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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

    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

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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)

  15. 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…

  16. 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.

  17. 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.

  18. 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...

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.)

  13. 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...

  14. 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.

  15. 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 ...

  16. 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.

  17. 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.

  18. 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%.

  19. 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.

  20. 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…

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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...

  6. 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.

  7. 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

  8. 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...

  9. 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.

  10. 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

  11. 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.

  12. 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.)

  13. 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....

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  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 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.

  2. 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.

  3. 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.

  4. 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.

  5. A deep learning / neuroevolution hybrid for visual control

    DEFF Research Database (Denmark)

    Poulsen, Andreas Precht; Thorhauge, Mark; Funch, Mikkel Hvilshj

    2017-01-01

    This paper presents a deep learning / neuroevolution hybrid approach called DLNE, which allows FPS bots to learn to aim & shoot based only on high-dimensional raw pixel input. The deep learning component is responsible for visual recognition and translating raw pixels to compact feature...... representations, while the evolving network takes those features as inputs to infer actions. The results suggest that combining deep learning and neuroevolution in a hybrid approach is a promising research direction that could make complex visual domains directly accessible to networks trained through evolution....

  6. 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

  7. Modernizing Training Options for Natural Areas Managers

    Science.gov (United States)

    Friedl, Sarah E.; Ober, Holly K.; Stein, Taylor V.; Andreu, Michael G.

    2015-01-01

    A recent shift in desires among working professionals from traditional learning environments to distance education has emerged due to reductions in travel and training budgets. To accommodate this, the Natural Areas Training Academy replaced traditionally formatted workshops with a hybrid approach. Surveys of participants before and after this…

  8. 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.

  9. 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.

  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. 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.

  12. 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.

  13. 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.

  14. 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.

  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 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. 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 ...

  18. 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

  19. 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.

  20. 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.

  1. 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).

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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)

  8. A Hybrid Neuro-Fuzzy Model For Integrating Large Earth-Science Datasets

    Science.gov (United States)

    Porwal, A.; Carranza, J.; Hale, M.

    2004-12-01

    A GIS-based hybrid neuro-fuzzy approach to integration of large earth-science datasets for mineral prospectivity mapping is described. It implements a Takagi-Sugeno type fuzzy inference system in the framework of a four-layered feed-forward adaptive neural network. Each unique combination of the datasets is considered a feature vector whose components are derived by knowledge-based ordinal encoding of the constituent datasets. A subset of feature vectors with a known output target vector (i.e., unique conditions known to be associated with either a mineralized or a barren location) is used for the training of an adaptive neuro-fuzzy inference system. Training involves iterative adjustment of parameters of the adaptive neuro-fuzzy inference system using a hybrid learning procedure for mapping each training vector to its output target vector with minimum sum of squared error. The trained adaptive neuro-fuzzy inference system is used to process all feature vectors. The output for each feature vector is a value that indicates the extent to which a feature vector belongs to the mineralized class or the barren class. These values are used to generate a prospectivity map. The procedure is demonstrated by an application to regional-scale base metal prospectivity mapping in a study area located in the Aravalli metallogenic province (western India). A comparison of the hybrid neuro-fuzzy approach with pure knowledge-driven fuzzy and pure data-driven neural network approaches indicates that the former offers a superior method for integrating large earth-science datasets for predictive spatial mathematical modelling.

  9. A hybrid mammalian cell cycle model

    Directory of Open Access Journals (Sweden)

    Vincent Noël

    2013-08-01

    Full Text Available Hybrid modeling provides an effective solution to cope with multiple time scales dynamics in systems biology. Among the applications of this method, one of the most important is the cell cycle regulation. The machinery of the cell cycle, leading to cell division and proliferation, combines slow growth, spatio-temporal re-organisation of the cell, and rapid changes of regulatory proteins concentrations induced by post-translational modifications. The advancement through the cell cycle comprises a well defined sequence of stages, separated by checkpoint transitions. The combination of continuous and discrete changes justifies hybrid modelling approaches to cell cycle dynamics. We present a piecewise-smooth version of a mammalian cell cycle model, obtained by hybridization from a smooth biochemical model. The approximate hybridization scheme, leading to simplified reaction rates and binary event location functions, is based on learning from a training set of trajectories of the smooth model. We discuss several learning strategies for the parameters of the hybrid model.

  10. 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.

  11. 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.

  12. 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.

  13. 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…

  14. 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

  15. 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.

  16. 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...

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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...

  2. 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

  3. 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)

  4. 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.

  5. 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.

  6. 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.

  7. 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.)

  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. Fuzzy Shannon Entropy: A Hybrid GIS-Based Landslide Susceptibility Mapping Method

    Directory of Open Access Journals (Sweden)

    Majid Shadman Roodposhti

    2016-09-01

    Full Text Available Assessing Landslide Susceptibility Mapping (LSM contributes to reducing the risk of living with landslides. Handling the vagueness associated with LSM is a challenging task. Here we show the application of hybrid GIS-based LSM. The hybrid approach embraces fuzzy membership functions (FMFs in combination with Shannon entropy, a well-known information theory-based method. Nine landslide-related criteria, along with an inventory of landslides containing 108 recent and historic landslide points, are used to prepare a susceptibility map. A random split into training (≈70% and testing (≈30% samples are used for training and validation of the LSM model. The study area—Izeh—is located in the Khuzestan province of Iran, a highly susceptible landslide zone. The performance of the hybrid method is evaluated using receiver operating characteristics (ROC curves in combination with area under the curve (AUC. The performance of the proposed hybrid method with AUC of 0.934 is superior to multi-criteria evaluation approaches using a subjective scheme in this research in comparison with a previous study using the same dataset through extended fuzzy multi-criteria evaluation with AUC value of 0.894, and was built on the basis of decision makers’ evaluation in the same study area.

  10. 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)

  11. 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)

  12. 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

  13. 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.

  14. Systems for hybrid cars

    Science.gov (United States)

    Bitsche, Otmar; Gutmann, Guenter

    Not only sharp competition but also legislation are pushing development of hybrid drive trains. Based on conventional internal combustion engine (ICE) vehicles, these drive trains offer a wide range of benefits from reduced fuel consumption and emission to multifaceted performance improvements. Hybrid electric drive trains may also facilitate the introduction of fuel cells (FC). The battery is the key component for all hybrid drive trains, as it dominates cost and performance issues. The selection of the right battery technology for the specific automotive application is an important task with an impact on costs of development and use. Safety, power, and high cycle life are a must for all hybrid applications. The greatest pressure to reduce cost is in soft hybrids, where lead-acid embedded in a considerate management presents the cheapest solution, with a considerable improvement in performance needed. From mild to full hybridization, an improvement in specific power makes higher costs more acceptable, provided that the battery's service life is equivalent to the vehicle's lifetime. Today, this is proven for the nickel-metal hydride system. Lithium ion batteries, which make use of a multiple safety concept, and with some development anticipated, provide even better prospects in terms of performance and costs. Also, their scalability permits their application in battery electric vehicles—the basis for better performance and enhanced user acceptance. Development targets for the batteries are discussed with a focus on system aspects such as electrical and thermal management and safety.

  15. Electric Vehicle Service Personnel Training Program

    Energy Technology Data Exchange (ETDEWEB)

    Bernstein, Gerald

    2013-06-21

    As the share of hybrid, plug-in hybrid (PHEV), electric (EV) and fuel-cell (FCV) vehicles grows in the national automotive fleet, an entirely new set of diagnostic and technical skills needs to be obtained by the maintenance workforce. Electrically-powered vehicles require new diagnostic tools, technique and vocabulary when compared to existing internal combustion engine-powered models. While the manufacturers of these new vehicles train their own maintenance personnel, training for students, independent working technicians and fleet operators is less focused and organized. This DOE-funded effort provided training to these three target groups to help expand availability of skills and to provide more competition (and lower consumer cost) in the maintenance of these hybrid- and electric-powered vehicles. Our approach was to start locally in the San Francisco Bay Area, one of the densest markets in the United States for these types of automobiles. We then expanded training to the Los Angeles area and then out-of-state to identify what types of curriculum was appropriate and what types of problems were encountered as training was disseminated. The fact that this effort trained up to 800 individuals with sessions varying from 2- day workshops to full-semester courses is considered a successful outcome. Diverse programs were developed to match unique time availability and educational needs of each of the three target audiences. Several key findings and observations arising from this effort include: • Recognition that hybrid and PHEV training demand is immediate; demand for EV training is starting to emerge; while demand for FCV training is still over the horizon • Hybrid and PHEV training are an excellent starting point for all EV-related training as they introduce all the basic concepts (electric motors, battery management, controllers, vocabulary, testing techniques) that are needed for all EVs, and these skills are in-demand in today’s market. • Faculty

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. Weather forecasting based on hybrid neural model

    Science.gov (United States)

    Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.

    2017-11-01

    Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.

  6. The relationship between intelligence and training gains is moderated by training strategy.

    Science.gov (United States)

    Lee, Hyunkyu; Boot, Walter R; Baniqued, Pauline L; Voss, Michelle W; Prakash, Ruchika Shaurya; Basak, Chandramallika; Kramer, Arthur F

    2015-01-01

    We examined the relationship between training regimen and fluid intelligence in the learning of a complex video game. Fifty non-game-playing young adults were trained on a game called Space Fortress for 30 hours with one of two training regimens: (1) Hybrid Variable-Priority Training (HVT), with part-task training and a focus on improving specific skills and managing task priorities, and (2) Full Emphasis Training (FET) in which participants practiced the whole game to obtain the highest overall score. Fluid intelligence was measured with the Raven's Progressive Matrix task before training. With FET, fluid intelligence was positively associated with learning, suggesting that intellectual ability played a substantial role in determining individual differences in training success. In contrast, with HVT, fluid intelligence was not associated with learning, suggesting that individual differences in fluid intelligence do not factor into training success in a regimen that emphasizes component tasks and flexible task coordination. By analyzing training effects in terms of individual differences and training regimens, the current study offers a training approach that minimizes the potentially limiting effect of individual differences.

  7. 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

  8. Probabilistic modelling and analysis of stand-alone hybrid power systems

    International Nuclear Information System (INIS)

    Lujano-Rojas, Juan M.; Dufo-López, Rodolfo; Bernal-Agustín, José L.

    2013-01-01

    As a part of the Hybrid Intelligent Algorithm, a model based on an ANN (artificial neural network) has been proposed in this paper to represent hybrid system behaviour considering the uncertainty related to wind speed and solar radiation, battery bank lifetime, and fuel prices. The Hybrid Intelligent Algorithm suggests a combination of probabilistic analysis based on a Monte Carlo simulation approach and artificial neural network training embedded in a genetic algorithm optimisation model. The installation of a typical hybrid system was analysed. Probabilistic analysis was used to generate an input–output dataset of 519 samples that was later used to train the ANNs to reduce the computational effort required. The generalisation ability of the ANNs was measured in terms of RMSE (Root Mean Square Error), MBE (Mean Bias Error), MAE (Mean Absolute Error), and R-squared estimators using another data group of 200 samples. The results obtained from the estimation of the expected energy not supplied, the probability of a determined reliability level, and the estimation of expected value of net present cost show that the presented model is able to represent the main characteristics of a typical hybrid power system under uncertain operating conditions. - Highlights: • This paper presents a probabilistic model for stand-alone hybrid power system. • The model considers the main sources of uncertainty related to renewable resources. • The Hybrid Intelligent Algorithm has been applied to represent hybrid system behaviour. • The installation of a typical hybrid system was analysed. • The results obtained from the study case validate the presented model

  9. 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.

  10. 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…

  11. 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.…

  12. 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

  13. Advanced hybrid and electric vehicles system optimization and vehicle integration

    CERN Document Server

    2016-01-01

    This contributed volume contains the results of the research program “Agreement for Hybrid and Electric Vehicles”, funded by the International Energy Agency. The topical focus lies on technology options for the system optimization of hybrid and electric vehicle components and drive train configurations which enhance the energy efficiency of the vehicle. The approach to the topic is genuinely interdisciplinary, covering insights from fields. The target audience primarily comprises researchers and industry experts in the field of automotive engineering, but the book may also be beneficial for graduate students.

  14. 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...

  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 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. 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

  18. 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...

  19. Genomic Prediction of Barley Hybrid Performance

    Directory of Open Access Journals (Sweden)

    Norman Philipp

    2016-07-01

    Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

  20. 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%

  1. 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

  2. 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.

  3. Configuration Synthesis of Novel Series-Parallel Hybrid Transmission Systems with Eight-Bar Mechanisms

    Directory of Open Access Journals (Sweden)

    Ngoc-Tan Hoang

    2017-07-01

    Full Text Available This paper presents a design approach for the configuration synthesis of series-parallel hybrid transmissions with eight-bar mechanisms. The final design consists of 54 mechanisms with eight members and twelve joints including a simple planetary gear train (PGT and a double planet PGT. Then, by using the techniques of power and clutch arrangements, new series-parallel hybrid transmissions are synthesized. The power arrangement process generates 97 clutchless hybrid systems. The clutch arrangement process generates 100 corresponding series-parallel transmissions. To demonstrate the feasibility of the synthesized configurations, a new hybrid transmission is selected as an example to analyze the working principle with operation modes and power flow paths.

  4. 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.

  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. 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

  7. 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…

  8. Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction

    Directory of Open Access Journals (Sweden)

    Chengdong Li

    2018-01-01

    Full Text Available To enhance the prediction performance for building energy consumption, this paper presents a modified deep belief network (DBN based hybrid model. The proposed hybrid model combines the outputs from the DBN model with the energy-consuming pattern to yield the final prediction results. The energy-consuming pattern in this study represents the periodicity property of building energy consumption and can be extracted from the observed historical energy consumption data. The residual data generated by removing the energy-consuming pattern from the original data are utilized to train the modified DBN model. The training of the modified DBN includes two steps, the first one of which adopts the contrastive divergence (CD algorithm to optimize the hidden parameters in a pre-train way, while the second one determines the output weighting vector by the least squares method. The proposed hybrid model is applied to two kinds of building energy consumption data sets that have different energy-consuming patterns (daily-periodicity and weekly-periodicity. In order to examine the advantages of the proposed model, four popular artificial intelligence methods—the backward propagation neural network (BPNN, the generalized radial basis function neural network (GRBFNN, the extreme learning machine (ELM, and the support vector regressor (SVR are chosen as the comparative approaches. Experimental results demonstrate that the proposed DBN based hybrid model has the best performance compared with the comparative techniques. Another thing to be mentioned is that all the predictors constructed by utilizing the energy-consuming patterns perform better than those designed only by the original data. This verifies the usefulness of the incorporation of the energy-consuming patterns. The proposed approach can also be extended and applied to some other similar prediction problems that have periodicity patterns, e.g., the traffic flow forecasting and the electricity consumption

  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. 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

  11. 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)

  12. 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.

  13. 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

  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. 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.

  16. A Hybrid Vision-Map Method for Urban Road Detection

    Directory of Open Access Journals (Sweden)

    Carlos Fernández

    2017-01-01

    Full Text Available A hybrid vision-map system is presented to solve the road detection problem in urban scenarios. The standardized use of machine learning techniques in classification problems has been merged with digital navigation map information to increase system robustness. The objective of this paper is to create a new environment perception method to detect the road in urban environments, fusing stereo vision with digital maps by detecting road appearance and road limits such as lane markings or curbs. Deep learning approaches make the system hard-coupled to the training set. Even though our approach is based on machine learning techniques, the features are calculated from different sources (GPS, map, curbs, etc., making our system less dependent on the training set.

  17. Engineering Hybrid Learning Communities: The Case of a Regional Parent Community

    Directory of Open Access Journals (Sweden)

    Sven Strickroth

    2014-09-01

    Full Text Available We present an approach (and a corresponding system design for supporting regionally bound hybrid learning communities (i.e., communities which combine traditional face-to-face elements with web based media such as online community platforms, e-mail and SMS newsletters. The goal of the example community used to illustrate the approach was to support and motivate (especially hard-to-reach underprivileged parents in the education of their young children. The article describes the design process used and the challenges faced during the socio-technical system design. An analysis of the community over more than one year indicates that the hybrid approach works better than the two separated “traditional” approaches separately. Synergy effects like advertising effects from the offline trainings for the online platform and vice versa occurred and regular newsletters turned out to have a noticeable effect on the community.

  18. 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. .

  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. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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)

  7. 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.

  8. 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...

  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. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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

  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. 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

  17. 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.

  18. 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

  19. 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

  20. 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)

  1. 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

  2. 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.

  3. Mild hybrids with CVT: comparison of electrical and mechanical torque assist

    NARCIS (Netherlands)

    Druten, van R.M.; Serrarens, A.F.A.; Vroemen, B.G.; Tillaart, van den E.L.; de Haas, J.

    2001-01-01

    This paper evaluates two mild hybrid drive trains for a mid-class passenger car with a gasoline engine by means of comptuer simulation. The term mild hybrid is used for vehicles with sustained electric propulsion. The mild hybrid drive trains both have a Continuously Variable Transmission (CVT) with

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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…

  14. 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

  15. 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.

  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. 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.

  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. 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.

  20. 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.

  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 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. Mining user-generated geographic content : an interactive, crowdsourced approach to validation and supervision

    NARCIS (Netherlands)

    Ostermann, F.O.; Garcia Chapeton, Gustavo Adolfo; Zurita-Milla, R.; Kraak, M.J.; Bergt, A.; Sarjakoski, T.; van Lammeren, R.; Rip, F.

    2017-01-01

    This paper describes a pilot study that implements a novel approach to validate data mining tasks by using the crowd to train a classifier. This hybrid approach to processing successfully addresses challenges faced during human curation or machine processing of user-generated geographic content

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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…

  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. 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

  18. Evaluation of a novel, hybrid model (Mumbai EUS II) for stepwise teaching and training in EUS-guided biliary drainage and rendezvous procedures.

