of a meta-heuristic method is proposed. The synergy of potentialities of both techniques allows finding solutions of more quality. The quality of each solution is obtained through a multi-objective function formed from the main cell parameters that are provided or obtained during the simulation with the CASMO-4 code. To evaluate this alternative of solution nuclear fuel cells of reference of nuclear power plant of Laguna Verde were used. The results show that in a systematic way the results improve when both methods are coupled. As a result of the hybridization process of the mentioned techniques an improvement is achieved in a range of 2% with regard to the achieved results in an independent way by the S15 method. (Author)

  19. Formal verification of dynamic hybrid systems: a NuSMV-based model checking approach

    Directory of Open Access Journals (Sweden)

    Xu Zhi

    2018-01-01

    Full Text Available Software security is an important and challenging research topic in developing dynamic hybrid embedded software systems. Ensuring the correct behavior of these systems is particularly difficult due to the interactions between the continuous subsystem and the discrete subsystem. Currently available security analysis methods for system risks have been limited, as they rely on manual inspections of the individual subsystems under simplifying assumptions. To improve this situation, a new approach is proposed that is based on the symbolic model checking tool NuSMV. A dual PID system is used as an example system, for which the logical part and the computational part of the system are modeled in a unified manner. Constraints are constructed on the controlled object, and a counter-example path is ultimately generated, indicating that the hybrid system can be analyzed by the model checking tool.

  20. Non-adaptive and adaptive hybrid approaches for enhancing water quality management

    Science.gov (United States)

    Kalwij, Ineke M.; Peralta, Richard C.

    2008-09-01

    SummaryUsing optimization to help solve groundwater management problems cost-effectively is becoming increasingly important. Hybrid optimization approaches, that combine two or more optimization algorithms, will become valuable and common tools for addressing complex nonlinear hydrologic problems. Hybrid heuristic optimizers have capabilities far beyond those of a simple genetic algorithm (SGA), and are continuously improving. SGAs having only parent selection, crossover, and mutation are inefficient and rarely used for optimizing contaminant transport management. Even an advanced genetic algorithm (AGA) that includes elitism (to emphasize using the best strategies as parents) and healing (to help assure optimal strategy feasibility) is undesirably inefficient. Much more efficient than an AGA is the presented hybrid (AGCT), which adds comprehensive tabu search (TS) features to an AGA. TS mechanisms (TS probability, tabu list size, search coarseness and solution space size, and a TS threshold value) force the optimizer to search portions of the solution space that yield superior pumping strategies, and to avoid reproducing similar or inferior strategies. An AGCT characteristic is that TS control parameters are unchanging during optimization. However, TS parameter values that are ideal for optimization commencement can be undesirable when nearing assumed global optimality. The second presented hybrid, termed global converger (GC), is significantly better than the AGCT. GC includes AGCT plus feedback-driven auto-adaptive control that dynamically changes TS parameters during run-time. Before comparing AGCT and GC, we empirically derived scaled dimensionless TS control parameter guidelines by evaluating 50 sets of parameter values for a hypothetical optimization problem. For the hypothetical area, AGCT optimized both well locations and pumping rates. The parameters are useful starting values because using trial-and-error to identify an ideal combination of control

  1. A hybrid approach for integrated healthcare cooperative purchasing and supply chain configuration.

    Science.gov (United States)

    Rego, Nazaré; Claro, João; Pinho de Sousa, Jorge

    2014-12-01

    This paper presents an innovative and flexible approach for recommending the number, size and composition of purchasing groups, for a set of hospitals willing to cooperate, while minimising their shared supply chain costs. This approach makes the financial impact of the various cooperation alternatives transparent to the group and the individual participants, opening way to a negotiation process concerning the allocation of the cooperation costs and gains. The approach was developed around a hybrid Variable Neighbourhood Search (VNS)/Tabu Search metaheuristic, resulting in a flexible tool that can be applied to purchasing groups with different characteristics, namely different operative and market circumstances, and to supply chains with different topologies and atypical cost characteristics. Preliminary computational results show the potential of the approach in solving a broad range of problems.

  2. A hybrid modelling approach to simulating foot-and-mouth disease outbreaks in Australian livestock

    Directory of Open Access Journals (Sweden)

    Richard A Bradhurst

    2015-03-01

    Full Text Available Foot-and-mouth disease (FMD is a highly contagious and economically important viral disease of cloven-hoofed animals. Australia's freedom from FMD underpins a valuable trade in live animals and animal products. An outbreak of FMD would result in the loss of export markets and cause severe disruption to domestic markets. The prevention of, and contingency planning for, FMD are of key importance to government, industry, producers and the community. The spread and control of FMD is complex and dynamic due to a highly contagious multi-host pathogen operating in a heterogeneous environment across multiple jurisdictions. Epidemiological modelling is increasingly being recognized as a valuable tool for investigating the spread of disease under different conditions and the effectiveness of control strategies. Models of infectious disease can be broadly classified as: population-based models that are formulated from the top-down and employ population-level relationships to describe individual-level behaviour, individual-based models that are formulated from the bottom-up and aggregate individual-level behaviour to reveal population-level relationships, or hybrid models which combine the two approaches into a single model.The Australian Animal Disease Spread (AADIS hybrid model employs a deterministic equation-based model (EBM to model within-herd spread of FMD, and a stochastic, spatially-explicit agent-based model (ABM to model between-herd spread and control. The EBM provides concise and computationally efficient predictions of herd prevalence and clinical signs over time. The ABM captures the complex, stochastic and heterogeneous environment in which an FMD epidemic operates. The AADIS event-driven hybrid EBM/ABM architecture is a flexible, efficient and extensible framework for modelling the spread and control of disease in livestock on a national scale. We present an overview of the AADIS hybrid approach and a description of the model

  3. The effects of verbal information and approach-avoidance training on children's fear-related responses.

    Science.gov (United States)

    Lester, Kathryn J; Lisk, Stephen C; Mikita, Nina; Mitchell, Sophie; Huijding, Jorg; Rinck, Mike; Field, Andy P

    2015-09-01

    This study examined the effects of verbal information and approach-avoidance training on fear-related cognitive and behavioural responses about novel animals. One hundred and sixty children (7-11 years) were randomly allocated to receive: a) positive verbal information about one novel animal and threat information about a second novel animal (verbal information condition); b) approach-avoidance training in which they repeatedly pushed away (avoid) or pulled closer (approach) pictures of the animals (approach-avoidance training), c) a combined condition in which verbal information was given prior to approach-avoidance training (verbal information + approach-avoidance training) and d) a combined condition in which approach-avoidance training was given prior to verbal information (approach-avoidance training + verbal information). Threat and positive information significantly increased and decreased fear beliefs and avoidance behaviour respectively. Approach-avoidance training was successful in training the desired behavioural responses but had limited effects on fear-related responses. Verbal information and both combined conditions resulted in significantly larger effects than approach-avoidance training. We found no evidence for an additive effect of these pathways. This study used a non-clinical sample and focused on novel animals rather than animals about which children already had experience or established fears. The study also compared positive information/approach with threat information/avoid training, limiting specific conclusions regarding the independent effects of these conditions. The present study finds little evidence in support of a possible causal role for behavioural response training in the aetiology of childhood fear. However, the provision of verbal information appears to be an important pathway involved in the aetiology of childhood fear. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. A hybrid bio-jetting approach for directly engineering living cells

    International Nuclear Information System (INIS)

    Kwok, Albert; Irvine, Scott; Arumuganathar, Sumathy; Jayasinghe, Suwan N; McEwan, Jean R

    2008-01-01

    This paper reports developments on a hybrid cell-engineering protocol coupling both bio-electrosprays and aerodynamically assisted bio-jets for process-handling living cells. The current work demonstrates the ability to couple these two cell-jetting protocols for handling a wide range of cells for deposition. The post-treated cells are assessed for their viability by way of flow cytometry, which illustrates a significant population of viable cells post-treatment in comparison to those controls. This work is the first example of coupling these two protocols for the process handling of living cells. The hybrid protocol demonstrates the achievement of stable cone jetting of a cellular suspension in the single-needle configuration which was previously unachieved with single-needle bio-electrosprays. Furthermore the living cells explored in these investigations expressed GFP, thus demonstrating the ability to couple gene therapy with this hybrid protocol. Hence, this approach could one day be explored for building biologically viable tissues incorporating a therapeutic payload for combating a range of cellular/tissue-based pathologies

  5. Opposition-Based Memetic Algorithm and Hybrid Approach for Sorting Permutations by Reversals.

    Science.gov (United States)

    Soncco-Álvarez, José Luis; Muñoz, Daniel M; Ayala-Rincón, Mauricio

    2018-02-21

    Sorting unsigned permutations by reversals is a difficult problem; indeed, it was proved to be NP-hard by Caprara (1997). Because of its high complexity, many approximation algorithms to compute the minimal reversal distance were proposed until reaching the nowadays best-known theoretical ratio of 1.375. In this article, two memetic algorithms to compute the reversal distance are proposed. The first one uses the technique of opposition-based learning leading to an opposition-based memetic algorithm; the second one improves the previous algorithm by applying the heuristic of two breakpoint elimination leading to a hybrid approach. Several experiments were performed with one-hundred randomly generated permutations, single benchmark permutations, and biological permutations. Results of the experiments showed that the proposed OBMA and Hybrid-OBMA algorithms achieve the best results for practical cases, that is, for permutations of length up to 120. Also, Hybrid-OBMA showed to improve the results of OBMA for permutations greater than or equal to 60. The applicability of our proposed algorithms was checked processing permutations based on biological data, in which case OBMA gave the best average results for all instances.

  6. Energy level alignment at hybridized organic-metal interfaces from a GW projection approach

    Science.gov (United States)

    Chen, Yifeng; Tamblyn, Isaac; Quek, Su Ying

    Energy level alignments at organic-metal interfaces are of profound importance in numerous (opto)electronic applications. Standard density functional theory (DFT) calculations generally give incorrect energy level alignments and missing long-range polarization effects. Previous efforts to address this problem using the many-electron GW method have focused on physisorbed systems where hybridization effects are insignificant. Here, we use state-of-the-art GW methods to predict the level alignment at the amine-Au interface, where molecular levels do hybridize with metallic states. This non-trivial hybridization implies that DFT result is a poor approximation to the quasiparticle states. However, we find that the self-energy operator is approximately diagonal in the molecular basis, allowing us to use a projection approach to predict the level alignments. Our results indicate that the metallic substrate reduces the HOMO-LUMO gap by 3.5 4.0 eV, depending on the molecular coverage/presence of Au adatoms. Our GW results are further compared with those of a simple image charge model that describes the level alignment in physisorbed systems. Syq and YC acknowledge Grant NRF-NRFF2013-07 and the medium-sized centre program from the National Research Foundation, Singapore.

  7. Nanotubule and Tour Molecule Based Molecular Electronics: Suggestion for a Hybrid Approach

    Science.gov (United States)

    Srivastava, Deepak; Saini, Subhash (Technical Monitor)

    1998-01-01

    Recent experimental and theoretical attempts and results indicate two distinct broad pathways towards future molecular electronic devices and architectures. The first is the approach via Tour type ladder molecules and their junctions which can be fabricated with solution phase chemical approaches. Second are fullerenes or nanotubules and their junctions which may have better conductance, switching and amplifying characteristics but can not be made through well controlled and defined chemical means. A hybrid approach combining the two pathways to take advantage of the characteristics of both is suggested. Dimension and scale of such devices would be somewhere in between isolated molecule and nanotubule based devices but it maybe possible to use self-assembly towards larger functional and logicalunits.

  8. Photo-Ionization of Noble Gases: A Demonstration of Hybrid Coupled Channels Approach

    Directory of Open Access Journals (Sweden)

    Vinay Pramod Majety

    2015-01-01

    Full Text Available We present here an application of the recently developed hybrid coupled channels approach to study photo-ionization of noble gas atoms: Neon and Argon. We first compute multi-photon ionization rates and cross-sections for these inert gas atoms with our approach and compare them with reliable data available from R-matrix Floquet theory. The good agreement between coupled channels and R-matrix Floquet theory show that our method treats multi-electron systems on par with the well established R-matrix theory. We then apply the time dependent surface flux (tSURFF method with our approach to compute total and angle resolved photo-electron spectra from Argon with linearly and circularly polarized 12 nm wavelength laser fields, a typical wavelength available from Free Electron Lasers (FELs.

  9. A Hybrid Approach to Processing Big Data Graphs on Memory-Restricted Systems

    KAUST Repository

    Harshvardhan,

    2015-05-01

    With the advent of big-data, processing large graphs quickly has become increasingly important. Most existing approaches either utilize in-memory processing techniques that can only process graphs that fit completely in RAM, or disk-based techniques that sacrifice performance. In this work, we propose a novel RAM-Disk hybrid approach to graph processing that can scale well from a single shared-memory node to large distributed-memory systems. It works by partitioning the graph into sub graphs that fit in RAM and uses a paging-like technique to load sub graphs. We show that without modifying the algorithms, this approach can scale from small memory-constrained systems (such as tablets) to large-scale distributed machines with 16, 000+ cores.

  10. Competence-based approaches to professional training and activities

    International Nuclear Information System (INIS)

    Ryzhov, S.B.; Shcheglov, V.A.; Savenkov, A.M.; Puzanova, O.V.

    2010-01-01

    The authors say that the personnel training system for the nuclear industry must represent a successive transition from one activity to another: from purely training activities to professional training activities to purely professional activities. Components of knowledge management include storage, transfer and efficiency of knowledge use. The competence of a specialist is determined by a combination of cognitive, functional and value and ethics components. In order to assure that the internship program is clearly structured, it must be comprised of a set of training modules. The examples of probation training modules for scientific and design organizations are given. Problems of assessing the quality of training of young specialists and building general professional competence are also discussed [ru

  11. When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

    KAUST Repository

    Liu, Xiao

    2017-03-21

    Privacy risks of recommender systems have caused increasing attention. Users’ private data is often collected by probably untrusted recommender system in order to provide high-quality recommendation. Meanwhile, malicious attackers may utilize recommendation results to make inferences about other users’ private data. Existing approaches focus either on keeping users’ private data protected during recommendation computation or on preventing the inference of any single user’s data from the recommendation result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP) with randomized perturbation (RP). We theoretically show the noise added by RP has limited effect on recommendation accuracy and the noise added by DP can be well controlled based on the sensitivity analysis of functions on the perturbed data. Extensive experiments on three large-scale real world datasets show that the hybrid approach generally provides more privacy protection with acceptable recommendation accuracy loss, and surprisingly sometimes achieves better privacy without sacrificing accuracy, thus validating its feasibility in practice.

  12. Identification and Prediction of Large Pedestrian Flow in Urban Areas Based on a Hybrid Detection Approach

    Directory of Open Access Journals (Sweden)

    Kaisheng Zhang

    2016-12-01

    Full Text Available Recently, population density has grown quickly with the increasing acceleration of urbanization. At the same time, overcrowded situations are more likely to occur in populous urban areas, increasing the risk of accidents. This paper proposes a synthetic approach to recognize and identify the large pedestrian flow. In particular, a hybrid pedestrian flow detection model was constructed by analyzing real data from major mobile phone operators in China, including information from smartphones and base stations (BS. With the hybrid model, the Log Distance Path Loss (LDPL model was used to estimate the pedestrian density from raw network data, and retrieve information with the Gaussian Progress (GP through supervised learning. Temporal-spatial prediction of the pedestrian data was carried out with Machine Learning (ML approaches. Finally, a case study of a real Central Business District (CBD scenario in Shanghai, China using records of millions of cell phone users was conducted. The results showed that the new approach significantly increases the utility and capacity of the mobile network. A more reasonable overcrowding detection and alert system can be developed to improve safety in subway lines and other hotspot landmark areas, such as the Bundle, People’s Square or Disneyland, where a large passenger flow generally exists.

  13. Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

    Directory of Open Access Journals (Sweden)

    JingRui Zhang

    2015-03-01

    Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

  14. Hybrid generative-discriminative approach to age-invariant face recognition

    Science.gov (United States)

    Sajid, Muhammad; Shafique, Tamoor

    2018-03-01

    Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

  15. Fuzzy hybrid MCDM approach for selection of wind turbine service technicians

    Directory of Open Access Journals (Sweden)

    Goutam Kumar Bose

    2016-01-01

    Full Text Available This research paper is aimed to present a fuzzy Hybrid Multi-criteria decision making (MCDM methodology for selecting employees. The present study aspires to present the hybrid approach of Fuzzy multiple MCDM techniques with tactical viewpoint to support the recruitment process of wind turbine service technicians. The methodology is based on the application of Fuzzy ARAS (Additive Ratio Assessment and Fuzzy MOORA (Multi-Objective Optimization on basis of Ratio Analysis which are integrated through group decision making (GDM method in the model for selection of wind turbine service technicians’ ranking. Here a group of experts from different fields of expertise are engaged to finalize the decision. Series of tests are conducted regarding physical fitness, technical written test, practical test along with general interview and medical examination to facilitate the final selection using the above techniques. In contrast to single decision making approaches, the proposed group decision making model efficiently supports the wind turbine service technicians ranking process. The effectiveness of the proposed approach manifest from the case study of service technicians required for the maintenance department of wind power plant using Fuzzy ARAS and Fuzzy MOORA. This set of potential technicians is evaluated based on five main criteria.

  16. An Approach for Designing Thermal Management Systems for Electric and Hybrid Vehicle Battery Packs

    International Nuclear Information System (INIS)

    Pesaran, Ahmad A.; Keyser, Matthew; Burch, Steve

    1999-01-01

    If battery packs for electric vehicles (EVs) and hybrid electric vehicles (HEVs) are to operate effectively in all climates, thermal management of the packs is essential. In this paper, we will review a systematic approach for designing and evaluating battery pack thermal management systems. A thermal management system using air as the heat transfer medium is less complicated than a system using liquid cooling/heating. Generally, for parallel HEVs, an air thermal management system is adequate, whereas for EVs and series HEVs, liquid-based systems may be required for optimum thermal performance. Further information on battery thermal management can be found on the Web site www.ctts.nrel.gov/BTM

  17. AEROSTATIC AND AERODYNAMIC MODULES OF A HYBRID BUOYANT AIRCRAFT: AN ANALYTICAL APPROACH

    Directory of Open Access Journals (Sweden)

    Anwar Ul Haque

    2015-05-01

    Full Text Available An analytical approach is essential for the estimation of the requirements of aerodynamic and aerostatic lift for a hybrid buoyant aircraft. Such aircrafts have two different modules to balance the weight of aircraft; aerostatic module and aerodynamic module. Both these modules are to be treated separately for estimation of the mass budget of propulsion systems and required power. In the present work, existing relationships of aircraft and airship are reviewed for its further application for these modules. Limitations of such relationships are also disussed and it is precieved that it will provide a strating point for better understanding of design anatomy of such aircraft.

  18. "Elephant trunk" and endovascular stentgrafting : a hybrid approach to the treatment of extensive thoracic aortic aneurysm

    OpenAIRE

    Holubec, Tomás; Raupach, Jan; Dominik, Jan; Vojácek, Jan

    2013-01-01

    hybrid approach to elephant trunk technique for treatment of thoracic aortic aneurysms combines a conventional surgical and endovascular therapy. Compared to surgery alone, there is a presumption that mortality and morbidity is reduced. We present a case report of a 42-year-old man with a giant aneurysm of the entire thoracic aorta, significant aortic and tricuspid regurgitation and ventricular septum defect. The patient underwent multiple consecutive operations and interventions having, am...

  19. Towards a comprehensive theory for He II: I. A zero-temperature hybrid approach

    International Nuclear Information System (INIS)

    Ghassib, H.B.; Khudeir, A.M.

    1982-09-01

    A simple hybrid approach based on a gauge theory as well as a Hartree formalism, is presented for He II at zero temperature. Although this is intended to be merely a first step in an all-embracing theory, it already resolves quite neatly several old inconsistencies and corrects a few errors. As an illustration of its feasibility, a crude but instructive calculation is performed for the static structure factor of the system at low momentum transfers. A number of planned extensions and generalizations are outlined. (author)

  20. An integrated optimization approach for a hybrid energy system in electric vehicles

    International Nuclear Information System (INIS)

    Hung, Yi-Hsuan; Wu, Chien-Hsun

    2012-01-01

    Highlights: ► Second-order control-oriented dynamics for a battery/supercapacitor EV is modeled. ► Multiple for-loop programming and global searchwith constraints are main design principles of integrated optimization algorithm (IOA). ► Optimal hybridization is derived based on maximizing energy storage capacity. ► Optimal energy management in three EV operation modes is searched based on minimizing total consumed power. ► Simulation results prove that 6+% of total energy is saved by the IOA method. -- Abstract: This paper develops a simple but innovative integrated optimization approach (IOA) for deriving the best solutions of component sizing and control strategies of a hybrid energy system (HES) which consists of a lithium battery and a supercapacitor module. To implement IOA, a multiple for-loop structure with a preset cost function is needed to globally calculate the best hybridization and energy management of the HES. For system hybridization, the optimal size ratio is evaluated by maximizing the HES energy stored capacity at various costs. For energy management, the optimal power distribution combined with a three-mode rule-based strategy is searched to minimize the total consumed energy. Combining above two for-loop structures and giving a time-dependent test scenario, the IOA is derived by minimizing the accumulated HES power. Simulation results show that 6% of the total HES energy can be saved in the IOA case compared with the original system in two driving cycles: ECE and UDDS, and two vehicle weights, respectively. It proves that the IOA effectively derives the maximum energy storage capacity and the minimum energy consumption of the HES at the same time. Experimental verification will be carried out in the near future.

  1. A Comparison of Hybrid Approaches for Turbofan Engine Gas Path Fault Diagnosis

    Science.gov (United States)

    Lu, Feng; Wang, Yafan; Huang, Jinquan; Wang, Qihang

    2016-09-01

    A hybrid diagnostic method utilizing Extended Kalman Filter (EKF) and Adaptive Genetic Algorithm (AGA) is presented for performance degradation estimation and sensor anomaly detection of turbofan engine. The EKF is used to estimate engine component performance degradation for gas path fault diagnosis. The AGA is introduced in the integrated architecture and applied for sensor bias detection. The contributions of this work are the comparisons of Kalman Filters (KF)-AGA algorithms and Neural Networks (NN)-AGA algorithms with a unified framework for gas path fault diagnosis. The NN needs to be trained off-line with a large number of prior fault mode data. When new fault mode occurs, estimation accuracy by the NN evidently decreases. However, the application of the Linearized Kalman Filter (LKF) and EKF will not be restricted in such case. The crossover factor and the mutation factor are adapted to the fitness function at each generation in the AGA, and it consumes less time to search for the optimal sensor bias value compared to the Genetic Algorithm (GA). In a word, we conclude that the hybrid EKF-AGA algorithm is the best choice for gas path fault diagnosis of turbofan engine among the algorithms discussed.

  2. Task to Training Matrix Design for Decommissioning Engineer on the basis of Systematic Approach to Training Methodology

    Energy Technology Data Exchange (ETDEWEB)

    Kwak, Jeong Keun [KHNP, Ulsan (Korea, Republic of)

    2016-10-15

    In nuclear history, before Chernobyl Accident, Three Mile Island (TMI) Accident was the severest accident. For this reason, to resolve the disclosed or potential possibilities of nuclear accident, more than one hundred countermeasures were proposed by United States Nuclear Regulatory Commission (USNRC). Among various recommendations by USNRC, one suggestion was related to training aspect. It was Systematic Approach to Training (SAT) and this event was the initiation of SAT methodology in the world. In Korea, upcoming June 2017, Kori Unit-1 NPP is scheduled to be shut down and it will experience NPP decommissioning for the first time. Present study aims to establish concrete training foundation for NPP decommissioning engineers based on Systematic Approach to Training (SAT) methodology, in particular, Task to Training Matrix (TTM). The objective of this paper is to organize TTM on the basis of SAT for NPP decommissioning engineer. For this reason, eighteen tasks are yielded through Job and Task Analysis (JTA) process. After that, for the settlement of Task to Training Matrix (TTM), various data are determined such as element, condition, standard, knowledge and skill, learning objective and training setting. When it comes to training in nuclear industry, SAT methodology has been the unwavering principle in Korea since NPPs export to UAE.

  3. An Alternative Approach to Preservice Police Training: Combining Training and Education Learning Outcomes

    Science.gov (United States)

    Martin, Richard H.

    2014-01-01

    Many states offer police and corrections officer certification through state approved police basic training, either after hire (in-service) or before hire (preservice). Only large agencies conduct their own basic training academies after being hired. The trend is to save money through preservice training offered by colleges. This especially…

  4. Establishing and maintaining instructional skills through initial and continuing training: A common sense approach

    International Nuclear Information System (INIS)

    Yoder, J.A.; Hall, J.D.; Betz, T.L.; Stoupe, P.J.

    1996-01-01

    Using this common sense approach to determining initial and continuing training for instructional staff members helped XYZ facility to develop a training program that will meet the specific needs of its staff. From the results of the analysis, XYZ can now provide the right training at the right time. THe competency-to-training matrix will assist XYZ in accomplishing this training. This matrix also groups the competencies into the five phases associated with the Systematic Approach to Training methodology. From this common sense approach, XYZ facility has a report detailing many solutions that go beyond training. Awareness of problems, causes, and solutions are the keys to successful facility management. Sharing these issues with the right facility personnel, XYZ will be able to meet and/or exceed the changing expectations placed on them due to ''downsizing'', ''rightsizing'', or ''reengineering''

  5. Developing the Mental Health Workforce: Review and Application of Training Approaches from Multiple Disciplines

    Science.gov (United States)

    Lyon, Aaron R.; Stirman, Shannon Wiltsey; Kerns, Suzanne E. U.; Bruns, Eric J.

