WorldWideScience

Sample records for feedforward models trained

  1. Adaptive training of feedforward neural networks by Kalman filtering

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.

    1995-02-01

    Adaptive training of feedforward neural networks by Kalman filtering is described. Adaptive training is particularly important in estimation by neural network in real-time environmental where the trained network is used for system estimation while the network is further trained by means of the information provided by the experienced/exercised ongoing operation. As result of this, neural network adapts itself to a changing environment to perform its mission without recourse to re-training. The performance of the training method is demonstrated by means of actual process signals from a nuclear power plant. (orig.)

  2. Training feed-forward neural networks with gain constraints

    Science.gov (United States)

    Hartman

    2000-04-01

    Inaccurate input-output gains (partial derivatives of outputs with respect to inputs) are common in neural network models when input variables are correlated or when data are incomplete or inaccurate. Accurate gains are essential for optimization, control, and other purposes. We develop and explore a method for training feedforward neural networks subject to inequality or equality-bound constraints on the gains of the learned mapping. Gain constraints are implemented as penalty terms added to the objective function, and training is done using gradient descent. Adaptive and robust procedures are devised for balancing the relative strengths of the various terms in the objective function, which is essential when the constraints are inconsistent with the data. The approach has the virtue that the model domain of validity can be extended via extrapolation training, which can dramatically improve generalization. The algorithm is demonstrated here on artificial and real-world problems with very good results and has been advantageously applied to dozens of models currently in commercial use.

  3. Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm

    Directory of Open Access Journals (Sweden)

    Haizhou Wu

    2016-01-01

    Full Text Available Symbiotic organisms search (SOS is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a challenging task to present a satisfactory and efficient training algorithm for feedforward neural networks (FNNs. In this paper, SOS is employed as a new method for training FNNs. To investigate the performance of the aforementioned method, eight different datasets selected from the UCI machine learning repository are employed for experiment and the results are compared among seven metaheuristic algorithms. The results show that SOS performs better than other algorithms for training FNNs in terms of converging speed. It is also proven that an FNN trained by the method of SOS has better accuracy than most algorithms compared.

  4. Shared internal models for feedforward and feedback control.

    Science.gov (United States)

    Wagner, Mark J; Smith, Maurice A

    2008-10-15

    A child often learns to ride a bicycle in the driveway, free of unforeseen obstacles. Yet when she first rides in the street, we hope that if a car suddenly pulls out in front of her, she will combine her innate goal of avoiding an accident with her learned knowledge of the bicycle, and steer away or brake. In general, when we train to perform a new motor task, our learning is most robust if it updates the rules of online error correction to reflect the rules and goals of the new task. Here we provide direct evidence that, after a new feedforward motor adaptation, motor feedback responses to unanticipated errors become precisely task appropriate, even when such errors were never experienced during training. To study this ability, we asked how, if at all, do online responses to occasional, unanticipated force pulses during reaching arm movements change after adapting to altered arm dynamics? Specifically, do they change in a task-appropriate manner? In our task, subjects learned novel velocity-dependent dynamics. However, occasional force-pulse perturbations produced unanticipated changes in velocity. Therefore, after adaptation, task-appropriate responses to unanticipated pulses should compensate corresponding changes in velocity-dependent dynamics. We found that after adaptation, pulse responses precisely compensated these changes, although they were never trained to do so. These results provide evidence for a smart feedback controller which automatically produces responses specific to the learned dynamics of the current task. To accomplish this, the neural processes underlying feedback control must (1) be capable of accurate real-time state prediction for velocity via a forward model and (2) have access to recently learned changes in internal models of limb dynamics.

  5. A Robust Feedforward Model of the Olfactory System.

    Directory of Open Access Journals (Sweden)

    Yilun Zhang

    2016-04-01

    Full Text Available Most natural odors have sparse molecular composition. This makes the principles of compressed sensing potentially relevant to the structure of the olfactory code. Yet, the largely feedforward organization of the olfactory system precludes reconstruction using standard compressed sensing algorithms. To resolve this problem, recent theoretical work has shown that signal reconstruction could take place as a result of a low dimensional dynamical system converging to one of its attractor states. However, the dynamical aspects of optimization slowed down odor recognition and were also found to be susceptible to noise. Here we describe a feedforward model of the olfactory system that achieves both strong compression and fast reconstruction that is also robust to noise. A key feature of the proposed model is a specific relationship between how odors are represented at the glomeruli stage, which corresponds to a compression, and the connections from glomeruli to third-order neurons (neurons in the olfactory cortex of vertebrates or Kenyon cells in the mushroom body of insects, which in the model corresponds to reconstruction. We show that should this specific relationship hold true, the reconstruction will be both fast and robust to noise, and in particular to the false activation of glomeruli. The predicted connectivity rate from glomeruli to third-order neurons can be tested experimentally.

  6. Enhanced HMAX model with feedforward feature learning for multiclass categorization

    Directory of Open Access Journals (Sweden)

    Yinlin eLi

    2015-10-01

    Full Text Available In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 milliseconds of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: 1 To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; 2 To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; 3 Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.

  7. Enhanced HMAX model with feedforward feature learning for multiclass categorization.

    Science.gov (United States)

    Li, Yinlin; Wu, Wei; Zhang, Bo; Li, Fengfu

    2015-01-01

    In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX) is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT) layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 ms of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: (1) To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; (2) To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; (3) Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.

  8. A Novel Feed-Forward Modeling System Leads to Sustained Improvements in Attention and Academic Performance.

    Science.gov (United States)

    McDermott, Ashley F; Rose, Maya; Norris, Troy; Gordon, Eric

    2016-01-28

    This study tested a novel feed-forward modeling (FFM) system as a nonpharmacological intervention for the treatment of ADHD children and the training of cognitive skills that improve academic performance. This study implemented a randomized, controlled, parallel design comparing this FFM with a nonpharmacological community care intervention. Improvements were measured on parent- and clinician-rated scales of ADHD symptomatology and on academic performance tests completed by the participant. Participants were followed for 3 months after training. Participants in the FFM training group showed significant improvements in ADHD symptomatology and academic performance, while the control group did not. Improvements from FFM were sustained 3 months later. The FFM appeared to be an effective intervention for the treatment of ADHD and improving academic performance. This FFM training intervention shows promise as a first-line treatment for ADHD while improving academic performance. © The Author(s) 2016.

  9. Modeling of quasistatic magnetic hysteresis with feed-forward neural networks

    International Nuclear Information System (INIS)

    Makaveev, Dimitre; Dupre, Luc; De Wulf, Marc; Melkebeek, Jan

    2001-01-01

    A modeling technique for rate-independent (quasistatic) scalar magnetic hysteresis is presented, using neural networks. Based on the theory of dynamic systems and the wiping-out and congruency properties of the classical scalar Preisach hysteresis model, the choice of a feed-forward neural network model is motivated. The neural network input parameters at each time step are the corresponding magnetic field strength and memory state, thereby assuring accurate prediction of the change of magnetic induction. For rate-independent hysteresis, the current memory state can be determined by the last extreme magnetic field strength and induction values, kept in memory. The choice of a network training set is motivated and the performance of the network is illustrated for a test set not used during training. Very accurate prediction of both major and minor hysteresis loops is observed, proving that the neural network technique is suitable for hysteresis modeling. [copyright] 2001 American Institute of Physics

  10. Objective Model Selection for Identifying the Human Feedforward Response in Manual Control.

    Science.gov (United States)

    Drop, Frank M; Pool, Daan M; van Paassen, Marinus Rene M; Mulder, Max; Bulthoff, Heinrich H

    2018-01-01

    Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification procedure is presented that aims at an objective model selection for identifying the human feedforward response, using linear time-invariant autoregressive with exogenous input models. A new model selection criterion is proposed to decide on the model order (number of parameters) and the presence of feedforward in addition to feedback. For a range of typical control tasks, it is shown by means of Monte Carlo computer simulations that the classical Bayesian information criterion (BIC) leads to selecting models that contain a feedforward path from data generated by a pure feedback model: "false-positive" feedforward detection. To eliminate these false-positives, the modified BIC includes an additional penalty on model complexity. The appropriate weighting is found through computer simulations with a hypothesized HC model prior to performing a tracking experiment. Experimental human-in-the-loop data will be considered in future work. With appropriate weighting, the method correctly identifies the HC dynamics in a wide range of control tasks, without false-positive results.