    Science.gov (United States)

    Dhir, Vinay; Itoi, Takao; Pausawasdi, Nonthalee; Khashab, Mouen A; Perez-Miranda, Manuel; Sun, Siyu; Park, Do Hyun; Iwashita, Takuji; Teoh, Anthony Y B; Maydeo, Amit P; Ho, Khek Yu

    2017-11-01

     EUS-guided biliary drainage (EUS-BD) and rendezvous (EUS-RV) are acceptable rescue options for patients with failed endoscopic retrograde cholangiopancreatography (ERCP). However, there are limited training opportunities at most centers owing to low case volumes. The existing models do not replicate the difficulties encountered during EUS-BD. We aimed to develop and validate a model for stepwise learning of EUS-BD and EUS-RV, which replicates the actual EUS-BD procedures.  A hybrid model was created utilizing pig esophagus and stomach, with a synthetic duodenum and biliary system. The model was objectively assessed on a grade of 1 - 4 by two experts. Twenty-eight trainees were given initial training with didactic lectures and live procedures. This was followed by hands-on training in EUS-BD and EUS-RV on the hybrid model. Trainees were assessed for objective criteria of technical difficulties.  Both the experts graded the model as very good or above for all parameters. All trainees could complete the requisite steps of EUS-BD and EUS-RV in a mean time of 11 minutes (8 - 18 minutes). Thirty-six technical difficulties were noted during the training (wrong scope position, 13; incorrect duct puncture, 12; guidewire related problems, 11). Technical difficulties peaked for EUS-RV, followed by hepaticogastrostomy (HGS) and choledochoduodenostomy (CDS) (20, 9, and 7, P  = 0.001). At 10 days follow-up, nine of 28 trainees had successfully performed three EUS-RV and seven EUS-BD procedures independently.  The Mumbai EUS II hybrid model replicates situations encountered during EUS-RV and EUS-BD. Stepwise mentoring improves the chances of success in EUS-RV and EUS-BD procedures.

  19. Evaluation of a novel, hybrid model (Mumbai EUS II) for stepwise teaching and training in EUS-guided biliary drainage and rendezvous procedures

    Science.gov (United States)

    Dhir, Vinay; Itoi, Takao; Pausawasdi, Nonthalee; Khashab, Mouen A.; Perez-Miranda, Manuel; Sun, Siyu; Park, Do Hyun; Iwashita, Takuji; Teoh, Anthony Y. B.; Maydeo, Amit P.; Ho, Khek Yu

    2017-01-01

    Background and aims  EUS-guided biliary drainage (EUS-BD) and rendezvous (EUS-RV) are acceptable rescue options for patients with failed endoscopic retrograde cholangiopancreatography (ERCP). However, there are limited training opportunities at most centers owing to low case volumes. The existing models do not replicate the difficulties encountered during EUS-BD. We aimed to develop and validate a model for stepwise learning of EUS-BD and EUS-RV, which replicates the actual EUS-BD procedures. Methods  A hybrid model was created utilizing pig esophagus and stomach, with a synthetic duodenum and biliary system. The model was objectively assessed on a grade of 1 – 4 by two experts. Twenty-eight trainees were given initial training with didactic lectures and live procedures. This was followed by hands-on training in EUS-BD and EUS-RV on the hybrid model. Trainees were assessed for objective criteria of technical difficulties. Results  Both the experts graded the model as very good or above for all parameters. All trainees could complete the requisite steps of EUS-BD and EUS-RV in a mean time of 11 minutes (8 – 18 minutes). Thirty-six technical difficulties were noted during the training (wrong scope position, 13; incorrect duct puncture, 12; guidewire related problems, 11). Technical difficulties peaked for EUS-RV, followed by hepaticogastrostomy (HGS) and choledochoduodenostomy (CDS) (20, 9, and 7, P  = 0.001). At 10 days follow-up, nine of 28 trainees had successfully performed three EUS-RV and seven EUS-BD procedures independently. Conclusions  The Mumbai EUS II hybrid model replicates situations encountered during EUS-RV and EUS-BD. Stepwise mentoring improves the chances of success in EUS-RV and EUS-BD procedures. PMID:29250585

  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. 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.

  2. 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.

  3. 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.

  4. 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)

  5. 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...

  6. 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

  7. 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.

  8. 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)

  9. 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)

  10. 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

  11. 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''

  12. 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...

  13. 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...

  14. 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.

  15. Professional Identity, Social Recognition and Entering the Workforce of the University Student with Hybrid Education

    Science.gov (United States)

    Damián, Javier

    2014-01-01

    This article shows progress of a research which aims to describe the factors that facilitate and hinder labor insertion of graduates with hybrid university education, since according to those responsible for the education policy, this type of training facilitates graduates to enter in the labor market. Through a qualitative approach we studied the…

  16. 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.

  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. 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.

  19. 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.

  20. 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

  1. 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.

  2. CoFe2O4-TiO2 Hybrid Nanomaterials: Synthesis Approaches Based on the Oil-in-Water Microemulsion Reaction Method

    Directory of Open Access Journals (Sweden)

    Arturo Adrián Rodríguez-Rodríguez

    2017-01-01

    Full Text Available CoFe2O4 nanoparticles decorated and wrapped with TiO2 nanoparticles have been prepared by mixing well-dispersed CoFe2O4 with amorphous TiO2 (impregnation approach and growing amorphous TiO2 over the magnetic core (seed approach, respectively, followed by thermal treatment to achieve TiO2 crystallinity. Synthesis strategies were based on the oil-in-water microemulsion reaction method. Thermally treated nanomaterials were characterized in terms of structure, morphology, and composition, to confirm hybrid nanoparticles formation and relate with the synthesis approaches; textural, optical, and magnetic properties were evaluated. X-ray diffraction revealed coexistence of cubic spinel-type CoFe2O4 and tetragonal anatase TiO2. Electron microscopy images depicted crystalline nanoparticles (sizes below 25 nm, with homogeneous Ti distribution for the hybrid nanoparticles synthesized by seed approach. EDX microanalysis and ICP-AES corroborated established chemical composition. XPS evidenced chemical states, as well as TiO2 predominance over CoFe2O4 surface. According to BET measurements, the hybrid nanoparticles were mesoporous. UV-Vis spectroscopy showed optical response along the UV-visible light region. Magnetic properties suggested the breaking order of magnetic domains due to modification with TiO2, especially for mediated seed approach sample. The properties of the obtained hybrid nanoparticles were different in comparison with its individual components. The results highlight the usefulness of designed microemulsion approaches for the straightforward synthesis of CoFe2O4-TiO2 nanostructured hybrids.

  3. 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.

  4. 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,

  5. Hybrid Radar Emitter Recognition Based on Rough k-Means Classifier and Relevance Vector Machine

    Science.gov (United States)

    Yang, Zhutian; Wu, Zhilu; Yin, Zhendong; Quan, Taifan; Sun, Hongjian

    2013-01-01

    Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for recognizing radar emitter signals. In this paper, a hybrid recognition approach is presented that classifies radar emitter signals by exploiting the different separability of samples. The proposed approach comprises two steps, namely the primary signal recognition and the advanced signal recognition. In the former step, a novel rough k-means classifier, which comprises three regions, i.e., certain area, rough area and uncertain area, is proposed to cluster the samples of radar emitter signals. In the latter step, the samples within the rough boundary are used to train the relevance vector machine (RVM). Then RVM is used to recognize the samples in the uncertain area; therefore, the classification accuracy is improved. Simulation results show that, for recognizing radar emitter signals, the proposed hybrid recognition approach is more accurate, and presents lower computational complexity than traditional approaches. PMID:23344380

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. 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

  13. 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.

  14. 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

  15. Design-order, non-conformal low-Mach fluid algorithms using a hybrid CVFEM/DG approach

    Science.gov (United States)

    Domino, Stefan P.

    2018-04-01

    A hybrid, design-order sliding mesh algorithm, which uses a control volume finite element method (CVFEM), in conjunction with a discontinuous Galerkin (DG) approach at non-conformal interfaces, is outlined in the context of a low-Mach fluid dynamics equation set. This novel hybrid DG approach is also demonstrated to be compatible with a classic edge-based vertex centered (EBVC) scheme. For the CVFEM, element polynomial, P, promotion is used to extend the low-order P = 1 CVFEM method to higher-order, i.e., P = 2. An equal-order low-Mach pressure-stabilized methodology, with emphasis on the non-conformal interface boundary condition, is presented. A fully implicit matrix solver approach that accounts for the full stencil connectivity across the non-conformal interface is employed. A complete suite of formal verification studies using the method of manufactured solutions (MMS) is performed to verify the order of accuracy of the underlying methodology. The chosen suite of analytical verification cases range from a simple steady diffusion system to a traveling viscous vortex across mixed-order non-conformal interfaces. Results from all verification studies demonstrate either second- or third-order spatial accuracy and, for transient solutions, second-order temporal accuracy. Significant accuracy gains in manufactured solution error norms are noted even with modest promotion of the underlying polynomial order. The paper also demonstrates the CVFEM/DG methodology on two production-like simulation cases that include an inner block subjected to solid rotation, i.e., each of the simulations include a sliding mesh, non-conformal interface. The first production case presented is a turbulent flow past a high-rate-of-rotation cube (Re, 4000; RPM, 3600) on like and mixed-order polynomial interfaces. The final simulation case is a full-scale Vestas V27 225 kW wind turbine (tower and nacelle omitted) in which a hybrid topology, low-order mesh is used. Both production simulations

  16. Hybrid feature selection for supporting lightweight intrusion detection systems

    Science.gov (United States)

    Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

    2017-08-01

    Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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 ...

  3. 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

  4. 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.

  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. 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…

  7. 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.

  8. Optimal energy management for a flywheel-based hybrid vehicle

    NARCIS (Netherlands)

    Berkel, van K.; Hofman, T.; Vroemen, B.G.; Steinbuch, M.

    2011-01-01

    This paper presents the modeling and design of an optimal Energy Management Strategy (EMS) for a flywheel-based hybrid vehicle, that does not use any electrical motor/generator, or a battery, for its hybrid functionalities. The hybrid drive train consists of only low-cost components, such as a

  9. 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.

  10. 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.

  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. 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.

  13. Hybrid and Electric Advanced Vehicle Systems Simulation

    Science.gov (United States)

    Beach, R. F.; Hammond, R. A.; Mcgehee, R. K.

    1985-01-01

    Predefined components connected to represent wide variety of propulsion systems. Hybrid and Electric Advanced Vehicle System (HEAVY) computer program is flexible tool for evaluating performance and cost of electric and hybrid vehicle propulsion systems. Allows designer to quickly, conveniently, and economically predict performance of proposed drive train.

  14. 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)

  15. 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...

  16. Intercultural exchange: an approach to training from a Franco-Canadian perspective.

    Science.gov (United States)

    Parent, Roger

    2007-01-01

    The current challenges of cultural diversity necessitate effective methods for training professionals in health, as well as other sectors, to work with the phenomenon of culture. This paper presents an overview of a semiotic-based approach to training in this regard. Recent publications by Anti Randviir in semiotics on the textual nature of cultural phenomena and by Annabel Levesque on the healthcare issues of Western, French-speaking Canadians provide the methodological frame and basic cultural reference for the overview. The anthropological definition of culture as a 'semiotic', or universe of meaning, offers interdisciplinary common ground for designing practical approaches to cultural analysis, intercultural communication and creativity training. This definition is consistent with convergent findings and research practice in social and cognitive psychology, administrative science, philosophy, ethnography, linguistics and semiotics. Cultural performances such as narrative constitute an effective methodological tool for interdisciplinary data gathering and for analysis of all kinds of cultures: organizational, family, ethnic, regional, transborder, etc. When combined with a functionalist and systemic approach to the study of culture, semiotic approaches to narrative analysis provide useful principles for decoding cultural modes of communication and for designing meaningful change based on cultural specificity.

  17. 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.

  18. 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…

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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)

  7. 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

  8. 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.

  9. 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.

  10. Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

    Science.gov (United States)

    Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

    2018-04-01

    A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

  11. Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

    Science.gov (United States)

    Asaithambi, Sasikumar; Rajappa, Muthaiah

    2018-05-01

    In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

  12. 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.

  13. 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....

  14. The effect of approach/avoidance training on alcohol consumption is mediated by change in alcohol action tendency.

    Directory of Open Access Journals (Sweden)

    Jason M Sharbanee

    Full Text Available Training people to respond to alcohol images by making avoidance joystick movements can affect subsequent alcohol consumption, and has shown initial efficacy as a treatment adjunct. However, the mechanisms that underlie the training's efficacy are unknown. The present study aimed to determine 1 whether the training's effect is mediated by a change in action tendency or a change in selective attention, and 2 whether the training's effect is moderated by individual differences in working memory capacity (WMC. Three groups of social drinkers (total N = 74 completed either approach-alcohol training, avoid-alcohol training or a sham-training on the Approach-Avoidance Task (AAT. Participants' WMC was assessed prior to training, while their alcohol-related action tendency and selective attention were assessed before and after the training on the recently developed Selective-Attention/Action Tendency Task (SA/ATT, before finally completing an alcohol taste-test. There was no significant main effect of approach/avoidance training on alcohol consumption during the taste-test. However, there was a significant indirect effect of training on alcohol consumption mediated by a change in action tendency, but no indirect effect mediated by a change in selective attention. There was inconsistent evidence of WMC moderating training efficacy, with moderation found only for the effect of approach-alcohol training on the AAT but not on the SA/ATT. Thus approach/avoidance training affects alcohol consumption specifically by changing the underlying action tendency. Multiple training sessions may be required in order to observe more substantive changes in drinking behaviour.

  15. 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

  16. 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)

  17. 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.

  18. 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...

  19. Insight and Evidence Motivating the Simplification of Dual-Analysis Hybrid Systems into Single-Analysis Hybrid Systems

    Science.gov (United States)

    Todling, Ricardo; Diniz, F. L. R.; Takacs, L. L.; Suarez, M. J.

    2018-01-01

    Many hybrid data assimilation systems currently used for NWP employ some form of dual-analysis system approach. Typically a hybrid variational analysis is responsible for creating initial conditions for high-resolution forecasts, and an ensemble analysis system is responsible for creating sample perturbations used to form the flow-dependent part of the background error covariance required in the hybrid analysis component. In many of these, the two analysis components employ different methodologies, e.g., variational and ensemble Kalman filter. In such cases, it is not uncommon to have observations treated rather differently between the two analyses components; recentering of the ensemble analysis around the hybrid analysis is used to compensated for such differences. Furthermore, in many cases, the hybrid variational high-resolution system implements some type of four-dimensional approach, whereas the underlying ensemble system relies on a three-dimensional approach, which again introduces discrepancies in the overall system. Connected to these is the expectation that one can reliably estimate observation impact on forecasts issued from hybrid analyses by using an ensemble approach based on the underlying ensemble strategy of dual-analysis systems. Just the realization that the ensemble analysis makes substantially different use of observations as compared to their hybrid counterpart should serve as enough evidence of the implausibility of such expectation. This presentation assembles numerous anecdotal evidence to illustrate the fact that hybrid dual-analysis systems must, at the very minimum, strive for consistent use of the observations in both analysis sub-components. Simpler than that, this work suggests that hybrid systems can reliably be constructed without the need to employ a dual-analysis approach. In practice, the idea of relying on a single analysis system is appealing from a cost-maintenance perspective. More generally, single-analysis systems avoid

  20. 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.

  1. Hybrid Wavelet De-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

    Science.gov (United States)

    WANG, D.; Wang, Y.; Zeng, X.

    2017-12-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

  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. 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…

  4. Modular component kit for hybrid drive systems; Modularer Komponentenbaukasten fuer Hybride Antriebssysteme

    Energy Technology Data Exchange (ETDEWEB)

    Riegger, Peter; Schalk, Johannes; Schmalzing, Claus-Oliver [MTU Friedrichshafen GmbH, Friedrichshafen (Germany). Bereich Forschung Technologieentwicklung

    2013-10-15

    By hybrid drives, fuel consumption in off-road applications can be significantly reduced. However, the additional power train components and degrees of freedom required in the design of hybridised systems involve an increase in system variants. To keep the number of variants as low as possible whilst simultaneously ensuring that hybrid drives can serve as wide a spectrum of applications as possible, MTU has developed a modular system of components. This makes it possible to use customer requirements as a basis for creating innovative drive systems for the widest range of applications. (orig.)

  5. 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)

  6. Comparison of different vehicle power trains

    Science.gov (United States)

    Mizsey, Peter; Newson, Esmond

    Four different alternatives of mobile power train developments (hybrid diesel, fuel cell operating with hydrogen produced on a petrochemical basis, methanol reformer-fuel cell system, gasoline reformer-fuel cell system), are compared with the gasoline internal combustion engine (ICE), for well-to-wheel efficiencies, CO 2 emissions, and investment costs. Although the ICE requires the lowest investment cost, it is not competitive in well-to-wheel efficiencies and less favourable than the above alternatives for CO 2 emissions. The hybrid diesel power train has the highest well-to-wheel efficiency (30%), but its well-to-wheel carbon dioxide emission is similar to that of the fuel cell power train operated with compressed hydrogen produced on a centralised petrochemical basis. This latter case, however, has the advantage over the hybrid diesel power train that the carbon dioxide emission is concentrated and easier to control than the several point-like sources of emissions. Among the five cases studied only the on-board reforming of methanol offers the possibility of using a renewable energy source (biomass).

  7. 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.

  8. 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…

  9. An Approach to Evaluate Stability for Cable-Based Parallel Camera Robots with Hybrid Tension-Stiffness Properties

    Directory of Open Access Journals (Sweden)

    Huiling Wei

    2015-12-01

    Full Text Available This paper focuses on studying the effect of cable tensions and stiffness on the stability of cable-based parallel camera robots. For this purpose, the tension factor and the stiffness factor are defined, and the expression of stability is deduced. A new approach is proposed to calculate the hybrid-stability index with the minimum cable tension and the minimum singular value. Firstly, the kinematic model of a cable-based parallel camera robot is established. Based on the model, the tensions are solved and a tension factor is defined. In order to obtain the tension factor, an optimization of the cable tensions is carried out. Then, an expression of the system's stiffness is deduced and a stiffness factor is defined. Furthermore, an approach to evaluate the stability of the cable-based camera robots with hybrid tension-stiffness properties is presented. Finally, a typical three-degree-of-freedom cable-based parallel camera robot with four cables is studied as a numerical example. The simulation results show that the approach is both reasonable and effective.