    2011-01-01

    Strategies specifically designed to facilitate the training of mental health practitioners in evidence-based practices (EBPs) have lagged behind the development of the interventions themselves. The current paper draws from an interdisciplinary literature (including medical training, adult education, and teacher training) to identify useful training and support approaches as well as important conceptual frameworks that may be applied to training in mental health. Theory and research findings are reviewed, which highlight the importance of continued consultation/ support following training workshops, congruence between the training content and practitioner experience, and focus on motivational issues. In addition, six individual approaches are presented with careful attention to their empirical foundations and potential applications. Common techniques are highlighted and applications and future directions for mental health workforce training and research are discussed. PMID:21190075

  6. Test facilities for hybrid and electric drive trains; Stazione di prova sistemi di trazione ibridi ed elettrici

    Energy Technology Data Exchange (ETDEWEB)

    Bernardini, G.; Ciancia, A.; De Andreis, L.; Pagni, G.; Pede, G.; Rossi, E.; Vellone, R. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dip. Energia

    1998-12-31

    ENEA (Italian National Agency for New Technologies, Energy and the Environment) is conducting a large research and development programme on innovative vehicles with high energy efficiency and low environmental impact. In particular conducts activities on electric and hybrid vehicles. Testing and evaluation activities play a strong role in this programme. A complete characterization chain has been then defined and set up with a network of facilities which covers main testing needs for single components, subsystems and complete vehicles, in simulated and real operating conditions. The test facility which has been realised is able to experiment and fully characterise complete drive-trains (and subsystems) for pure electric and hybrid vehicles. It is composed by a different section for each subsystem: 1) power generation; 2) energy storage and management; 3) driving motors. Each section acts as an experimental island, able to operate alone or jointly with the other sections. In fact, all the sections are remotely controlled and managed in order to create different assembly of the drive-train. The facility has been sized to allow the testing of drive-trains and subsystems of small and medium-sized vehicles (up to minibuses), but an extension to larger vehicles is possible. During 1996 and part of 1997 the Drive train Test Facility has been completed and made operative. This paper mainly presents the final configurations of these novel testing systems with peculiar features and characteristics. [Italiano] ENEA (Ente Nazionale per le nuove tecnologie, l`Energia e l`Ambiente) sta conducendo un vasto programma di ricerca e sviluppo sui veicoli innovativi ad alto rendimento energetico e basso impatto ambientale.

  7. Optimal design approach for heating irregular-shaped objects in three-dimensional radiant furnaces using a hybrid genetic algorithm-artificial neural network method

    Science.gov (United States)

    Darvishvand, Leila; Kamkari, Babak; Kowsary, Farshad

    2018-03-01

    In this article, a new hybrid method based on the combination of the genetic algorithm (GA) and artificial neural network (ANN) is developed to optimize the design of three-dimensional (3-D) radiant furnaces. A 3-D irregular shape design body (DB) heated inside a 3-D radiant furnace is considered as a case study. The uniform thermal conditions on the DB surfaces are obtained by minimizing an objective function. An ANN is developed to predict the objective function value which is trained through the data produced by applying the Monte Carlo method. The trained ANN is used in conjunction with the GA to find the optimal design variables. The results show that the computational time using the GA-ANN approach is significantly less than that of the conventional method. It is concluded that the integration of the ANN with GA is an efficient technique for optimization of the radiant furnaces.

  8. Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

    International Nuclear Information System (INIS)

    Meo, Santolo; Zohoori, Alireza; Vahedi, Abolfazl

    2016-01-01

    Highlights: • A new optimal design of flux switching permanent magnet generator is developed. • A prototype is employed to validate numerical data used for optimization. • A novel hybrid multi-objective particle swarm optimization approach is proposed. • Optimization targets are weight, cost, voltage and its total harmonic distortion. • The hybrid approach preference is proved compared with other optimization methods. - Abstract: In this paper a new hybrid approach obtained combining a multi-objective particle swarm optimization and artificial neural network is proposed for the design optimization of a direct-drive permanent magnet flux switching generators for low power wind applications. The targets of the proposed multi-objective optimization are to reduce the costs and weight of the machine while maximizing the amplitude of the induced voltage as well as minimizing its total harmonic distortion. The permanent magnet width, the stator and rotor tooth width, the rotor teeth number and stator pole number of the machine define the search space for the optimization problem. Four supervised artificial neural networks are designed for modeling the complex relationships among the weight, the cost, the amplitude and the total harmonic distortion of the output voltage respect to the quantities of the search space. Finite element analysis is adopted to generate training dataset for the artificial neural networks. Finite element analysis based model is verified by experimental results with a 1.5 kW permanent magnet flux switching generator prototype suitable for renewable energy applications, having 6/19 stator poles/rotor teeth. Finally the effectiveness of the proposed hybrid procedure is compared with the results given by conventional multi-objective optimization algorithms. The obtained results show the soundness of the proposed multi objective optimization technique and its feasibility to be adopted as suitable methodology for optimal design of permanent

  9. Comparison of Two Music Training Approaches on Music and Speech Perception in Cochlear Implant Users.

    Science.gov (United States)

    Fuller, Christina D; Galvin, John J; Maat, Bert; Başkent, Deniz; Free, Rolien H

    2018-01-01

    In normal-hearing (NH) adults, long-term music training may benefit music and speech perception, even when listening to spectro-temporally degraded signals as experienced by cochlear implant (CI) users. In this study, we compared two different music training approaches in CI users and their effects on speech and music perception, as it remains unclear which approach to music training might be best. The approaches differed in terms of music exercises and social interaction. For the pitch/timbre group, melodic contour identification (MCI) training was performed using computer software. For the music therapy group, training involved face-to-face group exercises (rhythm perception, musical speech perception, music perception, singing, vocal emotion identification, and music improvisation). For the control group, training involved group nonmusic activities (e.g., writing, cooking, and woodworking). Training consisted of weekly 2-hr sessions over a 6-week period. Speech intelligibility in quiet and noise, vocal emotion identification, MCI, and quality of life (QoL) were measured before and after training. The different training approaches appeared to offer different benefits for music and speech perception. Training effects were observed within-domain (better MCI performance for the pitch/timbre group), with little cross-domain transfer of music training (emotion identification significantly improved for the music therapy group). While training had no significant effect on QoL, the music therapy group reported better perceptual skills across training sessions. These results suggest that more extensive and intensive training approaches that combine pitch training with the social aspects of music therapy may further benefit CI users.

  10. NRC approach to evaluating training effectiveness in accordance with the policy statement on training

    International Nuclear Information System (INIS)

    Persensky, J.J.; Blumer, A.H.

    1985-01-01

    The activity of the past two years has provided an opportunity for the NRC to examine and realign the way in which it views the training process. In the process, it has provided the industry with an incentive to emphasize training as an opportunity for enlightened self-regulation. As a result, the NRC and industry perspectives on training have, for all intents and purposes, merged into a single performance orientation. This cooperation should provide the needed momentum towards improvements in training effectiveness. It is the NRC's goal to monitor this momentum and to encourage progress toward the ideal of systematic, performance-based training for all essential personnel in the nuclear industry

  11. Approach to training the operators of WWER-440 reactors

    International Nuclear Information System (INIS)

    Pironkov, L.; Minakova, R.

    2002-01-01

    The paper has three parts. (1) Personnel Training and Qualifications (2) Description of Kozloduy NPP Training and Qualification System (TQS) built in the last 7 years and its interfaces with the Certification System and (3) Application of the TQS for the Senior Reactor Operator (SRO). (author)

  12. Development Strategies for Online Volunteer Training Modules: A Team Approach

    Science.gov (United States)

    Robideau, Kari; Vogel, Eric

    2014-01-01

    Volunteers are central to the delivery of 4-H programs, and providing quality, relevant training is key to volunteer success. Online, asynchronous modules are an enhancement to a training delivery menu for adult volunteers, providing consistent, accessible options traditionally delivered primarily face to face. This article describes how Minnesota…

  13. Face-to-Face or Distance Training: Two Different Approaches To Motivate SMEs to Learn.

    Science.gov (United States)

    Lawless, Naomi; Allan, John; O'Dwyer, Michele

    2000-01-01

    Two approaches to training for small/medium-sized enterprises were compared: a British distance learning program and an Irish program offering face-to-face training for micro-enterprises. Both used constructivist, collaborative, and reflective methods. Advantages and disadvantages of each approach were identified. (SK)

  14. How Well Can We Learn With Standard BCI Training Approaches? A Pilot Study.

    OpenAIRE

    Jeunet , Camille; Cellard , Alison; Subramanian , Sriram; Hachet , Martin; N'Kaoua , Bernard; Lotte , Fabien

    2014-01-01

    International audience; While being very promising, brain-computer interfaces (BCI) remain barely used outside laboratories because they are not reliable enough. It has been suggested that current training approaches may be partly responsible for the poor reliability of BCIs as they do not satisfy recommendations from psychology and are thus inadequate. To determine to which extent such BCI training approaches (i.e., feedback and training tasks) are suitable to learn a skill, we used them in ...

  15. A simplified computational fluid-dynamic approach to the oxidizer injector design in hybrid rockets

    Science.gov (United States)

    Di Martino, Giuseppe D.; Malgieri, Paolo; Carmicino, Carmine; Savino, Raffaele

    2016-12-01

    Fuel regression rate in hybrid rockets is non-negligibly affected by the oxidizer injection pattern. In this paper a simplified computational approach developed in an attempt to optimize the oxidizer injector design is discussed. Numerical simulations of the thermo-fluid-dynamic field in a hybrid rocket are carried out, with a commercial solver, to investigate into several injection configurations with the aim of increasing the fuel regression rate and minimizing the consumption unevenness, but still favoring the establishment of flow recirculation at the motor head end, which is generated with an axial nozzle injector and has been demonstrated to promote combustion stability, and both larger efficiency and regression rate. All the computations have been performed on the configuration of a lab-scale hybrid rocket motor available at the propulsion laboratory of the University of Naples with typical operating conditions. After a preliminary comparison between the two baseline limiting cases of an axial subsonic nozzle injector and a uniform injection through the prechamber, a parametric analysis has been carried out by varying the oxidizer jet flow divergence angle, as well as the grain port diameter and the oxidizer mass flux to study the effect of the flow divergence on heat transfer distribution over the fuel surface. Some experimental firing test data are presented, and, under the hypothesis that fuel regression rate and surface heat flux are proportional, the measured fuel consumption axial profiles are compared with the predicted surface heat flux showing fairly good agreement, which allowed validating the employed design approach. Finally an optimized injector design is proposed.

  16. A hybrid filtering approach for storage optimization in main-memory cloud database

    Directory of Open Access Journals (Sweden)

    Ghada M. Afify

    2015-11-01

    Full Text Available Enterprises and cloud service providers face dramatic increase in the amount of data stored in private and public clouds. Thus, data storage costs are growing hastily because they use only one single high-performance storage tier for storing all cloud data. There’s considerable potential to reduce cloud costs by classifying data into active (hot and inactive (cold. In the main-memory databases research, recent works focus on approaches to identify hot/cold data. Most of these approaches track tuple accesses to identify hot/cold tuples. In contrast, we introduce a novel Hybrid Filtering Approach (HFA that tracks both tuples and columns accesses in main-memory databases. Our objective is to enhance the performance in terms of three dimensions: storage space, query elapsed time and CPU time. In order to validate the effectiveness of our approach, we realized its concrete implementation on Hekaton, a SQL’s server memory-optimized engine using the well-known TPC-H benchmark. Experimental results show that the proposed HFA outperforms Hekaton approach in respect of all performance dimensions. In specific, HFA reduces the storage space by average of 44–96%, reduces the query elapsed time by average of 25–93% and reduces the CPU time by average of 31–97% compared to the traditional database approach.

  17. An Odometry-free Approach for Simultaneous Localization and Online Hybrid Map Building

    Directory of Open Access Journals (Sweden)

    Wei Hong Chin

    2016-11-01

    Full Text Available In this paper, a new approach is proposed for mobile robot localization and hybrid map building simultaneously without using any odometry hardware system. The proposed method termed as Genetic Bayesian ARAM which comprises two main components: 1 Steady state genetic algorithm (SSGA for self-localization and occupancy grid map building; 2 Bayesian Adaptive Resonance Associative Memory (ARAM for online topological map building. The model of the explored environment is formed as a hybrid representation, both topological and grid-based, and it is incrementally constructed during the exploration process. During occupancy map building, robot estimated self-position is updated by SSGA. At the same time, robot estimated self position is transmit to Bayesian ARAM for topological map building and localization. The effectiveness of our proposed approach is validated by a number of standardized benchmark datasets and real experimental results carried on mobile robot. Benchmark datasets are used to verify the proposed method capable of generating topological map in different environment conditions. Real robot experiment is to verify the proposed method can be implemented in real world.

  18. Hybrid discrete PSO and OPF approach for optimization of biomass fueled micro-scale energy system

    International Nuclear Information System (INIS)

    Gómez-González, M.; López, A.; Jurado, F.

    2013-01-01

    Highlights: ► Method to determine the optimal location and size of biomass power plants. ► The proposed approach is a hybrid of PSO algorithm and optimal power flow. ► Comparison among the proposed algorithm and other methods. ► Computational costs are enough lower than that required for exhaustive search. - Abstract: This paper addresses generation of electricity in the specific aspect of finding the best location and sizing of biomass fueled gas micro-turbine power plants, taking into account the variables involved in the problem, such as the local distribution of biomass resources, biomass transportation and extraction costs, operation and maintenance costs, power losses costs, network operation costs, and technical constraints. In this paper a hybrid method is introduced employing discrete particle swarm optimization and optimal power flow. The approach can be applied to search the best sites and capacities to connect biomass fueled gas micro-turbine power systems in a distribution network among a large number of potential combinations and considering the technical constraints of the network. A fair comparison among the proposed algorithm and other methods is performed.

  19. Output Tracking Control of Switched Hybrid Systems: A Fliess Functional Expansion Approach

    Directory of Open Access Journals (Sweden)

    Fenghua He

    2013-01-01

    Full Text Available The output tracking problem is investigated for a nonlinear affine system with multiple modes of continuous control inputs. We convert the family of nonlinear affine systems under consideration into a switched hybrid system by introducing a multiple-valued logic variable. The Fliess functional expansion is adopted to express the input and output relationship of the switched hybrid system. The optimal switching control is determined for a multiple-step output tracking performance index. The proposed approach is applied to a multitarget tracking problem for a flight vehicle aiming for one real target with several decoys flying around it in the terminal guidance course. These decoys appear as apparent targets and have to be distinguished with the approaching of the flight vehicle. The guidance problem of one flight vehicle versus multiple apparent targets should be considered if no large miss distance might be caused due to the limitation of the flight vehicle maneuverability. The target orientation at each time interval is determined. Simulation results show the effectiveness of the proposed method.

  20. Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels

    Directory of Open Access Journals (Sweden)

    Antonino Laudani

    2015-01-01

    Full Text Available A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented. The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model. Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task. The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form. The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters. It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture. Validations are made on about 10000 PV panels belonging to the California Energy Commission database.

  1. A diagnostic expert system for the nuclear power plant b ased on the hybrid knowledge approach

    International Nuclear Information System (INIS)

    Yang, J.O.; Chang, S.H.

    1989-01-01

    A diagnostic expert system, the hybrid knowledge based plant operation supporting system (HYPOSS), which has been developed to support operators' decisionmaking during the transients of the nuclear power plant, is described. HYPOSS adopts the hybrid knowledge approach, which combines both shallow and deep knowledge to take advantage of the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure. They are structural, functional, behavioral, and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions, respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem-solving behavior modeled in HYPOSS. The event-based operational guidelines are provided to the operator according to the diagnosed results. If the exact anomalies cannot be identified while some of the critical safety functions are challenged, the function-based operational guidelines are provided to the operator. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies show good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

  2. A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran

    International Nuclear Information System (INIS)

    Mostafavi, Elham Sadat; Ramiyani, Sara Saeidi; Sarvar, Rahim; Moud, Hashem Izadi; Mousavi, Seyyed Mohammad

    2013-01-01

    This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated annealing (SA), called GP/SA. The solar radiation was formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years in two cities of Iran were used to develop GP/SA-based models. Separate models were established for each city. The generalization of the models was verified using a separate testing database. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the solar radiation. The derived models make accurate predictions of the solar global radiation and notably outperform the existing models. -- Highlights: ► A hybrid approach is presented for the estimation of the solar global radiation. ► The proposed method integrates the capabilities of GP and SA. ► Several climatological and meteorological parameters are included in the analysis. ► The GP/SA models make accurate predictions of the solar global radiation.

  3. Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

    Directory of Open Access Journals (Sweden)

    Yuliang Su

    2015-04-01

    Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

  4. Evaluating the influence of goal setting on intravenous catheterization skill acquisition and transfer in a hybrid simulation training context.

    Science.gov (United States)

    Brydges, Ryan; Mallette, Claire; Pollex, Heather; Carnahan, Heather; Dubrowski, Adam

    2012-08-01

    Educators often simplify complex tasks by setting learning objectives that focus trainees on isolated skills rather than the holistic task. We designed 2 sets of learning objectives for intravenous catheterization using goal setting theory. We hypothesized that setting holistic goals related to technical, cognitive, and communication skills would result in superior holistic performance, whereas setting isolated goals related to technical skills would result in superior technical performance. We randomly assigned practicing health care professionals to set holistic (n = 14) or isolated (n = 15) goals. All watched an instructional video and studied a list of 9 goals specific to their group. Participants practiced independently in a hybrid simulation (standardized patient combined with an arm simulator). The first and the last practice trials were videotaped for analysis. One-week later, participants completed a transfer test in another hybrid simulation scenario. Blinded experts evaluated performance on all 3 trials using the Direct Observation of Procedural Skills tool. The holistic group scored higher than the isolated group on the holistic Direct Observation of Procedural Skills score for all 3 trials [mean (SD), 45.0 (9.16) vs. 38.4 (9.17); P = 0.01]. The isolated group did not perform better than the holistic group on the technical skills score [10.3 (2.73) vs. 11.6 (3.01); P = 0.11]. Our results suggest that asking learners to set holistic goals did not interfere with their attaining competent holistic and technical skills during hybrid simulation training. This exploratory trial provides preliminary evidence for how to consider integrating hybrid simulation into medical curricula and for the design of learning goals in simulation-based education.

  5. A hybrid simulated annealing approach to handle energy resource management considering an intensive use of electric vehicles

    DEFF Research Database (Denmark)

    Sousa, Tiago; Vale, Zita; Carvalho, Joao Paulo

    2014-01-01

    The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed...... to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated...... annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA...

  6. A Hybrid Heuristic Optimization Approach for Leak Detection in Pipe Networks Using Ordinal Optimization Approach and the Symbiotic Organism Search

    Directory of Open Access Journals (Sweden)

    Chao-Chih Lin

    2017-10-01

    Full Text Available A new transient-based hybrid heuristic approach is developed to optimize a transient generation process and to detect leaks in pipe networks. The approach couples the ordinal optimization approach (OOA and the symbiotic organism search (SOS to solve the optimization problem by means of iterations. A pipe network analysis model (PNSOS is first used to determine steady-state head distribution and pipe flow rates. The best transient generation point and its relevant valve operation parameters are optimized by maximizing the objective function of transient energy. The transient event is created at the chosen point, and the method of characteristics (MOC is used to analyze the transient flow. The OOA is applied to sift through the candidate pipes and the initial organisms with leak information. The SOS is employed to determine the leaks by minimizing the sum of differences between simulated and computed head at the observation points. Two synthetic leaking scenarios, a simple pipe network and a water distribution network (WDN, are chosen to test the performance of leak detection ordinal symbiotic organism search (LDOSOS. Leak information can be accurately identified by the proposed approach for both of the scenarios. The presented technique makes a remarkable contribution to the success of leak detection in the pipe networks.

  7. Modeling the Effects of Stress: An Approach to Training

    Science.gov (United States)

    Cuper, Taryn

    2010-01-01

    Stress is an integral element of the operational conditions experienced by combat medics. The effects of stress can compromise the performance of combat medics who must reach and treat their comrades under often threatening circumstances. Examples of these effects include tunnel vision, loss of motor control, and diminished hearing, which can result in an inability to perceive further danger, satisfactorily treat the casualty, and communicate with others. While many training programs strive to recreate this stress to aid in the experiential learning process, stress inducement may not always be feasible or desired. In addition, live simulations are not always a practical, convenient, and repeatable method of training. Instead, presenting situational training on a personal computer is proposed as an effective training platform in which the effects of stress can be addressed in a different way. We explore the cognitive and motor effects of stress, as well as the benefits of training for mitigating these effects in real life. While many training applications focus on inducing stress in order to "condition" the stress response, the author explores the possibilities of modeling stress to produce a similar effect. Can presenting modeled effects of stress help prepare or inoculate soldiers for stressful situations in which they must perform at a high level? This paper investigates feasibility of modeling stress and describes the preliminary design considerations of a combat medic training system that utilizes this method of battlefield preparation.

  8. A NEW HYBRID DYNAMIC METROPOLITAN TRAIN MODEL UN NUEVO MODELO DINÁMICO HÍBRIDO DE TREN METROPOLITANO

    Directory of Open Access Journals (Sweden)

    Ingeborg Mahla

    2010-12-01

    Full Text Available An integral dynamic model of the metropolitan train type transport system is presented. The interactions between the trajectories of the trains in use and the passenger exchange between the cars and the platforms in the stations along the tracks are described. In contrast with the current traffic engineering models based on passenger flow, this model allows the simulation of passenger accumulation that occurs on the platforms when the train cannot transport the total number of passengers waiting for it. The dynamics of the metropolitan train is modeled with a hybrid system in which the platforms and the trains are considered as continuous modes and train arrival at the stations as discrete events.En este artículo se describe un modelo dinámico integral del sistema de transporte tipo tren metropolitano. En él se describen las interacciones entre las trayectorias de los trenes en circulación y el intercambio de pasajeros entre los coches y los andenes en las estaciones a lo largo de la vía. A diferencia de los actuales modelos de ingeniería de tráfico, basados en flujos de pasajeros, este modelo permite simular las acumulaciones que se producen en los andenes cuando el tren no logra transportar la cantidad total de pasajeros esperando en el andén. La dinámica del tren metropolitano es modelada como un sistema híbrido en el cual los andenes y los trenes son considerados modos continuos y los arribos de los trenes a las estaciones como eventos discretos.

  9. A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN

    Directory of Open Access Journals (Sweden)

    Yimei Kang

    2014-04-01

    Full Text Available Energy efficiency is usually a significant goal in wireless sensor networks (WSNs. In this work, an energy efficient chain (EEC data routing approach is first presented. The coverage and connectivity of WSNs are discussed based on EEC. A hybrid node scheduling approach is then proposed. It includes sleep scheduling for cyclically monitoring regions of interest in time-driven modes and wakeup scheduling for tracking emergency events in event-driven modes. A failure rate is introduced to the sleep scheduling to improve the reliability of the system. A wakeup sensor threshold and a sleep time threshold are introduced in the wakeup scheduling to reduce the consumption of energy to the possible extent. The results of the simulation show that the proposed algorithm can extend the effective lifetime of the network to twice that of PEAS. In addition, the proposed methods are computing efficient because they are very simple to implement.

  10. A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Jian Xiong

    2012-01-01

    Full Text Available This paper addresses multiobjective flexible job-shop scheduling problem (FJSP with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach (H-MOEA is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to maintain the diversity of individuals. In the proposed H-MOEA, well-designed chromosome representation and genetic operators are developed for FJSP. Moreover, a local search procedure based on critical path theory is incorporated in H-MOEA to improve the convergence ability of the algorithm. Experiment results on several well-known benchmark instances demonstrate the efficiency and stability of the proposed algorithm. The comparison with other recently published approaches validates that H-MOEA can obtain Pareto-optimal solutions with better quality and/or diversity.

  11. A Practical Approach to Improve Optical Channel Utilization Period for Hybrid FSO/RF Systems

    Directory of Open Access Journals (Sweden)

    Ahmet Akbulut

    2014-01-01

    Full Text Available In hybrid FSO/RF systems, mostly a hard switching mechanism is preferred in case of the FSO signal level falls below to the predefined threshold. In this work, a computationally simple approach is proposed to increase the utilization of the FSO channels bandwidth advantage. For the channel, clear air conditions have been supposed with the atmospheric turbulence. In this approach, FSO bit rate is adaptively changed to achieve desired BER performance. An IM/DD modulation, OOK (NRZ format has been used to show the benefit of the proposed method. Furthermore, to be more realistic with respect to the atmospheric turbulence variations within a day, some experimental observations have been followed up.

  12. Training Approach-Avoidance of Smiling Faces Affects Emotional Vulnerability in Socially Anxious Individuals

    Directory of Open Access Journals (Sweden)

    Mike eRinck

    2013-08-01

    Full Text Available Previous research revealed an automatic behavioral bias in high socially anxious individuals (HSAs: Although their explicit evaluations of smiling faces are positive, they show automatic avoidance of these faces. This is reflected by faster pushing than pulling of smiling faces in an Approach-Avoidance Task (AAT; Heuer, Rinck, & Becker, 2007. The current study addressed the causal role of this avoidance bias for social anxiety. To this end, we used the AAT to train HSAs, either to approach smiling faces or to avoid them. We examined whether such an AAT training could change HSAs’ automatic avoidance tendencies, and if yes, whether AAT effects would generalize to a new approach task with new facial stimuli, and to mood and anxiety in a social threat situation (a video-recorded self-presentation. We found that HSAs trained to approach smiling faces did indeed approach female faces faster after the training than HSAs trained to avoid smiling faces. Moreover, approach-faces training reduced emotional vulnerability: It led to more positive mood and lower anxiety after the self-presentation than avoid-faces training. These results suggest that automatic approach-avoidance tendencies have a causal role in social anxiety, and that they can be modified by a simple computerized training. This may open new avenues in the therapy of social phobia.