  11. CUDA-accelerated genetic feedforward-ANN training for data mining

    International Nuclear Information System (INIS)

    Patulea, Catalin; Peace, Robert; Green, James

    2010-01-01

    We present an implementation of genetic algorithm (GA) training of feedforward artificial neural networks (ANNs) targeting commodity graphics cards (GPUs). By carefully mapping the problem onto the unique GPU architecture, we achieve order-of-magnitude speedup over a conventional CPU implementation. Furthermore, we show that the speedup is consistent across a wide range of data set sizes, making this implementation ideal for large data sets. This performance boost enables the genetic algorithm to search a larger subset of the solution space, which results in more accurate pattern classification. Finally, we demonstrate this method in the context of the 2009 UC San Diego Data Mining Contest, achieving a world-class lift on a data set of 94682 e-commerce transactions.

  12. CUDA-accelerated genetic feedforward-ANN training for data mining

    Energy Technology Data Exchange (ETDEWEB)

    Patulea, Catalin; Peace, Robert; Green, James, E-mail: cpatulea@sce.carleton.ca, E-mail: rpeace@sce.carleton.ca, E-mail: jrgreen@sce.carleton.ca [School of Systems and Computer Engineering, Carleton University, Ottawa, K1S 5B6 (Canada)

    2010-11-01

    We present an implementation of genetic algorithm (GA) training of feedforward artificial neural networks (ANNs) targeting commodity graphics cards (GPUs). By carefully mapping the problem onto the unique GPU architecture, we achieve order-of-magnitude speedup over a conventional CPU implementation. Furthermore, we show that the speedup is consistent across a wide range of data set sizes, making this implementation ideal for large data sets. This performance boost enables the genetic algorithm to search a larger subset of the solution space, which results in more accurate pattern classification. Finally, we demonstrate this method in the context of the 2009 UC San Diego Data Mining Contest, achieving a world-class lift on a data set of 94682 e-commerce transactions.

  13. Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model.

    Science.gov (United States)

    Hardy, N F; Buonomano, Dean V

    2018-02-01

    Brain activity evolves through time, creating trajectories of activity that underlie sensorimotor processing, behavior, and learning and memory. Therefore, understanding the temporal nature of neural dynamics is essential to understanding brain function and behavior. In vivo studies have demonstrated that sequential transient activation of neurons can encode time. However, it remains unclear whether these patterns emerge from feedforward network architectures or from recurrent networks and, furthermore, what role network structure plays in timing. We address these issues using a recurrent neural network (RNN) model with distinct populations of excitatory and inhibitory units. Consistent with experimental data, a single RNN could autonomously produce multiple functionally feedforward trajectories, thus potentially encoding multiple timed motor patterns lasting up to several seconds. Importantly, the model accounted for Weber's law, a hallmark of timing behavior. Analysis of network connectivity revealed that efficiency-a measure of network interconnectedness-decreased as the number of stored trajectories increased. Additionally, the balance of excitation (E) and inhibition (I) shifted toward excitation during each unit's activation time, generating the prediction that observed sequential activity relies on dynamic control of the E/I balance. Our results establish for the first time that the same RNN can generate multiple functionally feedforward patterns of activity as a result of dynamic shifts in the E/I balance imposed by the connectome of the RNN. We conclude that recurrent network architectures account for sequential neural activity, as well as for a fundamental signature of timing behavior: Weber's law.

  14. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Directory of Open Access Journals (Sweden)

    René Felix Reinhart

    2017-02-01

    Full Text Available Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  15. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-02-08

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  16. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-01-01

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697

  17. Combined feedforward and model-assisted active disturbance rejection control for non-minimum phase system.

    Science.gov (United States)

    Sun, Li; Li, Donghai; Gao, Zhiqiang; Yang, Zhao; Zhao, Shen

    2016-09-01

    Control of the non-minimum phase (NMP) system is challenging, especially in the presence of modelling uncertainties and external disturbances. To this end, this paper presents a combined feedforward and model-assisted Active Disturbance Rejection Control (MADRC) strategy. Based on the nominal model, the feedforward controller is used to produce a tracking performance that has minimum settling time subject to a prescribed undershoot constraint. On the other hand, the unknown disturbances and uncertain dynamics beyond the nominal model are compensated by MADRC. Since the conventional Extended State Observer (ESO) is not suitable for the NMP system, a model-assisted ESO (MESO) is proposed based on the nominal observable canonical form. The convergence of MESO is proved in time domain. The stability, steady-state characteristics and robustness of the closed-loop system are analyzed in frequency domain. The proposed strategy has only one tuning parameter, i.e., the bandwidth of MESO, which can be readily determined with a prescribed robustness level. Some comparative examples are given to show the efficacy of the proposed method. This paper depicts a promising prospect of the model-assisted ADRC in dealing with complex systems. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Feedforward Control of a 3-D Physiological Articulatory Model for Vowel Production

    Institute of Scientific and Technical Information of China (English)

    FANG Qiang; Akikazu Nishikido; Jianwu Dang

    2009-01-01

    A three-dimensional (3-D) physiological articulatory model was developed to account for the bio-mechanical properties of the speech organs in speech production. Control of the model to investigate the mechanism of speech production requires an efficient control module to estimate muscle activation patterns, which is used to manipulate the 3-D physiological arUculatory model, according to the desired articulatory posture. For this purpose, a feedforward control strategy was developed by mapping the articulatory target to the corresponding muscle activation pattern via the intrinsic representation of vowel articulation. In this process, the articulatory postures are first mapped to the corresponding intrinsic representations; then, the articulatory postures are clustered in the intrinsic representations space and a nonlinear function is ap-proximated for each cluster to map the intrinsic representation of vowel articulation to the muscle activation pattern by using general regression neural networks (GRNN). The results show that the feedforward control module is able to manipulate the 3-D physiological articulatory model for vowel production with high accu-racy both acoustically and articulatodly.

  19. Modeling of an industrial process of pleuromutilin fermentation using feed-forward neural networks

    Directory of Open Access Journals (Sweden)

    L. Khaouane

    2013-03-01

    Full Text Available This work investigates the use of artificial neural networks in modeling an industrial fermentation process of Pleuromutilin produced by Pleurotus mutilus in a fed-batch mode. Three feed-forward neural network models characterized by a similar structure (five neurons in the input layer, one hidden layer and one neuron in the output layer are constructed and optimized with the aim to predict the evolution of three main bioprocess variables: biomass, substrate and product. Results show a good fit between the predicted and experimental values for each model (the root mean squared errors were 0.4624% - 0.1234 g/L and 0.0016 mg/g respectively. Furthermore, the comparison between the optimized models and the unstructured kinetic models in terms of simulation results shows that neural network models gave more significant results. These results encourage further studies to integrate the mathematical formulae extracted from these models into an industrial control loop of the process.