  10. Adaptive control using a hybrid-neural model: application to a polymerisation reactor

    Directory of Open Access Journals (Sweden)

    Cubillos F.

    2001-01-01

    Full Text Available This work presents the use of a hybrid-neural model for predictive control of a plug flow polymerisation reactor. The hybrid-neural model (HNM is based on fundamental conservation laws associated with a neural network (NN used to model the uncertain parameters. By simulations, the performance of this approach was studied for a peroxide-initiated styrene tubular reactor. The HNM was synthesised for a CSTR reactor with a radial basis function neural net (RBFN used to estimate the reaction rates recursively. The adaptive HNM was incorporated in two model predictive control strategies, a direct synthesis scheme and an optimum steady state scheme. Tests for servo and regulator control showed excellent behaviour following different setpoint variations, and rejecting perturbations. The good generalisation and training capacities of hybrid models, associated with the simplicity and robustness characteristics of the MPC formulations, make an attractive combination for the control of a polymerisation reactor.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. Hybrid Teaching in Extension: Learning at the Crossroads

    Science.gov (United States)

    Hino, Jeff; Kahn, Cub

    2016-01-01

    Extension clients' learning preferences are changing, with many increasingly going online for educational content. In response, Oregon State University Extension pilot tested a training program for Extension educators to explore hybrid teaching--a methodology that could provide more flexible access to a wider audience. Hybrid teaching offers a…

  16. 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.

  17. 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)

  18. Mechanical design of a free-wheel clutch for the thermal engine of a parallel hybrid vehicle with thermal and electrical power-train; Conception mecanique d'un accouplement a roue libre pour le moteur thermique d'un vehicule hybride parallele thermique et electrique

    Energy Technology Data Exchange (ETDEWEB)

    Santin, J.J.

    2001-07-01

    This thesis deals with the design of a free-wheel clutch. This unit is intended to replace the automated dry single-plate clutch of a parallel hybrid car with thermal and electric power-train. Furthermore, the car is a single shaft zero emission vehicle fitted with a controlled gearbox. Chapter one focuses on the type of hybrid vehicle studied. It shows the need to isolate the engine from the rest of the drive train, depending on the driving conditions. Chapter two presents and compares the two alternatives: automated clutch and free-wheel. In order to develop the free-wheel option, the torsional vibrations in the automotive drive line had to be closely studied. It required the design of a specific modular tool, as presented in chapter three, with the help of MATLAB SIMULINK. Lastly, chapter four shows how this tool was used during the design stage and specifies the way to build it. The free-wheel is then to be fitted to a prototype hybrid vehicle, constructed by both the LAMIH and PSA. (author)

  19. Toyota hybrid synergy drive

    Energy Technology Data Exchange (ETDEWEB)

    Gautschi, H.

    2008-07-01

    This presentation made at the Swiss 2008 research conference on traffic by Hannes Gautschi, director of service and training at the Toyota company in Switzerland, takes a look at Toyota's hybrid drive vehicles. The construction of the vehicles and their combined combustion engines and electric generators and drives is presented and the combined operation of these components is described. Braking and energy recovery are discussed. Figures on the performance, fuel consumption and CO{sub 2} output of the hybrid vehicles are compared with those of conventional vehicles.

  20. Model-based verification method for solving the parameter uncertainty in the train control system

    International Nuclear Information System (INIS)

    Cheng, Ruijun; Zhou, Jin; Chen, Dewang; Song, Yongduan

    2016-01-01

    This paper presents a parameter analysis method to solve the parameter uncertainty problem for hybrid system and explore the correlation of key parameters for distributed control system. For improving the reusability of control model, the proposed approach provides the support for obtaining the constraint sets of all uncertain parameters in the abstract linear hybrid automata (LHA) model when satisfying the safety requirements of the train control system. Then, in order to solve the state space explosion problem, the online verification method is proposed to monitor the operating status of high-speed trains online because of the real-time property of the train control system. Furthermore, we construct the LHA formal models of train tracking model and movement authority (MA) generation process as cases to illustrate the effectiveness and efficiency of the proposed method. In the first case, we obtain the constraint sets of uncertain parameters to avoid collision between trains. In the second case, the correlation of position report cycle and MA generation cycle is analyzed under both the normal and the abnormal condition influenced by packet-loss factor. Finally, considering stochastic characterization of time distributions and real-time feature of moving block control system, the transient probabilities of wireless communication process are obtained by stochastic time petri nets. - Highlights: • We solve the parameters uncertainty problem by using model-based method. • We acquire the parameter constraint sets by verifying linear hybrid automata models. • Online verification algorithms are designed to monitor the high-speed trains. • We analyze the correlation of key parameters and uncritical parameters. • The transient probabilities are obtained by using reliability analysis.

  1. 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.

  2. 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)

  3. Rule-based energy management strategies for hybrid vehicles

    NARCIS (Netherlands)

    Hofman, T.; Druten, van R.M.; Serrarens, A.F.A.; Steinbuch, M.

    2007-01-01

    Int. J. of Electric and Hybrid Vehicles (IJEHV), The highest control layer of a (hybrid) vehicular drive train is termed the Energy Management Strategy (EMS). In this paper an overview of different control methods is given and a new rule-based EMS is introduced based on the combination of Rule-Based

  4. 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.

  5. Real Time Energy Management Control Strategies for Hybrid Powertrains

    Science.gov (United States)

    Zaher, Mohamed Hegazi Mohamed

    In order to improve fuel efficiency and reduce emissions of mobile vehicles, various hybrid power-train concepts have been developed over the years. This thesis focuses on embedded control of hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real time energy management strategy for continuous operations. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, or the motion is driven by gravitational force, or load driven. There are three main concepts for regernerative energy storing devices in hybrid vehicles: electric, hydraulic, and flywheel. The real time control challenge is to balance the system power demand from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle, while making optimal use of the energy saving opportunities in a given operational, often repetitive cycle. In the worst case scenario, only engine is used and hybrid system completely disabled. A rule based control is developed and tuned for different work cycles and linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the machine and its position via GPS, and maps them to the gains.

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. Time-dependent mass of cosmological perturbations in the hybrid and dressed metric approaches to loop quantum cosmology

    Science.gov (United States)

    Elizaga Navascués, Beatriz; Martín de Blas, Daniel; Mena Marugán, Guillermo A.

    2018-02-01

    Loop quantum cosmology has recently been applied in order to extend the analysis of primordial perturbations to the Planck era and discuss the possible effects of quantum geometry on the cosmic microwave background. Two approaches to loop quantum cosmology with admissible ultraviolet behavior leading to predictions that are compatible with observations are the so-called hybrid and dressed metric approaches. In spite of their similarities and relations, we show in this work that the effective equations that they provide for the evolution of the tensor and scalar perturbations are somewhat different. When backreaction is neglected, the discrepancy appears only in the time-dependent mass term of the corresponding field equations. We explain the origin of this difference, arising from the distinct quantization procedures. Besides, given the privileged role that the big bounce plays in loop quantum cosmology, e.g. as a natural instant of time to set initial conditions for the perturbations, we also analyze the positivity of the time-dependent mass when this bounce occurs. We prove that the mass of the tensor perturbations is positive in the hybrid approach when the kinetic contribution to the energy density of the inflaton dominates over its potential, as well as for a considerably large sector of backgrounds around that situation, while this mass is always nonpositive in the dressed metric approach. Similar results are demonstrated for the scalar perturbations in a sector of background solutions that includes the kinetically dominated ones; namely, the mass then is positive for the hybrid approach, whereas it typically becomes negative in the dressed metric case. More precisely, this last statement is strictly valid when the potential is quadratic for values of the inflaton mass that are phenomenologically favored.

  11. 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.

  12. Hybrid brain-computer interfaces and hybrid neuroprostheses for restoration of upper limb functions in individuals with high-level spinal cord injury.

    Science.gov (United States)

    Rohm, Martin; Schneiders, Matthias; Müller, Constantin; Kreilinger, Alex; Kaiser, Vera; Müller-Putz, Gernot R; Rupp, Rüdiger

    2013-10-01

    The bilateral loss of the grasp function associated with a lesion of the cervical spinal cord severely limits the affected individuals' ability to live independently and return to gainful employment after sustaining a spinal cord injury (SCI). Any improvement in lost or limited grasp function is highly desirable. With current neuroprostheses, relevant improvements can be achieved in end users with preserved shoulder and elbow, but missing hand function. The aim of this single case study is to show that (1) with the support of hybrid neuroprostheses combining functional electrical stimulation (FES) with orthoses, restoration of hand, finger and elbow function is possible in users with high-level SCI and (2) shared control principles can be effectively used to allow for a brain-computer interface (BCI) control, even if only moderate BCI performance is achieved after extensive training. The individual in this study is a right-handed 41-year-old man who sustained a traumatic SCI in 2009 and has a complete motor and sensory lesion at the level of C4. He is unable to generate functionally relevant movements of the elbow, hand and fingers on either side. He underwent extensive FES training (30-45min, 2-3 times per week for 6 months) and motor imagery (MI) BCI training (415 runs in 43 sessions over 12 months). To meet individual needs, the system was designed in a modular fashion including an intelligent control approach encompassing two input modalities, namely an MI-BCI and shoulder movements. After one year of training, the end user's MI-BCI performance ranged from 50% to 93% (average: 70.5%). The performance of the hybrid system was evaluated with different functional assessments. The user was able to transfer objects of the grasp-and-release-test and he succeeded in eating a pretzel stick, signing a document and eating an ice cream cone, which he was unable to do without the system. This proof-of-concept study has demonstrated that with the support of hybrid FES

  13. MTU hybrid powerpack for railcars

    Energy Technology Data Exchange (ETDEWEB)

    Lehmann, Ingo; Schmalzing, Claus-Oliver [MTU Friedrichshafen GmbH (Germany); Werner, Claus [DB RegioNetz Verkehrs GmbH (Germany); Bold, Uwe [DB Systemtechnik Engineering Kassel (Germany)

    2011-11-15

    Up to 25 percent lower fuel consumption and emission-free train movements in station areas are possible with the MTU hybrid drive system. First field tests on tracks of the Deutsche Bahn started in autumn 2011. (orig.)

  14. 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

  15. OPTIMISATION OF BUFFER SIZE FOR ENHANCING QOS OF VIDEO TRAFFIC USING CROSS LAYERED HYBRID TRANSPORT LAYER PROTOCOL APPROACH

    Directory of Open Access Journals (Sweden)

    S. Matilda

    2011-03-01

    Full Text Available Video streaming is gaining importance, with the wide popularity of multimedia rich applications in the Internet. Video streams are delay sensitive and require seamless flow for continuous visualization. Properly designed buffers offer a solution to queuing delay. The diagonally opposite QoS metrics associated with video traffic poses an optimization problem, in the design of buffers. This paper is a continuation of our previous work [1] and deals with the design of buffers. It aims at finding the optimum buffer size for enhancing QoS offered to video traffic. Network-centric QoS provisioning approach, along with hybrid transport layer protocol approach is adopted, to arrive at an optimum size which is independent of RTT. In this combinational approach, buffers of routers and end devices are designed to satisfy the various QoS parameters at the transport layer. OPNET Modeler is used to simulate environments for testing the design. Based on the results of simulation it is evident that the hybrid transport layer protocol approach is best suited for transmitting video traffic as it supports the economical design.

  16. 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).

  17. 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.

  18. A Gold Standards Approach to Training Instructors to Evaluate Crew Performance

    Science.gov (United States)

    Baker, David P.; Dismukes, R. Key

    2003-01-01

    The Advanced Qualification Program requires that airlines evaluate crew performance in Line Oriented Simulation. For this evaluation to be meaningful, instructors must observe relevant crew behaviors and evaluate those behaviors consistently and accurately against standards established by the airline. The airline industry has largely settled on an approach in which instructors evaluate crew performance on a series of event sets, using standardized grade sheets on which behaviors specific to event set are listed. Typically, new instructors are given a class in which they learn to use the grade sheets and practice evaluating crew performance observed on videotapes. These classes emphasize reliability, providing detailed instruction and practice in scoring so that all instructors within a given class will give similar scores to similar performance. This approach has value but also has important limitations; (1) ratings within one class of new instructors may differ from those of other classes; (2) ratings may not be driven primarily by the specific behaviors on which the company wanted the crews to be scored; and (3) ratings may not be calibrated to company standards for level of performance skill required. In this paper we provide a method to extend the existing method of training instructors to address these three limitations. We call this method the "gold standards" approach because it uses ratings from the company's most experienced instructors as the basis for training rater accuracy. This approach ties the training to the specific behaviors on which the experienced instructors based their ratings.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. A PSO based Artificial Neural Network approach for short term unit commitment problem

    Directory of Open Access Journals (Sweden)

    AFTAB AHMAD

    2010-10-01

    Full Text Available Unit commitment (UC is a non-linear, large scale, complex, mixed-integer combinatorial constrained optimization problem. This paper proposes, a new hybrid approach for generating unit commitment schedules using swarm intelligence learning rule based neural network. The training data has been generated using dynamic programming for machines without valve point effects and using genetic algorithm for machines with valve point effects. A set of load patterns as inputs and the corresponding unit generation schedules as outputs are used to train the network. The neural network fine tunes the best results to the desired targets. The proposed approach has been validated for three thermal machines with valve point effects and without valve point effects. The results are compared with the approaches available in the literature. The PSO-ANN trained model gives better results which show the promise of the proposed methodology.

  5. 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.

  6. 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...

  7. 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…

  8. 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...

  9. 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.

  10. 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.

  11. Analysis of a gas turbine driven hybrid drive system for heavy vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Malmquist, Anders

    1999-07-01

    The goal of this thesis has been to analyze the performance and behavior of a gas turbine driven hybrid drive train. The thesis covers both computer simulations and experimental tests. In two case studies, a number of measurements have been made on gas turbine driven hybrid vehicles that are developed by Volvo and ABB. In the recent years, much effort is currently put into the design and analysis of hybrid drive trains. Many studies involve computer simulations, but they are often made on a general level. This thesis concentrate on gas turbine driven hybrids for heavy vehicles, a field that has previously not been covered to a large extent in academic studies. A major contribution to the field of hybrid drive train design is the development of detailed simulation models that have a close connection to hybrids that are actually built and tested. The access to detailed gas turbine data has further enhanced the possibility to design a dynamic model of the gas turbine driven and the electric circuits. The combination of simulations and extensive field experience gains new knowledge on the properties of gas turbines in hybrid drive trains. Two simulation models have been developed in Matlab and Simulink. One is a quasi-steady state model that can be used for drive cycle simulations, e.g. a complete bus line. The other is a transient model that combines the thermodynamic properties of the gas turbine, the mechanical properties of the combined turbine-generator shaft, the electric power circuit and the control system. The transient model has been used to simulate the power response during accelerations and retardation. An analysis of the internal energy flows and the system efficiency of a hybrid drive train contributes to the understanding of the properties of series hybrid drive trains. An important part of the topology is that the system is based on a DC/DC-converter that is connected between the battery and the DC-bus. It controls the DC-bus voltage and by this

  12. 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"…

  13. 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)

  14. 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

  15. 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.

  16. Modeling and design of hybrid vehicle propulsion systems for passenger cars

    NARCIS (Netherlands)

    Hofman, Theo; Steinbuch, Maarten; Van Dritten, Roëll; Serrarens, Alex

    2007-01-01

    Designing a hybrid drive train implies, that choices have to be made regarding the drive train structure, component technologies, and - sizes. Designing an appropriate Energy Management Strategy (EMS), that facilitates the usage of the chosen components and drive train structure to its best

  17. 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.

  18. 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

  19. Modeling and Design of a medium-duty hybrid electric truck

    NARCIS (Netherlands)

    Hofman, T.; Serrarens, A.F.A.; Druten, van R.M.; Steinbuch, M.

    2007-01-01

    In this paper the effect of vehicular drive train hybridization for a medium-duty hybrid electrictruck (7 ton) on fuel economy and performance (i.e., acceleration and gradability) is investigatedby changing the size of the power sources. Furthermore, the influence of optimal component sizingof a

  20. 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

  1. 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

  2. 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.

  3. A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

    Directory of Open Access Journals (Sweden)

    Abdullah M. Iliyasu

    2017-12-01

    Full Text Available A quantum hybrid (QH intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN algorithm (known simply as the Q-Fuzzy approach is proposed for efficient feature selection and classification of cells in cervical smeared (CS images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach. In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

  4. Decrease of spasticity after hybrid assistive limb® training for a patient with C4 quadriplegia due to chronic SCI.

    Science.gov (United States)

    Ikumi, Akira; Kubota, Shigeki; Shimizu, Yukiyo; Kadone, Hideki; Marushima, Aiki; Ueno, Tomoyuki; Kawamoto, Hiroaki; Hada, Yasushi; Matsumura, Akira; Sankai, Yoshiyuki; Yamazaki, Masashi

    2017-09-01

    Recently, locomotor training with robotic assistance has been found effective in treating spinal cord injury (SCI). Our case report examined locomotor training using the robotic suit hybrid assistive limb (HAL) in a patient with complete C4 quadriplegia due to chronic SCI. This is the first report examining HAL in complete C4 quadriplegia. The patient was a 19-year-old man who dislocated C3/4 during judo 4 years previously. Following the injury, he underwent C3/4 posterior spinal fusion but remained paralyzed despite rehabilitation. There was muscle atrophy under C5 level and no sensation around the anus, but partial sensation of pressure remained in the limbs. The American Spinal Injury Association impairment scale was Grade A (complete motor C4 lesion). HAL training was administered in 10 sessions (twice per week). The training sessions consisted of treadmill walking with HAL. For safety, 2 physicians and 1 therapist supported the subject for balance and weight-bearing. The device's cybernic autonomous control mode provides autonomic physical support based on predefined walking patterns. We evaluated the adverse events, walking time and distance, and the difference in muscle spasticity before and after HAL-training using a modified Ashworth scale (mAs). No adverse events were observed that required discontinuation of rehabilitation. Walking distance and time increased from 25.2 meters/7.6 minutes to 148.3 meter/15 minutes. The mAs score decreased after HAL training. Our case report indicates that HAL training is feasible and effective for complete C4 quadriplegia in chronic SCI.