  13. Training approach-avoidance of smiling faces affects emotional vulnerability in socially anxious individuals

    Science.gov (United States)

    Rinck, Mike; Telli, Sibel; Kampmann, Isabel L.; Woud, Marcella L.; Kerstholt, Merel; te Velthuis, Sarai; Wittkowski, Matthias; Becker, Eni S.

    2013-01-01

    Previous research revealed an automatic behavioral bias in high socially anxious individuals (HSAs): although their explicit evaluations of smiling faces are positive, they show automatic avoidance of these faces. This is reflected by faster pushing than pulling of smiling faces in an Approach-Avoidance Task (AAT; Heuer et al., 2007). The current study addressed the causal role of this avoidance bias for social anxiety. To this end, we used the AAT to train HSAs, either to approach smiling faces or to avoid them. We examined whether such an AAT training could change HSAs' automatic avoidance tendencies, and if yes, whether AAT effects would generalize to a new approach task with new facial stimuli, and to mood and anxiety in a social threat situation (a video-recorded self-presentation). We found that HSAs trained to approach smiling faces did indeed approach female faces faster after the training than HSAs trained to avoid smiling faces. Moreover, approach-faces training reduced emotional vulnerability: it led to more positive mood and lower anxiety after the self-presentation than avoid-faces training. These results suggest that automatic approach-avoidance tendencies have a causal role in social anxiety, and that they can be modified by a simple computerized training. This may open new avenues in the therapy of social phobia. PMID:23970862

  14. Hybrid qualifications. Increasing the value of vocational education and training in the comtext of Lifelong Learning

    DEFF Research Database (Denmark)

    Jørgensen, Christian Helms; Lindvig, Katrine

    The aim of this second report is to present the results of an empirical study of the perceptions and views of the key stakeholders (teachers, learners, employers, policy-makers) in relation to hybrid qualifications (vocational and general qualifications). A special attention is given to the new h...

  15. Near-term hybrid vehicle program, phase 1. Appendix B: Design trade-off studies. [various hybrid/electric power train configurations and electrical and mechanical drive-line components

    Science.gov (United States)

    1979-01-01

    The relative attractiveness of various hybrid/electric power train configurations and electrical and mechanical drive-line components was studied. The initial screening was concerned primarily with total vehicle weight and economic factors and identified the hybrid power train combinations which warranted detailed evaluation over various driving cycles. This was done using a second-by-second vehicle simulation program which permitted the calculations of fuel economy, electricity usage, and emissions as a function of distance traveled in urban and highway driving. Power train arrangement possibilities were examined in terms of their effect on vehicle handling, safety, serviceability, and passenger comfort. A dc electric drive system utilizing a separately excited motor with field control and battery switching was selected for the near term hybrid vehicle. Hybrid vehicle simulations showed that for the first 30 mi (the electric range of the vehicle) in urban driving, the fuel economy was 80 mpg using a gasoline engine and 100 mpg using a diesel engine. In urban driving the hybrid would save about 75% of the fuel used by the conventional vehicle and in combined urban/highway driving the fuel saving is about 50%.

  16. Approach to training the trainer at the Bell System Training Center

    International Nuclear Information System (INIS)

    Housley, E.A.; Stevenson, J.L.

    1981-01-01

    The major activity of the Bell System Training Center is to develop and deliver technical training. Experts in various technical areas are selected as course developers or instructors, usually on rotational assignments. Through a series of workshops, described in this paper, combined with coaching, use of job aids and working with more experienced peers, they become competent developers or instructors. There may be similarities between the mission of the Bell System Training Center and other contexts where criticality of job performance and technical subject matter are training characteristics

  17. A multivariate approach to heavy flavour tagging with cascade training

    International Nuclear Information System (INIS)

    Bastos, J; Liu, Y

    2007-01-01

    This paper compares the performance of artificial neural networks and boosted decision trees, with and without cascade training, for tagging b-jets in a collider experiment. It is shown, using a Monte Carlo simulation of WH→lνq q-bar events, that for a b-tagging efficiency of 50%, the light jet rejection power given by boosted decision trees without cascade training is about 55% higher than that given by artificial neural networks. The cascade training technique can improve the performance of boosted decision trees and artificial neural networks at this b-tagging efficiency level by about 35% and 80% respectively. We conclude that the cascade trained boosted decision trees method is the most promising technique for tagging heavy flavours at collider experiments

  18. The Culure Assimilator: An Approach to Cross-Cultural Training

    Science.gov (United States)

    Fiedler, Fred E.; And Others

    1971-01-01

    Evaluates the cultural assimilator, a kind of training manual to help members of one culture understand and adjust to another culture. Describes those constructed for the Arab countries, Iran, Thailand, Central America, and Greece. (MB)

  19. A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

    Science.gov (United States)

    Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

    2013-01-01

    In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800

  20. Systems Approach to Japanese Language Teacher Training Curriculum

    OpenAIRE

    Nuibe, Yoshinori

    1988-01-01

    The purpose of the present article is to present a conceptual framework for systematizing the Japanese-language teacher training curriculum. Firstly, I discussed what an outstanding Japanese language teacher is like. Secondly, I focussed on teacher development. Thirdly, I proposed the principles of constructing a systematic curriculum. Lastly, I insisted that a new curriculum for human dynamics in Japanese be introduced and established in the Japanese language teacher training course.

  1. Pervasive Sound Sensing: A Weakly Supervised Training Approach.

    Science.gov (United States)

    Kelly, Daniel; Caulfield, Brian

    2016-01-01

    Modern smartphones present an ideal device for pervasive sensing of human behavior. Microphones have the potential to reveal key information about a person's behavior. However, they have been utilized to a significantly lesser extent than other smartphone sensors in the context of human behavior sensing. We postulate that, in order for microphones to be useful in behavior sensing applications, the analysis techniques must be flexible and allow easy modification of the types of sounds to be sensed. A simplification of the training data collection process could allow a more flexible sound classification framework. We hypothesize that detailed training, a prerequisite for the majority of sound sensing techniques, is not necessary and that a significantly less detailed and time consuming data collection process can be carried out, allowing even a nonexpert to conduct the collection, labeling, and training process. To test this hypothesis, we implement a diverse density-based multiple instance learning framework, to identify a target sound, and a bag trimming algorithm, which, using the target sound, automatically segments weakly labeled sound clips to construct an accurate training set. Experiments reveal that our hypothesis is a valid one and results show that classifiers, trained using the automatically segmented training sets, were able to accurately classify unseen sound samples with accuracies comparable to supervised classifiers, achieving an average F -measure of 0.969 and 0.87 for two weakly supervised datasets.

  2. Proposed prediction algorithms based on hybrid approach to deal with anomalies of RFID data in healthcare

    Directory of Open Access Journals (Sweden)

    A. Anny Leema

    2013-07-01

    Full Text Available The RFID technology has penetrated the healthcare sector due to its increased functionality, low cost, high reliability, and easy-to-use capabilities. It is being deployed for various applications and the data captured by RFID readers increase according to timestamp resulting in an enormous volume of data duplication, false positive, and false negative. The dirty data stream generated by the RFID readers is one of the main factors limiting the widespread adoption of RFID technology. In order to provide reliable data to RFID application, it is necessary to clean the collected data and this should be done in an effective manner before they are subjected to warehousing. The existing approaches to deal with anomalies are physical, middleware, and deferred approach. The shortcomings of existing approaches are analyzed and found that robust RFID system can be built by integrating the middleware and deferred approach. Our proposed algorithms based on hybrid approach are tested in the healthcare environment which predicts false positive, false negative, and redundant data. In this paper, healthcare environment is simulated using RFID and the data observed by RFID reader consist of anomalies false positive, false negative, and duplication. Experimental evaluation shows that our cleansing methods remove errors in RFID data more accurately and efficiently. Thus, with the aid of the planned data cleaning technique, we can bring down the healthcare costs, optimize business processes, streamline patient identification processes, and improve patient safety.

  3. An Introduction to the Hybrid Approach of Neural Networks and the Linear Regression Model : An Illustration in the Hedonic Pricing Model of Building Costs

    OpenAIRE

    浅野, 美代子; マーコ, ユー K.W.

    2007-01-01

    This paper introduces the hybrid approach of neural networks and linear regression model proposed by Asano and Tsubaki (2003). Neural networks are often credited with its superiority in data consistency whereas the linear regression model provides simple interpretation of the data enabling researchers to verify their hypotheses. The hybrid approach aims at combing the strengths of these two well-established statistical methods. A step-by-step procedure for performing the hybrid approach is pr...

  4. Heuristic hybrid game approach for fleet condition-based maintenance planning

    International Nuclear Information System (INIS)

    Feng, Qiang; Bi, Xiong; Zhao, Xiujie; Chen, Yiran; Sun, Bo

    2017-01-01

    The condition-based maintenance (CBM) method is commonly used to select appropriate maintenance opportunities according to equipment status over a period of time. The CBM of aircraft fleets is a fleet maintenance planning problem. In this problem, mission requirements, resource constraints, and aircraft statuses are considered to find an optimal strategy set. Given that the maintenance strategies for each aircraft are finite, fleet CBM can be treated as a combinatorial optimization problem. In this study, the process of making a decision on the CBM of military fleets is analyzed. The fleet CBM problem is treated as a two-stage dynamic decision-making problem. Aircraft are divided into dispatch and standby sets; thus, the problem scale is significantly reduced. A heuristic hybrid game (HHG) approach comprising a competition game and a cooperative game is proposed on the basis of heuristic rule. In the dispatch set, a competition game approach is proposed to search for a local optimal strategy matrix. A cooperative game method for the two sets is also proposed to ensure global optimization. Finally, a case study regarding a fleet comprising 20 aircraft is conducted, with the results proving that the approach efficiently generates outcomes that meet the mission risk-oriented schedule requirement. - Highlights: • A new heuristic hybrid game method for fleet condition-based maintenance is proposed. • The problem is simplified by hierarchical solving based on dispatch and standby set. • The local optimal solution is got by competition game algorithm for dispatch set. • The global optimal solution is got by cooperative game algorithm between two sets.

  5. An approach for identification of unknown viruses using sequencing-by-hybridization.

    Science.gov (United States)

    Katoski, Sarah E; Meyer, Hermann; Ibrahim, Sofi

    2015-09-01

    Accurate identification of biological threat agents, especially RNA viruses, in clinical or environmental samples can be challenging because the concentration of viral genomic material in a given sample is usually low, viral genomic RNA is liable to degradation, and RNA viruses are extremely diverse. A two-tiered approach was used for initial identification, then full genomic characterization of 199 RNA viruses belonging to virus families Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, and Togaviridae. A Sequencing-by-hybridization (SBH) microarray was used to tentatively identify a viral pathogen then, the identity is confirmed by guided next-generation sequencing (NGS). After optimization and evaluation of the SBH and NGS methodologies with various virus species and strains, the approach was used to test the ability to identify viruses in blinded samples. The SBH correctly identified two Ebola viruses in the blinded samples within 24 hr, and by using guided amplicon sequencing with 454 GS FLX, the identities of the viruses in both samples were confirmed. SBH provides at relatively low-cost screening of biological samples against a panel of viral pathogens that can be custom-designed on a microarray. Once the identity of virus is deduced from the highest hybridization signal on the SBH microarray, guided (amplicon) NGS sequencing can be used not only to confirm the identity of the virus but also to provide further information about the strain or isolate, including a potential genetic manipulation. This approach can be useful in situations where natural or deliberate biological threat incidents might occur and a rapid response is required. © 2015 Wiley Periodicals, Inc.

  6. Optimal control of hybrid vehicles

    CERN Document Server

    Jager, Bram; Kessels, John

    2013-01-01

    Optimal Control of Hybrid Vehicles provides a description of power train control for hybrid vehicles. The background, environmental motivation and control challenges associated with hybrid vehicles are introduced. The text includes mathematical models for all relevant components in the hybrid power train. The power split problem in hybrid power trains is formally described and several numerical solutions detailed, including dynamic programming and a novel solution for state-constrained optimal control problems based on Pontryagin’s maximum principle.   Real-time-implementable strategies that can approximate the optimal solution closely are dealt with in depth. Several approaches are discussed and compared, including a state-of-the-art strategy which is adaptive for vehicle conditions like velocity and mass. Two case studies are included in the book: ·        a control strategy for a micro-hybrid power train; and ·        experimental results obtained with a real-time strategy implemented in...

  7. Development and Demonstration of a Low Cost Hybrid Drive Train for Medium and Heavy Duty Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Strangas, Elias; Schock, Harold; Zhu, Guoming; Moran, Kevin; Ruckle, Trevor; Foster, Shanelle; Cintron-Rivera, Jorge; Tariq, Abdul; Nino-Baron, Carlos

    2011-04-30

    The DOE sponsored effort is part of a larger effort to quantify the efficiency of hybrid powertrain systems through testing and modeling. The focus of the DOE sponsored activity was the design, development and testing of hardware to evaluate the efficiency of the electrical motors relevant to medium duty vehicles. Medium duty hybrid powertrain motors and generators were designed, fabricated, setup and tested. The motors were a permanent magnet configuration, constructed at Electric Apparatus Corporation in Howell, Michigan. The purpose of this was to identify the potential gains in terms of fuel cost savings that could be realized by implementation of such a configuration. As the electric motors constructed were prototype designs, the scope of the project did not include calculation of the costs of mass production of the subject electrical motors or generator.

  8. Hybrid Switching Controller Design for the Maneuvering and Transit of a Training Ship

    Directory of Open Access Journals (Sweden)

    Tomera Mirosław

    2017-03-01

    Full Text Available The paper presents the design of a hybrid controller used to control the movement of a ship in different operating modes, thereby improving the performance of basic maneuvers. This task requires integrating several operating modes, such as maneuvering the ship at low speeds, steering the ship at different speeds in the course or along the trajectory, and stopping the ship on the route. These modes are executed by five component controllers switched on and off by the supervisor depending on the type of operation performed. The desired route, containing the coordinates of waypoints and tasks performed along consecutive segments of the reference trajectory, is obtained by the supervisory system from the system operator. The former supports switching between component controllers and provides them with new set-points after each change in the reference trajectory segment, thereby ensuring stable operation of the entire hybrid switching controller.

  9. Energy storage options for fuel cell hybrid power-trains in road vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Davies, D; Mortimer, R; Moore, J

    2000-07-01

    The objective of this work was to identify and assess energy storage technologies that may be applicable for use in fuel cell hybrid electric vehicles (HEVs) in the time frame to 2010. The current and projected status of each technology was evaluated, based on recognised existing goals (such as USDoE and USABC) and performance requirements, so that potential commercial opportunities could be identified. (Author)

  10. The Importance of Being Hybrid for Spatial Epidemic Models:A Multi-Scale Approach

    Directory of Open Access Journals (Sweden)

    Arnaud Banos

    2015-11-01

    Full Text Available This work addresses the spread of a disease within an urban system, definedas a network of interconnected cities. The first step consists of comparing two differentapproaches: a macroscopic one, based on a system of coupled Ordinary DifferentialEquations (ODE Susceptible-Infected-Recovered (SIR systems exploiting populations onnodes and flows on edges (so-called metapopulational model, and a hybrid one, couplingODE SIR systems on nodes and agents traveling on edges. Under homogeneous conditions(mean field approximation, this comparison leads to similar results on the outputs on whichwe focus (the maximum intensity of the epidemic, its duration and the time of the epidemicpeak. However, when it comes to setting up epidemic control strategies, results rapidlydiverge between the two approaches, and it appears that the full macroscopic model is notcompletely adapted to these questions. In this paper, we focus on some control strategies,which are quarantine, avoidance and risk culture, to explore the differences, advantages anddisadvantages of the two models and discuss the importance of being hybrid when modelingand simulating epidemic spread at the level of a whole urban system.

  11. Modular approach for conversion to the ion-hybrid wave and α gyroresonance

    International Nuclear Information System (INIS)

    Kaufman, A.N.; Morehead, J.J.; Brizard, A.J.; Tracy, E.R.

    1997-01-01

    Linear conversion of an incoming magnetosonic wave (a.k.a. fast or compressional wave) to an ion-hybrid wave can be considered as a 3-step process in ray phase space. This is demonstrated by casting the cold-fluid model into the Friedland-Kaufman normal form for linear mode conversion. First, the incoming magnetosonic ray (MSR) converts a fraction of its action to an intermediate ion-hybrid ray (IHR), with the transmitted ray proceeding through the conversion layer. The IHR propagates in k-space to a second conversion point, where it converts in turn a fraction of its action into a reflected MSR, with the remainder of the its action constituting the converted IHR. The modular approach gives exact agreement with the more standard Budden formulation for the transmission, reflection and conversion coefficients, but has the important advantage of exposing the intermediate IHR. The existence of the intermediate IHR has important physical consequences as it can resonate with α particles. We estimate the time-integrated damping coefficient between the two conversions and show that ∫γdt is of order -100, thus the IH wave is completely annihilated between conversions and transfers its energy to the α close-quote s. This suggests that proposals to use the IH mode for current drive or DT heating are likely to fail in the presence of fusion α close-quote s. copyright 1997 American Institute of Physics

  12. Aeroacoustic analysis of the human phonation process based on a hybrid acoustic PIV approach

    Science.gov (United States)

    Lodermeyer, Alexander; Tautz, Matthias; Becker, Stefan; Döllinger, Michael; Birk, Veronika; Kniesburges, Stefan

    2018-01-01

    The detailed analysis of sound generation in human phonation is severely limited as the accessibility to the laryngeal flow region is highly restricted. Consequently, the physical basis of the underlying fluid-structure-acoustic interaction that describes the primary mechanism of sound production is not yet fully understood. Therefore, we propose the implementation of a hybrid acoustic PIV procedure to evaluate aeroacoustic sound generation during voice production within a synthetic larynx model. Focusing on the flow field downstream of synthetic, aerodynamically driven vocal folds, we calculated acoustic source terms based on the velocity fields obtained by time-resolved high-speed PIV applied to the mid-coronal plane. The radiation of these sources into the acoustic far field was numerically simulated and the resulting acoustic pressure was finally compared with experimental microphone measurements. We identified the tonal sound to be generated downstream in a small region close to the vocal folds. The simulation of the sound propagation underestimated the tonal components, whereas the broadband sound was well reproduced. Our results demonstrate the feasibility to locate aeroacoustic sound sources inside a synthetic larynx using a hybrid acoustic PIV approach. Although the technique employs a 2D-limited flow field, it accurately reproduces the basic characteristics of the aeroacoustic field in our larynx model. In future studies, not only the aeroacoustic mechanisms of normal phonation will be assessable, but also the sound generation of voice disorders can be investigated more profoundly.

  13. TRAINING OF E-LEARNING MANAGERS: COMPETENCY APPROACH

    Directory of Open Access Journals (Sweden)

    Nataliia V. Morze

    2017-09-01

    Full Text Available The article analyzes the competencies necessary for the successful professional activity of e-learning managers. The content of the professional qualification "e-learning manager" is revealed. The model of competency system of the e-learning manager is offered. The model, which defines the content, forms, methods and means of training, tools and indicators for assessing the results of training e-learning managers by levels, is substantiated. Examples of competency tasks for forming of professional competencies in innovative teaching methods and technologies, Web 2.0 services, e-learning expertise, e-environment design, IT infrastructure management, and the development of Soft skills are presented. It is proposed to solve the problem of training specialists who will be able not only to use ICT in educational activities, but also to master the competencies of e-learning management.

  14. Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

    Directory of Open Access Journals (Sweden)

    Ahmed Hussein

    2018-01-01

    Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

  15. Impact of locomotion training with a neurologic controlled hybrid assistive limb (HAL) exoskeleton on neuropathic pain and health related quality of life (HRQoL) in chronic SCI: a case study (.).

    Science.gov (United States)

    Cruciger, Oliver; Schildhauer, Thomas A; Meindl, Renate C; Tegenthoff, Martin; Schwenkreis, Peter; Citak, Mustafa; Aach, Mirko

    2016-08-01

    Chronic neuropathic pain (CNP) is a common condition associated with spinal cord injury (SCI) and has been reported to be severe, disabling and often treatment-resistant and therefore remains a clinical challenge for the attending physicians. The treatment usually includes pharmacological and/or nonpharmacological approaches. Body weight supported treadmill training (BWSTT) and locomotion training with driven gait orthosis (DGO) have evolved over the last decades and are now considered to be an established part in the rehabilitation of SCI patients. Conventional locomotion training goes along with improvements of the patients' walking abilities in particular speed and gait pattern. The neurologic controlled hybrid assistive limb (HAL®, Cyberdyne Inc., Ibraki, Japan) exoskeleton, however, is a new tailored approach to support motor functions synchronously to the patient's voluntary drive. This report presents two cases of severe chronic and therapy resistant neuropathic pain due to chronic SCI and demonstrates the beneficial effects of neurologic controlled exoskeletal intervention on pain severity and health-related quality of life (HRQoL). Both of these patients were engaged in a 12 weeks period of daily HAL®-supported locomotion training. In addition to improvements in motor functions and walking abilities, both show significant reduction in pain severity and improvements in all HRQoL domains. Although various causal factors likely contribute to abatement of CNP, the reported results occurred due to a new approach in the rehabilitation of chronic spinal cord injury patients. These findings suggest not only the feasibility of this new approach but in conclusion, demonstrate the effectiveness of neurologic controlled locomotion training in the long-term management of refractory neuropathic pain. Implications for Rehabilitation CNP remains a challenge in the rehabilitation of chronic SCI patients. Locomotion training with the HAL exoskeleton seems to improve CNP

  16. Distance learning approach to train health sciences students at the ...

    African Journals Online (AJOL)

    Background: The University of Nairobi (UoN) College of Health Sciences (CHS) established Partnership for Innovative Medical Education in Kenya (PRIME-K) programmeme to enhance health outcomes in Kenya through extending the reach of medical training outside Nairobi to help health sciences students enhance their ...

  17. Using Emotional Intelligence in Training Crisis Managers: The Pandora Approach

    Science.gov (United States)

    Mackinnon, Lachian; Bacon, Liz; Cortellessa, Gabriella; Cesta, Amedeo

    2013-01-01

    Multi-agency crisis management represents one of the most complex of real-world situations, requiring rapid negotiation and decision-making under extreme pressure. However, the training offered to strategic planners, called Gold Commanders, does not place them under any such pressure. It takes the form of paper-based, table-top exercises, or…

  18. Beyond Assertiveness Training: A Problem-Solving Approach.

    Science.gov (United States)

    Scott, Nancy A.

    1979-01-01

    Assertiveness training models show shortcomings in those situations where assertiveness results in stalemates or conflicts, or both. Deadlocks may occur when antagonists demonstrate appropriate assertive behavior. Conflict management using problem-solving skills allows individuals to learn appropriate methods of dealing with conflictual or…

  19. Routing Trains Through Railway Junctions: A New Set Packing Approach

    DEFF Research Database (Denmark)

    Lusby, Richard; Larsen, Jesper; Ryan, David

    how the problem can be formulated as a set packing model. To exploit the structure of the problem we present a solution procedure which entails solving the dual of this formulation through the dynamic addition of violated cuts (primal variables). A discussion of the variable (train path) generation...

  20. Training Needs Analysis: Weaknesses in the Conventional Approach.

    Science.gov (United States)

    Leat, Michael James; Lovel, Murray Jack

    1997-01-01

    Identification of the training and development needs of administrative support staff is not aided by conventional performance appraisal, which measures summary or comparative effectiveness. Meaningful diagnostic evaluation integrates three levels of analysis (organization, task, and individual), using behavioral expectation scales. (SK)

  1. Analysis of Video-Based Training Approaches and Professional Development

    Science.gov (United States)

    Leblanc, Serge

    2018-01-01

    The use of videos to analyze teaching practices or initial teacher training is aimed at helping build professional skills by establishing more explicit links between university education and internships and practical work in the schools. The purpose of this article is to familiarize the English-speaking community with French research via a study…

  2. Teacher Training in Family Involvement: An Interpersonal Approach.

    Science.gov (United States)

    Coleman, Mick; Wallinga, Charlotte

    2000-01-01

    Discusses ways to develop family-school-community involvement, based on an early childhood teacher training course in family involvement. Discusses strategies for using Maslow's Hierarchy of Needs to facilitate family involvement interactions, and using student teachers' experiences for structuring reflective thought about family involvement…

  3. A Novel Approach to Medicine Training for Psychiatry Residents

    Science.gov (United States)

    Onate, John; Hales, Robert; McCarron, Robert; Han, Jaesu; Pitman, Dorothy

    2008-01-01

    Objective: A unique rotation was developed to address limited outpatient internal medicine training in psychiatric residency by the University of California, Davis, Department of Psychiatry and Behavioral Sciences, which provides medical care to patients with mental illness. Methods: The number of patients seen by the service and the number of…

  4. Numerical Prediction of Combustion-induced Noise using a hybrid LES/CAA approach

    Science.gov (United States)

    Ihme, Matthias; Pitsch, Heinz; Kaltenbacher, Manfred

    2006-11-01

    Noise generation in technical devices is an increasingly important problem. Jet engines in particular produce sound levels that not only are a nuisance but may also impair hearing. The noise emitted by such engines is generated by different sources such as jet exhaust, fans or turbines, and combustion. Whereas the former acoustic mechanisms are reasonably well understood, combustion-generated noise is not. A methodology for the prediction of combustion-generated noise is developed. In this hybrid approach unsteady acoustic source terms are obtained from an LES and the propagation of pressure perturbations are obtained using acoustic analogies. Lighthill's acoustic analogy and a non-linear wave equation, accounting for variable speed of sound, have been employed. Both models are applied to an open diffusion flame. The effects on the far field pressure and directivity due to the variation of speed of sound are analyzed. Results for the sound pressure level will be compared with experimental data.