  20. Objective Model Selection for Identifying the Human Feedforward Response in Manual Control

    OpenAIRE

    Drop, F.M.; Pool, D.M.; van Paassen, M.M.; Mulder, M.; Bülthoff, Heinrich H.

    2017-01-01

    Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification proce...

  1. Multiple-Input Subject-Specific Modeling of Plasma Glucose Concentration for Feedforward Control.

    Science.gov (United States)

    Kotz, Kaylee; Cinar, Ali; Mei, Yong; Roggendorf, Amy; Littlejohn, Elizabeth; Quinn, Laurie; Rollins, Derrick K

    2014-11-26

    The ability to accurately develop subject-specific, input causation models, for blood glucose concentration (BGC) for large input sets can have a significant impact on tightening control for insulin dependent diabetes. More specifically, for Type 1 diabetics (T1Ds), it can lead to an effective artificial pancreas (i.e., an automatic control system that delivers exogenous insulin) under extreme changes in critical disturbances. These disturbances include food consumption, activity variations, and physiological stress changes. Thus, this paper presents a free-living, outpatient, multiple-input, modeling method for BGC with strong causation attributes that is stable and guards against overfitting to provide an effective modeling approach for feedforward control (FFC). This approach is a Wiener block-oriented methodology, which has unique attributes for meeting critical requirements for effective, long-term, FFC.

  2. Force control of a magnetorheological damper using an elementary hysteresis model-based feedforward neural network

    International Nuclear Information System (INIS)

    Ekkachai, Kittipong; Nilkhamhang, Itthisek; Tungpimolrut, Kanokvate

    2013-01-01

    An inverse controller is proposed for a magnetorheological (MR) damper that consists of a hysteresis model and a voltage controller. The force characteristics of the MR damper caused by excitation signals are represented by a feedforward neural network (FNN) with an elementary hysteresis model (EHM). The voltage controller is constructed using another FNN to calculate a suitable input signal that will allow the MR damper to produce the desired damping force. The performance of the proposed EHM-based FNN controller is experimentally compared to existing control methodologies, such as clipped-optimal control, signum function control, conventional FNN, and recurrent neural network with displacement or velocity inputs. The results show that the proposed controller, which does not require force feedback to implement, provides excellent accuracy, fast response time, and lower energy consumption. (paper)

  3. Jerk derivative feedforward control for motion systems

    NARCIS (Netherlands)

    Boerlage, M.L.G.; Tousain, R.L.; Steinbuch, M.

    2004-01-01

    This work discusses reference trajectory relevant model based feedforward design. For motion systems which contain at least one rigid body mode and which are subject to reference trajectories with mostly low frequency energy, the proposed feedforward controller improves tracking performance

  4. Feedforward self-modeling enhances skill acquisition in children learning trampoline skills.

    Science.gov (United States)

    Ste-Marie, Diane M; Vertes, Kelly; Rymal, Amanda M; Martini, Rose

    2011-01-01

    The purpose of this research was to examine whether children would benefit from a feedforward self-modeling (FSM) video and to explore possible explanatory mechanisms for the potential benefits, using a self-regulation framework. To this end, children were involved in learning two five-skill trampoline routines. For one of the routines, a FSM video was provided during acquisition, whereas only verbal instructions were provided for the alternate routine. The FSM involved editing video footage such that it showed the learner performing the trampoline routine at a higher skill level than their current capability. Analyses of the data showed that while physical performance benefits were observed for the routine that was learned with the FSM video, no differences were obtained in relation to the self-regulatory measures. Thus, the FSM video enhanced motor skill acquisition, but this could not be explained by changes to the varied self-regulatory processes examined.

  5. Feedforward self-modeling enhances skill acquisition in children learning trampoline skills

    Directory of Open Access Journals (Sweden)

    Diane M. Ste-Marie

    2011-07-01

    Full Text Available The purpose of this research was to examine whether children would benefit from a feedforward self-modeling (FSM video and to explore possible explanatory mechanisms for the potential benefits, using a self-regulation framework. To this end, children were involved in learning two five-skill trampoline routines. For one of the routines, a FSM video was provided during acquisition, whereas only verbal instructions were provided for the alternate routine. The FSM involved editing video footage such that it showed the learner performing the trampoline routine at a higher skill level than their current capability. Analyses of the data showed that while physical performance benefits were observed for the routine that was learned with the FSM video, no differences were obtained in relation to the self-regulatory measures. Thus, the FSM video enhanced motor skill acquisition, but this could not be explained by changes to the varied self-regulatory processes examined.

  6. Feedforward neural network model estimating pollutant removal process within mesophilic upflow anaerobic sludge blanket bioreactor treating industrial starch processing wastewater.

    Science.gov (United States)

    Antwi, Philip; Li, Jianzheng; Meng, Jia; Deng, Kaiwen; Koblah Quashie, Frank; Li, Jiuling; Opoku Boadi, Portia

    2018-06-01

    In this a, three-layered feedforward-backpropagation artificial neural network (BPANN) model was developed and employed to evaluate COD removal an upflow anaerobic sludge blanket (UASB) reactor treating industrial starch processing wastewater. At the end of UASB operation, microbial community characterization revealed satisfactory composition of microbes whereas morphology depicted rod-shaped archaea. pH, COD, NH 4 + , VFA, OLR and biogas yield were selected by principal component analysis and used as input variables. Whilst tangent sigmoid function (tansig) and linear function (purelin) were assigned as activation functions at the hidden-layer and output-layer, respectively, optimum BPANN architecture was achieved with Levenberg-Marquardt algorithm (trainlm) after eleven training algorithms had been tested. Based on performance indicators such the mean squared errors, fractional variance, index of agreement and coefficient of determination (R 2 ), the BPANN model demonstrated significant performance with R 2 reaching 87%. The study revealed that, control and optimization of an anaerobic digestion process with BPANN model was feasible. Copyright © 2018 Elsevier Ltd. All rights reserved.

  7. Modeling and inverse feedforward control for conducting polymer actuators with hysteresis

    International Nuclear Information System (INIS)

    Wang, Xiangjiang; Alici, Gursel; Tan, Xiaobo

    2014-01-01

    Conducting polymer actuators are biocompatible with a small footprint, and operate in air or liquid media under low actuation voltages. This makes them excellent actuators for macro- and micro-manipulation devices, however, their positioning ability or accuracy is adversely affected by their hysteresis non-linearity under open-loop control strategies. In this paper, we establish a hysteresis model for conducting polymer actuators, based on a rate-independent hysteresis model known as the Duhem model. The hysteresis model is experimentally identified and integrated with the linear dynamics of the actuator. This combined model is inverted to control the displacement of the tri-layer actuators considered in this study, without using any external feedback. The inversion requires an inverse hysteresis model which was experimentally identified using an inverse neural network model. Experimental results show that the position tracking errors are reduced by more than 50% when the hysteresis inverse model is incorporated into an inversion-based feedforward controller, indicating the potential of the proposed method in enabling wider use of such smart actuators. (paper)

  8. Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System

    Directory of Open Access Journals (Sweden)

    Long Wu

    2018-02-01

    Full Text Available Solid oxide fuel cell (SOFC is widely considered as an alternative solution among the family of the sustainable distributed generation. Its load flexibility enables it adjusting the power output to meet the requirements from power grid balance. Although promising, its control is challenging when faced with load changes, during which the output voltage is required to be maintained as constant and fuel utilization rate kept within a safe range. Moreover, it makes the control even more intractable because of the multivariable coupling and strong nonlinearity within the wide-range operating conditions. To this end, this paper developed a multiple model predictive control strategy for reliable SOFC operation. The resistance load is regarded as a measurable disturbance, which is an input to the model predictive control as feedforward compensation. The coupling is accommodated by the receding horizon optimization. The nonlinearity is mitigated by the multiple linear models, the weighted sum of which serves as the final control execution. The merits of the proposed control structure are demonstrated by the simulation results.