  5. Cardiac hybrid imaging

    Energy Technology Data Exchange (ETDEWEB)

    Gaemperli, Oliver [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); University Hospital Zurich, Nuclear Cardiology, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland)

    2014-05-15

    Hybrid cardiac single photon emission computed tomography (SPECT)/CT imaging allows combined assessment of anatomical and functional aspects of cardiac disease. In coronary artery disease (CAD), hybrid SPECT/CT imaging allows detection of coronary artery stenosis and myocardial perfusion abnormalities. The clinical value of hybrid imaging has been documented in several subsets of patients. In selected groups of patients, hybrid imaging improves the diagnostic accuracy to detect CAD compared to the single imaging techniques. Additionally, this approach facilitates functional interrogation of coronary stenoses and guidance with regard to revascularization procedures. Moreover, the anatomical information obtained from CT coronary angiography or coronary artery calcium scores (CACS) adds prognostic information over perfusion data from SPECT. The use of cardiac hybrid imaging has been favoured by the dissemination of dedicated hybrid systems and the release of dedicated image fusion software, which allow simple patient throughput for hybrid SPECT/CT studies. Further technological improvements such as more efficient detector technology to allow for low-radiation protocols, ultra-fast image acquisition and improved low-noise image reconstruction algorithms will be instrumental to further promote hybrid SPECT/CT in research and clinical practice. (orig.)

  6. 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...

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. Hybrid simulation models of production networks

    CERN Document Server

    Kouikoglou, Vassilis S

    2001-01-01

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

  13. Optical hybrid quantum teleportation and its applications

    Science.gov (United States)

    Takeda, Shuntaro; Okada, Masanori; Furusawa, Akira

    2017-08-01

    Quantum teleportation, a transfer protocol of quantum states, is the essence of many sophisticated quantum information protocols. There have been two complementary approaches to optical quantum teleportation: discrete variables (DVs) and continuous variables (CVs). However, both approaches have pros and cons. Here we take a "hybrid" approach to overcome the current limitations: CV quantum teleportation of DVs. This approach enabled the first realization of deterministic quantum teleportation of photonic qubits without post-selection. We also applied the hybrid scheme to several experiments, including entanglement swapping between DVs and CVs, conditional CV teleportation of single photons, and CV teleportation of qutrits. We are now aiming at universal, scalable, and fault-tolerant quantum computing based on these hybrid technologies.

  14. 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.

  15. Evaluating response shift in training evaluation: comparing the retrospective pretest with an adapted measurement invariance approach in a classroom management training program.

    Science.gov (United States)

    Piwowar, Valentina; Thiel, Felicitas

    2014-10-01

    Response shift (RS) can threaten the internal validity of pre-post designs. As RS may indicate a redefinition of the target construct, its occurrence in training evaluation is rather likely. The most common approach to deal with RS is to implement a retrospective pretest (then-test) instead of the traditional pre-test. In health psychology, an adapted measurement invariance approach (MIad) was developed as an alternative technique to study RS. Results produced by identifying RS with the two approaches were rarely studied simultaneously or within an experimental framework. To study RS in two different treatment conditions and compare results produced by both techniques in identifying various types of RS. We further studied validity aspects of the then-test. We evaluated RS by applying the then-test procedure (TP) and the measurement invariance apporach MIad within an experimental design: Participants either attended a short-term or a long-term classroom management training program. Participants were 146 student teachers in their first year of master's study. Pre (before training), post, and then self-ratings (after training) on classroom management knowledge were administered. Results indicated that the two approaches do not yield the same results. The MIad identified more and also group-specific RS as opposed to the findings of the TP, which found less and only little evidence for group-specific RS. Further research is needed to study the usability and validity of the respective approaches. In particular, the usability of the then-test seems to be challenged. © The Author(s) 2014.

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks

    Science.gov (United States)

    Wagstaff, Kiri L.; Sosnowski, Scott; Lane, Terran

    2012-01-01

    Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events as well as faster responses, such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if learners at individual nodes can communicate with their neighbors. In previous work, methods were developed by which classification algorithms deployed at sensor nodes can communicate information about event labels to each other, building on prior work with co-training, self-training, and active learning. The idea of collaborative learning was extended to function for clustering algorithms as well, similar to ideas from penta-training and consensus clustering. However, collaboration between these learner types had not been explored. A new protocol was developed by which classifiers and clusterers can share key information about their observations and conclusions as they learn. This is an active collaboration in which learners of either type can query their neighbors for information that they then use to re-train or re-learn the concept they are studying. The protocol also supports broadcasts from the classifiers and clusterers to the rest of the network to announce new discoveries. Classifiers observe an event and assign it a label (type). Clusterers instead group observations into clusters without assigning them a label, and they collaborate in terms of pairwise constraints between two events [same-cluster (mustlink) or different-cluster (cannot-link)]. Fundamentally, these two learner types speak different languages. To bridge this gap, the new communication protocol provides four types of exchanges: hybrid queries for information, hybrid "broadcasts" of learned information, each specified for classifiers-to-clusterers, and clusterers

  1. 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)

  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. 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...

  4. 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

  5. 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…

  6. 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.

  7. 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.

  8. Adaptive hybrid brain-computer interaction: ask a trainer for assistance!

    Science.gov (United States)

    Müller-Putz, Gernot R; Steyrl, David; Faller, Josef

    2014-01-01

    In applying mental imagery brain-computer interfaces (BCIs) to end users, training is a key part for novice users to get control. In general learning situations, it is an established concept that a trainer assists a trainee to improve his/her aptitude in certain skills. In this work, we want to evaluate whether we can apply this concept in the context of event-related desynchronization (ERD) based, adaptive, hybrid BCIs. Hence, in a first session we merged the features of a high aptitude BCI user, a trainer, and a novice user, the trainee, in a closed-loop BCI feedback task and automatically adapted the classifier over time. In a second session the trainees operated the system unassisted. Twelve healthy participants ran through this protocol. Along with the trainer, the trainees achieved a very high overall peak accuracy of 95.3 %. In the second session, where users operated the BCI unassisted, they still achieved a high overall peak accuracy of 83.6%. Ten of twelve first time BCI users successfully achieved significantly better than chance accuracy. Concluding, we can say that this trainer-trainee approach is very promising. Future research should investigate, whether this approach is superior to conventional training approaches. This trainer-trainee concept could have potential for future application of BCIs to end users.

  9. 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

  10. Autogenic Training as a behavioural approach to insomnia: a prospective cohort study.

    Science.gov (United States)

    Bowden, Ann; Lorenc, Ava; Robinson, Nicola

    2012-04-01

    Insomnia is commonly associated with chronic health problems. Behavioural and cognitive factors often perpetuate a vicious cycle of anxiety and sleep disturbance, leading to long-term insomnia. National Institute for Health and Clinical Excellence currently recommends behavioural approaches before prescribing hypnotics. Behavioural approaches aim to treat underlying causes, but are not widely available. Research usually includes patients diagnosed with insomnia rather than secondary, co-morbid sleep- related problems. To examine the effectiveness of autogenic training (AT) as a non-drug approach to sleep-related problems associated with chronic ill health. Prospective pre- and post-treatment cohort study. AT centre, Royal London Hospital for Integrated Medicine, University College London Hospitals NHS Foundation Trust. All patients referred for AT from April 2007 to April 2008 were invited to participate. Participants received standard 8-week training, with no specific focus on sleep. Sleep questionnaires were administered at four time points, 'Measure Your Medical Outcome Profile' (MYMOP) and Hospital Anxiety and Depression Scale, before and after treatment. Results before and after treatment were compared. Camden and Islington Community Local Research and Ethics Committee approved the study. The AT course was completed by 153 participants, of whom 73% were identified as having a sleep-related problem. Improvements in sleep patterns included: sleep onset latency (P = 0.049), falling asleep quicker after night waking (P training. AT may provide an approach to insomnia that could be incorporated into primary care.

  11. Genomic networks of hybrid sterility.

    Science.gov (United States)

    Turner, Leslie M; White, Michael A; Tautz, Diethard; Payseur, Bret A

    2014-02-01

    Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities"). The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus) provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is applicable in a broad

  12. 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.

  13. 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.

  14. Electrical potential-assisted DNA hybridization. How to mitigate electrostatics for surface DNA hybridization.

    Science.gov (United States)

    Tymoczko, Jakub; Schuhmann, Wolfgang; Gebala, Magdalena

    2014-12-24

    Surface-confined DNA hybridization reactions are sensitive to the number and identity of DNA capture probes and experimental conditions such as the nature and the ionic strength of the electrolyte solution. When the surface probe density is high or the concentration of bulk ions is much lower than the concentration of ions within the DNA layer, hybridization is significantly slowed down or does not proceed at all. However, high-density DNA monolayers are attractive for designing high-sensitivity DNA sensors. Thus, circumventing sluggish DNA hybridization on such interfaces allows a high surface concentration of target DNA and improved signal/noise ratio. We present potential-assisted hybridization as a strategy in which an external voltage is applied to the ssDNA-modified interface during the hybridization process. Results show that a significant enhancement of hybridization can be achieved using this approach.

  15. Optimizing Thermal-Elastic Properties of C/C–SiC Composites Using a Hybrid Approach and PSO Algorithm

    Science.gov (United States)

    Xu, Yingjie; Gao, Tian

    2016-01-01

    Carbon fiber-reinforced multi-layered pyrocarbon–silicon carbide matrix (C/C–SiC) composites are widely used in aerospace structures. The complicated spatial architecture and material heterogeneity of C/C–SiC composites constitute the challenge for tailoring their properties. Thus, discovering the intrinsic relations between the properties and the microstructures and sequentially optimizing the microstructures to obtain composites with the best performances becomes the key for practical applications. The objective of this work is to optimize the thermal-elastic properties of unidirectional C/C–SiC composites by controlling the multi-layered matrix thicknesses. A hybrid approach based on micromechanical modeling and back propagation (BP) neural network is proposed to predict the thermal-elastic properties of composites. Then, a particle swarm optimization (PSO) algorithm is interfaced with this hybrid model to achieve the optimal design for minimizing the coefficient of thermal expansion (CTE) of composites with the constraint of elastic modulus. Numerical examples demonstrate the effectiveness of the proposed hybrid model and optimization method. PMID:28773343

  16. 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.

  17. “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.

  18. New EDF approach to the mentification of NPP personnel training needs

    International Nuclear Information System (INIS)

    Hazet, Jean-Christophe

    2003-01-01

    The EDF ambition today is to be among the best electricity producers in the world. To do so, we have to take more responsibilities, to motivate and to give our employees a better level of competence, and to make them more involved in the culture and the success of our company. In order to reach these objectives a deeper analysis of the NPP training needs must be completed. Our answer, named 'Local Competencies Development System' (LCDS) consists in implementing a large decentralisation of the competencies management, done by the EDF Production Department in conjunction with the EDF Training Department. It takes place in a logical approach bound up with the historical development of our nuclear program. In addition to this LCDS a new organization of training centers instructors, in dedicated training teams, has been implemented in order to co-ordinate the different actions directly with the NPP. The purpose of this presentation is to take into account the LCDS on the operation personnel training side, a similar organization has been implemented for the maintenance side

  19. 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.

  20. Self-regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison Between Professional Training and English Learning.

    Science.gov (United States)

    Tseng, Min-Chen; Chen, Chia-Cheng

    2017-06-01

    This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between students' professional training and English learning. The participants consisted of 344 arts majors. The Academic Self-Regulation Questionnaire and the Revised Learning Process Questionnaire were adopted to examine students' self-regulatory behaviors and their approaches to learning. The results show that a positive and significant correlation was found in students' self-regulatory behaviors between professional training and English learning. The results indicated that increases in using self-regulatory behaviors in professional training were associated with increases in applying self-regulatory behaviors in learning English. Seeking assistance, self-evaluation, and planning and organizing were significant predictors for learning English. In addition, arts students used the deep approach more often than the surface approach in both their professional training and English learning. A positive correlation was found in DA, whereas a negative correlation was shown in SA between students' self-regulatory behaviors and their approaches to learning. Students with high self-regulation adopted a deep approach, and they applied the surface approach less in professional training and English learning. In addition, a SEM model confirmed that DA had a positive influence; however, SA had a negative influence on self-regulatory behaviors.

  1. 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.

  2. Hydrogen atom as a quantum-classical hybrid system

    International Nuclear Information System (INIS)

    Zhan, Fei; Wu, Biao

    2013-01-01

    Hydrogen atom is studied as a quantum-classical hybrid system, where the proton is treated as a classical object while the electron is regarded as a quantum object. We use a well known mean-field approach to describe this hybrid hydrogen atom; the resulting dynamics for the electron and the proton is compared to their full quantum dynamics. The electron dynamics in the hybrid description is found to be only marginally different from its full quantum counterpart. The situation is very different for the proton: in the hybrid description, the proton behaves like a free particle; in the fully quantum description, the wave packet center of the proton orbits around the center of mass. Furthermore, we find that the failure to describe the proton dynamics properly can be regarded as a manifestation of the fact that there is no conservation of momentum in the mean-field hybrid approach. We expect that such a failure is a common feature for all existing approaches for quantum-classical hybrid systems of Born-Oppenheimer type.

  3. Aerodynamic Shape Optimization Design of Wing-Body Configuration Using a Hybrid FFD-RBF Parameterization Approach

    Science.gov (United States)

    Liu, Yuefeng; Duan, Zhuoyi; Chen, Song

    2017-10-01

    Aerodynamic shape optimization design aiming at improving the efficiency of an aircraft has always been a challenging task, especially when the configuration is complex. In this paper, a hybrid FFD-RBF surface parameterization approach has been proposed for designing a civil transport wing-body configuration. This approach is simple and efficient, with the FFD technique used for parameterizing the wing shape and the RBF interpolation approach used for handling the wing body junction part updating. Furthermore, combined with Cuckoo Search algorithm and Kriging surrogate model with expected improvement adaptive sampling criterion, an aerodynamic shape optimization design system has been established. Finally, the aerodynamic shape optimization design on DLR F4 wing-body configuration has been carried out as a study case, and the result has shown that the approach proposed in this paper is of good effectiveness.

  4. Train Stop Scheduling in a High-Speed Rail Network by Utilizing a Two-Stage Approach

    Directory of Open Access Journals (Sweden)

    Huiling Fu

    2012-01-01

    Full Text Available Among the most commonly used methods of scheduling train stops are practical experience and various “one-step” optimal models. These methods face problems of direct transferability and computational complexity when considering a large-scale high-speed rail (HSR network such as the one in China. This paper introduces a two-stage approach for train stop scheduling with a goal of efficiently organizing passenger traffic into a rational train stop pattern combination while retaining features of regularity, connectivity, and rapidity (RCR. Based on a three-level station classification definition, a mixed integer programming model and a train operating tactics descriptive model along with the computing algorithm are developed and presented for the two stages. A real-world numerical example is presented using the Chinese HSR network as the setting. The performance of the train stop schedule and the applicability of the proposed approach are evaluated from the perspective of maintaining RCR.

  5. Hybrid Reality Lab Capabilities - Video 2

    Science.gov (United States)

    Delgado, Francisco J.; Noyes, Matthew

    2016-01-01

    Our Hybrid Reality and Advanced Operations Lab is developing incredibly realistic and immersive systems that could be used to provide training, support engineering analysis, and augment data collection for various human performance metrics at NASA. To get a better understanding of what Hybrid Reality is, let's go through the two most commonly known types of immersive realities: Virtual Reality, and Augmented Reality. Virtual Reality creates immersive scenes that are completely made up of digital information. This technology has been used to train astronauts at NASA, used during teleoperation of remote assets (arms, rovers, robots, etc.) and other activities. One challenge with Virtual Reality is that if you are using it for real time-applications (like landing an airplane) then the information used to create the virtual scenes can be old (i.e. visualized long after physical objects moved in the scene) and not accurate enough to land the airplane safely. This is where Augmented Reality comes in. Augmented Reality takes real-time environment information (from a camera, or see through window, and places digitally created information into the scene so that it matches with the video/glass information). Augmented Reality enhances real environment information collected with a live sensor or viewport (e.g. camera, window, etc.) with the information-rich visualization provided by Virtual Reality. Hybrid Reality takes Augmented Reality even further, by creating a higher level of immersion where interactivity can take place. Hybrid Reality takes Virtual Reality objects and a trackable, physical representation of those objects, places them in the same coordinate system, and allows people to interact with both objects' representations (virtual and physical) simultaneously. After a short period of adjustment, the individuals begin to interact with all the objects in the scene as if they were real-life objects. The ability to physically touch and interact with digitally created

  6. A Meta-analytic Comparison of Face-to-Face and Online Delivery in Ethics Instruction: The Case for a Hybrid Approach.

    Science.gov (United States)

    Todd, E Michelle; Watts, Logan L; Mulhearn, Tyler J; Torrence, Brett S; Turner, Megan R; Connelly, Shane; Mumford, Michael D

    2017-12-01

    Despite the growing body of literature on training in the responsible conduct of research, few studies have examined the effectiveness of delivery formats used in ethics courses (i.e., face-to-face, online, hybrid). The present effort sought to address this gap in the literature through a meta-analytic review of 66 empirical studies, representing 106 ethics courses and 10,069 participants. The frequency and effectiveness of 67 instructional and process-based content areas were also assessed for each delivery format. Process-based contents were best delivered face-to-face, whereas contents delivered online were most effective when restricted to compliance-based instructional contents. Overall, hybrid courses were found to be most effective, suggesting that ethics courses are best delivered using a blend of formats and content areas. Implications and recommendations for future development of ethics education courses in the sciences are discussed.