  5. Optimum design of brake friction material using hybrid entropy-GRA approach

    Directory of Open Access Journals (Sweden)

    Kumar Naresh

    2016-01-01

    Full Text Available The effect of Kevlar and natural fibres on the performance of brake friction materials was evaluated. Four friction material specimens were developed by varying the proportion of Kevlar and natural fibres. Two developed composite contained 5-10 wt.% of Kevlar fibre while in the other two the Kevlar fibre was replaced with same amount of natural fibre. SAE J661 protocol was used for the assessment of the tribological properties on a Chase testing machine. Result shows that the specimens containing Kevlar fibres shows higher friction and wear performance, whereas Kevlar replacement with natural fibre resulted in improved fade, recovery and friction fluctuations. Further hybrid entropy-GRA (grey relation analysis approach was applied to select the optimal friction materials using various performance defining attributes (PDA including friction, wear, fade, recovery, friction fluctuations and cost. The friction materials with 10 wt% of natural fibre exhibited the best overall quality.

  6. A Model Predictive Control Approach for Fuel Economy Improvement of a Series Hydraulic Hybrid Vehicle

    Directory of Open Access Journals (Sweden)

    Tri-Vien Vu

    2014-10-01

    Full Text Available This study applied a model predictive control (MPC framework to solve the cruising control problem of a series hydraulic hybrid vehicle (SHHV. The controller not only regulates vehicle velocity, but also engine torque, engine speed, and accumulator pressure to their corresponding reference values. At each time step, a quadratic programming problem is solved within a predictive horizon to obtain the optimal control inputs. The objective is to minimize the output error. This approach ensures that the components operate at high efficiency thereby improving the total efficiency of the system. The proposed SHHV control system was evaluated under urban and highway driving conditions. By handling constraints and input-output interactions, the MPC-based control system ensures that the system operates safely and efficiently. The fuel economy of the proposed control scheme shows a noticeable improvement in comparison with the PID-based system, in which three Proportional-Integral-Derivative (PID controllers are used for cruising control.

  7. A Hybrid dasymetric and machine learning approach to high-resolution residential electricity consumption modeling

    Energy Technology Data Exchange (ETDEWEB)

    Morton, April M [ORNL; Nagle, Nicholas N [ORNL; Piburn, Jesse O [ORNL; Stewart, Robert N [ORNL; McManamay, Ryan A [ORNL

    2017-01-01

    As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for detailed information regarding residential energy consumption patterns has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy consumption, the majority of techniques are highly dependent on region-specific data sources and often require building- or dwelling-level details that are not publicly available for many regions in the United States. Furthermore, many existing methods do not account for errors in input data sources and may not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more general hybrid approach to high-resolution residential electricity consumption modeling by merging a dasymetric model with a complementary machine learning algorithm. The method s flexible data requirement and statistical framework ensure that the model both is applicable to a wide range of regions and considers errors in input data sources.

  8. Dual-acting of Hybrid Compounds - A New Dawn in the Discovery of Multi-target Drugs: Lead Generation Approaches.

    Science.gov (United States)

    Abdolmaleki, Azizeh; Ghasemi, Jahan B

    2017-01-01

    Finding high quality beginning compounds is a critical job at the start of the lead generation stage for multi-target drug discovery (MTDD). Designing hybrid compounds as selective multitarget chemical entity is a challenge, opportunity, and new idea to better act against specific multiple targets. One hybrid molecule is formed by two (or more) pharmacophore group's participation. So, these new compounds often exhibit two or more activities going about as multi-target drugs (mtdrugs) and may have superior safety or efficacy. Application of integrating a range of information and sophisticated new in silico, bioinformatics, structural biology, pharmacogenomics methods may be useful to discover/design, and synthesis of the new hybrid molecules. In this regard, many rational and screening approaches have followed by medicinal chemists for the lead generation in MTDD. Here, we review some popular lead generation approaches that have been used for designing multiple ligands (DMLs). This paper focuses on dual- acting chemical entities that incorporate a part of two drugs or bioactive compounds to compose hybrid molecules. Also, it presents some of key concepts and limitations/strengths of lead generation methods by comparing combination framework method with screening approaches. Besides, a number of examples to represent applications of hybrid molecules in the drug discovery are included. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  9. Evaluation of wind power generation potential using a three hybrid approach for households in Ardebil Province, Iran

    International Nuclear Information System (INIS)

    Qolipour, Mojtaba; Mostafaeipour, Ali; Shamshirband, Shahaboddin; Alavi, Omid; Goudarzi, Hossein; Petković, Dalibor

    2016-01-01

    Highlights: • Technical–economic feasibility of small wind turbines for six areas in Ardabil province of Iran was investigated. • Hybrid approach of Data Envelopment Analysis, Balanced Scorecard, and Game Theory was analyzed. • HOMER software was used for economic evaluation. • Technical–economic feasibility was studied using wind speed data during 2008–2014. • The areas of Airport, Nir, Namin, BilaSavar, Firozabad and Ardabil were ranked from first to last, respectively. - Abstract: The objective of the present paper is to conduct a thorough technical–economic evaluation for the construction of small wind turbines in six areas within Ardabil province of Iran using the Hybrid Optimization of Multiple Energy Resources software, and also to rank these areas by a hybrid approach composed of Data Envelopment Analysis, Balanced Scorecard, and Game Theory methodologies. Higher accuracy of the proposed hybrid approach and its ability to properly detect the relationships between the decision-making components make it preferable over the simple Data Envelopment Analysis method. Technical–economic feasibility study is conducted by analyzing wind speed data for period from 2008 to 2014 using Hybrid Optimization of Multiple Energy Resources software. In the next step, the type of equipment used in the design, benefit, costs, total net costs, depreciation and amount of generated electricity are obtained separately for each location. The results show that; Airport, Nir, Namin, Bilasavar, Firozabad and Ardabil were rank first to last respectively.

  10. Improved Wetland Classification Using Eight-Band High Resolution Satellite Imagery and a Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Charles R. Lane

    2014-12-01

    Full Text Available Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of wetland maps derived with moderate resolution imagery and traditional techniques have been limited and often unsatisfactory. We explored and evaluated the utility of a newly launched high-resolution, eight-band satellite system (Worldview-2; WV2 for identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta of Lake Baikal, Russia, using a hybrid approach and a novel application of Indicator Species Analysis (ISA. We achieved an overall classification accuracy of 86.5% (Kappa coefficient: 0.85 for 22 classes of aquatic and wetland habitats and found that additional metrics, such as the Normalized Difference Vegetation Index and image texture, were valuable for improving the overall classification accuracy and particularly for discriminating among certain habitat classes. Our analysis demonstrated that including WV2’s four spectral bands from parts of the spectrum less commonly used in remote sensing analyses, along with the more traditional bandwidths, contributed to the increase in the overall classification accuracy by ~4% overall, but with considerable increases in our ability to discriminate certain communities. The coastal band improved differentiating open water and aquatic (i.e., vegetated habitats, and the yellow, red-edge, and near-infrared 2 bands improved discrimination among different vegetated aquatic and terrestrial habitats. The use of ISA provided statistical rigor in developing associations between spectral classes and field-based data. Our analyses demonstrated the utility of a hybrid approach and the benefit of additional bands and metrics in providing the first spatially explicit mapping of a large and heterogeneous wetland system.

  11. Andragogical Approach to the Quality and Effectiveness of Vocational Adults Training (A Retrospective Study [In Bulgarian

    Directory of Open Access Journals (Sweden)

    C. Katansky

    2009-06-01

    Full Text Available The article describes the basic results of a study dealing with the problem of quality and effectiveness of vocational training of adults in Bulgaria. Why is it retrospective? Because the subject of study is previous author’s andragogical investigations on the vocational qualification system, adults learners, training process and principals. The author uses the andragogigal methodology and results in order to develop a new approach to the problem and original definitions of vocational training quality and effectiveness.

  12. Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

    Science.gov (United States)

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

  13. A hybrid wavelet transform based short-term wind speed forecasting approach.

    Science.gov (United States)

    Wang, Jujie

    2014-01-01

    It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China's wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

  14. The effects of hybrid cycle training in inactive people with long-term spinal cord injury : design of a multicenter randomized controlled trial

    NARCIS (Netherlands)

    Bakkum, Arjan J. T.; de Groot, Sonja; van der Woude, Lucas H. V.; Janssen, Thomas W. J.

    2013-01-01

    Purpose: Physical activity in people with long-term spinal cord injury (SCI) is important to stay fit and healthy. The purpose of this study is to evaluate the effects of hybrid cycle training (hand cycling in combination with functional electrical stimulation-induced leg cycling) on fitness,

  15. Training and learning robotic surgery, time for a more structured approach: a systematic review

    NARCIS (Netherlands)

    Schreuder, H. W. R.; Wolswijk, R.; Zweemer, R. P.; Schijven, M. P.; Verheijen, R. H. M.

    2012-01-01

    Background Robotic assisted laparoscopic surgery is growing rapidly and there is an increasing need for a structured approach to train future robotic surgeons. Objectives To review the literature on training and learning strategies for robotic assisted laparoscopic surgery. Search strategy A

  16. Continuous Training and Wages: An Empirical Analysis Using a Comparison-Group Approach

    Science.gov (United States)

    Gorlitz, Katja

    2011-01-01

    Using German linked employer-employee data, this paper investigates the short-term impact of on-the-job training on wages. The applied estimation approach was first introduced by Leuven and Oosterbeek (2008). Wages of employees who intended to participate in training but did not do so because of a random event are compared to wages of training…

  17. Two Methods of Interpersonal Skills Training; Conceptual- versus Response-Oriented Approaches.

    Science.gov (United States)

    Bohart, Arthur C.; And Others

    1979-01-01

    Training people in warmth, empathy, and genuineness might fulfill a specific helping role and increase their general social comfort for others. By using conceptual and response-oriented approaches, authors show that training individuals to be effective counselors also helped them be more interpersonally effective. (Author/BEF)

  18. Perceptual Training Methods Compared: The Relative Efficacy of Different Approaches to Enhancing Sport-Specific Anticipation

    Science.gov (United States)

    Abernethy, Bruce; Schorer, Jorg; Jackson, Robin C.; Hagemann, Norbert

    2012-01-01

    The comparative efficacy of different perceptual training approaches for the improvement of anticipation was examined using a goalkeeping task from European handball that required the rapid prediction of shot direction. Novice participants (N = 60) were assigned equally to four different training groups and two different control groups (a placebo…

  19. An Evaluation System for Training Programs: A Case Study Using a Four-Phase Approach

    Science.gov (United States)

    Lingham, Tony; Richley, Bonnie; Rezania, Davar

    2006-01-01

    Purpose: With the increased importance of training in organizations, creating important and meaningful programs are critical to an organization and its members. The purpose of this paper is to suggest a four-phase systematic approach to designing and evaluating training programs that promotes collaboration between organizational leaders, trainers,…

  20. The Learning Transfer Approach To Estimating the Benefits of Training: Empirical Evidence.

    Science.gov (United States)

    Donovan, Paul; Hannigan, Kevin; Crowe, Deirdre

    2001-01-01

    The Learning Transfer Systems Inventory provides a systematic approach for predicting training effectiveness through needs assessment, organizational analysis to determine issues affecting training outcomes, and assessment of needed resources. Data from 158 management trainers demonstrated its effectiveness in assessing how well an organization…

  1. A data fusion approach for track monitoring from multiple in-service trains

    Science.gov (United States)

    Lederman, George; Chen, Siheng; Garrett, James H.; Kovačević, Jelena; Noh, Hae Young; Bielak, Jacobo

    2017-10-01

    We present a data fusion approach for enabling data-driven rail-infrastructure monitoring from multiple in-service trains. A number of researchers have proposed using vibration data collected from in-service trains as a low-cost method to monitor track geometry. The majority of this work has focused on developing novel features to extract information about the tracks from data produced by individual sensors on individual trains. We extend this work by presenting a technique to combine extracted features from multiple passes over the tracks from multiple sensors aboard multiple vehicles. There are a number of challenges in combining multiple data sources, like different relative position coordinates depending on the location of the sensor within the train. Furthermore, as the number of sensors increases, the likelihood that some will malfunction also increases. We use a two-step approach that first minimizes position offset errors through data alignment, then fuses the data with a novel adaptive Kalman filter that weights data according to its estimated reliability. We show the efficacy of this approach both through simulations and on a data-set collected from two instrumented trains operating over a one-year period. Combining data from numerous in-service trains allows for more continuous and more reliable data-driven monitoring than analyzing data from any one train alone; as the number of instrumented trains increases, the proposed fusion approach could facilitate track monitoring of entire rail-networks.

  2. A 3D visualization approach for process training in office environments

    NARCIS (Netherlands)

    Aysolmaz, Banu; Brown, Ross; Bruza, Peter; Reijers, Hajo A.

    2016-01-01

    Process participants need to learn how to perform in the context of their business processes. Process training is challenging due to cognitive difficulties in relating process model elements to real world concepts. In this paper we present a 3D VirtualWorld (VW) process training approach for office

  3. Approaches to, and perceived benefits of, training in the secondary wood industry

    Science.gov (United States)

    Matthew S. Bumgardner; Urs Buehlmann; Albert T. Schuler; Brooke Baldwin Wisdom; Brooke Baldwin Wisdom

    2005-01-01

    Practitioners and researchers alike have noted that a well-trained workforce is an important component of the competitiveness of U.S. manufacturers in the global economy. This study compares four secondary wood industry sectors on their approaches to, and perceived benefits of, training production employees. The study was based on an Internet survey in the autumn of...

  4. Comparison of Two Music Training Approaches on Music and Speech Perception in Cochlear Implant Users

    NARCIS (Netherlands)

    Fuller, Christina D; Galvin, John J; Maat, Bert; Başkent, Deniz; Free, Rolien H

    2018-01-01

    In normal-hearing (NH) adults, long-term music training may benefit music and speech perception, even when listening to spectro-temporally degraded signals as experienced by cochlear implant (CI) users. In this study, we compared two different music training approaches in CI users and their effects

  5. Innovative Approach to the Organization of Future Social Workers' Practical Training: Foreign Experience

    Science.gov (United States)

    Polishchuk, Vira; Slozanska, Hanna

    2014-01-01

    Innovative approaches to practical training of future social workers in higher educational establishments have been defined. Peculiarities of foreign experience of social workers' practical training in higher educational establishments have been analyzed. Experience of organizing practice for bachelor students studying at "Social Work"…

  6. Systematic Approach to Training for System Engineers in Nuclear Power Plants

    International Nuclear Information System (INIS)

    Kwak, Jeong-keun

    2015-01-01

    In my paper, comprehensive preparations, tangible applications, and final establishments of training for system engineers are described using practical materials in KHNP. The purpose of this paper is to formulate SAT based training in KHNP, especially for system engineers. Hence, to achieve this goal, over one year study was performed considering voluminous materials and working experiences. Through the process, SAT based training package for system engineers was finished, in the end. In terms of training in NPPs, SAT methodology is the unwavering trend in South Korea since NPPs export to UAE. Therefore, materialization of SAT based training for system engineers from the origin of SAT to the finalization of SAT should not be overlooked. A variety of accident preventive approaches have been adopted since the first commercial NPP operation in Calder Hall, United Kingdom. Among diverse event preventive ways, training has played an important role for the improvement of NPPs reliability and safety. This is reason why nuclear industry in every country has established and maintained own training institutes and methods. Since the Three Mile Island (TMI) accident, United States Nuclear Regulatory Commission (USNRC) recommended many betterment plans to US nuclear industry for the elevation of NPPs safety. In the suggested considerations, systematic approach to training, so called SAT appeared in the world. Basically, SAT is composed of five stages, what is called ADDIE. Hence, through ADDIE process, holistic and trustworthy training could be realized in the actual NPPs operation and maintenance. For this reason, SAT is the representative training methodology in the US nuclear business

  7. Systematic Approach to Training for System Engineers in Nuclear Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    Kwak, Jeong-keun [Korea Hydro and Nuclear Power Co., Ulsan (Korea, Republic of)

    2015-10-15

    In my paper, comprehensive preparations, tangible applications, and final establishments of training for system engineers are described using practical materials in KHNP. The purpose of this paper is to formulate SAT based training in KHNP, especially for system engineers. Hence, to achieve this goal, over one year study was performed considering voluminous materials and working experiences. Through the process, SAT based training package for system engineers was finished, in the end. In terms of training in NPPs, SAT methodology is the unwavering trend in South Korea since NPPs export to UAE. Therefore, materialization of SAT based training for system engineers from the origin of SAT to the finalization of SAT should not be overlooked. A variety of accident preventive approaches have been adopted since the first commercial NPP operation in Calder Hall, United Kingdom. Among diverse event preventive ways, training has played an important role for the improvement of NPPs reliability and safety. This is reason why nuclear industry in every country has established and maintained own training institutes and methods. Since the Three Mile Island (TMI) accident, United States Nuclear Regulatory Commission (USNRC) recommended many betterment plans to US nuclear industry for the elevation of NPPs safety. In the suggested considerations, systematic approach to training, so called SAT appeared in the world. Basically, SAT is composed of five stages, what is called ADDIE. Hence, through ADDIE process, holistic and trustworthy training could be realized in the actual NPPs operation and maintenance. For this reason, SAT is the representative training methodology in the US nuclear business.

  8. Sail training: an innovative approach to graduate nurse preceptor development.

    Science.gov (United States)

    Nicol, Pam; Young, Melisa

    2007-01-01

    A 1-day sail-training program that aims to increase graduate nurse preceptor skills was evaluated. Preliminary results suggest that this experiential learning is an effective way to develop graduate nurse preceptors. Awareness of graduate nurses' needs has been heightened, and skills in clinical teaching have been developed. It is indicated from the limited results that the outcomes are sustained over time, but further evaluation is needed.

  9. Infrared exploration of the architectural heritage: from passive infrared thermography to hybrid infrared thermography (HIRT approach

    Directory of Open Access Journals (Sweden)

    Sfarra, S.

    2016-09-01

    Full Text Available Up to now, infrared thermographic approaches have been considered either passive or active. In the latter case, the heat flux is historically attributed to a non-natural heat source. The use of the sun has recently been incorporated into the active approach thanks to multi-temporal inspections. In this paper, an innovative hybrid thermographic (HIRT approach is illustrated. It combines both the time component and the solar source to obtain quantitative information such as the defect depth. Thermograms were obtained by inspecting the facade of the Santa Maria Collemaggio church (L’Aquila, Italy, whereas quantitative results related to the sub-superficial discontinuities were obtained thanks to the use of advanced techniques. Experimental results linked to passive approach (i.e., the mosaicking procedure of the thermograms performed by selecting a set of historic churches are also included in order to explain, when and where, the hybrid procedure should be used.Hasta la fecha, los enfoques sobre la termografía infrarroja han sido considerados, o pasivos, o activos. En este último caso, el flujo de calor se obtiene a través de una fuente de calor no natural. El uso de energía solar ha sido recientemente incorporado al enfoque activo gracias a los estudios multitemporales. En este trabajo, se ilustra un enfoque innovador de la termografía híbrida (HIRT. Se combina tanto el componente de tiempo y la fuente de energía solar para recuperar la información cuantitativa así como la profundidad del defecto. Las imágenes térmicas se obtuvieron mediante el análisis de la fachada de la Iglesia de Santa María Collemaggio (L’Aquila, Italia, mientras que los resultados cuantitativos inherentes a las discontinuidades sub-superficiales se obtuvieron gracias al uso de otras técnicas avanzadas. Los resultados experimentales vinculados al enfoque pasivo (es decir, el proceso de mosaico de las imágenes térmicas derivan de un conjunto de Iglesias

  10. EMuRgency - New approaches for resuscitation support and training in the Euregio Meuse-Rhine

    NARCIS (Netherlands)

    Kalz, Marco; Skorning, Max; Haberstroh, Max; Gorgels, Ton; Klerkx, Joris; Vergnion, Michel; Van Poucke, Sven; Lenssen, Niklas; Biermann, Henning; Schuffelen, Petra; Pijls, Ruud; Ternier, Stefaan; De Vries, Fred; Van der Baaren, John; Parra, Gonzalo; Specht, Marcus

    2012-01-01

    Kalz, M., Skorning, M., Haberstroh, M., Gorgels, T., Klerkx, J., Vergnion, M., ...Specht, M. (2012). EMuRgency – New approaches for resuscitation support and training in the Euregio Meuse-Rhine. Resuscitation, 83 (S1). e37.

  11. Incorporating historical information in biosimilar trials: Challenges and a hybrid Bayesian-frequentist approach.

    Science.gov (United States)

    Mielke, Johanna; Schmidli, Heinz; Jones, Byron

    2018-05-01

    For the approval of biosimilars, it is, in most cases, necessary to conduct large Phase III clinical trials in patients to convince the regulatory authorities that the product is comparable in terms of efficacy and safety to the originator product. As the originator product has already been studied in several trials beforehand, it seems natural to include this historical information into the showing of equivalent efficacy. Since all studies for the regulatory approval of biosimilars are confirmatory studies, it is required that the statistical approach has reasonable frequentist properties, most importantly, that the Type I error rate is controlled-at least in all scenarios that are realistic in practice. However, it is well known that the incorporation of historical information can lead to an inflation of the Type I error rate in the case of a conflict between the distribution of the historical data and the distribution of the trial data. We illustrate this issue and confirm, using the Bayesian robustified meta-analytic-predictive (MAP) approach as an example, that simultaneously controlling the Type I error rate over the complete parameter space and gaining power in comparison to a standard frequentist approach that only considers the data in the new study, is not possible. We propose a hybrid Bayesian-frequentist approach for binary endpoints that controls the Type I error rate in the neighborhood of the center of the prior distribution, while improving the power. We study the properties of this approach in an extensive simulation study and provide a real-world example. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Cognitive Effects of Mindfulness Training: Results of a Pilot Study Based on a Theory Driven Approach

    OpenAIRE

    Wimmer, Lena; Bellingrath, Silja; von Stockhausen, Lisa

    2016-01-01

    The present paper reports a pilot study which tested cognitive effects of mindfulness practice in a theory-driven approach. Thirty-four fifth graders received either a mindfulness training which was based on the mindfulness-based stress reduction approach (experimental group), a concentration training (active control group), or no treatment (passive control group). Based on the operational definition of mindfulness by Bishop et al. (2004), effects on sustained attention, cognitive flexibility...

  13. A hybrid life cycle and multi-criteria decision analysis approach for identifying sustainable development strategies of Beijing's taxi fleet

    International Nuclear Information System (INIS)

    Cai, Yanpeng; Applegate, Scott; Yue, Wencong; Cai, Jianying; Wang, Xuan; Liu, Gengyuan; Li, Chunhui

    2017-01-01

    To identify and evaluate sustainable strategies of taxi fleet in Beijing in terms of economic, policy, and environmental implications, a hybrid approach was developed through incorporating multi-criteria decision analysis (MCDA) methods within a general life-cycle analysis (LCA) framework. The approach can (a) help comprehensive evaluate environmental impacts of multiple types of vehicles, (b) facilitate analysis of environmental, economic and policy features of such vehicles, and (c) identify desirable taxi fleet development strategies for the city. The developed approach represented an improvement of the decision-making capability for taxi implementation based on multiple available technologies and their performance that can be specifically tailored to Beijing. The results demonstrated that the proposed approach could comprehensively reflect multiple implications of strategies for the taxi fleet in Beijing to reduce air pollution in the city. The results also indicated that the electric vehicle powered with the year 2020 electricity projections would be the ideal solution, outranking the other alternatives. The conventional vehicle ranked the lowest among the alternatives. The plug-in hybrid vehicle powered by 2020 electricity projects ranked the third, followed by the plug-in hybrid vehicle ranking the fourth, and the hybrid vehicle ranking the fifth. - Highlights: • An hybrid approach was proposed for evaluating sustainable strategies of Beijing's taxi fleet. • This approach was based on the combination of multi-criteria decision analysis methods and life-cycle assessment. • Environmental, economic and policy performances of multiple strategies were compared. • Detailed responses of taxi drivers and local residents were interviewed. • The electric vehicle would be the ideal solution for Beijing Taxi fleet.

  14. The Systematic Approach to Training: Analysis and Evaluation in the Department of Safeguards

    International Nuclear Information System (INIS)

    Ticevic, S.; Weichselbraun, A.; Pickett, S.; Crete, J.-M.

    2015-01-01

    In applying a systematic approach to training (SAT), identifying the learning needs is the first step - a learning needs analysis allows the organization to identify the competencies required to perform a particular job. A systematic approach can provide a clear structure for training and education programme development as well as the necessary evaluation and feedback so that the organization can adjust the development accordingly and deliver the optimal learning experience. In this presentation we will describes two key elements of a SAT used in the Safeguards Training Section in the Department of Safeguards: Analysis and Evaluation. Analysis is the first part of a SAT needed to define competencies for Safeguards staff in order to improve training development within the Department. We describe the training needs analysis used to capture and articulate the various competencies required for safeguards implementation based upon an analysis of tasks and activities carried out by staff members in the Department. Firstly, we highlight the different qualitative methods used to gather information from staff and the process of evaluating and organizing this information into a structured framework. Secondly, we describe how this framework provides the necessary reference to specify learning objectives, evaluate training effectiveness, review and revise training offerings, and select appropriate training paths based on identified needs. In addition, as part of the SAT, evaluation is performed to identify the usefulness of course outcomes and improvements for future offerings based on lessons learned, to ensure that appropriate knowledge and skills are being taught and to demonstrate the value of training by meeting the organization's needs. We present how the Kirkpatrick four-level evaluation model has been implemented by Safeguards Training Section in order to evaluate course effectiveness after the training has been completed, and discuss how the current evaluation

  15. Local vascular adaptations after hybrid training in spinal cord-injured subjects.

    NARCIS (Netherlands)

    Thijssen, D.H.J.; Heesterbeek, P.J.C.; Kuppevelt, D. van; Duysens, J.E.J.; Hopman, M.T.E.