  9. Interpretation of correlated neural variability from models of feed-forward and recurrent circuits

    Science.gov (United States)

    2018-01-01

    Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures—recurrent connections, shared feed-forward projections, and shared gain fluctuations—on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing. PMID:29408930

  10. Interpretation of correlated neural variability from models of feed-forward and recurrent circuits.

    Directory of Open Access Journals (Sweden)

    Volker Pernice

    2018-02-01

    Full Text Available Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures-recurrent connections, shared feed-forward projections, and shared gain fluctuations-on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing.

  11. Feedforward and feedback projections of caudal belt and parabelt areas of auditory cortex: refining the hierarchical model

    Directory of Open Access Journals (Sweden)

    Troy A Hackett

    2014-04-01

    Full Text Available Our working model of the primate auditory cortex recognizes three major regions (core, belt, parabelt, subdivided into thirteen areas. The connections between areas are topographically ordered in a manner consistent with information flow along two major anatomical axes: core-belt-parabelt and caudal-rostral. Remarkably, most of the connections supporting this model were revealed using retrograde tracing techniques. Little is known about laminar circuitry, as anterograde tracing of axon terminations has rarely been used. The purpose of the present study was to examine the laminar projections of three areas of auditory cortex, pursuant to analysis of all areas. The selected areas were: middle lateral belt (ML; caudomedial belt (CM; and caudal parabelt (CPB. Injections of anterograde tracers yielded data consistent with major features of our model, and also new findings that compel modifications. Results supporting the model were: 1 feedforward projection from ML and CM terminated in CPB; 2 feedforward projections from ML and CPB terminated in rostral areas of the belt and parabelt; and 3 feedback projections typified inputs to the core region from belt and parabelt. At odds with the model was the convergence of feedforward inputs into rostral medial belt from ML and CPB. This was unexpected since CPB is at a higher stage of the processing hierarchy, with mainly feedback projections to all other belt areas. Lastly, extending the model, feedforward projections from CM, ML, and CPB overlapped in the temporal parietal occipital area (TPO in the superior temporal sulcus, indicating significant auditory influence on sensory processing in this region. The combined results refine our working model and highlight the need to complete studies of the laminar inputs to all areas of auditory cortex. Their documentation is essential for developing informed hypotheses about the neurophysiological influences of inputs to each layer and area.

  12. Feedforward Object-Vision Models Only Tolerate Small Image Variations Compared to Human

    Directory of Open Access Journals (Sweden)

    Masoud eGhodrati

    2014-07-01

    Full Text Available Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modelling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well when images with more complex variations of the same object are applied to them. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e. briefly presented masked stimuli with complex image variations, human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modelling. We show that this approach is not of significant help in solving the computational crux of object recognition (that is invariant object recognition when the identity-preserving image variations become more complex.

  13. Control of a flexible beam actuated by macro-fiber composite patches: I. Modeling and feedforward trajectory control

    International Nuclear Information System (INIS)

    Schröck, Johannes; Meurer, Thomas; Kugi, Andreas

    2011-01-01

    This paper considers a systematic approach for motion planning and feedforward control design for a flexible cantilever actuated by piezoelectric macro-fiber composite (MFC) patches. For accurate feedforward tracking control, special attention has to be paid to the inherent nonlinear hysteresis and creep behavior of these actuators. In order to account for these effects an appropriate compensator is applied which allows us to perform the tracking controller design on the basis of a linear infinite-dimensional model. A detailed analysis of the nonlinear actuator behavior as well as the compensator design and the overall experimental validation is presented in the companion paper (Schröck et al 2011 Smart Mater. Struct. 20 015016). The governing equations of motion of the hysteresis and creep compensated cantilever are determined by means of the extended Hamilton's principle. This allows us to consider the influence of the bonded patch actuators on the mechanical properties of the underlying beam structure in a straightforward manner and results in a model with spatially varying system parameters. For the solution of the motion planning and feedforward control problem a flatness-based methodology is proposed. In a first step, the infinite-dimensional system of the MFC-actuated flexible cantilever is approximated by a finite-dimensional model, where all system variables, i.e. the states, input and output, can be parameterized in terms of a so-called flat output. In a second step, it is shown by numerical simulations that these parameterizations converge with increasing system order of the finite-dimensional model such that the feedforward control input can be directly calculated in order to realize prescribed output trajectories

  14. Predictive zero-dimensional combustion model for DI diesel engine feed-forward control

    International Nuclear Information System (INIS)

    Catania, Andrea Emilio; Finesso, Roberto; Spessa, Ezio

    2011-01-01

    Highlights: → Zero-dimensional low-throughput combustion model for real-time control in diesel engine applications. → Feed-forward control of MFB50, p max and IMEP in both conventional and PCCI combustion modes. → Capability of resolving the contribution to HRR of each injection pulse in multiple injection schedule. → Ignition delay and model parameters estimated through physically consistent and easy-to-tune correlations. - Abstract: An innovative zero-dimensional predictive combustion model has been developed for the estimation of HRR (heat release rate) and in-cylinder pressure traces. This model has been assessed and applied to conventional and PCCI (premixed charge compression ignition) DI diesel engines for model-based feed-forward control purposes. The injection rate profile is calculated on the basis of the injected fuel quantities and on the injection parameters, such as SOI (start of injection), ET (energizing time), and DT (dwell time), taking the injector NOD (nozzle opening delay) and NCD (nozzle closure delay) into account. The injection rate profile in turn allows the released chemical energy Q ch to be estimated. The approach starts from the assumption that, at each time instant, the HRR is proportional to the energy associated with the accumulated fuel mass in the combustion chamber. The main novelties of the proposed approach consist of the method that is adopted to estimate the fuel ignition delay and of injection rate splitting for HRR estimation. The procedure allows an accurate calculation to be made of the different combustion parameters that are important for engine calibration, such as SOC (start of combustion) and MFB50 (50% of fuel mass fraction burned angle). On the basis of an estimation of the fuel released chemical energy, of the heat globally exchanged from the charge with the walls and of the energy associated with the fuel evaporation, the charge net energy is calculated, for a subsequent evaluation of the in

  15. Predictive zero-dimensional combustion model for DI diesel engine feed-forward control

    Energy Technology Data Exchange (ETDEWEB)

    Catania, Andrea Emilio; Finesso, Roberto [IC Engines Advanced Laboratory, Politecnico di Torino, c.so Duca degli Abruzzi 24, 10129 Torino (Italy); Spessa, Ezio, E-mail: ezio.spessa@polito.it [IC Engines Advanced Laboratory, Politecnico di Torino, c.so Duca degli Abruzzi 24, 10129 Torino (Italy)