  7. Hybrid Arrays for Chemical Sensing

    Science.gov (United States)

    Kramer, Kirsten E.; Rose-Pehrsson, Susan L.; Johnson, Kevin J.; Minor, Christian P.

    In recent years, multisensory approaches to environment monitoring for chemical detection as well as other forms of situational awareness have become increasingly popular. A hybrid sensor is a multimodal system that incorporates several sensing elements and thus produces data that are multivariate in nature and may be significantly increased in complexity compared to data provided by single-sensor systems. Though a hybrid sensor is itself an array, hybrid sensors are often organized into more complex sensing systems through an assortment of network topologies. Part of the reason for the shift to hybrid sensors is due to advancements in sensor technology and computational power available for processing larger amounts of data. There is also ample evidence to support the claim that a multivariate analytical approach is generally superior to univariate measurements because it provides additional redundant and complementary information (Hall, D. L.; Linas, J., Eds., Handbook of Multisensor Data Fusion, CRC, Boca Raton, FL, 2001). However, the benefits of a multisensory approach are not automatically achieved. Interpretation of data from hybrid arrays of sensors requires the analyst to develop an application-specific methodology to optimally fuse the disparate sources of data generated by the hybrid array into useful information characterizing the sample or environment being observed. Consequently, multivariate data analysis techniques such as those employed in the field of chemometrics have become more important in analyzing sensor array data. Depending on the nature of the acquired data, a number of chemometric algorithms may prove useful in the analysis and interpretation of data from hybrid sensor arrays. It is important to note, however, that the challenges posed by the analysis of hybrid sensor array data are not unique to the field of chemical sensing. Applications in electrical and process engineering, remote sensing, medicine, and of course, artificial

  8. Design of Optimal Hybrid Position/Force Controller for a Robot Manipulator Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Vikas Panwar

    2007-01-01

    Full Text Available The application of quadratic optimization and sliding-mode approach is considered for hybrid position and force control of a robot manipulator. The dynamic model of the manipulator is transformed into a state-space model to contain two sets of state variables, where one describes the constrained motion and the other describes the unconstrained motion. The optimal feedback control law is derived solving matrix differential Riccati equation, which is obtained using Hamilton Jacobi Bellman optimization. The optimal feedback control law is shown to be globally exponentially stable using Lyapunov function approach. The dynamic model uncertainties are compensated with a feedforward neural network. The neural network requires no preliminary offline training and is trained with online weight tuning algorithms that guarantee small errors and bounded control signals. The application of the derived control law is demonstrated through simulation with a 4-DOF robot manipulator to track an elliptical planar constrained surface while applying the desired force on the surface.

  9. 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.

  10. Hybrid Approach for Biliary Interventions Employing MRI-Guided Bile Duct Puncture with Near-Real-Time Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Wybranski, Christian, E-mail: Christian.Wybranski@uk-koeln.de [University Hospital of Cologne, Department of Diagnostic and Interventional Radiology (Germany); Pech, Maciej [Otto-von-Guericke University Medical School, Department of Radiology and Nuclear Medicine (Germany); Lux, Anke [Otto-von-Guericke University Medical School, Institute of Biometry and Medical Informatics (Germany); Ricke, Jens; Fischbach, Frank; Fischbach, Katharina [Otto-von-Guericke University Medical School, Department of Radiology and Nuclear Medicine (Germany)

    2017-06-15

    ObjectiveTo assess the feasibility of a hybrid approach employing MRI-guided bile duct (BD) puncture for subsequent fluoroscopy-guided biliary interventions in patients with non-dilated (≤3 mm) or dilated BD (≥3 mm) but unfavorable conditions for ultrasonography (US)-guided BD puncture.MethodsA total of 23 hybrid interventions were performed in 21 patients. Visualization of BD and puncture needles (PN) in the interventional MR images was rated on a 5-point Likert scale by two radiologists. Technical success, planning time, BD puncture time and positioning adjustments of the PN as well as technical success of the biliary intervention and complication rate were recorded.ResultsVisualization even of third-order non-dilated BD and PN was rated excellent by both radiologists with good to excellent interrater agreement. MRI-guided BD puncture was successful in all cases. Planning and BD puncture times were 1:36 ± 2.13 (0:16–11:07) min. and 3:58 ± 2:35 (1:11–9:32) min. Positioning adjustments of the PN was necessary in two patients. Repeated capsular puncture was not necessary in any case. All biliary interventions were completed successfully without major complications.ConclusionA hybrid approach which employs MRI-guided BD puncture for subsequent fluoroscopy-guided biliary intervention is feasible in clinical routine and yields high technical success in patients with non-dilated BD and/or unfavorable conditions for US-guided puncture. Excellent visualization of BD and PN in near-real-time interventional MRI allows successful cannulation of the BD.

  11. A hybrid fuzzy logic and extreme learning machine for improving efficiency of circulating water systems in power generation plant

    Science.gov (United States)

    Aziz, Nur Liyana Afiqah Abdul; Siah Yap, Keem; Afif Bunyamin, Muhammad

    2013-06-01

    This paper presents a new approach of the fault detection for improving efficiency of circulating water system (CWS) in a power generation plant using a hybrid Fuzzy Logic System (FLS) and Extreme Learning Machine (ELM) neural network. The FLS is a mathematical tool for calculating the uncertainties where precision and significance are applied in the real world. It is based on natural language which has the ability of "computing the word". The ELM is an extremely fast learning algorithm for neural network that can completed the training cycle in a very short time. By combining the FLS and ELM, new hybrid model, i.e., FLS-ELM is developed. The applicability of this proposed hybrid model is validated in fault detection in CWS which may help to improve overall efficiency of power generation plant, hence, consuming less natural recourses and producing less pollutions.

  12. A hybrid fuzzy logic and extreme learning machine for improving efficiency of circulating water systems in power generation plant

    International Nuclear Information System (INIS)

    Aziz, Nur Liyana Afiqah Abdul; Yap, Keem Siah; Bunyamin, Muhammad Afif

    2013-01-01

    This paper presents a new approach of the fault detection for improving efficiency of circulating water system (CWS) in a power generation plant using a hybrid Fuzzy Logic System (FLS) and Extreme Learning Machine (ELM) neural network. The FLS is a mathematical tool for calculating the uncertainties where precision and significance are applied in the real world. It is based on natural language which has the ability of c omputing the word . The ELM is an extremely fast learning algorithm for neural network that can completed the training cycle in a very short time. By combining the FLS and ELM, new hybrid model, i.e., FLS-ELM is developed. The applicability of this proposed hybrid model is validated in fault detection in CWS which may help to improve overall efficiency of power generation plant, hence, consuming less natural recourses and producing less pollutions.

  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. 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,…

  15. 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.

  16. 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.

  17. Performance Analysis of a Hybrid Power Cutting System for Roadheader

    Directory of Open Access Journals (Sweden)

    Yang Yang

    2017-01-01

    Full Text Available An electrohydraulic hybrid power cutting transmission system for roadheader under specific working condition was proposed in this paper. The overall model for the new system composed of an electric motor model, a hydraulic pump-motor model, a torsional planetary set model, and a hybrid power train model was established. The working mode characteristics were simulated under the conditions of taking the effect of cutting picks into account. The advantages of new hybrid power cutting system about the dynamic response under shock load were investigated compared with the traditional cutting system. The results illustrated that the hybrid power system had an obvious cushioning in terms of the dynamic load of cutting electric motor and planetary gear set. Besides, the hydraulic motor could provide an auxiliary power to improve the performance of the electric motor. With further analysis, a dynamic load was found to have a high relation to the stiffness and damping of coupling in the transmission train. The results could be a useful guide for the design of cutting transmission of roadheader.

  18. 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.

  19. CULTOROLOGICAL APPROACH TO TRAINING OF THE FUTURE MANAGERS OF TOURISM IN PRECARPATHIA

    Directory of Open Access Journals (Sweden)

    Marianna Chorna

    2015-04-01

    Full Text Available The article deals with the «culturological approach» to the professional training of future managers of tourism in Precarpathia. As the Precarpathian region attracts thousands of tourists year-round the demand of training qualified specialists in the sphere of tourism and hospitality is constantly growing. Nowadays the question of a successful and perspectives career in tourism results in training a new standard professional, a specialist of many-sided knowledge,with the ability to fulfil tasks concerning thinking over, making and realizing management decisions. In order to develop tourist  Carpathian region, the Precarpathian National University named after V.Stefanyk educates future experts in such specialities as "Tourism" and "Hospitality Industry". Involving youth in social cultural values and ideals, education contributes to maintaining social order and by providing realization of new technologies, scientific rethinking of existing knowledge education promotes social changes, society development, i.e. education operates as an agent of moral regulation facilitating social integration. Different interpretations of the concept «culture» were studied. The conclusion that culture is a multiaspect and multifunctional notion was made. Cultorological approach in education provides effectiveness of the process of putting culture as a social phenomenon into action. The fact of culturological direction extending of the whole educational process in the university interrelating to its components (common-cultural, professional and functional is of great importance. Cultorological approach introduction to the process of training of the future tourism experts that is aimed at the developing of civil society values and an independent creative personality is a premise of modernization of higher education in Ukraine.

  20. 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

  1. 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.

  2. A hybrid pareto mixture for conditional asymmetric fat-tailed distributions.

    Science.gov (United States)

    Carreau, Julie; Bengio, Yoshua

    2009-07-01

    In many cases, we observe some variables X that contain predictive information over a scalar variable of interest Y , with (X,Y) pairs observed in a training set. We can take advantage of this information to estimate the conditional density p(Y|X = x). In this paper, we propose a conditional mixture model with hybrid Pareto components to estimate p(Y|X = x). The hybrid Pareto is a Gaussian whose upper tail has been replaced by a generalized Pareto tail. A third parameter, in addition to the location and spread parameters of the Gaussian, controls the heaviness of the upper tail. Using the hybrid Pareto in a mixture model results in a nonparametric estimator that can adapt to multimodality, asymmetry, and heavy tails. A conditional density estimator is built by modeling the parameters of the mixture estimator as functions of X. We use a neural network to implement these functions. Such conditional density estimators have important applications in many domains such as finance and insurance. We show experimentally that this novel approach better models the conditional density in terms of likelihood, compared to competing algorithms: conditional mixture models with other types of components and a classical kernel-based nonparametric model.

  3. Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.

    Directory of Open Access Journals (Sweden)

    Jakub Jończyk

    Full Text Available The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand-receptor interactions for reference compounds.

  4. 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

  5. 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.

  6. Near-term hybrid vehicle program, phase 1

    Science.gov (United States)

    1979-01-01

    The preliminary design of a hybrid vehicle which fully meets or exceeds the requirements set forth in the Near Term Hybrid Vehicle Program is documented. Topics addressed include the general layout and styling, the power train specifications with discussion of each major component, vehicle weight and weight breakdown, vehicle performance, measures of energy consumption, and initial cost and ownership cost. Alternative design options considered and their relationship to the design adopted, computer simulation used, and maintenance and reliability considerations are also discussed.

  7. 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.

  8. A hybrid wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series.

    Science.gov (United States)

    Wang, Dong; Borthwick, Alistair G; He, Handan; Wang, Yuankun; Zhu, Jieyu; Lu, Yuan; Xu, Pengcheng; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

    2018-01-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. 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

  10. Hybrid Method Simulation of Slender Marine Structures

    DEFF Research Database (Denmark)

    Christiansen, Niels Hørbye

    This present thesis consists of an extended summary and five appended papers concerning various aspects of the implementation of a hybrid method which combines classical simulation methods and artificial neural networks. The thesis covers three main topics. Common for all these topics...... only recognize patterns similar to those comprised in the data used to train the network. Fatigue life evaluation of marine structures often considers simulations of more than a hundred different sea states. Hence, in order for this method to be useful, the training data must be arranged so...... that a single neural network can cover all relevant sea states. The applicability and performance of the present hybrid method is demonstrated on a numerical model of a mooring line attached to a floating offshore platform. The second part of the thesis demonstrates how sequential neural networks can be used...

  11. A Structural Equation Modelling Approach for Massive Blended Synchronous Teacher Training

    Science.gov (United States)

    Kannan, Kalpana; Narayanan, Krishnan

    2015-01-01

    This paper presents a structural equation modelling (SEM) approach for blended synchronous teacher training workshop. It examines the relationship among various factors that influence the Satisfaction (SAT) of participating teachers. Data were collected with the help of a questionnaire from about 500 engineering college teachers. These teachers…

  12. Making a Math Teaching Aids of Junior High School Based on Scientific Approach Through an Integrated and Sustainable Training

    Science.gov (United States)

    Pujiastuti, E.; Mashuri

    2017-04-01

    Not all of teachers of Mathematics in Junior High School (JHS) can design and create teaching aids. Moreover, if teaching aids should be designed so that it can be used in learning through scientific approaches. The problem: How to conduct an integrated and sustainable training that the math teacher of JHS, especially in Semarang can design and create teaching aids that can be presented to the scientific approach? The purpose of this study to find a way of integrated and continuous training so that the math teacher of JHS can design and create teaching aids that can be presented to the scientific approach. This article was based on research with a qualitative approach. Through trials activities of resulting of training model, Focus Group Discussions (FGD), interviews, and triangulation of the results of the research were: (1) Produced a training model of integrated and sustainable that the mathematics teacher of JHS can design and create teaching aids that can be presented to the scientific approach. (2) In training, there was the provision of material and workshop (3) There was a mentoring in the classroom. (4) Sustainability of the consultation. Our advice: (1) the trainer should be clever, (2) the training can be held at the holidays, while the assistance during the holiday season was over.

  13. Hybrid Turbine Electric Vehicle

    Science.gov (United States)

    Viterna, Larry A.

    1997-01-01

    Hybrid electric power trains may revolutionize today's ground passenger vehicles by significantly improving fuel economy and decreasing emissions. The NASA Lewis Research Center is working with industry, universities, and Government to develop and demonstrate a hybrid electric vehicle. Our partners include Bowling Green State University, the Cleveland Regional Transit Authority, Lincoln Electric Motor Division, the State of Ohio's Department of Development, and Teledyne Ryan Aeronautical. The vehicle will be a heavy class urban transit bus offering double the fuel economy of today's buses and emissions that are reduced to 1/10th of the Environmental Protection Agency's standards. At the heart of the vehicle's drive train is a natural-gas-fueled engine. Initially, a small automotive engine will be tested as a baseline. This will be followed by the introduction of an advanced gas turbine developed from an aircraft jet engine. The engine turns a high-speed generator, producing electricity. Power from both the generator and an onboard energy storage system is then provided to a variable-speed electric motor attached to the rear drive axle. An intelligent power-control system determines the most efficient operation of the engine and energy storage system.

  14. Genomic networks of hybrid sterility.

    Directory of Open Access Journals (Sweden)

    Leslie M Turner

    2014-02-01

    Full Text Available Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities". The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL. Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is

  15. Hybrid Neuroprosthesis for the Upper Limb: Combining Brain-Controlled Neuromuscular Stimulation with a Multi-Joint Arm Exoskeleton.

    Science.gov (United States)

    Grimm, Florian; Walter, Armin; Spüler, Martin; Naros, Georgios; Rosenstiel, Wolfgang; Gharabaghi, Alireza

    2016-01-01

    Brain-machine interface-controlled (BMI) neurofeedback training aims to modulate cortical physiology and is applied during neurorehabilitation to increase the responsiveness of the brain to subsequent physiotherapy. In a parallel line of research, robotic exoskeletons are used in goal-oriented rehabilitation exercises for patients with severe motor impairment to extend their range of motion (ROM) and the intensity of training. Furthermore, neuromuscular electrical stimulation (NMES) is applied in neurologically impaired patients to restore muscle strength by closing the sensorimotor loop. In this proof-of-principle study, we explored an integrated approach for providing assistance as needed to amplify the task-related ROM and the movement-related brain modulation during rehabilitation exercises of severely impaired patients. For this purpose, we combined these three approaches (BMI, NMES, and exoskeleton) in an integrated neuroprosthesis and studied the feasibility of this device in seven severely affected chronic stroke patients who performed wrist flexion and extension exercises while receiving feedback via a virtual environment. They were assisted by a gravity-compensating, seven degree-of-freedom exoskeleton which was attached to the paretic arm. NMES was applied to the wrist extensor and flexor muscles during the exercises and was controlled by a hybrid BMI based on both sensorimotor cortical desynchronization (ERD) and electromyography (EMG) activity. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. The hybrid BMI controlled the stimulation significantly better than the offline analyzed ERD (p = 0.028) or EMG (p = 0.021) modality alone. Neuromuscular stimulation could be well integrated into the exoskeleton-based training and amplified both the task-related ROM (p = 0.009) and the movement-related brain modulation (p = 0.019). Combining a hybrid BMI with neuromuscular stimulation

  16. Hybrid Neuroprosthesis for the Upper Limb: Combining Brain-Controlled Neuromuscular Stimulation with a Multi-Joint Arm Exoskeleton

    Science.gov (United States)

    Grimm, Florian; Walter, Armin; Spüler, Martin; Naros, Georgios; Rosenstiel, Wolfgang; Gharabaghi, Alireza

    2016-01-01

    Brain-machine interface-controlled (BMI) neurofeedback training aims to modulate cortical physiology and is applied during neurorehabilitation to increase the responsiveness of the brain to subsequent physiotherapy. In a parallel line of research, robotic exoskeletons are used in goal-oriented rehabilitation exercises for patients with severe motor impairment to extend their range of motion (ROM) and the intensity of training. Furthermore, neuromuscular electrical stimulation (NMES) is applied in neurologically impaired patients to restore muscle strength by closing the sensorimotor loop. In this proof-of-principle study, we explored an integrated approach for providing assistance as needed to amplify the task-related ROM and the movement-related brain modulation during rehabilitation exercises of severely impaired patients. For this purpose, we combined these three approaches (BMI, NMES, and exoskeleton) in an integrated neuroprosthesis and studied the feasibility of this device in seven severely affected chronic stroke patients who performed wrist flexion and extension exercises while receiving feedback via a virtual environment. They were assisted by a gravity-compensating, seven degree-of-freedom exoskeleton which was attached to the paretic arm. NMES was applied to the wrist extensor and flexor muscles during the exercises and was controlled by a hybrid BMI based on both sensorimotor cortical desynchronization (ERD) and electromyography (EMG) activity. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. The hybrid BMI controlled the stimulation significantly better than the offline analyzed ERD (p = 0.028) or EMG (p = 0.021) modality alone. Neuromuscular stimulation could be well integrated into the exoskeleton-based training and amplified both the task-related ROM (p = 0.009) and the movement-related brain modulation (p = 0.019). Combining a hybrid BMI with neuromuscular stimulation

  17. Hybrid neuroprosthesis for the upper limb: combining brain-controlled neuromuscular stimulation with a multi-joint arm exoskeleton

    Directory of Open Access Journals (Sweden)

    Florian Grimm

    2016-08-01

    Full Text Available Brain-machine interface-controlled (BMI neurofeedback training aims to modulate cortical physiology and is applied during neurorehabilitation to increase the responsiveness of the brain to subsequent physiotherapy. In a parallel line of research, robotic exoskeletons are used in goal-oriented rehabilitation exercises for patients with severe motor impairment to extend their range of motion and the intensity of training. Furthermore, neuromuscular electrical stimulation (NMES is applied in neurologically impaired patients to restore muscle strength by closing the sensorimotor loop. In this proof-of-principle study, we explored an integrated approach for providing assistance as needed to amplify the task-related range of motion and the movement-related brain modulation during rehabilitation exercises of severely impaired patients. For this purpose, we combined these three approaches (BMI, NMES, and exoskeleton in an integrated neuroprosthesis and studied the feasibility of this device in seven severely affected chronic stroke patients who performed wrist flexion and extension exercises while receiving feedback via a virtual environment. They were assisted by a gravity-compensating, seven degree-of-freedom exoskeleton which was attached to the paretic arm. Neuromuscular electrical stimulation was applied to the wrist extensor and flexor muscles during the exercises and was controlled by a hybrid BMI based on both sensorimotor cortical desynchronization (ERD and electromyography (EMG activity. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e. induced no overt support. The hybrid BMI controlled the stimulation significantly better than the offline analyzed ERD (p=0.028 or EMG (p=0.021 modality alone. Neuromuscular stimulation could be well integrated into the exoskeleton-based training and amplified both the task-related range of motion (p=0.009 and the movement-related brain modulation (p=0

  18. 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...