    2005-01-01

    PURPOSE: Studies investigating vascular adaptations in non-exercised areas during whole body exercise training show conflicting results. Individuals with spinal cord injury (SCI) provide a unique model to examine vascular adaptations in active tissue vs adjacent inactive areas. The purpose of this

  16. Hybrid Air Quality Modeling Approach for use in the Hear-road Exposures to Urban air pollutant Study(NEXUS)

    Science.gov (United States)

    The paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associa...

  17. A hybrid regional approach to model discharge at multiple sub-basins within the Calapooia Watershed, Oregon, USA

    Science.gov (United States)

    Modeling is a useful tool for quantifying ecosystem services and understanding their temporal dynamics. Here we describe a hybrid regional modeling approach for sub-basins of the Calapooia watershed that incorporates both a precipitation-runoff model and an indexed regression mo...

  18. Comparing Hybrid Learning with Traditional Approaches on Learning the Microsoft Office Power Point 2003 Program in Tertiary Education

    Science.gov (United States)

    Vernadakis, Nikolaos; Antoniou, Panagiotis; Giannousi, Maria; Zetou, Eleni; Kioumourtzoglou, Efthimis

    2011-01-01

    The purpose of this study was to determine the effectiveness of a hybrid learning approach to deliver a computer science course concerning the Microsoft office PowerPoint 2003 program in comparison to delivering the same course content in the form of traditional lectures. A hundred and seventy-two first year university students were randomly…

  19. Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

    DEFF Research Database (Denmark)

    Shuai, Hang; Ai, Xiaomeng; Wen, Jinyu

    2017-01-01

    This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future...

  20. Optimization of Hybrid Power Trains by Mechanistic System Simulations Optimisation de groupes motopropulseurs électriques hybrides par simulation du système mécanique

    Directory of Open Access Journals (Sweden)

    Katrašnik T.

    2013-05-01

    Full Text Available The paper presents a mechanistic system level simulation model for mode/big hybrid and conventional vehicle topologies. The paper addresses the Dynamic interaction between different domains: internal combustion engine. exhaust after treatment devices, electric components. mechanical drive train. cooling circuit system and corresponding control units. To achieve a good ratio between accuracy. predictability and computational speed of the model an innovative time domain decoupling is presented, which is based on applying domain specific integration steps to ditferent domains and subsequent consistent cross-domain coupling ol’thefluxes. In addition, a computationally efficient frunieveork for transporting active and passive gaseous species is introduced to combine computational efficiency with the need for modeling pollutant transport in the gas path. The applicability and versatility of the mechanistic system level simulations model is presented through analyses of transient phenomena caused by the high interdependency of the sub-systems, i.e. domains. Results of a hyt’hrid vehicle are compared to results of a conventional vehicle to highlight differences in operating regimes of partiular components that are inherent to particular poster train topology. L’article présente un modèle de simulation au niveau mécanique destiné à la modélisation de topologies de véhicules hydrides et conventionnels. L’article décrit l’interaction dynamique entre différents domaines : moteur à combustion interne, dispositifs de post-traitement d’échappement, composants électriques, chaîne cinématique mécanique, circuit de refroidissement et les unités de contrôle correspondantes. Afin d’obtenir un rapport correct entre précision, prévisibilité et vitesse de calculs du modèle, un découplage innovant du domaine temporel est présenté, lequel est basé sur l’application à différents domaines, d’étapes d’intégration sp

  1. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.

    Science.gov (United States)

    Murat, Miraemiliana; Chang, Siow-Wee; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

    2017-01-01

    Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99

  2. Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

    Science.gov (United States)

    Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.

    2017-11-01

    The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general

  3. METHODICAL APPROACH TO DEFINING INFRASTRUCTURE COMPONENT OF THE COSTS FOR THE PARTICULAR PASSENGER TRAIN TRAFFIC

    Directory of Open Access Journals (Sweden)

    Yu. S. Barash

    2015-06-01

    Full Text Available Purpose. In the scientific paper a methodical approach concerning determining the infrastructure component of the costs for traffic of the particular passenger train should be developed. It takes into account the individual characteristics of the particular train traffic. Methodology. To achieve the research purposes was used a method which is based on apportionment of expenses for the traffic of a particular passenger train taking into account the factors affecting the magnitude of costs. This methodology allows allocating properly infrastructure costs for a particular train and, consequently, to determine the accurate profitability of each train. Findings. All expenditures relating to passenger traffic of a long distance were allocated from first cost of passenger and freight traffic. These costs are divided into four components. Three groups of expenses were allocated in infrastructure component, which are calculated according to the certain principle taking into account the individual characteristics of the particular train traffic. Originality. The allocation method of all passenger transportation costs of all Ukrzaliznytsia departments for a particular passenger train was improved. It is based on principles of general indicators formation of each department costs, which correspond to the main influential factors of operating trains. The methodical approach to determining the cost of infrastructure component is improved, which takes into account the effect of the speed and weight of a passenger train on the wear of the railway track superstructure and contact network. All this allows allocating to reasonably the costs of particular passenger train traffic and to determine its profitability. Practical value. Implementing these methods allows calculating the real, economically justified costs of a particular train that will correctly determine the profitability of a particular passenger train and on this basis it allows to make management

  4. ENEN's approaches and initiatives for nuclear education and training

    International Nuclear Information System (INIS)

    Safieh, Joseph; De Regge, Peter; Kusumi, Ryoko

    2011-01-01

    The European Nuclear Education Network (ENEN), established in 2003 through the EU Fifth Framework Programme (FP) project, was given a more permanent character by the foundation of the ENEN Association, a legal nonprofit-making body pursuing an instructive and scientific aim. Its main objective is the preservation and further development of expertise in the nuclear fields by higher education and training. This objective is realized through the cooperation between EU universities involved in education and research in nuclear disciplines, nuclear research centers and the nuclear industry. As of May 2009, the ENEN has 47 members in 17 EU countries. Since 2007 the ENEN Association has concluded a Memorandum of Understanding (MoU) with partners beyond Europe for further cooperation, such as South Africa, Russian Federation and Japan. The ENEN has good collaboration with national networks and international organizations, like Belgian Nuclear Education Network (BNEN) and the International Atomic Energy Agency (IAEA). The ENEN has provided support to its Members for the organization of and participation to selected E and T courses in nuclear fields. Based on the mutual recognition of those courses, the ENEN developed a reference curriculum in nuclear engineering, consisting of a core package of courses and optional substitute courses in nuclear disciplines, to be realized as the European Master of Science in Nuclear Engineering (EMSNE). From the experience gained through the EMSNE, a European Master of Science in Nuclear Disciplines will be delivered in the near future, extending ENEN's certification to other disciplines such as radiation protection and waste management and disposal. The ENEN-II Coordination Action consolidated and expanded the achievements of the ENEN and the NEPTUNO projects attained by the ENEN in respectively the 5th and 6th Framework Programmes. The objective of the ENEN-II project was to develop the ENEN Association in a sustainable way in the areas

  5. Ecosystem Approaches to Human Health Graduate Training Awards ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    IDRC's Ecosystem Approaches to Human Health (Ecohealth) program initiative ... Each grant will consist of CA $15 000 for field research and up to CA $4 000 for ... Nutrition, health policy, and ethics in the age of public-private partnerships.

  6. A hybrid deterministic-probabilistic approach to model the mechanical response of helically arranged hierarchical strands

    Science.gov (United States)

    Fraldi, M.; Perrella, G.; Ciervo, M.; Bosia, F.; Pugno, N. M.

    2017-09-01

    Very recently, a Weibull-based probabilistic strategy has been successfully applied to bundles of wires to determine their overall stress-strain behaviour, also capturing previously unpredicted nonlinear and post-elastic features of hierarchical strands. This approach is based on the so-called "Equal Load Sharing (ELS)" hypothesis by virtue of which, when a wire breaks, the load acting on the strand is homogeneously redistributed among the surviving wires. Despite the overall effectiveness of the method, some discrepancies between theoretical predictions and in silico Finite Element-based simulations or experimental findings might arise when more complex structures are analysed, e.g. helically arranged bundles. To overcome these limitations, an enhanced hybrid approach is proposed in which the probability of rupture is combined with a deterministic mechanical model of a strand constituted by helically-arranged and hierarchically-organized wires. The analytical model is validated comparing its predictions with both Finite Element simulations and experimental tests. The results show that generalized stress-strain responses - incorporating tension/torsion coupling - are naturally found and, once one or more elements break, the competition between geometry and mechanics of the strand microstructure, i.e. the different cross sections and helical angles of the wires in the different hierarchical levels of the strand, determines the no longer homogeneous stress redistribution among the surviving wires whose fate is hence governed by a "Hierarchical Load Sharing" criterion.

  7. A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings.

    Science.gov (United States)

    Liu, Jie; Hu, Youmin; Wu, Bo; Wang, Yan; Xie, Fengyun

    2017-05-18

    The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD). Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features' information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components.

  8. A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings

    Directory of Open Access Journals (Sweden)

    Jie Liu

    2017-05-01

    Full Text Available The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD. Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features’ information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components.

  9. A hybrid modelling approach to develop scenarios for China's carbon dioxide emissions to 2050

    International Nuclear Information System (INIS)

    Gambhir, Ajay; Schulz, Niels; Napp, Tamaryn; Tong, Danlu; Munuera, Luis; Faist, Mark; Riahi, Keywan

    2013-01-01

    This paper describes a hybrid modelling approach to assess the future development of China's energy system, for both a “hypothetical counterfactual baseline” (HCB) scenario and low carbon (“abatement”) scenarios. The approach combines a technology-rich integrated assessment model (MESSAGE) of China's energy system with a set of sector-specific, bottom-up, energy demand models for the transport, buildings and industrial sectors developed by the Grantham Institute for Climate Change at Imperial College London. By exploring technology-specific solutions in all major sectors of the Chinese economy, we find that a combination of measures, underpinned by low-carbon power options based on a mix of renewables, nuclear and carbon capture and storage, would fundamentally transform the Chinese energy system, when combined with increasing electrification of demand-side sectors. Energy efficiency options in these demand sectors are also important. - Highlights: • Combining energy supply and demand models reveals low-carbon technology choices across China's economy. • China could reduce its CO 2 emissions to close to 3 Gt in 2050, costing around 2% of GDP. • Decarbonising the power sector underpins the energy system transformation. • Electrification of industrial processes, building heating and transport is required. • Energy efficiency across the demand side is also important

  10. A Two-Step Hybrid Approach for Modeling the Nonlinear Dynamic Response of Piezoelectric Energy Harvesters

    Directory of Open Access Journals (Sweden)

    Claudio Maruccio

    2018-01-01

    Full Text Available An effective hybrid computational framework is described here in order to assess the nonlinear dynamic response of piezoelectric energy harvesting devices. The proposed strategy basically consists of two steps. First, fully coupled multiphysics finite element (FE analyses are performed to evaluate the nonlinear static response of the device. An enhanced reduced-order model is then derived, where the global dynamic response is formulated in the state-space using lumped coefficients enriched with the information derived from the FE simulations. The electromechanical response of piezoelectric beams under forced vibrations is studied by means of the proposed approach, which is also validated by comparing numerical predictions with some experimental results. Such numerical and experimental investigations have been carried out with the main aim of studying the influence of material and geometrical parameters on the global nonlinear response. The advantage of the presented approach is that the overall computational and experimental efforts are significantly reduced while preserving a satisfactory accuracy in the assessment of the global behavior.

  11. Multimodal Logistics Network Design over Planning Horizon through a Hybrid Meta-Heuristic Approach

    Science.gov (United States)

    Shimizu, Yoshiaki; Yamazaki, Yoshihiro; Wada, Takeshi

    Logistics has been acknowledged increasingly as a key issue of supply chain management to improve business efficiency under global competition and diversified customer demands. This study aims at improving a quality of strategic decision making associated with dynamic natures in logistics network optimization. Especially, noticing an importance to concern with a multimodal logistics under multiterms, we have extended a previous approach termed hybrid tabu search (HybTS). The attempt intends to deploy a strategic planning more concretely so that the strategic plan can link to an operational decision making. The idea refers to a smart extension of the HybTS to solve a dynamic mixed integer programming problem. It is a two-level iterative method composed of a sophisticated tabu search for the location problem at the upper level and a graph algorithm for the route selection at the lower level. To keep efficiency while coping with the resulting extremely large-scale problem, we invented a systematic procedure to transform the original linear program at the lower-level into a minimum cost flow problem solvable by the graph algorithm. Through numerical experiments, we verified the proposed method outperformed the commercial software. The results indicate the proposed approach can make the conventional strategic decision much more practical and is promising for real world applications.

  12. Covercrete with hybrid functions - A novel approach to durable reinforced concrete structures

    Energy Technology Data Exchange (ETDEWEB)

    Tang, L.; Zhang, E.Q. [Chalmers University of Technology, SE-412 96 Gothenburg (Sweden); Fu, Y. [KTH Royal Institute of Technology, SE-106 91 Stockholm (Sweden); Schouenborg, B.; Lindqvist, J.E. [CBI Swedish Cement and Concrete Research Institute, c/o SP, Box 857, SE-501 15 Boraas (Sweden)

    2012-12-15

    Due to the corrosion of steel in reinforced concrete structures, the concrete with low water-cement ratio (w/c), high cement content, and large cover thickness is conventionally used for prolonging the passivation period of steel. Obviously, this conventional approach to durable concrete structures is at the sacrifice of more CO{sub 2} emission and natural resources through consuming higher amount of cement and more constituent materials, which is against sustainability. By placing an economically affordable conductive mesh made of carbon fiber or conductive polymer fiber in the near surface zone of concrete acting as anode we can build up a cathodic prevention system with intermittent low current density supplied by, e.g., the solar cells. In such a way, the aggressive negative ions such as Cl{sup -}, CO{sub 3}{sup 2-}, and SO{sub 4}{sup 2-} can be stopped near the cathodic (steel) zone. Thus the reinforcement steel is prevented from corrosion even in the concrete with relatively high w/c and small cover thickness. This conductive mesh functions not only as electrode, but also as surface reinforcement to prevent concrete surface from cracking. Therefore, this new type of covercrete has hybrid functions. This paper presents the theoretical analysis of feasibility of this approach and discusses the potential durability problems and possible solutions to the potential problems. (Copyright copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  13. A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

    Science.gov (United States)

    Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

    2015-06-01

    The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

  14. Developing hybrid approaches to predict pKa values of ionizable groups

    Science.gov (United States)

    Witham, Shawn; Talley, Kemper; Wang, Lin; Zhang, Zhe; Sarkar, Subhra; Gao, Daquan; Yang, Wei

    2011-01-01

    Accurate predictions of pKa values of titratable groups require taking into account all relevant processes associated with the ionization/deionization. Frequently, however, the ionization does not involve significant structural changes and the dominating effects are purely electrostatic in origin allowing accurate predictions to be made based on the electrostatic energy difference between ionized and neutral forms alone using a static structure. On another hand, if the change of the charge state is accompanied by a structural reorganization of the target protein, then the relevant conformational changes have to be taken into account in the pKa calculations. Here we report a hybrid approach that first predicts the titratable groups, which ionization is expected to cause conformational changes, termed “problematic” residues, then applies a special protocol on them, while the rest of the pKa’s are predicted with rigid backbone approach as implemented in multi-conformation continuum electrostatics (MCCE) method. The backbone representative conformations for “problematic” groups are generated with either molecular dynamics simulations with charged and uncharged amino acid or with ab-initio local segment modeling. The corresponding ensembles are then used to calculate the pKa of the “problematic” residues and then the results are averaged. PMID:21744395

  15. Hybrid approaches to clinical trial monitoring: Practical alternatives to 100% source data verification

    Directory of Open Access Journals (Sweden)

    Sourabh De

    2011-01-01

    Full Text Available For years, a vast majority of clinical trial industry has followed the tenet of 100% source data verification (SDV. This has been driven partly by the overcautious approach to linking quality of data to the extent of monitoring and SDV and partly by being on the safer side of regulations. The regulations however, do not state any upper or lower limits of SDV. What it expects from researchers and the sponsors is methodologies which ensure data quality. How the industry does it is open to innovation and application of statistical methods, targeted and remote monitoring, real time reporting, adaptive monitoring schedules, etc. In short, hybrid approaches to monitoring. Coupled with concepts of optimum monitoring and SDV at site and off-site monitoring techniques, it should be possible to save time required to conduct SDV leading to more available time for other productive activities. Organizations stand to gain directly or indirectly from such savings, whether by diverting the funds back to the R&D pipeline; investing more in technology infrastructure to support large trials; or simply increasing sample size of trials. Whether it also affects the work-life balance of monitors who may then need to travel with a less hectic schedule for the same level of quality and productivity can be predicted only when there is more evidence from field.

  16. Hybrid approaches to clinical trial monitoring: Practical alternatives to 100% source data verification.

    Science.gov (United States)

    De, Sourabh

    2011-07-01

    For years, a vast majority of clinical trial industry has followed the tenet of 100% source data verification (SDV). This has been driven partly by the overcautious approach to linking quality of data to the extent of monitoring and SDV and partly by being on the safer side of regulations. The regulations however, do not state any upper or lower limits of SDV. What it expects from researchers and the sponsors is methodologies which ensure data quality. How the industry does it is open to innovation and application of statistical methods, targeted and remote monitoring, real time reporting, adaptive monitoring schedules, etc. In short, hybrid approaches to monitoring. Coupled with concepts of optimum monitoring and SDV at site and off-site monitoring techniques, it should be possible to save time required to conduct SDV leading to more available time for other productive activities. Organizations stand to gain directly or indirectly from such savings, whether by diverting the funds back to the R&D pipeline; investing more in technology infrastructure to support large trials; or simply increasing sample size of trials. Whether it also affects the work-life balance of monitors who may then need to travel with a less hectic schedule for the same level of quality and productivity can be predicted only when there is more evidence from field.

  17. A New Hybrid Approach for Augmented Reality Maintenance in Scientific Facilities

    Directory of Open Access Journals (Sweden)

    Héctor Martínez

    2013-09-01

    Full Text Available Maintenance in scientific facilities is a difficult issue, especially in large and hazardous facilities, due to the complexity of tasks and equipment. Augmented reality is a technology that has already shown great promise in the maintenance field. With the help of augmented reality applications, maintenance tasks can be carried out faster and more safely. The problem with current applications is that they are small-scale prototypes that do not easily scale to large facility maintenance applications. This paper presents a new hybrid approach that enables the creation of augmented reality maintenance applications for large and hazardous scientific facilities. In this paper, a new augmented reality marker and the algorithm for its recognition is proposed. The performance of the algorithm is verified in three test cases, showing promising results in two of them. Improvements in robustness in the third test case in which the camera is moving quickly or when light conditions are extreme are subject to further studies. The proposed new approach will be integrated into an existing augmented reality maintenance system.

  18. Higher specialty training in genitourinary medicine: A curriculum competencies-based approach.

    Science.gov (United States)

    Desai, Mitesh; Davies, Olubanke; Menon-Johansson, Anatole; Sethi, Gulshan Cindy

    2018-01-01

    Specialty trainees in genitourinary medicine (GUM) are required to attain competencies described in the GUM higher specialty training curriculum by the end of their training, but learning opportunities available may conflict with service delivery needs. In response to poor feedback on trainee satisfaction surveys, a four-year modular training programme was developed to achieve a curriculum competencies-based approach to training. We evaluated the clinical opportunities of the new programme to determine: (1) Whether opportunity cost of training to service delivery is justifiable; (2) Which competencies are inadequately addressed by direct clinical opportunities alone and (3) Trainee satisfaction. Local faculty and trainees assessed the 'usefulness' of the new modular programme to meet each curriculum competence. The annual General Medical Council (GMC) national training survey assessed trainee satisfaction. The clinical opportunities provided by the modular training programme were sufficiently useful for attaining many competencies. Trainee satisfaction as captured by the GMC survey improved from two reds pre- to nine greens post-intervention on a background of rising clinical activity in the department. The curriculum competencies-based approach to training offers an objective way to balance training with service provision and led to an improvement in GMC survey satisfaction.

  19. Analyzing Hollywood’s Animations Movies with Training Approach

    Directory of Open Access Journals (Sweden)

    H. Bashir

    2017-03-01

    Full Text Available Today, one of the most influential and popular media production in the world in terms of the impact on education and training of children and adolescents, is animation movies especially those that are made in Hollywood. Since these 3D Animation movies have been created, these kind of products have been changed considerably and concepts of them have promoted significantly. Due to this, in this research, using qualitative content analysis, the content of these types of animations have been studied. In this study, six animation movies "Ice Age", "Kung Fu Panda", "Frozen", "Brave", "Ratatouille" and "Everyone’s Hero," are analyzed and in the end Codes and then themes of each of them are extracted. Finally, themes categorized into concepts that result in extracted 26 concepts which training effects of these concepts have been studied in three levels. Some of more important of main concepts in findings are relativity of values, desacralizing, emphasizing on the importance of family, the necessity of believing in something that needs to be done, and so on. Eventually impacts of different levels’ concepts have been studied and compared from positive and negative impacts and then theoretical and practical aspects.

  20. River flow prediction using hybrid models of support vector regression with the wavelet transform, singular spectrum analysis and chaotic approach

    Science.gov (United States)

    Baydaroğlu, Özlem; Koçak, Kasım; Duran, Kemal

    2018-06-01

    Prediction of water amount that will enter the reservoirs in the following month is of vital importance especially for semi-arid countries like Turkey. Climate projections emphasize that water scarcity will be one of the serious problems in the future. This study presents a methodology for predicting river flow for the subsequent month based on the time series of observed monthly river flow with hybrid models of support vector regression (SVR). Monthly river flow over the period 1940-2012 observed for the Kızılırmak River in Turkey has been used for training the method, which then has been applied for predictions over a period of 3 years. SVR is a specific implementation of support vector machines (SVMs), which transforms the observed input data time series into a high-dimensional feature space (input matrix) by way of a kernel function and performs a linear regression in this space. SVR requires a special input matrix. The input matrix was produced by wavelet transforms (WT), singular spectrum analysis (SSA), and a chaotic approach (CA) applied to the input time series. WT convolutes the original time series into a series of wavelets, and SSA decomposes the time series into a trend, an oscillatory and a noise component by singular value decomposition. CA uses a phase space formed by trajectories, which represent the dynamics producing the time series. These three methods for producing the input matrix for the SVR proved successful, while the SVR-WT combination resulted in the highest coefficient of determination and the lowest mean absolute error.

  1. “ELEPHANT TRUNK” AND ENDOVASCULAR STENTGRAFTING – A HYBRID APPROACH TO THE TREATMENT OF EXTENSIVE THORACIC AORTIC ANEURYSM

    Directory of Open Access Journals (Sweden)

    Tomáš Holubec

    2013-01-01

    Full Text Available A hybrid approach to elephant trunk technique for treatment of thoracic aortic aneurysms combines a conventional surgical and endovascular therapy. Compared to surgery alone, there is a presumption that mortality and morbidity is reduced. We present a case report of a 42-year-old man with a giant aneurysm of the entire thoracic aorta, significant aortic and tricuspid regurgitation and ventricular septum defect. The patient underwent multiple consecutive operations and interventions having, among others, finally replaced the entire thoracic aorta with the use of the hybrid elephant trunk technique.

  2. A New Approach for Education and Training of Medical Physicists in Cuba: From University to Clinical Training

    International Nuclear Information System (INIS)

    Alfonso-Laguardia, R.; Rivero Blanco, J.M.