    2011-09-15

    Highlights: {yields} Zero-dimensional low-throughput combustion model for real-time control in diesel engine applications. {yields} Feed-forward control of MFB50, p{sub max} and IMEP in both conventional and PCCI combustion modes. {yields} Capability of resolving the contribution to HRR of each injection pulse in multiple injection schedule. {yields} Ignition delay and model parameters estimated through physically consistent and easy-to-tune correlations. - Abstract: An innovative zero-dimensional predictive combustion model has been developed for the estimation of HRR (heat release rate) and in-cylinder pressure traces. This model has been assessed and applied to conventional and PCCI (premixed charge compression ignition) DI diesel engines for model-based feed-forward control purposes. The injection rate profile is calculated on the basis of the injected fuel quantities and on the injection parameters, such as SOI (start of injection), ET (energizing time), and DT (dwell time), taking the injector NOD (nozzle opening delay) and NCD (nozzle closure delay) into account. The injection rate profile in turn allows the released chemical energy Q{sub ch} to be estimated. The approach starts from the assumption that, at each time instant, the HRR is proportional to the energy associated with the accumulated fuel mass in the combustion chamber. The main novelties of the proposed approach consist of the method that is adopted to estimate the fuel ignition delay and of injection rate splitting for HRR estimation. The procedure allows an accurate calculation to be made of the different combustion parameters that are important for engine calibration, such as SOC (start of combustion) and MFB50 (50% of fuel mass fraction burned angle). On the basis of an estimation of the fuel released chemical energy, of the heat globally exchanged from the charge with the walls and of the energy associated with the fuel evaporation, the charge net energy is calculated, for a subsequent

  16. Feedforward mapping for engine control

    OpenAIRE

    Aran, Volkan; Ünel, Mustafa; Unel, Mustafa

    2016-01-01

    Feedforward control is widely used in electronic control units of internal combustion engines besides feedback controls. However, almost all feedforward control values are used in table form, also called maps, having engine speed and engine torque in their axes. Table approach limits all inte ractions in two input dimensions. This paper focuses on application of Gaussian process modelling of errors of inverse parametric model of the valve position. Validation results based on ...

  17. Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

    Directory of Open Access Journals (Sweden)

    Miaolei Zhou

    Full Text Available As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

  18. Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

    Science.gov (United States)

    Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan

    2014-01-01

    As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

  19. Spike-timing computation properties of a feed-forward neural network model

    Directory of Open Access Journals (Sweden)

    Drew Benjamin Sinha

    2014-01-01

    Full Text Available Brain function is characterized by dynamical interactions among networks of neurons. These interactions are mediated by network topology at many scales ranging from microcircuits to brain areas. Understanding how networks operate can be aided by understanding how the transformation of inputs depends upon network connectivity patterns, e.g. serial and parallel pathways. To tractably determine how single synapses or groups of synapses in such pathways shape transformations, we modeled feed-forward networks of 7-22 neurons in which synaptic strength changed according to a spike-timing dependent plasticity rule. We investigated how activity varied when dynamics were perturbed by an activity-dependent electrical stimulation protocol (spike-triggered stimulation; STS in networks of different topologies and background input correlations. STS can successfully reorganize functional brain networks in vivo, but with a variability in effectiveness that may derive partially from the underlying network topology. In a simulated network with a single disynaptic pathway driven by uncorrelated background activity, structured spike-timing relationships between polysynaptically connected neurons were not observed. When background activity was correlated or parallel disynaptic pathways were added, however, robust polysynaptic spike timing relationships were observed, and application of STS yielded predictable changes in synaptic strengths and spike-timing relationships. These observations suggest that precise input-related or topologically induced temporal relationships in network activity are necessary for polysynaptic signal propagation. Such constraints for polysynaptic computation suggest potential roles for higher-order topological structure in network organization, such as maintaining polysynaptic correlation in the face of relatively weak synapses.

  20. Quantifying feedforward control: a linear scaling model for fingertip forces and object weight.

    Science.gov (United States)

    Lu, Ying; Bilaloglu, Seda; Aluru, Viswanath; Raghavan, Preeti

    2015-07-01

    The ability to predict the optimal fingertip forces according to object properties before the object is lifted is known as feedforward control, and it is thought to occur due to the formation of internal representations of the object's properties. The control of fingertip forces to objects of different weights has been studied extensively by using a custom-made grip device instrumented with force sensors. Feedforward control is measured by the rate of change of the vertical (load) force before the object is lifted. However, the precise relationship between the rate of change of load force and object weight and how it varies across healthy individuals in a population is not clearly understood. Using sets of 10 different weights, we have shown that there is a log-linear relationship between the fingertip load force rates and weight among neurologically intact individuals. We found that after one practice lift, as the weight increased, the peak load force rate (PLFR) increased by a fixed percentage, and this proportionality was common among the healthy subjects. However, at any given weight, the level of PLFR varied across individuals and was related to the efficiency of the muscles involved in lifting the object, in this case the wrist and finger extensor muscles. These results quantify feedforward control during grasp and lift among healthy individuals and provide new benchmarks to interpret data from neurologically impaired populations as well as a means to assess the effect of interventions on restoration of feedforward control and its relationship to muscular control. Copyright © 2015 the American Physiological Society.

  1. Stochastic Feedforward Control Technique

    Science.gov (United States)

    Halyo, Nesim

    1990-01-01

    Class of commanded trajectories modeled as stochastic process. Advanced Transport Operating Systems (ATOPS) research and development program conducted by NASA Langley Research Center aimed at developing capabilities for increases in capacities of airports, safe and accurate flight in adverse weather conditions including shear, winds, avoidance of wake vortexes, and reduced consumption of fuel. Advances in techniques for design of modern controls and increased capabilities of digital flight computers coupled with accurate guidance information from Microwave Landing System (MLS). Stochastic feedforward control technique developed within context of ATOPS program.

  2. Toward heterogeneity in feedforward network with synaptic delays based on FitzHugh-Nagumo model

    Science.gov (United States)

    Qin, Ying-Mei; Men, Cong; Zhao, Jia; Han, Chun-Xiao; Che, Yan-Qiu

    2018-01-01

    We focus on the role of heterogeneity on the propagation of firing patterns in feedforward network (FFN). Effects of heterogeneities both in parameters of neuronal excitability and synaptic delays are investigated systematically. Neuronal heterogeneity is found to modulate firing rates and spiking regularity by changing the excitability of the network. Synaptic delays are strongly related with desynchronized and synchronized firing patterns of the FFN, which indicate that synaptic delays may play a significant role in bridging rate coding and temporal coding. Furthermore, quasi-coherence resonance (quasi-CR) phenomenon is observed in the parameter domain of connection probability and delay-heterogeneity. All these phenomena above enable a detailed characterization of neuronal heterogeneity in FFN, which may play an indispensable role in reproducing the important properties of in vivo experiments.

  3. Combined feedforward and feedback control of end milling system

    OpenAIRE

    Čuš, Franc; Župerl, Uroš; Balič, Jože

    2012-01-01

    Purpose: Purpose of this paper. An intelligent control system is presented that uses a combination of feedforward and feedback for cutting force control in end milling.Design/methodology/approach: The network is trained by the feedback output that is minimized during training and most control action for disturbance rejection is finally performed by the rapid feedforward action of the network.Findings: The feedback controller corrects for errors caused by external disturbances. The feedforward...

  4. Training effectiveness evaluation model

    International Nuclear Information System (INIS)

    Penrose, J.B.