  19. An online hybrid brain-computer interface combining multiple physiological signals for webpage browse.

    Science.gov (United States)

    Long Chen; Zhongpeng Wang; Feng He; Jiajia Yang; Hongzhi Qi; Peng Zhou; Baikun Wan; Dong Ming

    2015-08-01

    The hybrid brain computer interface (hBCI) could provide higher information transfer rate than did the classical BCIs. It included more than one brain-computer or human-machine interact paradigms, such as the combination of the P300 and SSVEP paradigms. Research firstly constructed independent subsystems of three different paradigms and tested each of them with online experiments. Then we constructed a serial hybrid BCI system which combined these paradigms to achieve the functions of typing letters, moving and clicking cursor, and switching among them for the purpose of browsing webpages. Five subjects were involved in this study. They all successfully realized these functions in the online tests. The subjects could achieve an accuracy above 90% after training, which met the requirement in operating the system efficiently. The results demonstrated that it was an efficient system capable of robustness, which provided an approach for the clinic application.

  20. 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.

  1. Nafion–clay hybrids with a network structure

    KAUST Repository

    Burgaz, Engin; Lian, Huiqin; Alonso, Rafael Herrera; Estevez, Luis; Kelarakis, Antonios; Giannelis, Emmanuel P.

    2009-01-01

    Nafion-clay hybrid membranes with a unique microstructure were synthesized using a fundamentally new approach. The new approach is based on depletion aggregation of suspended particles - a well-known phenomenon in colloids. For certain concentrations of clay and polymer, addition of Nafion solution to clay suspensions in water leads to a gel. Using Cryo-TEM we show that the clay particles in the hybrid gels form a network structure with an average cell size in the order of 500 nm. The hybrid gels are subsequently cast to produce hybrid Nafion-clay membranes. Compared to pure Nafion the swelling of the hybrid membranes in water and methanol is dramatically reduced while their selectivity (ratio of conductivity over permeability) increases. The small decrease of ionic conductivity for the hybrid membranes is more than compensated by the large decrease in methanol permeability. Lastly the hybrid membranes are much stiffer and can withstand higher temperatures compared to pure Nafion. Both of these characteristics are highly desirable for use in fuel cell applications, since a) they will allow the use of a thinner membrane circumventing problems associated with the membrane resistance and b) enable high temperature applications. © 2009 Elsevier Ltd. All rights reserved.

  2. Nafion–clay hybrids with a network structure

    KAUST Repository

    Burgaz, Engin

    2009-05-01

    Nafion-clay hybrid membranes with a unique microstructure were synthesized using a fundamentally new approach. The new approach is based on depletion aggregation of suspended particles - a well-known phenomenon in colloids. For certain concentrations of clay and polymer, addition of Nafion solution to clay suspensions in water leads to a gel. Using Cryo-TEM we show that the clay particles in the hybrid gels form a network structure with an average cell size in the order of 500 nm. The hybrid gels are subsequently cast to produce hybrid Nafion-clay membranes. Compared to pure Nafion the swelling of the hybrid membranes in water and methanol is dramatically reduced while their selectivity (ratio of conductivity over permeability) increases. The small decrease of ionic conductivity for the hybrid membranes is more than compensated by the large decrease in methanol permeability. Lastly the hybrid membranes are much stiffer and can withstand higher temperatures compared to pure Nafion. Both of these characteristics are highly desirable for use in fuel cell applications, since a) they will allow the use of a thinner membrane circumventing problems associated with the membrane resistance and b) enable high temperature applications. © 2009 Elsevier Ltd. All rights reserved.

  3. Epitaxial growth of hybrid nanostructures

    Science.gov (United States)

    Tan, Chaoliang; Chen, Junze; Wu, Xue-Jun; Zhang, Hua

    2018-02-01

    Hybrid nanostructures are a class of materials that are typically composed of two or more different components, in which each component has at least one dimension on the nanoscale. The rational design and controlled synthesis of hybrid nanostructures are of great importance in enabling the fine tuning of their properties and functions. Epitaxial growth is a promising approach to the controlled synthesis of hybrid nanostructures with desired structures, crystal phases, exposed facets and/or interfaces. This Review provides a critical summary of the state of the art in the field of epitaxial growth of hybrid nanostructures. We discuss the historical development, architectures and compositions, epitaxy methods, characterization techniques and advantages of epitaxial hybrid nanostructures. Finally, we provide insight into future research directions in this area, which include the epitaxial growth of hybrid nanostructures from a wider range of materials, the study of the underlying mechanism and determining the role of epitaxial growth in influencing the properties and application performance of hybrid nanostructures.

  4. A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation

    International Nuclear Information System (INIS)

    Mohammadi, Kasra; Shamshirband, Shahaboddin; Tong, Chong Wen; Arif, Muhammad; Petković, Dalibor; Ch, Sudheer

    2015-01-01

    Highlights: • Horizontal global solar radiation (HGSR) is predicted based on a new hybrid approach. • Support Vector Machines and Wavelet Transform algorithm (SVM–WT) are combined. • Different sets of meteorological elements are used to predict HGSR. • The precision of SVM–WT is assessed thoroughly against ANN, GP and ARMA. • SVM–WT would be an appealing approach to predict HGSR and outperforms others. - Abstract: In this paper, a new hybrid approach by combining the Support Vector Machine (SVM) with Wavelet Transform (WT) algorithm is developed to predict horizontal global solar radiation. The predictions are conducted on both daily and monthly mean scales for an Iranian coastal city. The proposed SVM–WT method is compared against other existing techniques to demonstrate its efficiency and viability. Three different sets of parameters are served as inputs to establish three models. The results indicate that the model using relative sunshine duration, difference between air temperatures, relative humidity, average temperature and extraterrestrial solar radiation as inputs shows higher performance than other models. The statistical analysis demonstrates that SVM–WT approach enjoys very good performance and outperforms other approaches. For the best SVM–WT model, the obtained statistical indicators of mean absolute percentage error, mean absolute bias error, root mean square error, relative root mean square error and coefficient of determination for daily estimation are 6.9996%, 0.8405 MJ/m 2 , 1.4245 MJ/m 2 , 7.9467% and 0.9086, respectively. Also, for monthly mean estimation the values are 3.2601%, 0.5104 MJ/m 2 , 0.6618 MJ/m 2 , 3.6935% and 0.9742, respectively. Based upon relative percentage error, for the best SVM–WT model, 88.70% of daily predictions fall within the acceptable range of −10% to +10%

  5. 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…

  6. 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…

  7. A hybrid particle–field molecular dynamics approach: a route toward efficient coarse-grained models for biomembranes

    International Nuclear Information System (INIS)

    Milano, Giuseppe; De Nicola, Antonio; Kawakatsu, Toshihiro

    2013-01-01

    This paper gives an overview of the coarse-grained models of phospholipids recently developed by the authors in the frame of a hybrid particle–field molecular dynamics technique. This technique employs a special class of coarse-grained models that are gaining popularity because they allow simulations of large scale systems and, at the same time, they provide sufficiently detailed chemistry for the mapping scheme adopted. The comparison of the computational costs of our approach with standard molecular dynamics simulations is a function of the system size and the number of processors employed in the parallel calculations. Due to the low amount of data exchange, the larger the number of processors, the better are the performances of the hybrid particle–field models. This feature makes these models very promising ones in the exploration of several problems in biophysics. (paper)

  8. 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.

  9. 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

  10. 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.

  11. Weighted hybrid technique for recommender system

    Science.gov (United States)

    Suriati, S.; Dwiastuti, Meisyarah; Tulus, T.

    2017-12-01

    Recommender system becomes very popular and has important role in an information system or webpages nowadays. A recommender system tries to make a prediction of which item a user may like based on his activity on the system. There are some familiar techniques to build a recommender system, such as content-based filtering and collaborative filtering. Content-based filtering does not involve opinions from human to make the prediction, while collaborative filtering does, so collaborative filtering can predict more accurately. However, collaborative filtering cannot give prediction to items which have never been rated by any user. In order to cover the drawbacks of each approach with the advantages of other approach, both approaches can be combined with an approach known as hybrid technique. Hybrid technique used in this work is weighted technique in which the prediction score is combination linear of scores gained by techniques that are combined.The purpose of this work is to show how an approach of weighted hybrid technique combining content-based filtering and item-based collaborative filtering can work in a movie recommender system and to show the performance comparison when both approachare combined and when each approach works alone. There are three experiments done in this work, combining both techniques with different parameters. The result shows that the weighted hybrid technique that is done in this work does not really boost the performance up, but it helps to give prediction score for unrated movies that are impossible to be recommended by only using collaborative filtering.

  12. Achieving a hybrid brain-computer interface with tactile selective attention and motor imagery

    Science.gov (United States)

    Ahn, Sangtae; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan

    2014-12-01

    Objective. We propose a new hybrid brain-computer interface (BCI) system that integrates two different EEG tasks: tactile selective attention (TSA) using a vibro-tactile stimulator on the left/right finger and motor imagery (MI) of left/right hand movement. Event-related desynchronization (ERD) from the MI task and steady-state somatosensory evoked potential (SSSEP) from the TSA task are retrieved and combined into two hybrid senses. Approach. One hybrid approach is to measure two tasks simultaneously; the features of each task are combined for testing. Another hybrid approach is to measure two tasks consecutively (TSA first and MI next) using only MI features. For comparison with the hybrid approaches, the TSA and MI tasks are measured independently. Main results. Using a total of 16 subject datasets, we analyzed the BCI classification performance for MI, TSA and two hybrid approaches in a comparative manner; we found that the consecutive hybrid approach outperformed the others, yielding about a 10% improvement in classification accuracy relative to MI alone. It is understood that TSA may play a crucial role as a prestimulus in that it helps to generate earlier ERD prior to MI and thus sustains ERD longer and to a stronger degree; this ERD may give more discriminative information than ERD in MI alone. Significance. Overall, our proposed consecutive hybrid approach is very promising for the development of advanced BCI systems.

  13. Natural training tools of informatics in conditions of embodied and mental approach realization

    Directory of Open Access Journals (Sweden)

    Daria A. Barkhatova

    2017-01-01

    Full Text Available Modern processes of globalization and informatization of human activity cause the necessity of change of the educational paradigm in the field of information training of a person, focused on the formation of the strong fundamental knowledge and abilities, which are necessary for person’s information activities and self-education during all life.In connection with these requirements, it is necessary to pay attention to new approaches in education, based on achievements of cognitive science and modern pedagogic. One of such approaches is embodied and mental approach. The paper is devoted to the description of a way of realization of embodied and mental approach in training of informatics through application of the natural tools, providing the fullest and deep understanding of the educational material, and development of cognitive abilities of students.In the paper the theoretical analysis of psychology-pedagogical and methodical literature on a research subject is carried out, results are generalized, natural tools are modeled and results of their partial approbation are described. Achievement of necessary quality of education is offered due to the use of modern techniques, focused on the development of cognitive abilities and improvement of quality of the knowledge. In the conditions of information education, the combination of embodied and mental approaches will allow to acquaint students with the essence of the studied subject due to activation of motor area of the memory and the kinesthetic and visual perception channels. The instrument of realization of this idea is offered to use natural tools in informatics, what is actualized by age features of cognitive abilities of students and individual requirements to ways of perception and mastering of the material, matched according to the level of their knowledge.The research results describe the models of natural tools, developed by students and lecturers of the basic Department of Informatics

  14. Simulation and training of ultrasound supported anaesthesia: a low-cost approach

    Science.gov (United States)

    Schaaf, T.; Lamontain, M.; Hilpert, J.; Schilling, F.; Tolxdorff, T.

    2010-03-01

    The use of ultrasound imaging technology during techniques of peripheral nerve blockade offers several clinical benefits. Here we report on a new method to educate residents in ultrasound-guided regional anesthesia. The daily challenge for the anesthesiologists is the 3D angle-depending handling of the stimulation needle and the ultrasound probe while watching the 2D ultrasound image on the monitor. Purpose: Our approach describes how a computer-aided simulation and training set for ultrasound-guided regional anesthesia could be built based on wireless low-cost devices and an interactive simulation of a 2D ultrasound image. For training purposes the injection needle and the ultrasound probe are replaced by wireless Bluetooth-connected 3D tracking devices, which are embedded in WII-mote controllers (Nintendo-Brand). In correlation to the tracked 3D positions of the needle and transducer models the visibility and position of the needle should be simulated in the 2D generated ultrasound image. Conclusion: In future, this tracking and visualization software module could be integrated in a more complex training set, where complex injection paths could be trained based on a 3D segmented model and the training results could be part of a curricular e-learning module.

  15. Preparing mental health professionals for new directions in mental health practice: Evaluating the sensory approaches e-learning training package.

    Science.gov (United States)

    Meredith, Pamela; Yeates, Harriet; Greaves, Amanda; Taylor, Michelle; Slattery, Maddy; Charters, Michelle; Hill, Melissa

    2018-02-01

    The application of sensory modulation approaches in mental health settings is growing in recognition internationally. However, a number of barriers have been identified as limiting the implementation of the approach, including workplace culture and a lack of accessible and effective sensory approaches training. The aim of this project was to investigate the efficacy of providing this training through a custom-designed e-learning package. Participants in the present study were predominately nurses and occupational therapists working in mental health settings in Queensland, Australia. Data were collected from 121 participants using an online survey. Significant improvements were found between pre- and post-training in participants' real and perceived levels of knowledge, their perceived levels of confidence, and their attitudes towards using sensory modulation approaches in mental health settings. The findings of the study suggest that the custom-designed sensory approaches e-learning package is an effective, accessible, acceptable, and usable method to train health professionals in sensory modulation approaches. As this study is the first to analyse the efficacy of an e-learning sensory approaches package, the results are considered preliminary, and further investigation is required. © 2017 Australian College of Mental Health Nurses Inc.

  16. Training symmetry of weight distribution after stroke: a randomized controlled pilot study comparing task-related reach, Bobath and feedback training approaches.

    Science.gov (United States)

    Mudie, M H; Winzeler-Mercay, U; Radwan, S; Lee, L

    2002-09-01

    To determine (1) the most effective of three treatment approaches to retrain seated weight distribution long-term after stroke and (2) whether improvements could be generalized to weight distribution in standing. Inpatient rehabilitation unit. Forty asymmetrical acute stroke subjects were randomly allocated to one of four groups in this pilot study. Changes in weight distribution were compared between the 10 subjects of each of three treatment groups (task-specific reach, Bobath, or Balance Performance Monitor [BPM] feedback training) and a no specific treatment control group. One week of measurement only was followed by two weeks of daily training sessions with the treatment to which the subject was randomly allocated. Measurements were performed using the BPM daily before treatment sessions, two weeks after cessation of treatment and 12 weeks post study. Weight distribution was calculated in terms of mean balance (percentage of total body weight) or the mean of 300 balance points over a 30-s data run. In the short term, the Bobath approach was the most effective treatment for retraining sitting symmetry after stroke (p = 0.004). Training with the BPM and no training were also significant (p = 0.038 and p = 0.035 respectively) and task-specific reach training failed to reach significance (p = 0.26). At 12 weeks post study 83% of the BPM training group, 38% of the task-specific reach group, 29% of the Bobath group and 0% of the untrained group were found to be distributing their weight to both sides. Some generalization of symmetry training in sitting to standing was noted in the BPM training group which appeared to persist long term. Results should be treated with caution due to the small group sizes. However, these preliminary findings suggest that it might be possible to restore postural symmetry in sitting in the early stages of rehabilitation with therapy that focuses on creating an awareness of body position.