    2016-01-01

    Full text: According to the international recommendations of IAEA and the International Organization for Medical Physics (IOMP), the education and training of clinically qualified medical physicists (CQMP) should include three main academic and professional elements: a university level education, a postgraduate education specific in medical physics (MP) and a supervised clinical training. In Cuba, most of the medical physicists working in radiation oncology (RO) or nuclear medicine (NM) services have graduated from nuclear related programmes of the High Institute on Applied Technologies and Sciences (InSTEC), who further perform a postgraduate study in medical physics (MP), at the level of a so-called Diploma course or a Master in Sciences. Nevertheless, the third level of education, namely the supervised clinical training has not yet been established, due to the lack of official recognition of the profession of MP by the health authorities. A new approach for comprehensive training of CQMP is presented, where, by maintaining the three elements of education, the process is optimized so that a medical physicist is prepared with the highest level of theoretical and clinical training, in agreement with the current demand of the advanced technologies put in service in Cuban hospitals. (author

  3. Practical approach in training (on-the-job) for workers in nuclear industries

    International Nuclear Information System (INIS)

    Vianna, Vilson Bedim; Rocha, Janine Gandolpho da

    2005-01-01

    This work approaches the 'on-the-job training' - a method of practical training - used in nuclear industries for workers who handle radioactive nuclides. The required training must, in accordance with the ISO 9000 standard, be geared to meet the needs of the organization, including the minimization of errors in operation with radionuclides, which involves various aspects (standard, social, environmental, personal and process safety etc.). Therefore, the training process must have the commitment of everybody and have a logical and documented sequence, where both the individual and the needs of the company are raised and analyzed. The clear identification of the radiological risks associated to the hands-on training is critical to the safety of who is being trained and should be part of the training content. However, the greatest challenge is a mechanism allowing to transform the hands-on training in practical learning. The role of training in the modern nuclear industry should not be restricted to provide conditions for better training or development of the employee, but also motivate the continuous improvement of the company and of the productive process

  4. Innovative molecular approach to the identification of Colossoma macropomum and its hybrids

    Directory of Open Access Journals (Sweden)

    Fátima Gomes

    2012-06-01

    Full Text Available Tambaqui (Colossoma macropomum is the fish species most commonly raised in the Brazilian fish farms. The species is highly adaptable to captive conditions, and is both fast-growing and relatively fecund. In recent years, artificial breeding has produced hybrids with Characiform species, known as "Tambacu" and "Tambatinga". Identifying hybrids is a difficult process, given their morphological similarities with the parent species. This study presents an innovative molecular approach to the identification of hybrids based primarily on Multiplex PCR of a nuclear gene (α-Tropomyosin, which was tested on 93 specimens obtained from fish farms in northern Brazil. The sequencing of a 505-bp fragment of the Control Region (CR permitted the identification of the maternal lineage of the specimen, all of which corresponded to C. macropomum. Unexpectedly, only two CR haplotype were found in 93 samples, a very low genetic diversity for the pisciculture of Tambaqui. Multiplex PCR identified 42 hybrids, in contrast with 23 identified by the supplier on the basis of external morphology. This innovative tool has considerable potential for the development of the Brazilian aquaculture, given the possibility of the systematic identification of the genetic traits of both fry-producing stocks, and the fry and juveniles raised in farms.O Tambaqui (Colossoma macropomum é a espécie de peixe mais comumente cultivada em pisciculturas no Brasil. A espécie é altamente adaptada às condições de cativeiro, apresentando rápido crescimento e alta fecundidade. Nos últimos anos tem ocorrido o cruzamento artificial entre espécies de Characiformes, produzindo os híbridos "Tambacu" e "Tambatinga". A identificação de híbridos é uma tarefa difícil, em virtude da grande similaridade morfológica entre as espécies parentais. O presente estudo apresenta uma abordagem molecular inovadora para identificação de híbridos com base em PCR Multiplex de um gene nuclear (

  5. General practitioners' approach to malingering in basic military training centres.

    Science.gov (United States)

    Kokcu, Alper Tunga; Kurt, E

    2017-04-01

    Malingering can be defined as the abuse of the right to benefit from the health services. In this study, the frequency of the malingering cases in Basic Military Training Centres (BMTCs) and the behaviours and the attitudes of the military physicians towards the recruits who are suspected malingerers were described. A total of 17 general practitioners in nine different BMTCs in different regions of Turkey constitute the universe of this descriptive study. In the questionnaire, there were a total of 30 questions about the descriptive characteristics of the participants and their attitudes and behaviours towards malingering. Informed consent form and a questionnaire were applied through the intranet via participants' emails. In the study, 15 physicians were reached with a response rate of 88.2%. All of the physicians suspected malingering in some of the soldiers who were examined. A total of 80% of the physicians (n=12) suspected malingering in at least 10% of the patients they examined. Only 13.3% of the physicians (n=2) had officially diagnosed a case of malingering in the last training period. All of the participants stated that they did not report the official decision for every soldier suspected of malingering. Instead of reporting official decision for malingering, the military physicians apply alternative procedures for suspected malingerers. In countries where the military service is compulsory, prevalence of malingering is estimated to be higher (approximately 5-25%). The problem of malingering is often underestimated due to the fact it is usually overlooked. Malingering remains a problem for the entire military healthcare system, due to the difficulties in exact diagnosis. Therefore, it can be useful to take some practical administrative measures for the soldiers who are prone to malingering, in order to discourage the behaviour. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to

  6. Recent Development in Pulmonary Valve Replacement after Tetralogy of Fallot Repair: The Emergence of Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Tariq eSuleiman

    2015-06-01

    Full Text Available In the current era approximately 90% of infants born with tetralogy of Fallot (ToF are expected to live beyond 40 years of age making it the fastest growing population amongst patients with congenital heart disease. One of the most common late consequences after repair of ToF, is pulmonary valve regurgitation (PVR. Significant PVR results in progressive dilatation and dysfunction of the right ventricle, decrease in exercise tolerance, arrhythmias, heart failure, and increased risk of sudden death. The conventional approach of dealing with this problem is to perform pulmonary valve replacement using cardiopulmonary bypass (CPB and cardioplegic arrest. However, this approach is associated not only with long operative times but also side effects related to the use of CPB. Development of percutaneous approaches to valve disease is one of the most exciting areas of research and clinical innovation in cardiovascular research. The main development has been that of transcatheter pulmonary valve replacement for the rehabilitation of conduits between the right ventricle and pulmonary artery in patients after surgery for ToF. However, with the percutaneous technique, a limited size of prosthesis can be inserted. Moreover, the technique does not offer the opportunity of treating additional defects that are frequently associated with severe PR, such as pulmonary artery dilatation, and it cannot be used in the significantly dilated native right ventricular outlet tract (RVOT. The advent of the hybrid surgical options for treating cardiac disease has integrated the techniques of interventional cardiology with the techniques of cardiac surgery to provide a form of therapy that combines the respective strengths of both fields.In this review, we present and compare recent advances in procedures to replace the pulmonary valve in patients with ToF presenting with severe PVR and dilated RVOT.

  7. A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.

    Science.gov (United States)

    Xue, Xiaoming; Zhou, Jianzhong

    2017-01-01

    To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  8. A hybrid agent-based computational economics and optimization approach for supplier selection problem

    Directory of Open Access Journals (Sweden)

    Zahra Pourabdollahi

    2017-12-01

    Full Text Available Supplier evaluation and selection problem is among the most important of logistics decisions that have been addressed extensively in supply chain management. The same logistics decision is also important in freight transportation since it identifies trade relationships between business establishments and determines commodity flows between production and consumption points. The commodity flows are then used as input to freight transportation models to determine cargo movements and their characteristics including mode choice and shipment size. Various approaches have been proposed to explore this latter problem in previous studies. Traditionally, potential suppliers are evaluated and selected using only price/cost as the influential criteria and the state-of-practice methods. This paper introduces a hybrid agent-based computational economics and optimization approach for supplier selection. The proposed model combines an agent-based multi-criteria supplier evaluation approach with a multi-objective optimization model to capture both behavioral and economical aspects of the supplier selection process. The model uses a system of ordered response models to determine importance weights of the different criteria in supplier evaluation from a buyers’ point of view. The estimated weights are then used to calculate a utility for each potential supplier in the market and rank them. The calculated utilities are then entered into a mathematical programming model in which best suppliers are selected by maximizing the total accrued utility for all buyers and minimizing total shipping costs while balancing the capacity of potential suppliers to ensure market clearing mechanisms. The proposed model, herein, was implemented under an operational agent-based supply chain and freight transportation framework for the Chicago Metropolitan Area.

  9. Super-resolution nanofabrication with metal-ion doped hybrid material through an optical dual-beam approach

    International Nuclear Information System (INIS)

    Cao, Yaoyu; Li, Xiangping; Gu, Min

    2014-01-01

    We apply an optical dual-beam approach to a metal-ion doped hybrid material to achieve nanofeatures beyond the optical diffraction limit. By spatially inhibiting the photoreduction and the photopolymerization, we realize a nano-line, consisting of polymer matrix and in-situ generated gold nanoparticles, with a lateral size of sub 100 nm, corresponding to a factor of 7 improvement compared to the diffraction limit. With the existence of gold nanoparticles, a plasmon enhanced super-resolution fabrication mechanism in the hybrid material is observed, which benefits in a further reduction in size of the fabricated feature. The demonstrated nanofeature in hybrid materials paves the way for realizing functional nanostructures

  10. An Approach to Ethical Practice in Management and Trainer Training.

    Science.gov (United States)

    Johnston, Rita

    1992-01-01

    Concern with ethics has given rise to two educational approaches, one derived from philosophical principles of social ethics, the other based on case studies of practical issues. A combination of these is necessary to ensure situational applicability and to avoid moral relativism and expediency. (SK)

  11. Examination of Pre-Service Teacher's Training through Tutoring Approach

    Science.gov (United States)

    Wu, Hsiao-ping; Guerra, Myriam Jimena

    2017-01-01

    Pre-service teacher preparation in the United States is becoming progressively more challenging with respect to the demands on teachers. This study examined the impact of tutoring approach on pre-service teachers? skills to work with English language learners through a qualitative research design. Content analysis was used at the thematic level on…

  12. A Multimedia Approach to ODL for Agricultural Training in Cambodia

    Science.gov (United States)

    Grunfeld, Helena; Ng, Maria Lee Hoon

    2013-01-01

    Open distance learning (ODL) has long been an important option for formal and non-formal education (NFE) in most developed and developing countries, but less so in post-conflict countries, including Cambodia. However, in Cambodia there is now greater awareness that ODL can complement traditional face-to-face educational approaches, particularly as…

  13. Structured-Exercise-Program (SEP): An Effective Training Approach to Key Healthcare Professionals

    Science.gov (United States)

    Miazi, Mosharaf H.; Hossain, Taleb; Tiroyakgosi, C.

    2014-01-01

    Structured exercise program is an effective approach to technology dependent resource limited healthcare area for professional training. The result of a recently conducted data analysis revealed this. The aim of the study is to know the effectiveness of the applied approach that was designed to observe the level of adherence to newly adopted…

  14. Assessing Changes in Job Behavior Due to Training: A Guide to the Participant Action Plan Approach.

    Science.gov (United States)

    Office of Personnel Management, Washington, DC.

    This guide provides a brief introduction to the Participant Action Plan Approach (PAPA) and a user's handbook. Part I outlines five steps of PAPA which determine how job behavior is changed by training course or program participation. Part II, the manual, is arranged by the five steps of the PAPA approach. Planning for PAPA discusses making…

  15. Skills Training for School Leavers: Some Alternative Approaches. Current Issues Brief No. 2.

    Science.gov (United States)

    Fraser, Doug

    In the face of escalating youth unemployment, some new approaches are needed for training out-of-school youth in Australia. The current system of apprenticeship has become outmoded because many of the skilled trades that the system prepares young people for will soon be non-existent. One approach to this problem has been implementation of…

  16. "GARDEN OF CHILDHOOD" as an Innovative Approach to Training and Education of Children at Preschool Institutions

    Science.gov (United States)

    Alekseeva, Larisa; Shkolyar, Luidmila; Savenkova, Luibov

    2016-01-01

    The authors reveal an innovative approach to training and education of preschool children. This approach is called "GARDEN OF CHILDHOOD". It is based on the idea that the development of the preschool child's personality should be joyous and free "cultural self-creation" in terms of the collective co-creation, where adults and…

  17. Practical Skills Training in Agricultural Education--A Comparison between Traditional and Blended Approaches

    Science.gov (United States)

    Deegan, Donna; Wims, Padraig; Pettit, Tony

    2016-01-01

    Purpose: In this article the use of blended learning multimedia materials as an education tool was compared with the traditional approach for skills training. Design/Methodology/Approach: This study was conducted in Ireland using a pre-test, post-test experimental design. All students were instructed on how to complete two skills using either a…

  18. E-learning on the job : training taking a more virtual approach

    Energy Technology Data Exchange (ETDEWEB)

    Macedo, R.

    2008-07-15

    A growing number of companies are using web-based e-learning systems to train employees. The activities of 3 E-learning companies were described in this article, notably dominKnow Learning Systems, NGRAIN Corporation and Blatant Media. One of the greatest challenges facing the oilsands industry is to build a skilled labour force to operate massive upgraders. The benefit of the e-learning approach is that consistent information can be delivered to learners, with no variation in information. The training takes on many forms, either through online simulations or simply placing a manual online. In addition to saving time, e-learning familiarizes workers with specific pieces of equipment that would be much too expensive to purchase. Three-dimensional equipment simulations are also made available for training purposes. This article presented an online e-learning approach that has been used effectively for safety training and corporate governance. E-learning simplified the process compared to actual classroom training. It allowed staff to combine training time with regular work schedules. The online e-learning approach was shown to save companies many of hours in training time. 2 figs.

  19. A systematic approach to the training in the nuclear power industry: The need for standard

    International Nuclear Information System (INIS)

    Wilkinson, J.D.

    1995-01-01

    The five elements of a open-quotes Systematic Approach to Trainingclose quotes (SAT) are analysis, design, development, implementation and evaluation. These elements are also present in the effective application of basic process control. The fundamental negative feedback process control loop is therefore an excellent model for a successful, systematic approach to training in the nuclear power industry. Just as standards are required in today's manufacturing and service industries, eg ISO 9000, so too are control standards needed in the training industry and in particular in the training of nuclear power plant staff. The International Atomic Energy Agency (IAEA) produced its TECDOC 525 on open-quotes Training to Establish and Maintain the Qualification and Competence of Nuclear Power Plant Operations Personnelclose quotes in 1989 and the American Nuclear Society published its open-quotes Selection, Qualification, and Training of Personnel for Nuclear Power Plants, an American National Standardclose quotes in 1993. It is important that community colleges, training vendors and organizations such as the Instrument Society of America (ISA), who may be supplying basic or prerequisite training to the nuclear power industry, become aware of these and other standards relating to training in the nuclear power industry

  20. Approaches to Education and Training for Kenya's Nuclear Power Program

    International Nuclear Information System (INIS)

    Kalambuka, H.A.

    2014-01-01

    1. Review of status and development of E and T for the nuclear power program in Kenya; 2. Review of challenges in nuclear E and T, and the initiatives being undertaken to mitigate them: • Recommendations for strategic action; 3. State of nuclear skills in the context of key drivers of the global revival in nuclear energy; 4. Point of view: Education in Applied Nuclear and Radiation physics at Nairobi: • Its growth has helped identify the gaps, and relevant practical approaches for realizing the broad spectrum of technical capacity to conduct a national NPP; 5. Proposed approach to support the E and T infrastructure necessary to allow the country to plan, construct, operate, regulate, and safely and securely handle nuclear facilities sustainably; 6. Specified E and T initiatives in the context of the national industrial development strategy and nuclear energy policy and funding for the complete life cycle and technology localization. (author)

  1. Deterministic linear-optics quantum computing based on a hybrid approach

    International Nuclear Information System (INIS)

    Lee, Seung-Woo; Jeong, Hyunseok

    2014-01-01

    We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources

  2. Deterministic linear-optics quantum computing based on a hybrid approach

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung-Woo; Jeong, Hyunseok [Center for Macroscopic Quantum Control, Department of Physics and Astronomy, Seoul National University, Seoul, 151-742 (Korea, Republic of)

    2014-12-04

    We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources.

  3. Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction

    Science.gov (United States)

    Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro

    Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

  4. A Hybrid Information Mining Approach for Knowledge Discovery in Cardiovascular Disease (CVD

    Directory of Open Access Journals (Sweden)

    Stefania Pasanisi

    2018-04-01

    Full Text Available The healthcare ambit is usually perceived as “information rich” yet “knowledge poor”. Nowadays, an unprecedented effort is underway to increase the use of business intelligence techniques to solve this problem. Heart disease (HD is a major cause of mortality in modern society. This paper analyzes the risk factors that have been identified in cardiovascular disease (CVD surveillance systems. The Heart Care study identifies attributes related to CVD risk (gender, age, smoking habit, etc. and other dependent variables that include a specific form of CVD (diabetes, hypertension, cardiac disease, etc.. In this paper, we combine Clustering, Association Rules, and Neural Networks for the assessment of heart-event-related risk factors, targeting the reduction of CVD risk. With the use of the K-means algorithm, significant groups of patients are found. Then, the Apriori algorithm is applied in order to understand the kinds of relations between the attributes within the dataset, first looking within the whole dataset and then refining the results through the subsets defined by the clusters. Finally, both results allow us to better define patients’ characteristics in order to make predictions about CVD risk with a Multilayer Perceptron Neural Network. The results obtained with the hybrid information mining approach indicate that it is an effective strategy for knowledge discovery concerning chronic diseases, particularly for CVD risk.

  5. Online energy management strategy of fuel cell hybrid electric vehicles based on data fusion approach

    Science.gov (United States)

    Zhou, Daming; Al-Durra, Ahmed; Gao, Fei; Ravey, Alexandre; Matraji, Imad; Godoy Simões, Marcelo

    2017-10-01

    Energy management strategy plays a key role for Fuel Cell Hybrid Electric Vehicles (FCHEVs), it directly affects the efficiency and performance of energy storages in FCHEVs. For example, by using a suitable energy distribution controller, the fuel cell system can be maintained in a high efficiency region and thus saving hydrogen consumption. In this paper, an energy management strategy for online driving cycles is proposed based on a combination of the parameters from three offline optimized fuzzy logic controllers using data fusion approach. The fuzzy logic controllers are respectively optimized for three typical driving scenarios: highway, suburban and city in offline. To classify patterns of online driving cycles, a Probabilistic Support Vector Machine (PSVM) is used to provide probabilistic classification results. Based on the classification results of the online driving cycle, the parameters of each offline optimized fuzzy logic controllers are then fused using Dempster-Shafer (DS) evidence theory, in order to calculate the final parameters for the online fuzzy logic controller. Three experimental validations using Hardware-In-the-Loop (HIL) platform with different-sized FCHEVs have been performed. Experimental comparison results show that, the proposed PSVM-DS based online controller can achieve a relatively stable operation and a higher efficiency of fuel cell system in real driving cycles.

  6. A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products

    Directory of Open Access Journals (Sweden)

    Animesh Debnath

    2017-07-01

    Full Text Available Due to the increasing size of the population, society faces several challenges for sustainable and adequate agricultural production, quality, distribution, and food safety in the strategic project portfolio selection (SPPS. The initial adaptation of strategic portfolio management of genetically modified (GM Agro by-products (Ab-Ps is a huge challenge in terms of processing the agro food product supply-chain practices in an environmentally nonthreatening way. As a solution to the challenges, the socio-economic characteristics for SPPS of GM food purchasing scenarios are studied. Evaluation and selection of the GM agro portfolio management are the dynamic issues due to physical and immaterial criteria involving a hybrid multiple criteria decision making (MCDM approach, combining modified grey Decision-Making Trial and Evaluation Laboratory (DEMATEL, Multi-Attributive Border Approximation area Comparison (MABAC and sensitivity analysis. Evaluation criteria are grouped into social, differential and beneficial clusters, and the modified DEMATEL procedure is used to derive the criteria weights. The MABAC method is applied to rank the strategic project portfolios according to the aggregated preferences of decision makers (DMs. The usefulness of the proposed research framework is validated with a case study. The GM by-products are found to be the best portfolio. Moreover, this framework can unify the policies of agro technological improvement, corporate social responsibility (CSR and agro export promotion.

  7. An event driven hybrid identity management approach to privacy enhanced e-health.

    Science.gov (United States)

    Sánchez-Guerrero, Rosa; Almenárez, Florina; Díaz-Sánchez, Daniel; Marín, Andrés; Arias, Patricia; Sanvido, Fabio

    2012-01-01

    Credential-based authorization offers interesting advantages for ubiquitous scenarios involving limited devices such as sensors and personal mobile equipment: the verification can be done locally; it offers a more reduced computational cost than its competitors for issuing, storing, and verification; and it naturally supports rights delegation. The main drawback is the revocation of rights. Revocation requires handling potentially large revocation lists, or using protocols to check the revocation status, bringing extra communication costs not acceptable for sensors and other limited devices. Moreover, the effective revocation consent--considered as a privacy rule in sensitive scenarios--has not been fully addressed. This paper proposes an event-based mechanism empowering a new concept, the sleepyhead credentials, which allows to substitute time constraints and explicit revocation by activating and deactivating authorization rights according to events. Our approach is to integrate this concept in IdM systems in a hybrid model supporting delegation, which can be an interesting alternative for scenarios where revocation of consent and user privacy are critical. The delegation includes a SAML compliant protocol, which we have validated through a proof-of-concept implementation. This article also explains the mathematical model describing the event-based model and offers estimations of the overhead introduced by the system. The paper focus on health care scenarios, where we show the flexibility of the proposed event-based user consent revocation mechanism.

  8. A hybrid computational-experimental approach for automated crystal structure solution

    Science.gov (United States)

    Meredig, Bryce; Wolverton, C.

    2013-02-01

    Crystal structure solution from diffraction experiments is one of the most fundamental tasks in materials science, chemistry, physics and geology. Unfortunately, numerous factors render this process labour intensive and error prone. Experimental conditions, such as high pressure or structural metastability, often complicate characterization. Furthermore, many materials of great modern interest, such as batteries and hydrogen storage media, contain light elements such as Li and H that only weakly scatter X-rays. Finally, structural refinements generally require significant human input and intuition, as they rely on good initial guesses for the target structure. To address these many challenges, we demonstrate a new hybrid approach, first-principles-assisted structure solution (FPASS), which combines experimental diffraction data, statistical symmetry information and first-principles-based algorithmic optimization to automatically solve crystal structures. We demonstrate the broad utility of FPASS to clarify four important crystal structure debates: the hydrogen storage candidates MgNH and NH3BH3; Li2O2, relevant to Li-air batteries; and high-pressure silane, SiH4.

  9. A hybrid approach to fault diagnosis of roller bearings under variable speed conditions

    Science.gov (United States)

    Wang, Yanxue; Yang, Lin; Xiang, Jiawei; Yang, Jianwei; He, Shuilong

    2017-12-01

    Rolling element bearings are one of the main elements in rotating machines, whose failure may lead to a fatal breakdown and significant economic losses. Conventional vibration-based diagnostic methods are based on the stationary assumption, thus they are not applicable to the diagnosis of bearings working under varying speeds. This constraint limits the bearing diagnosis to the industrial application significantly. A hybrid approach to fault diagnosis of roller bearings under variable speed conditions is proposed in this work, based on computed order tracking (COT) and variational mode decomposition (VMD)-based time frequency representation (VTFR). COT is utilized to resample the non-stationary vibration signal in the angular domain, while VMD is used to decompose the resampled signal into a number of band-limited intrinsic mode functions (BLIMFs). A VTFR is then constructed based on the estimated instantaneous frequency and instantaneous amplitude of each BLIMF. Moreover, the Gini index and time-frequency kurtosis are both proposed to quantitatively measure the sparsity and concentration measurement of time-frequency representation, respectively. The effectiveness of the VTFR for extracting nonlinear components has been verified by a bat signal. Results of this numerical simulation also show the sparsity and concentration of the VTFR are better than those of short-time Fourier transform, continuous wavelet transform, Hilbert-Huang transform and Wigner-Ville distribution techniques. Several experimental results have further demonstrated that the proposed method can well detect bearing faults under variable speed conditions.

  10. Nucleon polarizabilities from deuteron Compton scattering within a Green's function hybrid approach

    Energy Technology Data Exchange (ETDEWEB)

    Hildebrandt, R.P.; Hemmert, T.R. [Technische Universitaet Muenchen, Institut fuer Theoretische Physik (T39), Physik-Department, Garching (Germany); Griesshammer, H.W. [Technische Universitaet Muenchen, Institut fuer Theoretische Physik (T39), Physik-Department, Garching (Germany); Universitaet Erlangen-Nuernberg, Institut fuer Theoretische Physik III, Naturwissenschaftliche Fakultaet I, Erlangen (Germany); The George Washington University, Center for Nuclear Studies, Department of Physics, Washington DC (United States)

    2010-10-15

    We examine elastic Compton scattering from the deuteron for photon energies ranging from zero to 100MeV, using state-of-the-art deuteron wave functions and NN potentials. Nucleon-nucleon rescattering between emission and absorption of the two photons is treated by Green's functions in order to ensure gauge invariance and the correct Thomson limit. With this Green's function hybrid approach, we fulfill the low-energy theorem of deuteron Compton scattering and there is no significant dependence on the deuteron wave function used. Concerning the nucleon structure, we use the chiral effective field theory with explicit {delta} (1232) degrees of freedom within the small-scale expansion up to leading-one-loop order. Agreement with available data is good at all energies. Our 2-parameter fit to all elastic {gamma} d data leads to values for the static isoscalar dipole polarizabilities which are in excellent agreement with the isoscalar Baldin sum rule. Taking this value as additional input, we find {alpha}{sub E}{sup s} = (11.3{+-}0.7(stat){+-}0.6(Baldin){+-}1(theory)){sup .}10{sup -4} fm{sup 3} and {beta}{sub M}{sup s} = (3.2{+-}0.7(stat){+-}0.6(Baldin){+-}1(theory)){sup .}10{sup -4} fm{sup 3} and conclude by comparison to the proton numbers that neutron and proton polarizabilities are the same within rather small errors. (orig.)

  11. A hybrid system approach to airspeed, angle of attack and sideslip estimation in Unmanned Aerial Vehicles

    KAUST Repository

    Shaqura, Mohammad

    2015-06-01

    Fixed wing Unmanned Aerial Vehicles (UAVs) are an increasingly common sensing platform, owing to their key advantages: speed, endurance and ability to explore remote areas. While these platforms are highly efficient, they cannot easily be equipped with air data sensors commonly found on their larger scale manned counterparts. Indeed, such sensors are bulky, expensive and severely reduce the payload capability of the UAVs. In consequence, UAV controllers (humans or autopilots) have little information on the actual mode of operation of the wing (normal, stalled, spin) which can cause catastrophic losses of control when flying in turbulent weather conditions. In this article, we propose a real-time air parameter estimation scheme that can run on commercial, low power autopilots in real-time. The computational method is based on a hybrid decomposition of the modes of operation of the UAV. A Bayesian approach is considered for estimation, in which the estimated airspeed, angle of attack and sideslip are described statistically. An implementation on a UAV is presented, and the performance and computational efficiency of this method are validated using hardware in the loop (HIL) simulation and experimental flight data and compared with classical Extended Kalman Filter estimation. Our benchmark tests shows that this method is faster than EKF by up to two orders of magnitude. © 2015 IEEE.