    1993-01-01

    NAESCO's Training Effectiveness Evaluation Model (TEEM) integrates existing evaluation procedures with new procedures. The new procedures are designed to measure training impact on organizational productivity. TEEM seeks to enhance organizational productivity through proactive training focused on operation results. These results can be identified and measured by establishing and tracking performance indicators. Relating training to organizational productivity is not easy. TEEM is a team process. It offers strategies to assess more effectively organizational costs and benefits of training. TEEM is one organization's attempt to refine, manage and extend its training evaluation program

  5. Fruit Classification by Wavelet-Entropy and Feedforward Neural Network Trained by Fitness-Scaled Chaotic ABC and Biogeography-Based Optimization

    Directory of Open Access Journals (Sweden)

    Shuihua Wang

    2015-08-01

    Full Text Available Fruit classification is quite difficult because of the various categories and similar shapes and features of fruit. In this work, we proposed two novel machine-learning based classification methods. The developed system consists of wavelet entropy (WE, principal component analysis (PCA, feedforward neural network (FNN trained by fitness-scaled chaotic artificial bee colony (FSCABC and biogeography-based optimization (BBO, respectively. The K-fold stratified cross validation (SCV was utilized for statistical analysis. The classification performance for 1653 fruit images from 18 categories showed that the proposed “WE + PCA + FSCABC-FNN” and “WE + PCA + BBO-FNN” methods achieve the same accuracy of 89.5%, higher than state-of-the-art approaches: “(CH + MP + US + PCA + GA-FNN ” of 84.8%, “(CH + MP + US + PCA + PSO-FNN” of 87.9%, “(CH + MP + US + PCA + ABC-FNN” of 85.4%, “(CH + MP + US + PCA + kSVM” of 88.2%, and “(CH + MP + US + PCA + FSCABC-FNN” of 89.1%. Besides, our methods used only 12 features, less than the number of features used by other methods. Therefore, the proposed methods are effective for fruit classification.

  6. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM

    OpenAIRE

    Cancelier, A.; Claumann, C. A.; Bolzan, A.; Machado, R. A. F.

    2016-01-01

    Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, ...

  7. A feed-forward spiking model of shape-coding by IT cells

    Directory of Open Access Journals (Sweden)

    August eRomeo

    2014-05-01

    Full Text Available The ability to recognize a shape is linked to figure-ground organization. Cell preferences appear to be correlated across contrast-polarity reversals and mirror reversals of polygon displays, but not so much across figure-ground (FG reversals. Here we present a network structure which explains both shape-coding by IT cells and the suppression of responses to figure-ground reversed stimuli. In the model figure-ground discrimination is achieved much before shape discrimination, that is itself evidenced by the difference in the spiking onsets of a couple of cells selective for two image categories.

  8. Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions.

    Science.gov (United States)

    Wagatsuma, Nobuhiko; Sakai, Ko

    2016-01-01

    Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional

  9. Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions

    Science.gov (United States)

    Wagatsuma, Nobuhiko; Sakai, Ko

    2017-01-01

    Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional

  10. Aircraft automatic-flight-control system with inversion of the model in the feed-forward path using a Newton-Raphson technique for the inversion

    Science.gov (United States)

    Smith, G. A.; Meyer, G.; Nordstrom, M.

    1986-01-01

    A new automatic flight control system concept suitable for aircraft with highly nonlinear aerodynamic and propulsion characteristics and which must operate over a wide flight envelope was investigated. This exact model follower inverts a complete nonlinear model of the aircraft as part of the feed-forward path. The inversion is accomplished by a Newton-Raphson trim of the model at each digital computer cycle time of 0.05 seconds. The combination of the inverse model and the actual aircraft in the feed-forward path alloys the translational and rotational regulators in the feedback path to be easily designed by linear methods. An explanation of the model inversion procedure is presented. An extensive set of simulation data for essentially the full flight envelope for a vertical attitude takeoff and landing aircraft (VATOL) is presented. These data demonstrate the successful, smooth, and precise control that can be achieved with this concept. The trajectory includes conventional flight from 200 to 900 ft/sec with path accelerations and decelerations, altitude changes of over 6000 ft and 2g and 3g turns. Vertical attitude maneuvering as a tail sitter along all axes is demonstrated. A transition trajectory from 200 ft/sec in conventional flight to stationary hover in the vertical attitude includes satisfactory operation through lift-cure slope reversal as attitude goes from horizontal to vertical at constant altitude. A vertical attitude takeoff from stationary hover to conventional flight is also demonstrated.

  11. Prior-knowledge-based feedforward network simulation of true boiling point curve of crude oil.

    Science.gov (United States)

    Chen, C W; Chen, D Z

    2001-11-01

    Theoretical results and practical experience indicate that feedforward networks can approximate a wide class of functional relationships very well. This property is exploited in modeling chemical processes. Given finite and noisy training data, it is important to encode the prior knowledge in neural networks to improve the fit precision and the prediction ability of the model. In this paper, as to the three-layer feedforward networks and the monotonic constraint, the unconstrained method, Joerding's penalty function method, the interpolation method, and the constrained optimization method are analyzed first. Then two novel methods, the exponential weight method and the adaptive method, are proposed. These methods are applied in simulating the true boiling point curve of a crude oil with the condition of increasing monotonicity. The simulation experimental results show that the network models trained by the novel methods are good at approximating the actual process. Finally, all these methods are discussed and compared with each other.

  12. Stochastic resonance in feedforward acupuncture networks

    Science.gov (United States)

    Qin, Ying-Mei; Wang, Jiang; Men, Cong; Deng, Bin; Wei, Xi-Le; Yu, Hai-Tao; Chan, Wai-Lok

    2014-10-01

    Effects of noises and some other network properties on the weak signal propagation are studied systematically in feedforward acupuncture networks (FFN) based on FitzHugh-Nagumo neuron model. It is found that noises with medium intensity can enhance signal propagation and this effect can be further increased by the feedforward network structure. Resonant properties in the noisy network can also be altered by several network parameters, such as heterogeneity, synapse features, and feedback connections. These results may also provide a novel potential explanation for the propagation of acupuncture signal.

  13. Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm

    Directory of Open Access Journals (Sweden)

    Jie-Sheng Wang

    2015-01-01

    Full Text Available For predicting the key technology indicators (concentrate grade and tailings recovery rate of flotation process, a feed-forward neural network (FNN based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO algorithm and gravitational search algorithm (GSA is proposed. Although GSA has better optimization capability, it has slow convergence velocity and is easy to fall into local optimum. So in this paper, the velocity vector and position vector of GSA are adjusted by PSO algorithm in order to improve its convergence speed and prediction accuracy. Finally, the proposed hybrid algorithm is adopted to optimize the parameters of FNN soft-sensor model. Simulation results show that the model has better generalization and prediction accuracy for the concentrate grade and tailings recovery rate to meet the online soft-sensor requirements of the real-time control in the flotation process.

  14. Nonlinear programming with feedforward neural networks.

    Energy Technology Data Exchange (ETDEWEB)

    Reifman, J.

    1999-06-02

    We provide a practical and effective method for solving constrained optimization problems by successively training a multilayer feedforward neural network in a coupled neural-network/objective-function representation. Nonlinear programming problems are easily mapped into this representation which has a simpler and more transparent method of solution than optimization performed with Hopfield-like networks and poses very mild requirements on the functions appearing in the problem. Simulation results are illustrated and compared with an off-the-shelf optimization tool.

  15. Nonlinear Feedforward Control for Wind Disturbance Rejection on Autonomous Helicopter

    DEFF Research Database (Denmark)

    Bisgaard, Morten; la Cour-Harbo, Anders; A. Danapalasingam, Kumeresan

    2010-01-01

    for the purpose. The model is inverted for the calculation of rotor collective and cyclic pitch angles given the wind disturbance. The control strategy is then applied on a small helicopter in a controlled wind environment and flight tests demonstrates the effectiveness and advantage of the feedforward controller.......This paper presents the design and verification of a model based nonlinear feedforward controller for wind disturbance rejection on autonomous helicopters. The feedforward control is based on a helicopter model that is derived using a number of carefully chosen simplifications to make it suitable...