  17. 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…

  18. Optimisation of Software-Defined Networks Performance Using a Hybrid Intelligent System

    Directory of Open Access Journals (Sweden)

    Ann Sabih

    2017-06-01

    Full Text Available This paper proposes a novel intelligent technique that has been designed to optimise the performance of Software Defined Networks (SDN. The proposed hybrid intelligent system has employed integration of intelligence-based optimisation approaches with the artificial neural network. These heuristic optimisation methods include Genetic Algorithms (GA and Particle Swarm Optimisation (PSO. These methods were utilised separately in order to select the best inputs to maximise SDN performance. In order to identify SDN behaviour, the neural network model is trained and applied. The maximal optimisation approach has been identified using an analytical approach that considered SDN performance and the computational time as objective functions. Initially, the general model of the neural network was tested with unseen data before implementing the model using GA and PSO to determine the optimal performance of SDN. The results showed that the SDN represented by Artificial Neural Network ANN, and optmised by PSO, generated a better configuration with regards to computational efficiency and performance index.

  19. Genomic Prediction of Sunflower Hybrids Oil Content

    Directory of Open Access Journals (Sweden)

    Brigitte Mangin

    2017-09-01

    Full Text Available Prediction of hybrid performance using incomplete factorial mating designs is widely used in breeding programs including different heterotic groups. Based on the general combining ability (GCA of the parents, predictions are accurate only if the genetic variance resulting from the specific combining ability is small and both parents have phenotyped descendants. Genomic selection (GS can predict performance using a model trained on both phenotyped and genotyped hybrids that do not necessarily include all hybrid parents. Therefore, GS could overcome the issue of unknown parent GCA. Here, we compared the accuracy of classical GCA-based and genomic predictions for oil content of sunflower seeds using several GS models. Our study involved 452 sunflower hybrids from an incomplete factorial design of 36 female and 36 male lines. Re-sequencing of parental lines allowed to identify 468,194 non-redundant SNPs and to infer the hybrid genotypes. Oil content was observed in a multi-environment trial (MET over 3 years, leading to nine different environments. We compared GCA-based model to different GS models including female and male genomic kinships with the addition of the female-by-male interaction genomic kinship, the use of functional knowledge as SNPs in genes of oil metabolic pathways, and with epistasis modeling. When both parents have descendants in the training set, the predictive ability was high even for GCA-based prediction, with an average MET value of 0.782. GS performed slightly better (+0.2%. Neither the inclusion of the female-by-male interaction, nor functional knowledge of oil metabolism, nor epistasis modeling improved the GS accuracy. GS greatly improved predictive ability when one or both parents were untested in the training set, increasing GCA-based predictive ability by 10.4% from 0.575 to 0.635 in the MET. In this scenario, performing GS only considering SNPs in oil metabolic pathways did not improve whole genome GS prediction but

  20. 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…

  1. Leadership, clinician managers and a thing called "hybridity".

    Science.gov (United States)

    Fulop, Liz

    2012-01-01

    In many countries leadership theories and leadership development programs in healthcare have been dominated by individualistic and heroic approaches that focus on developing the skills and competencies of health professionals. Alternative approaches have been proffered but mainly in the form of post-heroic and distributed forms of leadership. The notion of "hybridity" has emerged to challenge the assumptions of distributed leadership. The paper seeks to explore how the concept of hybridity can be used to re-theorize leadership in healthcare as it relates to clinician managers (or hybrid-professional managers). The theoretical developments are explored and empirical material is presented from research in Australian public hospitals to support the case for the existence of hybridized forms of leadership in healthcare. The paper discusses whether hybridity needs re-theorizing to adequately account for clinician leadership. It contributes to debates surrounding the role of clinician leadership in healthcare reform particularly in relation to those doctors who occupy management positions at the division or unit levels as distinct to CEOs. The study uses qualitative research, i.e. interactive interviews to present accounts of how healthcare professionals describe leadership. It undertakes both deductive and inductive theme analysis of the interview material. There is support for hybridized configurations of leadership in interview materials of healthcare professionals but other aspects were also noted that cannot be explained by this approach alone. The paper is the first to examine the concept of hybridity in the context of clinician leadership. Many approaches to leadership in healthcare fail to address the complexity of leadership within the ranks of clinician managers and thus are unable to deal adequately with the role of leadership in healthcare reform and change.

  2. 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.

  3. 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.

  4. 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

  5. A uniform approach for on-site training and qualification of health physics technicians

    International Nuclear Information System (INIS)

    Till, J.E.

    1977-01-01

    Estimates show that in the U.S. approx. 75% of the health physics technicians received their training through courses offered by their employer. The quality and the extent of this training vary considerably among nuclear facilities. This paper describes a uniform approach for on-site training and qualification of health physics technicians applicable to all nuclear facilities. The program consists of four levels of qualification: Health Physics Technician Trainee, Technician I, Technician II and Senior Technician. The training is divided into modules that are composed of formal lectures, practical factors, experience, and a comprehensive examination. The minimum time required from hiring of inexperienced trainees to qualification as Senior Technicians is approx. 24 months. A qualification guide lists each step a technician must complete in the training program and provides documentation which facilitates audits by internal and external groups. Although items in the program would differ between facilities, the program provides specific titles for technicians, based on their training and experience, which would be applicable throughout the nuclear industry. (author)

  6. A systematic approach to human performance improvement in nuclear power plants: Training solutions

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-03-01

    In 1996, the IAEA published Technical Reports Series No. 380, Nuclear Power Plant Personnel Training and its Evaluation: A Guidebook. This publication provides guidance with respect to development, implementation and evaluation of training programmes for all NPP personnel. The IAEA International Working Group on Training and Qualification of Nuclear Power Plant Personnel recommended that an additional publication be prepared that provided further details concerning the training of NPP personnel on non-technical or soft skills. This report has been prepared in response to that recommendation. In the past, much of the focus of formal NPP training and development programmes was on the technical skills of NPP personnel, particularly those of control room operators. The environment in which NPPs operate is continually changing, placing new demands on NPP personnel to work more efficiently and effectively while continuing to maintain the high levels of safety required of NPPs. In this report, an integrated approach that considers training along with other ways to achieve desired levels of human performance is suggested.

  7. A systematic approach to human performance improvement in nuclear power plants: Training solutions

    International Nuclear Information System (INIS)

    2001-03-01

    In 1996, the IAEA published Technical Reports Series No. 380, Nuclear Power Plant Personnel Training and its Evaluation: A Guidebook. This publication provides guidance with respect to development, implementation and evaluation of training programmes for all NPP personnel. The IAEA International Working Group on Training and Qualification of Nuclear Power Plant Personnel recommended that an additional publication be prepared that provided further details concerning the training of NPP personnel on non-technical or soft skills. This report has been prepared in response to that recommendation. In the past, much of the focus of formal NPP training and development programmes was on the technical skills of NPP personnel, particularly those of control room operators. The environment in which NPPs operate is continually changing, placing new demands on NPP personnel to work more efficiently and effectively while continuing to maintain the high levels of safety required of NPPs. In this report, an integrated approach that considers training along with other ways to achieve desired levels of human performance is suggested

  8. 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…

  9. Hybrid spacecraft attitude control system

    Directory of Open Access Journals (Sweden)

    Renuganth Varatharajoo

    2016-02-01

    Full Text Available The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.

  10. Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension

    Directory of Open Access Journals (Sweden)

    Ueno Kazuko

    2009-04-01

    Full Text Available Abstract Background Model checking approaches were applied to biological pathway validations around 2003. Recently, Fisher et al. have proved the importance of model checking approach by inferring new regulation of signaling crosstalk in C. elegans and confirming the regulation with biological experiments. They took a discrete and state-based approach to explore all possible states of the system underlying vulval precursor cell (VPC fate specification for desired properties. However, since both discrete and continuous features appear to be an indispensable part of biological processes, it is more appropriate to use quantitative models to capture the dynamics of biological systems. Our key motivation of this paper is to establish a quantitative methodology to model and analyze in silico models incorporating the use of model checking approach. Results A novel method of modeling and simulating biological systems with the use of model checking approach is proposed based on hybrid functional Petri net with extension (HFPNe as the framework dealing with both discrete and continuous events. Firstly, we construct a quantitative VPC fate model with 1761 components by using HFPNe. Secondly, we employ two major biological fate determination rules – Rule I and Rule II – to VPC fate model. We then conduct 10,000 simulations for each of 48 sets of different genotypes, investigate variations of cell fate patterns under each genotype, and validate the two rules by comparing three simulation targets consisting of fate patterns obtained from in silico and in vivo experiments. In particular, an evaluation was successfully done by using our VPC fate model to investigate one target derived from biological experiments involving hybrid lineage observations. However, the understandings of hybrid lineages are hard to make on a discrete model because the hybrid lineage occurs when the system comes close to certain thresholds as discussed by Sternberg and Horvitz in

  11. Program Hybrid/GDH. Revision

    International Nuclear Information System (INIS)

    Blann, M.; Bisplinghoff, J.

    1975-10-01

    This code is the most recent in a series of codes for doing a-priori pre-equilibrium decay calculations. It has been written to permit the user to exercise many options at time of execution. It will, for example, permit calculation with either Hybrid model or the geometry dependent Hybrid model (GDH). Intranuclear transition rates can be calculated using either a nucleon-nucleon scattering approach (improved over earlier results) or based on the imaginary optical potential. Transition rates based on exciton lifetimes can be selected (as suggested in the Hybrid model formulation) or an average lifetime for each n-exciton configuration may be selected

  12. Design Procedure for Hybrid Ventilation

    DEFF Research Database (Denmark)

    Heiselberg, Per; Tjelflaat, Per Olaf

    Mechanical and natural ventilation systems have developed separately during many years. The natural next step in this development is development of ventilation concepts that utilises and combines the best features from each system into a new type of ventilation system - Hybrid Ventilation....... Buildings with hybrid ventilation often include other sustainable technologies and an energy optimisation requires an integrated approach in the design of the building and its mechanical systems. Therefore, the hybrid ventilation design procedure differs from the design procedure for conventional HVAC....... The first ideas on a design procedure for hybrid ventilation is presented and the different types of design methods, that is needed in different phases of the design process, is discussed....

  13. Enhancing Self-Practice/Self-Reflection (SP/SR) approach to cognitive behaviour training through the use of reflective blogs.

    Science.gov (United States)

    Farrand, Paul; Perry, Jon; Linsley, Sue

    2010-07-01

    Self-Practice/Self-Reflection (SP/SR) is increasingly beginning to feature as a central component of CBT training programmes (Bennett-Levy et al., 2001). Programmes including a reflective element, however, are not unproblematic and it has been documented that simply setting time aside for reflection does not necessarily result in trainees using such time to reflect. Such limitations may be overcome by including a requirement to post reflections on reflective blogs. To examine the effect that a requirement to contribute to a reflective blog had upon a SP/SR approach to CBT training. A focus group methodology was adopted with data analyzed using a general inductive qualitative approach. The requirement to use blogs to reflect upon the self-practice of CBT techniques enhanced SP/SR, established a learning community, and improved course supervision, although some technical difficulties arose. Consideration should be given towards using reflective blogs to support a SP/SR approach to CBT training. Benefits afforded by the use of reflective blogs further establish SP/SR as a valid and flexible training approach.

  14. The Regional-Matrix Approach to the Training of Highly Qualified Personnel for the Sustainable Development of the Mining Region

    Science.gov (United States)

    Zhernov, Evgeny; Nehoda, Evgenia

    2017-11-01

    The state, regional and industry approaches to the problem of personnel training for building an innovative knowledge economy at all levels that ensures sustainable development of the region are analyzed in the article using the cases of the Kemerovo region and the coal industry. A new regional-matrix approach to the training of highly qualified personnel is proposed, which allows to link the training systems with the regional economic matrix "natural resources - cognitive resources" developed by the author. A special feature of the new approach is the consideration of objective conditions and contradictions of regional systems of personnel training, which have formed as part of economic systems of regions differ-entiated in the matrix. The methodology of the research is based on the statement about the interconnectivity of general and local knowledge, from which the understanding of the need for a combination of regional, indus-try and state approaches to personnel training is derived. A new form of representing such a combination is the proposed approach, which is based on matrix analysis. The results of the research can be implemented in the practice of modernization of professional education of workers in the coal industry of the natural resources extractive region.

  15. Original Framework for Optimizing Hybrid Energy Supply

    Directory of Open Access Journals (Sweden)

    Amevi Acakpovi

    2016-01-01

    Full Text Available This paper proposes an original framework for optimizing hybrid energy systems. The recent growth of hybrid energy systems in remote areas across the world added to the increasing cost of renewable energy has triggered the inevitable development of hybrid energy systems. Hybrid energy systems always pose a problem of optimization of cost which has been approached with different perspectives in the recent past. This paper proposes a framework to guide the techniques of optimizing hybrid energy systems in general. The proposed framework comprises four stages including identification of input variables for energy generation, establishment of models of energy generation by individual sources, development of artificial intelligence, and finally summation of selected sources. A case study of a solar, wind, and hydro hybrid system was undertaken with a linear programming approach. Substantial results were obtained with regard to how load requests were constantly satisfied while minimizing the cost of electricity. The developed framework gained its originality from the fact that it has included models of individual sources of energy that even make the optimization problem more complex. This paper also has impacts on the development of policies which will encourage the integration and development of renewable energies.

  16. Effects and mechanism of the HECT study (hybrid exercise-cognitive trainings in mild ischemic stroke with cognitive decline: fMRI for brain plasticity, biomarker and behavioral analysis

    Directory of Open Access Journals (Sweden)

    Ting-ting Yeh

    2018-03-01

    Methods and significance: This study is a single-blind randomized controlled trial. A target sample size of 75 participants is needed to obtain a statistical power of 95% with a significance level of 5%. Stroke survivors with mild cognitive decline will be stratified by Mini-Mental State Examination scores and then randomized 1:1:1 to sequential exercise-cognitive training, dual-task exercise-cognitive training or control groups. All groups will undergo training 60 min/day, 3 days/week, for a total of 12 weeks. The primary outcome is the resting-state functional connectivity and neural activation in the frontal, parietal and occipital lobes in functional magnetic resonance imaging. Secondary outcomes include physiological biomarkers, cognitive functions, physical function, daily functions and quality of life. This study may differentiate the effects of two hybridized trainings on cognitive function and health-related conditions and detect appropriate neurological and physiological indices to predict training effects. This study capitalizes on the groundwork for a non-pharmacological intervention of cognitive decline after stroke.

  17. New Intelligent Transmission Concept for Hybrid Mobile Robot Speed Control

    Directory of Open Access Journals (Sweden)

    Nazim Mir-Nasiri

    2008-11-01

    Full Text Available This paper presents a new concept of a mobile robot speed control by using two degree of freedom gear transmission. The developed intelligent speed controller utilizes a gear box which comprises of epicyclic gear train with two inputs, one coupled with the engine shaft and another with the shaft of a variable speed dc motor. The net output speed is a combination of the two input speeds and is governed by the transmission ratio of the planetary gear train. This new approach eliminates the use of a torque converter which is otherwise an indispensable part of all available automatic transmissions, thereby reducing the power loss that occurs in the box during the fluid coupling. By gradually varying the speed of the dc motor a stepless transmission has been achieved. The other advantages of the developed controller are pulling over and reversing the vehicle, implemented by intelligent mixing of the dc motor and engine speeds. This approach eliminates traditional braking system in entire vehicle design. The use of two power sources, IC engine and battery driven DC motor, utilizes the modern idea of hybrid vehicles. The new mobile robot speed controller is capable of driving the vehicle even in extreme case of IC engine failure, for example, due to gas depletion..

  18. New Intelligent Transmission Concept for Hybrid Mobile Robot Speed Control

    Directory of Open Access Journals (Sweden)

    Nazim Mir-Nasiri

    2005-09-01

    Full Text Available This paper presents a new concept of a mobile robot speed control by using two degree of freedom gear transmission. The developed intelligent speed controller utilizes a gear box which comprises of epicyclic gear train with two inputs, one coupled with the engine shaft and another with the shaft of a variable speed dc motor. The net output speed is a combination of the two input speeds and is governed by the transmission ratio of the planetary gear train. This new approach eliminates the use of a torque converter which is otherwise an indispensable part of all available automatic transmissions, thereby reducing the power loss that occurs in the box during the fluid coupling. By gradually varying the speed of the dc motor a stepless transmission has been achieved. The other advantages of the developed controller are pulling over and reversing the vehicle, implemented by intelligent mixing of the dc motor and engine speeds. This approach eliminates traditional braking system in entire vehicle design. The use of two power sources, IC engine and battery driven DC motor, utilizes the modern idea of hybrid vehicles. The new mobile robot speed controller is capable of driving the vehicle even in extreme case of IC engine failure, for example, due to gas depletion.

  19. Model-based design approaches for plug-in hybrid vehicle design

    Energy Technology Data Exchange (ETDEWEB)

    Mendes, C.J. [CrossChasm Technologies, Cambridge, ON (Canada); Stevens, M.B.; Fowler, M.W. [Waterloo Univ., ON (Canada). Dept. of Chemical Engineering; Fraser, R.A. [Waterloo Univ., ON (Canada). Dept. of Mechanical Engineering; Wilhelm, E.J. [Paul Scherrer Inst., Villigen (Switzerland). Energy Systems Analysis

    2007-07-01

    A model-based design process for plug-in hybrid vehicles (PHEVs) was presented. The paper discussed steps between the initial design concept and a working vehicle prototype, and focused on an investigation of the software-in-the-loop (SIL), hardware-in-the-loop (HIL), and component-in-the-loop (CIL) design phases. The role and benefits of using simulation were also reviewed. A method for mapping and identifying components was provided along with a hybrid control strategy and component-level control optimization process. The role of simulation in component evaluation, architecture design, and de-bugging procedures was discussed, as well as the role simulation networks can play in speeding deployment times. The simulations focused on work performed on a 2005 Chevrolet Equinox converted to a fuel cell hybrid electric vehicle (FCHEV). Components were aggregated to create a complete virtual vehicle. A simplified vehicle model was implemented onto the on-board vehicle control hardware. Optimization metrics were estimated at 10 alpha values during each control loop iteration. The simulation was then used to tune the control system under a variety of drive cycles and conditions. A CIL technique was used to place a physical hybrid electric vehicle (HEV) component under the control of a real time HEV/PHEV simulation. It was concluded that controllers should have a standardized component description that supports integration into advanced testing procedures. 4 refs., 9 figs.