  12. Hybrid 3D printing and electrodeposition approach for controllable 3D alginate hydrogel formation.

    Science.gov (United States)

    Shang, Wanfeng; Liu, Yanting; Wan, Wenfeng; Hu, Chengzhi; Liu, Zeyang; Wong, Chin To; Fukuda, Toshio; Shen, Yajing

    2017-06-07

    Calcium alginate hydrogels are widely used as biocompatible materials in a substantial number of biomedical applications. This paper reports on a hybrid 3D printing and electrodeposition approach for forming 3D calcium alginate hydrogels in a controllable manner. Firstly, a specific 3D hydrogel printing system is developed by integrating a customized ejection syringe with a conventional 3D printer. Then, a mixed solution of sodium alginate and CaCO 3 nanoparticles is filled into the syringe and can be continuously ejected out of the syringe nozzle onto a conductive substrate. When applying a DC voltage (∼5 V) between the substrate (anode) and the nozzle (cathode), the Ca 2+ released from the CaCO 3 particles can crosslink the alginate to form calcium alginate hydrogel on the substrate. To elucidate the gel formation mechanism and better control the gel growth, we can further establish and verify a gel growth model by considering several key parameters, i.e., applied voltage and deposition time. The experimental results indicate that the alginate hydrogel of various 3D structures can be formed by controlling the movement of the 3D printer. A cell viability test is conducted and shows that the encapsulated cells in the gel can maintain a high survival rate (∼99% right after gel formation). This research establishes a reliable method for the controllable formation of 3D calcium alginate hydrogel, exhibiting great potential for use in basic biology and applied biomedical engineering.

  13. A hybrid clustering and classification approach for predicting crash injury severity on rural roads.

    Science.gov (United States)

    Hasheminejad, Seyed Hessam-Allah; Zahedi, Mohsen; Hasheminejad, Seyed Mohammad Hossein

    2018-03-01

    As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011-2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.

  14. Hybrid Vibration Control under Broadband Excitation and Variable Temperature Using Viscoelastic Neutralizer and Adaptive Feedforward Approach

    Directory of Open Access Journals (Sweden)

    João C. O. Marra

    2016-01-01

    Full Text Available Vibratory phenomena have always surrounded human life. The need for more knowledge and domain of such phenomena increases more and more, especially in the modern society where the human-machine integration becomes closer day after day. In that context, this work deals with the development and practical implementation of a hybrid (passive-active/adaptive vibration control system over a metallic beam excited by a broadband signal and under variable temperature, between 5 and 35°C. Since temperature variations affect directly and considerably the performance of the passive control system, composed of a viscoelastic dynamic vibration neutralizer (also called a viscoelastic dynamic vibration absorber, the associative strategy of using an active-adaptive vibration control system (based on a feedforward approach with the use of the FXLMS algorithm working together with the passive one has shown to be a good option to compensate the neutralizer loss of performance and generally maintain the extended overall level of vibration control. As an additional gain, the association of both vibration control systems (passive and active-adaptive has improved the attenuation of vibration levels. Some key steps matured over years of research on this experimental setup are presented in this paper.

  15. Polymer Combustion as a Basis for Hybrid Propulsion: A Comprehensive Review and New Numerical Approaches

    Directory of Open Access Journals (Sweden)

    Vasily Novozhilov

    2011-10-01

    Full Text Available Hybrid Propulsion is an attractive alternative to conventional liquid and solid rocket motors. This is an active area of research and technological developments. Potential wide application of Hybrid Engines opens the possibility for safer and more flexible space vehicle launching and manoeuvring. The present paper discusses fundamental combustion issues related to further development of Hybrid Rockets. The emphasis is made on the two aspects: (1 properties of potential polymeric fuels, and their modification, and (2 implementation of comprehensive CFD models for combustion in Hybrid Engines. Fundamentals of polymeric fuel combustion are discussed. Further, steps necessary to accurately describe their burning behaviour by means of CFD models are investigated. Final part of the paper presents results of preliminary CFD simulations of fuel burning process in Hybrid Engine using a simplified set-up.

  16. Approach bias modification training and consumption: A review of the literature.

    Science.gov (United States)

    Kakoschke, Naomi; Kemps, Eva; Tiggemann, Marika

    2017-01-01

    Recent theoretical perspectives and empirical evidence have suggested that biased cognitive processing is an important contributor to unhealthy behaviour. Approach bias modification is a novel intervention in which approach biases for appetitive cues are modified. The current review of the literature aimed to evaluate the effectiveness of modifying approach bias for harmful consumption behaviours, including alcohol use, cigarette smoking, and unhealthy eating. Relevant publications were identified through a search of four electronic databases (PsycINFO, Google Scholar, ScienceDirect and Scopus) that were conducted between October and December 2015. Eligibility criteria included the use of a human adult sample, at least one session of avoidance training, and an outcome measure related to the behaviour of interest. The fifteen identified publications (comprising 18 individual studies) were coded on a number of characteristics, including consumption behaviour, participants, task, training and control conditions, number of training sessions and trials, outcome measure, and results. The results generally showed positive effects of approach-avoidance training, including reduced consumption behaviour in the laboratory, lower relapse rates, and improvements in self-reported measures of behaviour. Importantly, all studies (with one exception) that reported favourable consumption outcomes also demonstrated successful reduction of the approach bias for appetitive cues. Thus, the current review concluded that approach bias modification is effective for reducing both approach bias and unhealthy consumption behaviour. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. A Hybrid Approach to Finding Relevant Social Media Content for Complex Domain Specific Information Needs.

    Science.gov (United States)

    Cameron, Delroy; Sheth, Amit P; Jaykumar, Nishita; Thirunarayan, Krishnaprasad; Anand, Gaurish; Smith, Gary A

    2014-12-01

    While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex domain specific information needs. The domain of prescription drug abuse, for example, requires knowledge of both ontological concepts and "intelligible constructs" not typically modeled in ontologies. These intelligible constructs convey essential information that include notions of intensity, frequency, interval, dosage and sentiments, which could be important to the holistic needs of the information seeker. In this paper, we present a hybrid approach to domain specific information retrieval that integrates ontology-driven query interpretation with synonym-based query expansion and domain specific rules, to facilitate search in social media on prescription drug abuse. Our framework is based on a context-free grammar (CFG) that defines the query language of constructs interpretable by the search system. The grammar provides two levels of semantic interpretation: 1) a top-level CFG that facilitates retrieval of diverse textual patterns, which belong to broad templates and 2) a low-level CFG that enables interpretation of specific expressions belonging to such textual patterns. These low-level expressions occur as concepts from four different categories of data: 1) ontological concepts, 2) concepts in lexicons (such as emotions and sentiments), 3) concepts in lexicons with only partial ontology representation, called lexico-ontology concepts (such as side effects and routes of administration (ROA)), and 4) domain specific expressions (such as date, time, interval, frequency and dosage) derived solely through rules. Our approach is embodied in a novel Semantic Web platform called PREDOSE, which provides search support for complex domain specific information needs in prescription drug abuse epidemiology. When applied to a corpus of over 1 million drug abuse-related web forum posts, our search framework proved effective in retrieving

  18. Cooperative approach to training for radiological emergency preparedness and response in Southeast Asia

    International Nuclear Information System (INIS)

    Bus, John; Popp, Andrew; Holland, Brian; Murray, Allan

    2011-01-01

    The paper describes the collaborative and systematic approach to training for nuclear and radiological emergency preparedness and response and the outcomes of this work with ANSTO's Southeast Asian counterparts, particularly in the Philippines. The standards and criteria being applied are discussed, along with the methods, design and conduct of workshops, table-top and field exercises. The following elements of this training will be presented: (a) identifying the priority areas for training through needs analysis;(b) strengthening individual profesional expertise through a structured approach to training; and (c) enhancing individual Agency and National nuclear and radiological emergency preparedness and response arrangements and capabilities. Whilst the work is motivated by nuclear security concerns, the implications for effective and sustainable emergency response to any nuclear or radiological incidents are noted. (author)

  19. Analysis phase of systematic approach to training (SAT) for nuclear plant personnel

    International Nuclear Information System (INIS)

    2000-08-01

    The IAEA and many Member States have recognized the benefits of a systematic approach when training nuclear power plant personnel. The Systematic Approach to Training (SAT) fully described in the IAEA publications, is recommended as the best practice for attaining and maintaining the competence and qualification of NPP personnel. Typically, SAT is organised into distinct phases of Analysis, Design, Development, Implementation, and Evaluation, and relies on Feedback as a process for continuous improvement This document is addressed to nuclear power operating organisations facing the challenge of developing training programs for their own personnel. The intention was to provide Member States with examples of the Analysis phase to form foundation of SAT-based training programs. This document is also available in CD form

  20. The Neurorehabilitation Training Toolkit (NTT: A Novel Worldwide Accessible Motor Training Approach for At-Home Rehabilitation after Stroke

    Directory of Open Access Journals (Sweden)

    Sergi Bermúdez i Badia

    2012-01-01

    Full Text Available After stroke, enduring rehabilitation is required for maximum recovery, and ideally throughout life to prevent functional deterioration. Hence we developed a new concept for at-home low-cost motor rehabilitation, the NTT, an Internet-based interactive system for upper-limb rehabilitation. In this paper we present the NTT design concepts, its implementation and a proof of concept study with 10 healthy participants. The NTT brings together concepts of optimal learning, engagement, and storytelling to deliver a personalized training to its users. In this study we evaluate the feasibility of NTT as a tool capable of automatically assessing and adapting to its user. This is achieved by means of a psychometric study where we show that the NTT is able to assess movement kinematics—movement smoothness, range of motion, arm displacement and arm coordination—in healthy users. Subsequently, a modeling approach is presented to understand how the measured movement kinematics relate to training parameters, and how these can be modified to adapt the training to meet the needs of patients. Finally, an adaptive algorithm for the personalization of training considering motivational and performance aspects is proposed. In the next phase we will deploy and evaluate the NTT with stroke patients at their homes.

  1. Experimental Study Comparing a Traditional Approach to Performance Appraisal Training to a Whole-Brain Training Method at C.B. Fleet Laboratories

    Science.gov (United States)

    Selden, Sally; Sherrier, Tom; Wooters, Robert

    2012-01-01

    The purpose of this study is to examine the effects of a new approach to performance appraisal training. Motivated by split-brain theory and existing studies of cognitive information processing and performance appraisals, this exploratory study examined the effects of a whole-brain approach to training managers for implementing performance…

  2. Graduate Education and Simulation Training for CBRNE Disasters Using a Multimodal Approach to Learning. Part 2: Education and Training from the Perspectives of Educators and Students

    Science.gov (United States)

    2013-08-01

    quantify learning effectiveness and retention rates by comparing didactic lectures, reading, audiovisual presentations, demonstrations, discussion...Graduate Education and Simulation Training   for CBRNE Disasters Using a Multimodal  Approach to  Learning   Part 2: Education and Training from the...TITLE AND SUBTITLE Graduate Education and Simulation Training for CBRNE Disasters Using a Multimodal 5a. CONTRACT NUMBER Approach to Learning

  3. Alternative policy impacts on US GHG emissions and energy security: A hybrid modeling approach

    International Nuclear Information System (INIS)

    Sarica, Kemal; Tyner, Wallace E.

    2013-01-01

    This study addresses the possible impacts of energy and climate policies, namely corporate average fleet efficiency (CAFE) standard, renewable fuel standard (RFS) and clean energy standard (CES), and an economy wide equivalent carbon tax on GHG emissions in the US to the year 2045. Bottom–up and top–down modeling approaches find widespread use in energy economic modeling and policy analysis, in which they differ mainly with respect to the emphasis placed on technology of the energy system and/or the comprehensiveness of endogenous market adjustments. For this study, we use a hybrid energy modeling approach, MARKAL–Macro, that combines the characteristics of two divergent approaches, in order to investigate and quantify the cost of climate policies for the US and an equivalent carbon tax. The approach incorporates Macro-economic feedbacks through a single sector neoclassical growth model while maintaining sectoral and technological detail of the bottom–up optimization framework with endogenous aggregated energy demand. Our analysis is done for two important objectives of the US energy policy: GHG reduction and increased energy security. Our results suggest that the emission tax achieves results quite similar to the CES policy but very different results in the transportation sector. The CAFE standard and RFS are more expensive than a carbon tax for emission reductions. However, the CAFE standard and RFS are much more efficient at achieving crude oil import reductions. The GDP losses are 2.0% and 1.2% relative to the base case for the policy case and carbon tax. That difference may be perceived as being small given the increased energy security gained from the CAFE and RFS policy measures and the uncertainty inherent in this type of analysis. - Highlights: • Evaluates US impacts of three energy/climate policies and a carbon tax (CT) • Analysis done with bottom–up MARKAL model coupled with a macro model • Electricity clean energy standard very close to

  4. IMPROVING THE POSITIONING ACCURACY OF TRAIN ON THE APPROACH SECTION TO THE RAILWAY CROSSING

    Directory of Open Access Journals (Sweden)

    V. I. Havryliuk

    2016-02-01

    Full Text Available Purpose. In the paper it is necessary to analyze possibility of improving the positioning accuracy of train on the approach section to crossing for traffic safety control at railway crossings. Methodology. Researches were performed using developed mathematical model, describing dependence of the input impedance of the coded and audio frequency track circuits on a train coordinate at various values of ballast isolation resistances and for all usable frequencies. Findings. The paper presents the developed mathematical model, describing dependence of the input impedance of the coded and audio-frequency track circuits on the train coordinate at various values of ballast isolation resistances and for all frequencies used in track circuits. The relative error determination of train coordinate by input impedance caused by variation of the ballast isolation resistance for the coded track circuits was investigated. The values of relative error determination of train coordinate can achieve up to 40-50 % and these facts do not allow using this method directly for coded track circuits. For short audio frequency track circuits on frequencies of continuous cab signaling (25, 50 Hz the relative error does not exceed acceptable values, this allow using the examined method for determination of train location on the approach section to railway crossing. Originality. The developed mathematical model allowed determination of the error dependence of train coordinate by using input impedance of the track circuit for coded and audio-frequency track circuits at various frequencies of the signal current and at different ballast isolation resistances. Practical value. The authors proposethe method for train location determination on approach section to the crossing, equipped with audio-frequency track circuits, which is a combination of discrete and continuous monitoring of the train location.

  5. The feasibility of a train-the-trainer approach to end of life care training in care homes: an evaluation.

    Science.gov (United States)

    Mayrhofer, Andrea; Goodman, Claire; Smeeton, Nigel; Handley, Melanie; Amador, Sarah; Davies, Sue

    2016-01-22

    there is organisational stability, peer to peer approaches to skills training in end of life care can, with expert facilitation, cascade and sustain learning in care homes.

  6. B-1 Systems Approach to Training. Volume 3. Appendix B. Bibliography and Data Collection Trips

    Science.gov (United States)

    1975-07-01

    the Fourth Annual Symposium on Psychology in the Air Force, 1974, ~ •—- ~ - --- - Creelman , J.A., Evaluation of Approach Training Procedures...of Engineering Psychology , American Psychologist, 1972, 27 (7), 615-622. Adams, J.A., and Hufford, I.E., Effects of Programmed Perceptual Training on...Control, Wright-Patterson Air Force Base, Ohio, April 7-9, 1970. Aldrich, T.B., Proceedings of the Annual Symposium on Psychology in the Air Force (2nd

  7. B-1 Systems Approach to Training. Simulation Technology Assessment Report (STAR)

    Science.gov (United States)

    1975-07-01

    Psychology in the Air Force, 1974. Creelman , J.A., Evaluation of Approach Training Procedures, U.S. Naval School of Aviation Med., Proj. No. NM001-109-107...training. 3.2 PHYSICAL VERSUS PSYCHOLOGICAL SIMULATION In the previous section, the term "physical simulation" was used to represent the case where... psychology that there is no "step function" threshold. Rather, detection capability plotted against phys- ical parameter strength results in an ogival

  8. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach

    Directory of Open Access Journals (Sweden)

    Miraemiliana Murat

    2017-09-01

    Full Text Available Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM, Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD, Histogram of Oriented Gradients (HOG, Hu invariant moments (Hu and Zernike moments (ZM. Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN, random forest (RF, support vector machine (SVM, k-nearest neighbour (k-NN, linear discriminant analysis (LDA and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM. In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS and Pearson’s coefficient correlation (PCC. The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia

  9. HYBRID TEACHER TRAINING: THE CONSTRUCTION OF PEDAGOGICAL PRACTICE AS ARTICULATOR AXIS FOR THE USE OF TECHNOLOGIES IN AN INCLUSIVE SCHOOL

    Directory of Open Access Journals (Sweden)

    Danielle Aparecida do Nascimento dos Santos

    2013-07-01

    Full Text Available This paper aims to present data related to the preparation, implementation, monitoring, development and evaluation of Articulator Axis: Inclusion and Special Education of hybrid Pedagogy UNIVESP/UNESP course. It is explained the theoretical, methodological and practical contributions that supported the organization of the discipline, designed with the premise to train teachers in order to provide analysis tools on the policies and practices of school inclusion of students of Special Education. As well as offering elements to teachers who attend the course for an analysis of practices and resources that can be used in the context of an inclusive school, through the promotion of school activities that develop the skills of all. The discipline was developed in five (5 blocks of 24 (twenty four hours per week, which were proposed activities and studies on the activities related to elementary and high school, aggregated to Specialized Educational Service and the use of Digital Information and Communication Technologies, according to the specific educational needs of students of Special Education and considering its importance within the policies of inclusion and its application in school contexts linked to the disciplines of didactic contents of the course.

  10. A quality approach for conducting training needs assessments in the Ministry of Health, State of Bahrain.

    Science.gov (United States)

    Benjamin, S; al-Darazi, F

    2000-01-01

    In health care organizations around the world, Training Needs Assessments (TNAs) have generally followed a professions-based approach. For example, the training needs of doctors, nurses, each allied health profession, and distinct support staff have been analyzed separately--individualized TNAs conducted for each speciality and functional area. Although a professions-based TNA model can provide useful information to human resource development (HRD) professionals, there are two major drawbacks: (1) it is possible that important training needs might be overlooked because of lack of information sharing among professions and (2) such an approach does not encourage an interdisciplinary, team orientation to service provision. This paper proposes an improved method of conceptualizing TNAs, using an approach that builds on the quality management literature (TQM, CQI, etc.) which stresses the importance of customer- and service-orientations to organizing and measuring organizational and individual performance.

  11. Combination of Biorthogonal Wavelet Hybrid Kernel OCSVM with Feature Weighted Approach Based on EVA and GRA in Financial Distress Prediction

    Directory of Open Access Journals (Sweden)

    Chao Huang

    2014-01-01

    Full Text Available Financial distress prediction plays an important role in the survival of companies. In this paper, a novel biorthogonal wavelet hybrid kernel function is constructed by combining linear kernel function with biorthogonal wavelet kernel function. Besides, a new feature weighted approach is presented based on economic value added (EVA and grey relational analysis (GRA. Considering the imbalance between financially distressed companies and normal ones, the feature weighted one-class support vector machine based on biorthogonal wavelet hybrid kernel (BWH-FWOCSVM is further put forward for financial distress prediction. The empirical study with real data from the listed companies on Growth Enterprise Market (GEM in China shows that the proposed approach has good performance.

  12. IITET and shadow TT: an innovative approach to training at the point of need

    Science.gov (United States)

    Gross, Andrew; Lopez, Favio; Dirkse, James; Anderson, Darran; Berglie, Stephen; May, Christopher; Harkrider, Susan

    2014-06-01

    The Image Intensification and Thermal Equipment Training (IITET) project is a joint effort between Night Vision and Electronics Sensors Directorate (NVESD) Modeling and Simulation Division (MSD) and the Army Research Institute (ARI) Fort Benning Research Unit. The IITET effort develops a reusable and extensible training architecture that supports the Army Learning Model and trains Manned-Unmanned Teaming (MUM-T) concepts to Shadow Unmanned Aerial Systems (UAS) payload operators. The training challenge of MUM-T during aviation operations is that UAS payload operators traditionally learn few of the scout-reconnaissance skills and coordination appropriate to MUM-T at the schoolhouse. The IITET effort leveraged the simulation experience and capabilities at NVESD and ARI's research to develop a novel payload operator training approach consistent with the Army Learning Model. Based on the training and system requirements, the team researched and identified candidate capabilities in several distinct technology areas. The training capability will support a variety of training missions as well as a full campaign. Data from these missions will be captured in a fully integrated AAR capability, which will provide objective feedback to the user in near-real-time. IITET will be delivered via a combination of browser and video streaming technologies, eliminating the requirement for a client download and reducing user computer system requirements. The result is a novel UAS Payload Operator training capability, nested within an architecture capable of supporting a wide variety of training needs for air and ground tactical platforms and sensors, and potentially several other areas requiring vignette-based serious games training.

  13. Targeted and untargeted high resolution mass approach for a putative profiling of glycosylated simple phenols in hybrid grapes.

    Science.gov (United States)

    Barnaba, Chiara; Dellacassa, Eduardo; Nicolini, Giorgio; Giacomelli, Mattia; Roman Villegas, Tomas; Nardin, Tiziana; Larcher, Roberto

    2017-08-01

    Vitis vinifera is one of the most widespread grapevines around the world representing the raw material for high quality wine production. The availability of more resistant interspecific hybrid vine varieties, developed from crosses between Vitis vinifera and other Vitis species, has generated much interest, also due to the low environmental effect of production. However, hybrid grape wine composition and varietal differences between interspecific hybrids have not been well defined, particularly for the simple phenols profile. The dynamic of these phenols in wines, where the glycosylated forms can be transformed into the free ones during winemaking, also raises an increasing health interest by their role as antoxidants in wine consumers. In this work an on-line SPE clean-up device, to reduce matrix interference, was combined with ultra-high liquid chromatography-high resolution mass spectrometry in order to increase understanding of the phenolic composition of hybrid grape varieties. Specifically, the phenolic composition of 4 hybrid grape varieties (red, Cabernet Cantor and Prior; white, Muscaris and Solaris) and 2 European grape varieties (red, Merlot; white, Chardonnay) was investigated, focusing on free and glycosidically bound simple phenols and considering compound distribution in pulp, skin, seeds and wine. Using a targeted approach 53 free simple phenols and 7 glycosidic precursors were quantified with quantification limits ranging from 0.001 to 2mgKg -1 and calibration R 2 of 0.99 for over 86% of compounds. The untargeted approach made it possible to tentatively identify 79 glycosylated precursors of selected free simple phenols in the form of -hexoside (N=30), -pentoside (21), -hexoside-hexoside (17), -hexoside-pentoside (4), -pentoside-hexoside (5) and -pentoside-pentoside (2) derivatives on the basis of accurate mass, isotopic pattern and MS/MS fragmentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Evaluation of training programs and entry-level qualifications for nuclear-power-plant control-room personnel based on the systems approach to training

    International Nuclear Information System (INIS)

    Haas, P.M.; Selby, D.L.; Hanley, M.J.; Mercer, R.T.

    1983-09-01

    This report summarizes results of research sponsored by the US Nuclear Regulatory Commission (NRC) Office of Nuclear Regulatory Research to initiate the use of the Systems Approach to Training in the evaluation of training programs and entry level qualifications for nuclear power plant (NPP) personnel. Variables (performance shaping factors) of potential importance to personnel selection and training are identified, and research to more rigorously define an operationally useful taxonomy of those variables is recommended. A high-level model of the Systems Approach to Training for use in the nuclear industry, which could serve as a model for NRC evaluation of industry programs, is presented. The model is consistent with current publically stated NRC policy, with the approach being followed by the Institute for Nuclear Power Operations, and with current training technology. Checklists to be used by NRC evaluators to assess training programs for NPP control-room personnel are proposed which are based on this model

  15. Evaluation of training programs and entry-level qualifications for nuclear-power-plant control-room personnel based on the systems approach to training

    Energy Technology Data Exchange (ETDEWEB)

    Haas, P M; Selby, D L; Hanley, M J; Mercer, R T

    1983-09-01

    This report summarizes results of research sponsored by the US Nuclear Regulatory Commission (NRC) Office of Nuclear Regulatory Research to initiate the use of the Systems Approach to Training in the evaluation of training programs and entry level qualifications for nuclear power plant (NPP) personnel. Variables (performance shaping factors) of potential importance to personnel selection and training are identified, and research to more rigorously define an operationally useful taxonomy of those variables is recommended. A high-level model of the Systems Approach to Training for use in the nuclear industry, which could serve as a model for NRC evaluation of industry programs, is presented. The model is consistent with current publically stated NRC policy, with the approach being followed by the Institute for Nuclear Power Operations, and with current training technology. Checklists to be used by NRC evaluators to assess training programs for NPP control-room personnel are proposed which are based on this model.

  16. Training organizational supervisors to detect and prevent cyber insider threats: two approaches

    Directory of Open Access Journals (Sweden)

    Dee H. Andrews

    2013-05-01

    Full Text Available Cyber insider threat is intentional theft from, or sabotage of, a cyber system by someone within the organization. This article explores the use of advanced cognitive and instructional principles to accelerate learning in organizational supervisors to mitigate the cyber threat. It examines the potential advantage of using serious games to engage supervisors. It also posits two systematic instructional approaches for this training challenge – optimal path modelling and a competency-based approach. The paper concludes by discussing challenges of evaluating training for seldom occurring real world phenomena, like detecting a cyber-insider threat.

  17. Developing a Scientific Virtue-Based Approach to Science Ethics Training.

    Science.gov (United States)

    Pennock, Robert T; O'Rourke, Michael

    2017-02-01

    Responsible conduct of research training typically includes only a subset of the issues that ought to be included in science ethics and sometimes makes ethics appear to be a set of externally imposed rules rather than something intrinsic to scientific practice. A new approach to science ethics training based upon Pennock's notion of the scientific virtues may help avoid such problems. This paper motivates and describes three implementations-theory-centered, exemplar-centered, and concept-centered-that we have developed in courses and workshops to introduce students to this scientific virtue-based approach.