  16. Model of rotary-actuated flexible beam with notch filter vibration suppression controller and torque feedforward load compensation controller

    International Nuclear Information System (INIS)

    Bills, K.C.; Kress, R.L.; Kwon, D.S.; Baker, C.P.

    1994-01-01

    This paper describes ORNL's development of an environment for the simulation of robotic manipulators. Simulation includes the modeling of kinematics, dynamics, sensors, actuators, control systems, operators, and environments. Models will be used for manipulator design, proposal evaluation, control system design and analysis, graphical preview of proposed motions, safety system development, and training. Of particular interest is the development of models for robotic manipulators having at least one flexible link. As a first application, models have been developed for the Pacific Northwest Laboratory's Flexible Beam Test Bed (PNL FBTB), which is a 1-Degree-of-Freedom, flexible arm with a hydraulic base actuator. ORNL transferred control algorithms developed for the PNL FBTB to controlling IGRIP models. A robust notch filter is running in IGRIP controlling a full dynamics model of the PNL test bed. Model results provide a reasonable match to the experimental results (quantitative results are being determined) and can run on ORNL's Onyx machine in approximately realtime. The flexible beam is modeled as six rigid sections with torsional springs between each segment. The spring constants were adjusted to match the physical response of the flexible beam model to the experimental results. The controller is able to improve performance on the model similar to the improvement seen on the experimental system. Some differences are apparent, most notably because the IGRIP model presently uses a different trajectory planner than the one used by ORNL on the PNL test bed. In the future, the trajectory planner will be modified so that the experiments and models are the same. The successful completion of this work provides the ability to link C code with IGRIP, thus allowing controllers to be developed, tested, and tuned in simulation and then ported directly to hardware systems using the C language

  17. Research on Modeling of the Agile Satellite Using a Single Gimbal Magnetically Suspended CMG and the Disturbance Feedforward Compensation for Rotors

    Science.gov (United States)

    Cui, Peiling; Yan, Ning

    2012-01-01

    The magnetically suspended Control Moment Gyroscope (CMG) has the advantages of long-life, micro-vibration and being non-lubricating, and is the ideal actuator for agile maneuver satellite attitude control. However, the stability of the rotor in magnetic bearing and the precision of the output torque of a magnetically suspended CMG are affected by the rapid maneuvers of satellites. In this paper, a dynamic model of the agile satellite including a magnetically suspended single gimbal control moment gyroscope is built and the equivalent disturbance torque effected on the rotor is obtained. The feedforward compensation control method is used to depress the disturbance on the rotor. Simulation results are given to show that the rotor displacement is obviously reduced. PMID:23235442

  18. Research on Modeling of the Agile Satellite Using a Single Gimbal Magnetically Suspended CMG and the Disturbance Feedforward Compensation for Rotors

    Directory of Open Access Journals (Sweden)

    Ning Yan

    2012-12-01

    Full Text Available The magnetically suspended Control Moment Gyroscope (CMG has the advantages of long-life, micro-vibration and being non-lubricating, and is the ideal actuator for agile maneuver satellite attitude control. However, the stability of the rotor in magnetic bearing and the precision of the output torque of a magnetically suspended CMG are affected by the rapid maneuvers of satellites. In this paper, a dynamic model of the agile satellite including a magnetically suspended single gimbal control moment gyroscope is built and the equivalent disturbance torque effected on the rotor is obtained. The feedforward compensation control method is used to depress the disturbance on the rotor. Simulation results are given to show that the rotor displacement is obviously reduced.

  19. On Optimal Input Design for Feed-forward Control

    OpenAIRE

    Hägg, Per; Wahlberg, Bo

    2013-01-01

    This paper considers optimal input design when the intended use of the identified model is to construct a feed-forward controller based on measurable disturbances. The objective is to find a minimum power excitation signal to be used in a system identification experiment, such that the corresponding model-based feed-forward controller guarantees, with a given probability, that the variance of the output signal is within given specifications. To start with, some low order model problems are an...

  20. Kinetic model-based feed-forward controlled fed-batch fermentation of Lactobacillus rhamnosus for the production of lactic acid from Arabic date juice.

    Science.gov (United States)

    Choi, Minsung; Al-Zahrani, Saeed M; Lee, Sang Yup

    2014-06-01

    Arabic date is overproduced in Arabic countries such as Saudi Arabia and Iraq and is mostly composed of sugars (70-80 wt%). Here we developed a fed-batch fermentation process by using a kinetic model for the efficient production of lactic acid to a high concentration from Arabic date juice. First, a kinetic model of Lactobacillus rhamnosus grown on date juice in batch fermentation was constructed in EXCEL so that the estimation of parameters and simulation of the model can be easily performed. Then, several fed-batch fermentations were conducted by employing different feeding strategies including pulsed feeding, exponential feeding, and modified exponential feeding. Based on the results of fed-batch fermentations, the kinetic model for fed-batch fermentation was also developed. This new model was used to perform feed-forward controlled fed-batch fermentation, which resulted in the production of 171.79 g l(-1) of lactic acid with the productivity and yield of 1.58 and 0.87 g l(-1) h(-1), respectively.

  1. Regularization and Complexity Control in Feed-forward Networks

    OpenAIRE

    Bishop, C. M.

    1995-01-01

    In this paper we consider four alternative approaches to complexity control in feed-forward networks based respectively on architecture selection, regularization, early stopping, and training with noise. We show that there are close similarities between these approaches and we argue that, for most practical applications, the technique of regularization should be the method of choice.

  2. Decoding small surface codes with feedforward neural networks

    Science.gov (United States)

    Varsamopoulos, Savvas; Criger, Ben; Bertels, Koen

    2018-01-01

    Surface codes reach high error thresholds when decoded with known algorithms, but the decoding time will likely exceed the available time budget, especially for near-term implementations. To decrease the decoding time, we reduce the decoding problem to a classification problem that a feedforward neural network can solve. We investigate quantum error correction and fault tolerance at small code distances using neural network-based decoders, demonstrating that the neural network can generalize to inputs that were not provided during training and that they can reach similar or better decoding performance compared to previous algorithms. We conclude by discussing the time required by a feedforward neural network decoder in hardware.

  3. Single-hidden-layer feed-forward quantum neural network based on Grover learning.

    Science.gov (United States)

    Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

    2013-09-01

    In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Feed-forward and generalized regression neural networks in modeling feeding behavior of pigs in the grow-finishing phase

    Science.gov (United States)

    Feeding patterns in group-housed grow-finishing pigs have been investigated for use in management decisions, identifying sick animals, and determining genetic differences within a herd. Development of models to predict swine feeding behaviour has been limited due the large number of potential enviro...

  5. Extended Model-Based Feedforward Compensation in L1 Adaptive Control for Mechanical Manipulators: Design and Experiments

    Directory of Open Access Journals (Sweden)

    Moussab eBennehar

    2015-12-01

    Full Text Available This paper deals with a new control scheme for Parallel Kinematic Manipulators (PKMs based on the L1 adaptive control theory. The original L1 adaptive controller is extended by including an adaptive loop based on the dynamics of the PKM. The additional model-based term is in charge of the compensation of the modeled nonlinear dynamics in the aim of improving the tracking performance. Moreover, the proposed controller is enhanced to reduce the internal forces, which may appear in the case of Redundantly Actuated PKMs (RA-PKMs. The generated control inputs are first regulated through a projection mechanism that reduces the antagonistic internal forces, before being applied to the manipulator. To validate the proposed controller and to show its effectiveness, real-time experiments are conducted on a new four degrees-of-freedom (4-DOFs RA-PKM developed in our laboratory.