  20. The voluntary driven exoskeleton Hybrid Assistive Limb (HAL) for postoperative training of thoracic ossification of the posterior longitudinal ligament: a case report.

    Science.gov (United States)

    Fujii, Kengo; Abe, Tetsuya; Kubota, Shigeki; Marushima, Aiki; Kawamoto, Hiroaki; Ueno, Tomoyuki; Matsushita, Akira; Nakai, Kei; Saotome, Kosaku; Kadone, Hideki; Endo, Ayumu; Haginoya, Ayumu; Hada, Yasushi; Matsumura, Akira; Sankai, Yoshiyuki; Yamazaki, Masashi

    2017-05-01

    The hybrid assistive limb (HAL) is a wearable robot suit that assists in voluntary control of knee and hip joint motion by detecting bioelectric signals on the surface of the skin with high sensitivity. HAL has been reported to be effective for functional recovery in motor impairments. However, few reports have revealed the utility of HAL for patients who have undergone surgery for thoracic ossification of the posterior longitudinal ligament (thoracic OPLL). Herein, we present a postoperative thoracic OPLL patient who showed remarkable functional recovery after training with HAL. A 63-year-old woman, who could not walk due to muscle weakness before surgery, underwent posterior decompression and fusion. Paralysis was re-aggravated after the initial postoperative rising. We diagnosed that paralysis was due to residual compression from the anterior lesion and microinstability after posterior fixation, and prescribed bed rest for a further 3 weeks. The incomplete paralysis gradually recovered, and walking training with HAL was started on postoperative day 44 in addition to standard physical therapy. The patient underwent 10 sessions of HAL training until discharge on postoperative day 73. Results of a 10-m walk test were assessed after every session, and the patient's speed and cadence markedly improved. At discharge, the patient could walk with 2 crutches and no assistance. Furthermore, no adverse events associated with HAL training occurred. HAL training for postoperative thoracic OPLL patients may enhance improvement in walking ability, even if severe impairment of ambulation and muscle weakness exist preoperatively.

  1. Specification of real-time automation systems with HybridUML; Spezifikation von Echtzeit-Automatisierungssystemen mit HybridUML

    Energy Technology Data Exchange (ETDEWEB)

    Berkenkoetter, K.; Bisanz, S.; Hannemann, U.; Peleska, J. [Univ. Bremen (Germany)

    2004-07-01

    Complex automation systems require specification formalisms supporting the description of real-time requirements with respect to both discrete and time-continuous observables. For this purpose, the authors have designed the HybridUML specification language. Discrete events, communication, and variable assignments are specified by state machines, timers, and invariant conditions. The time-continuous aspects of system behaviour are described by associating differential equations or time-dependent algebraic conditions with system states. The complexity of large systems is controlled by decomposing the specification into parallel components and hierarchical state machines. Instead of inventing a new language syntax, HybridUML is represented as a profile of the Unified Modeling Language UML 2.0. This allows to re-use the syntactic framework of well-accepted graphical UML constructs and development support provided by various UML case tools. The profile is associated with a precise language semantics linking unambiguous meaning to all HybridUML specifications. As a consequence, HybridUML specifications can be compiled into executable code which is suitable for execution in hard realtime on multi-processor computers. This serves both for the development of automation systems and for specification-based testing in real-time. This paper contains an introduction to HybridUML which is illustrated by an example from the field of automated train control. (orig.)

  2. Implementation and Operational Research: Cost and Efficiency of a Hybrid Mobile Multidisease Testing Approach With High HIV Testing Coverage in East Africa.

    Science.gov (United States)

    Chang, Wei; Chamie, Gabriel; Mwai, Daniel; Clark, Tamara D; Thirumurthy, Harsha; Charlebois, Edwin D; Petersen, Maya; Kabami, Jane; Ssemmondo, Emmanuel; Kadede, Kevin; Kwarisiima, Dalsone; Sang, Norton; Bukusi, Elizabeth A; Cohen, Craig R; Kamya, Moses; Havlir, Diane V; Kahn, James G

    2016-11-01

    In 2013-2014, we achieved 89% adult HIV testing coverage using a hybrid testing approach in 32 communities in Uganda and Kenya (SEARCH: NCT01864603). To inform scalability, we sought to determine: (1) overall cost and efficiency of this approach; and (2) costs associated with point-of-care (POC) CD4 testing, multidisease services, and community mobilization. We applied microcosting methods to estimate costs of population-wide HIV testing in 12 SEARCH trial communities. Main intervention components of the hybrid approach are census, multidisease community health campaigns (CHC), and home-based testing for CHC nonattendees. POC CD4 tests were provided for all HIV-infected participants. Data were extracted from expenditure records, activity registers, staff interviews, and time and motion logs. The mean cost per adult tested for HIV was $20.5 (range: $17.1-$32.1) (2014 US$), including a POC CD4 test at $16 per HIV+ person identified. Cost per adult tested for HIV was $13.8 at CHC vs. $31.7 by home-based testing. The cost per HIV+ adult identified was $231 ($87-$1245), with variability due mainly to HIV prevalence among persons tested (ie, HIV positivity rate). The marginal costs of multidisease testing at CHCs were $1.16/person for hypertension and diabetes, and $0.90 for malaria. Community mobilization constituted 15.3% of total costs. The hybrid testing approach achieved very high HIV testing coverage, with POC CD4, at costs similar to previously reported mobile, home-based, or venue-based HIV testing approaches in sub-Saharan Africa. By leveraging HIV infrastructure, multidisease services were offered at low marginal costs.

  3. Fast accurate MEG source localization using a multilayer perceptron trained with real brain noise

    International Nuclear Information System (INIS)

    Jun, Sung Chan; Pearlmutter, Barak A.; Nolte, Guido

    2002-01-01

    Iterative gradient methods such as Levenberg-Marquardt (LM) are in widespread use for source localization from electroencephalographic (EEG) and magnetoencephalographic (MEG) signals. Unfortunately, LM depends sensitively on the initial guess, necessitating repeated runs. This, combined with LM's high per-step cost, makes its computational burden quite high. To reduce this burden, we trained a multilayer perceptron (MLP) as a real-time localizer. We used an analytical model of quasistatic electromagnetic propagation through a spherical head to map randomly chosen dipoles to sensor activities according to the sensor geometry of a 4D Neuroimaging Neuromag-122 MEG system, and trained a MLP to invert this mapping in the absence of noise or in the presence of various sorts of noise such as white Gaussian noise, correlated noise, or real brain noise. A MLP structure was chosen to trade off computation and accuracy. This MLP was trained four times, with each type of noise. We measured the effects of initial guesses on LM performance, which motivated a hybrid MLP-start-LM method, in which the trained MLP initializes LM. We also compared the localization performance of LM, MLPs, and hybrid MLP-start-LMs for realistic brain signals. Trained MLPs are much faster than other methods, while the hybrid MLP-start-LMs are faster and more accurate than fixed-4-start-LM. In particular, the hybrid MLP-start-LM initialized by a MLP trained with the real brain noise dataset is 60 times faster and is comparable in accuracy to random-20-start-LM, and this hybrid system (localization error: 0.28 cm, computation time: 36 ms) shows almost as good performance as optimal-1-start-LM (localization error: 0.23 cm, computation time: 22 ms), which initializes LM with the correct dipole location. MLPs trained with noise perform better than the MLP trained without noise, and the MLP trained with real brain noise is almost as good an initial guesser for LM as the correct dipole location. (author) )

  4. 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.

  5. 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

  6. Hybridization and genome evolution I: The role of contingency during hybrid speciation

    Directory of Open Access Journals (Sweden)

    Fabrice EROUKHMANOFF, Richard I. BAILEY, Glenn-Peter SæTRE

    2013-10-01

    Full Text Available Homoploid hybrid speciation (HHS involves the recombination of two differentiated genomes into a novel, functional one without a change in chromosome number. Theoretically, there are numerous ways for two parental genomes to recombine. Hence, chance may play a large role in the formation of a hybrid species. If these genome combinations can evolve rapidly following hybridization and sympatric situations are numerous, recurrent homoploid hybrid speciation is a possibility. We argue that three different, but not mutually exclusive, types of contingencies could influence this process. First, many of these “hopeful monsters” of recombinant parent genotypes would likely have low fitness. Only specific combinations of parental genomic contributions may produce viable, intra-fertile hybrid species able to accommodate potential constraints arising from intragenomic conflict. Second, ecological conditions (competition, geography of the contact zones or the initial frequency of both parent species might favor different outcomes ranging from sympatric coexistence to the formation of hybrid swarms and ultimately hybrid speciation. Finally, history may also play an important role in promoting or constraining recurrent HHS if multiple hybridization events occur sequentially and parental divergence or isolation differs along this continuum. We discuss under which conditions HHS may occur multiple times in parallel and to what extent recombination and selection may fuse the parent genomes in the same or different ways. We conclude by examining different approaches that might help to solve this intriguing evolutionary puzzle [Current Zoology 59 (5: 667-674, 2013]. 

  7. A Flipped Classroom Approach to Improving the Quality of Delirium Care Using an Interprofessional Train-the-Trainer Program.

    Science.gov (United States)

    Sockalingam, Sanjeev; James, Sandra-Li; Sinyi, Rebecca; Carroll, Aideen; Laidlaw, Jennifer; Yanofsky, Richard; Sheehan, Kathleen

    2016-01-01

    Given the prevalence and morbidity associated with delirium, there is a need for effective and efficient institutional approaches to delirium training in health care settings. Novel education methods, specifically the "flipped classroom" (FC) and "train-the-trainer" (TTT), have the potential to address these delirium training gaps. This study evaluates the effect of a TTT FC interprofessional delirium training program on participants' perceived ability to manage delirium, delirium knowledge, and clinicians' delirium assessment behaviors. FC Delirium TTT sessions were implemented in a large four-hospital network and consisted of presession online work and a 3-hour in-session component. The 156 TTT interprofessional participants who attended the sessions (ie, trainers) were expected to then deliver delirium training to their patient care units. Delirium care self-efficacy and knowledge test scores were measured before, after, and 6 months after the training session. Clinician delirium assessment rates were measured by chart audits before and 3 months after trainer's implementation of delirium training sessions. Delirium knowledge test scores (7.8 ± 1.6 versus 9.7 ± 1.2, P approach can improve participants' perceived delirium care skills and confidence, and delirium knowledge up to 6 months after the session. This approach provides a model for implementing hospitalwide delirium education that can change delirium assessment behavior while minimizing time and personnel requirements.

  8. A Hybrid Backward-Forward Iterative Model for Improving Capacity Building of Earth Observations for Sustainable Societal Application

    Science.gov (United States)

    Hossain, F.; Iqbal, N.; Lee, H.; Muhammad, A.

    2015-12-01

    When it comes to building durable capacity for implementing state of the art technology and earth observation (EO) data for improved decision making, it has been long recognized that a unidirectional approach (from research to application) often does not work. Co-design of capacity building effort has recently been recommended as a better alternative. This approach is a two-way street where scientists and stakeholders engage intimately along the entire chain of actions from design of research experiments to packaging of decision making tools and each party provides an equal amount of input. Scientists execute research experiments based on boundary conditions and outputs that are defined as tangible by stakeholders for decision making. On the other hand, decision making tools are packaged by stakeholders with scientists ensuring the application-specific science is relevant. In this talk, we will overview one such iterative capacity building approach that we have implemented for gravimetry-based satellite (GRACE) EO data for improved groundwater management in Pakistan. We call our approach a hybrid approach where the initial step is a forward model involving a conventional short-term (3 day) capacity building workshop in the stakeholder environment addressing a very large audience. In this forward model, the net is cast wide to 'shortlist' a set of highly motivated stakeholder agency staffs who are then engaged more directly in 1-1 training. In the next step (the backward model), these short listed staffs are then brought back in the research environment of the scientists (supply) for 1-1 and long-term (6 months) intense brainstorming, training, and design of decision making tools. The advantage of this backward model is that it allows for a much better understanding for scientists of the ground conditions and hurdles of making a EO-based scientific innovation work for a specific decision making problem that is otherwise fundamentally impossible in conventional

  9. 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.

  10. "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...

  11. 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)

  12. 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.

  13. TEMPTING system: a hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries.

    Science.gov (United States)

    Chang, Yung-Chun; Dai, Hong-Jie; Wu, Johnny Chi-Yang; Chen, Jian-Ming; Tsai, Richard Tzong-Han; Hsu, Wen-Lian

    2013-12-01

    Patient discharge summaries provide detailed medical information about individuals who have been hospitalized. To make a precise and legitimate assessment of the abundant data, a proper time layout of the sequence of relevant events should be compiled and used to drive a patient-specific timeline, which could further assist medical personnel in making clinical decisions. The process of identifying the chronological order of entities is called temporal relation extraction. In this paper, we propose a hybrid method to identify appropriate temporal links between a pair of entities. The method combines two approaches: one is rule-based and the other is based on the maximum entropy model. We develop an integration algorithm to fuse the results of the two approaches. All rules and the integration algorithm are formally stated so that one can easily reproduce the system and results. To optimize the system's configuration, we used the 2012 i2b2 challenge TLINK track dataset and applied threefold cross validation to the training set. Then, we evaluated its performance on the training and test datasets. The experiment results show that the proposed TEMPTING (TEMPoral relaTion extractING) system (ranked seventh) achieved an F-score of 0.563, which was at least 30% better than that of the baseline system, which randomly selects TLINK candidates from all pairs and assigns the TLINK types. The TEMPTING system using the hybrid method also outperformed the stage-based TEMPTING system. Its F-scores were 3.51% and 0.97% better than those of the stage-based system on the training set and test set, respectively. Copyright © 2013 Elsevier Inc. All rights reserved.

  14. Operation management of daily economic dispatch using novel hybrid particle swarm optimization and gravitational search algorithm with hybrid mutation strategy

    Science.gov (United States)

    Wang, Yan; Huang, Song; Ji, Zhicheng

    2017-07-01

    This paper presents a hybrid particle swarm optimization and gravitational search algorithm based on hybrid mutation strategy (HGSAPSO-M) to optimize economic dispatch (ED) including distributed generations (DGs) considering market-based energy pricing. A daily ED model was formulated and a hybrid mutation strategy was adopted in HGSAPSO-M. The hybrid mutation strategy includes two mutation operators, chaotic mutation, Gaussian mutation. The proposed algorithm was tested on IEEE-33 bus and results show that the approach is effective for this problem.

  15. 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

  16. Training Inference Making Skills Using a Situation Model Approach Improves Reading Comprehension

    Directory of Open Access Journals (Sweden)

    Lisanne eBos

    2016-02-01

    Full Text Available This study aimed to enhance third and fourth graders’ text comprehension at the situation model level. Therefore, we tested a reading strategy training developed to target inference making skills, which are widely considered to be pivotal to situation model construction. The training was grounded in contemporary literature on situation model-based inference making and addressed the source (text-based versus knowledge-based, type (necessary versus unnecessary for (re-establishing coherence, and depth of an inference (making single lexical inferences versus combining multiple lexical inferences, as well as the type of searching strategy (forward versus backward. Results indicated that, compared to a control group (n = 51, children who followed the experimental training (n = 67 improved their inference making skills supportive to situation model construction. Importantly, our training also resulted in increased levels of general reading comprehension and motivation. In sum, this study showed that a ‘level of text representation’-approach can provide a useful framework to teach inference making skills to third and fourth graders.

  17. A hybrid approach to predict the relationship between tablet tensile strength and compaction pressure using analytical powder compression.

    Science.gov (United States)

    Persson, Ann-Sofie; Alderborn, Göran

    2018-04-01

    The objective was to present a hybrid approach to predict the strength-pressure relationship (SPR) of tablets using common compression parameters and a single measurement of tablet tensile strength. Experimental SPR were derived for six pharmaceutical powders with brittle and ductile properties and compared to predicted SPR based on a three-stage approach. The prediction was based on the Kawakita b -1 parameter and the in-die Heckel yield stress, an estimate of maximal tensile strength, and a parameter proportionality factor α. Three values of α were used to investigate the influence of the parameter on the SPR. The experimental SPR could satisfactorily be described by the three stage model, however for sodium bicarbonate the tensile strength plateau could not be observed experimentally. The shape of the predicted SPR was to a minor extent influenced by the Kawakita b -1 but the width of the linear region was highly influenced by α. An increased α increased the width of the linear region and thus also the maximal predicted tablet tensile strength. Furthermore, the correspondence between experimental and predicted SPR was influenced by the α value and satisfactory predictions were in general obtained for α = 4.1 indicating the predictive potential of the hybrid approach. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  18. 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.

  19. 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

  20. Resource approach in providing health-saving process of future teachers training

    Directory of Open Access Journals (Sweden)

    Mykytiuk S.A.

    2012-12-01

    Full Text Available The mechanisms of realization of resource approach are exposed in organization of pedagogical education. There were defined the ways of providing health-saving teacher training, namely: assessment criteria of adjustment of social order and personal professional development needs, means of implementing the tasks of pedagogical education concept according to the resource approach. The methods of maintainance and strengthening of health of future teachers are specified in the process of professional preparation. It is marked that resource approach unites requirement to the competence of teacher, provides the account of age-dependent features of organism of student and periods of becoming of personality of student and teacher. Resource approach is given by possibility to take into account the specific of labour and level of knowledge, abilities and skills of every student. Resource approach harmonizes the actual aspects of complex of the modern scientific going near education of students and professional preparation of future teachers.