  18. G-centers in irradiated silicon revisited: A screened hybrid density functional theory approach

    KAUST Repository

    Wang, H.; Chroneos, A.; Londos, C. A.; Sgourou, E. N.; Schwingenschlö gl, Udo

    2014-01-01

    Electronic structure calculations employing screened hybrid density functional theory are used to gain fundamental insight into the interaction of carbon interstitial (Ci) and substitutional (Cs) atoms forming the CiCs defect known as G

  19. A Formal Approach to User Interface Design using Hybrid System Theory, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Optimal Synthesis Inc.(OSI) proposes to develop an aiding tool for user interface design that is based on mathematical formalism of hybrid system theory. The...

  20. An Information-Theoretic Approach for Indirect Train Traffic Monitoring Using Building Vibration

    Directory of Open Access Journals (Sweden)

    Susu Xu

    2017-05-01

    Full Text Available This paper introduces an indirect train traffic monitoring method to detect and infer real-time train events based on the vibration response of a nearby building. Monitoring and characterizing traffic events are important for cities to improve the efficiency of transportation systems (e.g., train passing, heavy trucks, and traffic. Most prior work falls into two categories: (1 methods that require intensive labor to manually record events or (2 systems that require deployment of dedicated sensors. These approaches are difficult and costly to execute and maintain. In addition, most prior work uses dedicated sensors designed for a single purpose, resulting in deployment of multiple sensor systems. This further increases costs. Meanwhile, with the increasing demands of structural health monitoring, many vibration sensors are being deployed in commercial buildings. Traffic events create ground vibration that propagates to nearby building structures inducing noisy vibration responses. We present an information-theoretic method for train event monitoring using commonly existing vibration sensors deployed for building health monitoring. The key idea is to represent the wave propagation in a building induced by train traffic as information conveyed in noisy measurement signals. Our technique first uses wavelet analysis to detect train events. Then, by analyzing information exchange patterns of building vibration signals, we infer the category of the events (i.e., southbound or northbound train. Our algorithm is evaluated with an 11-story building where trains pass by frequently. The results show that the method can robustly achieve a train event detection accuracy of up to a 93% true positive rate and an 80% true negative rate. For direction categorization, compared with the traditional signal processing method, our information-theoretic approach reduces categorization error from 32.1 to 12.1%, which is a 2.5× improvement.

  1. Early experience with the Occlutech PLD occluder for mitral paravalvar leak closure through a hybrid transapical approach.

    Science.gov (United States)

    Bedair, Radwa; Morgan, Gareth J; Bapat, Vinayak; Kapetanakis, Stamatis; Goreczny, Sebastian; Simpson, John; Qureshi, Shakeel A

    2016-12-10

    We sought to evaluate the feasibility and efficacy of hybrid transapical closure of paravalvar mitral leaks using a new Occlutech PLD occluder in patients with heart failure and/or haemolytic anaemia. Retrospective analysis of clinical and procedural data was undertaken for patients who had attempted closure of paravalvar mitral leaks via a hybrid transapical approach with the Occlutech PLD occluder. Eight patients (four males, median age 69 years) underwent closure of 10 mitral paravalvar leaks using eight Occlutech PLD occluders and two AMPLATZER Vascular Plugs (AVP II). Successful deployment, with significant reduction of the paravalvar leak was achieved in seven patients with short procedure (median 131 min) and fluoroscopy times (median 22 min). One patient had mechanical interference with prosthetic valve function, requiring surgery. Another patient with a high EuroSCORE (48.8%) died of multi-organ failure two days after the procedure. Clinical improvement in either heart failure or haemolysis was seen in all discharged patients. In our series of patients with challenging anatomy, the Occlutech PLD occluders performed well when implanted via a hybrid transapical approach. Further work is needed to assess this methodology fully for a wider population and to assess other deployment approaches for this promising new occluder.

  2. Numerical methodologies for investigation of moderate-velocity flow using a hybrid computational fluid dynamics - molecular dynamics simulation approach

    International Nuclear Information System (INIS)

    Ko, Soon Heum; Kim, Na Yong; Nikitopoulos, Dimitris E.; Moldovan, Dorel; Jha, Shantenu

    2014-01-01

    Numerical approaches are presented to minimize the statistical errors inherently present due to finite sampling and the presence of thermal fluctuations in the molecular region of a hybrid computational fluid dynamics (CFD) - molecular dynamics (MD) flow solution. Near the fluid-solid interface the hybrid CFD-MD simulation approach provides a more accurate solution, especially in the presence of significant molecular-level phenomena, than the traditional continuum-based simulation techniques. It also involves less computational cost than the pure particle-based MD. Despite these advantages the hybrid CFD-MD methodology has been applied mostly in flow studies at high velocities, mainly because of the higher statistical errors associated with low velocities. As an alternative to the costly increase of the size of the MD region to decrease statistical errors, we investigate a few numerical approaches that reduce sampling noise of the solution at moderate-velocities. These methods are based on sampling of multiple simulation replicas and linear regression of multiple spatial/temporal samples. We discuss the advantages and disadvantages of each technique in the perspective of solution accuracy and computational cost.

  3. Introgressive hybridization in Iberian cyprinid fishes:a cytogenomic approach to homoploid Leuciscinae

    OpenAIRE

    Pereira, Carla Sofia Alves, 1983-

    2013-01-01

    Tese de doutoramento, Biologia (Biologia Evolutiva), Universidade de Lisboa, Faculdade de Ciências, 2013 Hybridization is currently a well-recognized process amongst animals responsible for biodiversity, evolution and speciation processes while defying most species concepts. Hybridization is prevalent among fishes, particularly cyprinids, which therefore constitute good models of study (1) to access general patterns of genomic variation, (2) to identify the genetic basis and the evolutiona...

  4. A Hybrid Change Detection Approach for Damage Detection and Recovery Monitoring

    Science.gov (United States)

    de Alwis Pitts, Dilkushi; Wieland, Marc; Wang, Shifeng; So, Emily; Pittore, Massimiliano

    2014-05-01

    Following a disaster, change detection via pre- and post-event very high resolution remote sensing images is an essential technique for damage assessment and recovery monitoring over large areas in complex urban environments. Most assessments to date focus on detection, destruction and recovery of man-made objects that facilitate shelter and accessibility, such as buildings, roads, bridges, etc., as indicators for assessment and better decision making. Moreover, many current change-detection mechanisms do not use all the data and knowledge which are often available for the pre-disaster state. Recognizing the continuous rather than dichotomous character of the data-rich/data-poor distinction permits the incorporation of ancillary data and existing knowledge into the processing flow. Such incorporation could improve the reliability of the results and thereby enhance the usability of robust methods for disaster management. This study proposes an application-specific and robust change detection method from multi-temporal very high resolution multi-spectral satellite images. This hybrid indicator-specific method uses readily available pre-disaster GIS data and integrates existing knowledge into the processing flow to optimize the change detection while offering the possibility to target specific types of changes to man-made objects. The indicator-specific information of the GIS objects is used as a series of masks to treat the GIS objects with similar characteristics similarly for better accuracy. The proposed approach is based on a fusion of a multi-index change detection method based on gradient, texture and edge similarity filters. The change detection index is flexible for disaster cases in which the pre-disaster and post-disaster images are not of the same resolution. The proposed automated method is evaluated with QuickBird and Ikonos datasets for abrupt changes soon after disaster. The method could also be extended in a semi-automated way for monitoring

  5. MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics

    Directory of Open Access Journals (Sweden)

    Hardy Nigel

    2006-06-01

    Full Text Available Abstract Background The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5–6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behaviour of the cell can be observed using large-scale metabolomic studies. The metabolomic data produced need to be structured and annotated in a machine-usable form to facilitate the exploration of the hidden links between the genes and their functions. Description MeMo is a formal model for representing metabolomic data and the associated metadata. Two predominant platforms (SQL and XML are used to encode the model. MeMo has been implemented as a relational database using a hybrid approach combining the advantages of the two technologies. It represents a practical solution for handling the sheer volume and complexity of the metabolomic data effectively and efficiently. The MeMo model and the associated software are available at http://dbkgroup.org/memo/. Conclusion The maturity of relational database technology is used to support efficient data processing. The scalability and self-descriptiveness of XML are used to simplify the relational schema and facilitate the extensibility of the model necessitated by the creation of new experimental techniques. Special consideration is given to data integration issues as part of the systems biology agenda. MeMo has been physically integrated and cross-linked to related metabolomic and genomic databases. Semantic integration with other relevant databases has been supported through ontological annotation. Compatibility with other data formats is supported by automatic conversion.

  6. A Game-Theoretic approach to Fault Diagnosis of Hybrid Systems

    Directory of Open Access Journals (Sweden)

    Davide Bresolin

    2011-06-01

    Full Text Available Physical systems can fail. For this reason the problem of identifying and reacting to faults has received a large attention in the control and computer science communities. In this paper we study the fault diagnosis problem for hybrid systems from a game-theoretical point of view. A hybrid system is a system mixing continuous and discrete behaviours that cannot be faithfully modeled neither by using a formalism with continuous dynamics only nor by a formalism including only discrete dynamics. We use the well known framework of hybrid automata for modeling hybrid systems, and we define a Fault Diagnosis Game on them, using two players: the environment and the diagnoser. The environment controls the evolution of the system and chooses whether and when a fault occurs. The diagnoser observes the external behaviour of the system and announces whether a fault has occurred or not. Existence of a winning strategy for the diagnoser implies that faults can be detected correctly, while computing such a winning strategy corresponds to implement a diagnoser for the system. We will show how to determine the existence of a winning strategy, and how to compute it, for some decidable classes of hybrid automata like o-minimal hybrid automata.

  7. Is there a place for a holistic approach in surgical training?

    Science.gov (United States)

    Atayoglu, Timucin; Buchholz, Noor; Atayoglu, Ayten Guner; Caliskan, Mujgan

    2014-03-01

    The holistic approach in medicine is a framework that considers and treats all aspects of a patient's needs, as it relates to their health. The goal of such an approach is to prevent illness, and to maximise the well-being of individuals and families. Holistic medicine is also referred to as integrative, which has been interpreted by some professionals as the combination of evidence-based medicine and complementary medicine. The speciality of Family Medicine (FM) is often referred to as General Practice (GP), a terminology which emphasises the holistic nature of that discipline. Furthermore, GP/FM professional bodies in some countries have incorporated the holistic and integrative approach into curricula and guidelines for doctors in training, which reflects its acceptance as a component of medical training. However, despite this validation, and despite research showing the effectiveness of such strategies in enhancing the outcomes of surgery, a holistic framework or integrative approach has not been equally integrated into speciality training for would-be surgeons. We argue that it would be advisable to include holistic approaches into surgical training and help surgeons to recognise their role in the continuum of care.

  8. Prediction of Currency Volume Issued in Taiwan Using a Hybrid Artificial Neural Network and Multiple Regression Approach

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2013-01-01

    Full Text Available Because the volume of currency issued by a country always affects its interest rate, price index, income levels, and many other important macroeconomic variables, the prediction of currency volume issued has attracted considerable attention in recent years. In contrast to the typical single-stage forecast model, this study proposes a hybrid forecasting approach to predict the volume of currency issued in Taiwan. The proposed hybrid models consist of artificial neural network (ANN and multiple regression (MR components. The MR component of the hybrid models is established for a selection of fewer explanatory variables, wherein the selected variables are of higher importance. The ANN component is then designed to generate forecasts based on those important explanatory variables. Subsequently, the model is used to analyze a real dataset of Taiwan's currency from 1996 to 2011 and twenty associated explanatory variables. The prediction results reveal that the proposed hybrid scheme exhibits superior forecasting performance for predicting the volume of currency issued in Taiwan.

  9. Simulation of a Wall-Bounded Flow using a Hybrid LES/RAS Approach with Turbulence Recycling

    Science.gov (United States)

    Quinlan, Jesse R.; Mcdaniel, James; Baurle, Robert A.

    2012-01-01

    Simulations of a supersonic recessed-cavity flow are performed using a hybrid large-eddy/ Reynolds-averaged simulation approach utilizing an inflow turbulence recycling procedure and hybridized inviscid flux scheme. Calorically perfect air enters the three-dimensional domain at a free stream Mach number of 2.92. Simulations are performed to assess grid sensitivity of the solution, efficacy of the turbulence recycling, and effect of the shock sensor used with the hybridized inviscid flux scheme. Analysis of the turbulent boundary layer upstream of the rearward-facing step for each case indicates excellent agreement with theoretical predictions. Mean velocity and pressure results are compared to Reynolds-averaged simulations and experimental data for each case, and these comparisons indicate good agreement on the finest grid. Simulations are repeated on a coarsened grid, and results indicate strong grid density sensitivity. The effect of turbulence recycling on the solution is illustrated by performing coarse grid simulations with and without inflow turbulence recycling. Two shock sensors, one of Ducros and one of Larsson, are assessed for use with the hybridized inviscid flux reconstruction scheme.

  10. Odor Perception by Dogs: Evaluating Two Training Approaches for Odor Learning of Sniffer Dogs.

    Science.gov (United States)

    Fischer-Tenhagen, Carola; Johnen, Dorothea; Heuwieser, Wolfgang; Becker, Roland; Schallschmidt, Kristin; Nehls, Irene

    2017-06-01

    In this study, a standardized experimental set-up with various combinations of herbs as odor sources was designed. Two training approaches for sniffer dogs were compared; first, training with a pure reference odor, and second, training with a variety of odor mixtures with the target odor as a common denominator. The ability of the dogs to identify the target odor in a new context was tested. Six different herbs (basil, St. John's wort, dandelion, marjoram, parsley, ribwort) were chosen to produce reference materials in various mixtures with (positive) and without (negative) chamomile as the target odor source. The dogs were trained to show 1 of 2 different behaviors, 1 for the positive, and 1 for the negative sample as a yes/no task. Tests were double blind with one sample presented at a time. In both training approaches, dogs were able to detect chamomile as the target odor in any presented mixture with an average sensitivity of 72% and a specificity of 84%. Dogs trained with odor mixture containing the target odor had more correct indications in the transfer task. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  11. Evaluation and Validation of Assembling Corrected PacBio Long Reads for Microbial Genome Completion via Hybrid Approaches.

    Science.gov (United States)

    Lin, Hsin-Hung; Liao, Yu-Chieh

    2015-01-01

    Despite the ever-increasing output of next-generation sequencing data along with developing assemblers, dozens to hundreds of gaps still exist in de novo microbial assemblies due to uneven coverage and large genomic repeats. Third-generation single-molecule, real-time (SMRT) sequencing technology avoids amplification artifacts and generates kilobase-long reads with the potential to complete microbial genome assembly. However, due to the low accuracy (~85%) of third-generation sequences, a considerable amount of long reads (>50X) are required for self-correction and for subsequent de novo assembly. Recently-developed hybrid approaches, using next-generation sequencing data and as few as 5X long reads, have been proposed to improve the completeness of microbial assembly. In this study we have evaluated the contemporary hybrid approaches and demonstrated that assembling corrected long reads (by runCA) produced the best assembly compared to long-read scaffolding (e.g., AHA, Cerulean and SSPACE-LongRead) and gap-filling (SPAdes). For generating corrected long reads, we further examined long-read correction tools, such as ECTools, LSC, LoRDEC, PBcR pipeline and proovread. We have demonstrated that three microbial genomes including Escherichia coli K12 MG1655, Meiothermus ruber DSM1279 and Pdeobacter heparinus DSM2366 were successfully hybrid assembled by runCA into near-perfect assemblies using ECTools-corrected long reads. In addition, we developed a tool, Patch, which implements corrected long reads and pre-assembled contigs as inputs, to enhance microbial genome assemblies. With the additional 20X long reads, short reads of S. cerevisiae W303 were hybrid assembled into 115 contigs using the verified strategy, ECTools + runCA. Patch was subsequently applied to upgrade the assembly to a 35-contig draft genome. Our evaluation of the hybrid approaches shows that assembling the ECTools-corrected long reads via runCA generates near complete microbial genomes, suggesting

  12. HyDEn: A Hybrid Steganocryptographic Approach for Data Encryption Using Randomized Error-Correcting DNA Codes

    Directory of Open Access Journals (Sweden)

    Dan Tulpan

    2013-01-01

    Full Text Available This paper presents a novel hybrid DNA encryption (HyDEn approach that uses randomized assignments of unique error-correcting DNA Hamming code words for single characters in the extended ASCII set. HyDEn relies on custom-built quaternary codes and a private key used in the randomized assignment of code words and the cyclic permutations applied on the encoded message. Along with its ability to detect and correct errors, HyDEn equals or outperforms existing cryptographic methods and represents a promising in silico DNA steganographic approach.

  13. Mentoring SFRM: A New Approach to International Space Station Flight Control Training

    Science.gov (United States)

    Huning, Therese; Barshi, Immanuel; Schmidt, Lacey

    2009-01-01

    The Mission Operations Directorate (MOD) of the Johnson Space Center is responsible for providing continuous operations support for the International Space Station (ISS). Operations support requires flight controllers who are skilled in team performance as well as the technical operations of the ISS. Space Flight Resource Management (SFRM), a NASA adapted variant of Crew Resource Management (CRM), is the competency model used in the MOD. ISS flight controller certification has evolved to include a balanced focus on development of SFRM and technical expertise. The latest challenge the MOD faces is how to certify an ISS flight controller (Operator) to a basic level of effectiveness in 1 year. SFRM training uses a twopronged approach to expediting operator certification: 1) imbed SFRM skills training into all Operator technical training and 2) use senior flight controllers as mentors. This paper focuses on how the MOD uses senior flight controllers as mentors to train SFRM skills.

  14. Effects of an explicit problem-solving skills training program using a metacomponential approach for outpatients with acquired brain injury.

    Science.gov (United States)

    Fong, Kenneth N K; Howie, Dorothy R

    2009-01-01

    We investigated the effects of an explicit problem-solving skills training program using a metacomponential approach with 33 outpatients with moderate acquired brain injury, in the Hong Kong context. We compared an experimental training intervention with this explicit problem-solving approach, which taught metacomponential strategies, with a conventional cognitive training approach that did not have this explicit metacognitive training. We found significant advantages for the experimental group on the Metacomponential Interview measure in association with the explicit metacomponential training, but transfer to the real-life problem-solving measures was not evidenced in statistically significant findings. Small sample size, limited time of intervention, and some limitations with these tools may have been contributing factors to these results. The training program was demonstrated to have a significantly greater effect than the conventional training approach on metacomponential functioning and the component of problem representation. However, these benefits were not transferable to real-life situations.

  15. Cognitive Effects of Mindfulness Training: Results of a Pilot Study Based on a Theory Driven Approach.

    Science.gov (United States)

    Wimmer, Lena; Bellingrath, Silja; von Stockhausen, Lisa

    2016-01-01

    The present paper reports a pilot study which tested cognitive effects of mindfulness practice in a theory-driven approach. Thirty-four fifth graders received either a mindfulness training which was based on the mindfulness-based stress reduction approach (experimental group), a concentration training (active control group), or no treatment (passive control group). Based on the operational definition of mindfulness by Bishop et al. (2004), effects on sustained attention, cognitive flexibility, cognitive inhibition, and data-driven as opposed to schema-based information processing were predicted. These abilities were assessed in a pre-post design by means of a vigilance test, a reversible figures test, the Wisconsin Card Sorting Test, a Stroop test, a visual search task, and a recognition task of prototypical faces. Results suggest that the mindfulness training specifically improved cognitive inhibition and data-driven information processing.

  16. Cognitive effects of mindfulness training: Results of a pilot study based on a theory driven approach

    Directory of Open Access Journals (Sweden)

    Lena Wimmer

    2016-07-01

    Full Text Available The present paper reports a pilot study which tested cognitive effects of mindfulness practice in a theory-driven approach. Thirty-four fifth graders received either a mindfulness training which was based on the mindfulness-based stress reduction approach (experimental group, a concentration training (active control group or no treatment (passive control group. Based on the operational definition of mindfulness by Bishop et al. (2004, effects on sustained attention, cognitive flexibility, cognitive inhibition and data-driven as opposed to schema-based information processing were predicted. These abilities were assessed in a pre-post design by means of a vigilance test, a reversible figures test, the Wisconsin Card Sorting Test, a Stroop test, a visual search task, and a recognition task of prototypical faces. Results suggest that the mindfulness training specifically improved cognitive inhibition and data-driven information processing.

  17. Approach-Avoidance Training Effects Are Moderated by Awareness of Stimulus-Action Contingencies.

    Science.gov (United States)

    Van Dessel, Pieter; De Houwer, Jan; Gast, Anne

    2016-01-01

    Prior research suggests that repeatedly approaching or avoiding a stimulus changes the liking of that stimulus. In two experiments, we investigated the relationship between, on one hand, effects of approach-avoidance (AA) training on implicit and explicit evaluations of novel faces and, on the other hand, contingency awareness as indexed by participants' memory for the relation between stimulus and action. We observed stronger effects for faces that were classified as contingency aware and found no evidence that AA training caused changes in stimulus evaluations in the absence of contingency awareness. These findings challenge the standard view that AA training effects are (exclusively) the product of implicit learning processes, such as the automatic formation of associations in memory. © 2015 by the Society for Personality and Social Psychology, Inc.

  18. Application of a Sensemaking Approach to Ethics Training in the Physical Sciences and Engineering

    Science.gov (United States)

    Kligyte, Vykinta; Marcy, Richard T.; Waples, Ethan P.; Sevier, Sydney T.; Godfrey, Elaine S.; Mumford, Michael D.; Hougen, Dean F.

    2008-06-01

    Integrity is a critical determinant of the effectiveness of research organizations in terms of producing high quality research and educating the new generation of scientists. A number of responsible conduct of research (RCR) training programs have been developed to address this growing organizational concern. However, in spite of a significant body of research in ethics training, it is still unknown which approach has the highest potential to enhance researchers' integrity. One of the approaches showing some promise in improving researchers' integrity has focused on the development of ethical decision-making skills. The current effort proposes a novel curriculum that focuses on broad metacognitive reasoning strategies researchers use when making sense of day-to-day social and professional practices that have ethical implications for the physical sciences and engineering. This sensemaking training has been implemented in a professional sample of scientists conducting research in electrical engineering, atmospheric and computer sciences at a large multi-cultural, multi-disciplinary, and multi-university research center. A pre-post design was used to assess training effectiveness using scenario-based ethical decision-making measures. The training resulted in enhanced ethical decision-making of researchers in relation to four ethical conduct areas, namely data management, study conduct, professional practices, and business practices. In addition, sensemaking training led to researchers' preference for decisions involving the application of the broad metacognitive reasoning strategies. Individual trainee and training characteristics were used to explain the study findings. Broad implications of the findings for ethics training development, implementation, and evaluation in the sciences are discussed.

  19. Mentoring SFRM: A New Approach to International Space Station Flight Controller Training

    Science.gov (United States)

    Huning, Therese; Barshi, Immanuel; Schmidt, Lacey

    2008-01-01

    The Mission Operations Directorate (MOD) of the Johnson Space Center is responsible for providing continuous operations support for the International Space Station (ISS). Operations support requires flight controllers who are skilled in team performance as well as the technical operations of the ISS. Space Flight Resource Management (SFRM), a NASA adapted variant of Crew Resource Management (CRM), is the competency model used in the MOD. ISS flight controller certification has evolved to include a balanced focus on development of SFRM and technical expertise. The latest challenge the MOD faces is how to certify an ISS flight controller (operator) to a basic level of effectiveness in 1 year. SFRM training uses a two-pronged approach to expediting operator certification: 1) imbed SFRM skills training into all operator technical training and 2) use senior flight controllers as mentors. This paper focuses on how the MOD uses senior flight controllers as mentors to train SFRM skills. Methods: A mentor works with an operator throughout the training flow. Inserted into the training flow are guided-discussion sessions and on-the-job observation opportunities focusing on specific SFRM skills, including: situational leadership, conflict management, stress management, cross-cultural awareness, self care and team care while on-console, communication, workload management, and situation awareness. The mentor and operator discuss the science and art behind the skills, cultural effects on skills applications, recognition of good and bad skills applications, recognition of how skills application changes subtly in different situations, and individual goals and techniques for improving skills. Discussion: This mentoring program provides an additional means of transferring SFRM knowledge compared to traditional CRM training programs. Our future endeavors in training SFRM skills (as well as other organization s) may benefit from adding team performance skills mentoring. This paper

  20. The effects of verbal information and approach-avoidance training on children's fear-related responses

    Science.gov (United States)

    Lester, Kathryn J.; Lisk, Stephen C.; Mikita, Nina; Mitchell, Sophie; Huijding, Jorg; Rinck, Mike; Field, Andy P.

    2015-01-01

    Background and objectives This study examined the effects of verbal information and approach-avoidance training on fear-related cognitive and behavioural responses about novel animals. Methods One hundred and sixty children (7–11 years) were randomly allocated to receive: a) positive verbal information about one novel animal and threat information about a second novel animal (verbal information condition); b) approach-avoidance training in which they repeatedly pushed away (avoid) or pulled closer (approach) pictures of the animals (approach-avoidance training), c) a combined condition in which verbal information was given prior to approach-avoidance training (verbal information + approach-avoidance training) and d) a combined condition in which approach-avoidance training was given prior to verbal information (approach-avoidance training + verbal information). Results Threat and positive information significantly increased and decreased fear beliefs and avoidance behaviour respectively. Approach-avoidance training was successful in training the desired behavioural responses but had limited effects on fear-related responses. Verbal information and both combined conditions resulted in significantly larger effects than approach-avoidance training. We found no evidence for an additive effect of these pathways. Limitations This study used a non-clinical sample and focused on novel animals rather than animals about which children already had experience or established fears. The study also compared positive information/approach with threat information/avoid training, limiting specific conclusions regarding the independent effects of these conditions. Conclusions The present study finds little evidence in support of a possible causal role for behavioural response training in the aetiology of childhood fear. However, the provision of verbal information appears to be an important pathway involved in the aetiology of childhood fear. PMID:25698069