  6. neural network based model o work based model of an industrial oil

    African Journals Online (AJOL)

    eobe

    technique. g, Neural Network Model, Regression, Mean Square Error, PID controller. ... during the training processes. An additio ... used to carry out simulation studies of the mode .... A two-layer feed-forward neural network with Matlab.

  7. On optimal feedforward and ILC : the role of feedback for optimal performance and inferential control

    NARCIS (Netherlands)

    van Zundert, J.C.D.; Oomen, T.A.E

    2017-01-01

    The combination of feedback control with inverse model feedforward control or iterative learning control is known to yield high performance. The aim of this paper is to clarify the role of feedback in the design of feedforward controllers, with specific attention to the inferential situation. Recent

  8. Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators

    NARCIS (Netherlands)

    Beijen, M.A.; Heertjes, M.F.; Van Dijk, J.; Hakvoort, W. B.J.

    2018-01-01

    © 2017 Elsevier Ltd This paper proposes a multi-input multi-output (MIMO) disturbance feedforward controller to improve the rejection of floor vibrations in active vibration isolation systems for high-precision machinery. To minimize loss of performance due to model uncertainties, the feedforward

  9. Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators

    NARCIS (Netherlands)

    Beijen, M.A.; Heertjes, M.F.; van Dijk, J.W.; Hakvoort, W.B.J.

    2018-01-01

    This paper proposes a multi-input multi-output (MIMO) disturbance feedforward controller to improve the rejection of floor vibrations in active vibration isolation systems for high-precision machinery. To minimize loss of performance due to model uncertainties, the feedforward controller is

  10. Combined Effects of Feedforward Inhibition and Excitation in Thalamocortical Circuit on the Transitions of Epileptic Seizures

    Science.gov (United States)

    Fan, Denggui; Duan, Lixia; Wang, Qian; Luan, Guoming

    2017-01-01

    The mechanisms underlying electrophysiologically observed two-way transitions between absence and tonic-clonic epileptic seizures in cerebral cortex remain unknown. The interplay within thalamocortical network is believed to give rise to these epileptic multiple modes of activity and transitions between them. In particular, it is thought that in some areas of cortex there exists feedforward inhibition from specific relay nucleus of thalamus (TC) to inhibitory neuronal population (IN) which has even more stronger functions on cortical activities than the known feedforward excitation from TC to excitatory neuronal population (EX). Inspired by this, we proposed a modified computational model by introducing feedforward inhibitory connectivity within thalamocortical circuit, to systematically investigate the combined effects of feedforward inhibition and excitation on transitions of epileptic seizures. We first found that the feedforward excitation can induce the transition from tonic oscillation to spike and wave discharges (SWD) in cortex, i.e., the epileptic tonic-absence seizures, with the fixed weak feedforward inhibition. Thereinto, the phase of absence seizures corresponding to strong feedforward excitation can be further transformed into the clonic oscillations with the increasing of feedforward inhibition, representing the epileptic absence-clonic seizures. We also observed the other fascinating dynamical states, such as periodic 2/3/4-spike and wave discharges, reversed SWD and clonic oscillations, as well as saturated firings. More importantly, we can identify the stable parameter regions representing the tonic-clonic oscillations and SWD discharges of epileptic seizures on the 2-D plane composed of feedforward inhibition and excitation, where the physiologically plausible transition pathways between tonic-clonic and absence seizures can be figured out. These results indicate the functional role of feedforward pathways in controlling epileptic seizures and

  11. Combined Effects of Feedforward Inhibition and Excitation in Thalamocortical Circuit on the Transitions of Epileptic Seizures

    Directory of Open Access Journals (Sweden)

    Denggui Fan

    2017-07-01

    Full Text Available The mechanisms underlying electrophysiologically observed two-way transitions between absence and tonic-clonic epileptic seizures in cerebral cortex remain unknown. The interplay within thalamocortical network is believed to give rise to these epileptic multiple modes of activity and transitions between them. In particular, it is thought that in some areas of cortex there exists feedforward inhibition from specific relay nucleus of thalamus (TC to inhibitory neuronal population (IN which has even more stronger functions on cortical activities than the known feedforward excitation from TC to excitatory neuronal population (EX. Inspired by this, we proposed a modified computational model by introducing feedforward inhibitory connectivity within thalamocortical circuit, to systematically investigate the combined effects of feedforward inhibition and excitation on transitions of epileptic seizures. We first found that the feedforward excitation can induce the transition from tonic oscillation to spike and wave discharges (SWD in cortex, i.e., the epileptic tonic-absence seizures, with the fixed weak feedforward inhibition. Thereinto, the phase of absence seizures corresponding to strong feedforward excitation can be further transformed into the clonic oscillations with the increasing of feedforward inhibition, representing the epileptic absence-clonic seizures. We also observed the other fascinating dynamical states, such as periodic 2/3/4-spike and wave discharges, reversed SWD and clonic oscillations, as well as saturated firings. More importantly, we can identify the stable parameter regions representing the tonic-clonic oscillations and SWD discharges of epileptic seizures on the 2-D plane composed of feedforward inhibition and excitation, where the physiologically plausible transition pathways between tonic-clonic and absence seizures can be figured out. These results indicate the functional role of feedforward pathways in controlling epileptic

  12. Experimental evaluation of feedforward control for the trajectory tracking of power in nuclear reactors

    International Nuclear Information System (INIS)

    Lau, S.H.; Bernard, J.A.; Lanning, D.D.

    1991-01-01

    This paper reports on an experimental comparison of feedforward control techniques for the trajectory-tracking of neutronic power was performed on the 5-MWt MIT Research Reactor. Included in the comparison were pure feedforward control in which the actuator signal is found solely by processing a demanded output through a system model, hybrid feedforward/feedback control in which the actuator signal is obtained by summing feedforward and feedback components, and period-generated control in which feedback is used to update the demand trajectory prior to its being processed through the system model for calculation of the actuator signal. This latter approach was found to be the most effective. In addition to the experimental results, discussions are given of both the rationale for model-based, feedforward control and the designs of the various controllers

  13. Quantum generalisation of feedforward neural networks

    Science.gov (United States)

    Wan, Kwok Ho; Dahlsten, Oscar; Kristjánsson, Hlér; Gardner, Robert; Kim, M. S.

    2017-09-01

    We propose a quantum generalisation of a classical neural network. The classical neurons are firstly rendered reversible by adding ancillary bits. Then they are generalised to being quantum reversible, i.e., unitary (the classical networks we generalise are called feedforward, and have step-function activation functions). The quantum network can be trained efficiently using gradient descent on a cost function to perform quantum generalisations of classical tasks. We demonstrate numerically that it can: (i) compress quantum states onto a minimal number of qubits, creating a quantum autoencoder, and (ii) discover quantum communication protocols such as teleportation. Our general recipe is theoretical and implementation-independent. The quantum neuron module can naturally be implemented photonically.

  14. A feedforward IMC structure for controlling the charging temperature of a TES system of a solar cooker

    International Nuclear Information System (INIS)

    Mawire, A.; McPherson, M.

    2008-01-01

    A feedforward internal model control (IMC) structure for controlling and maintaining the outlet charging temperature of a thermal energy storage (TES) system of a solar cooker is presented. The TES system consists of a packed pebble bed in thermal contact with a heat transfer oil contained in a storage tank. An electrical hot plate simulates the collector/concentrator which heats up the oil circulating in a hollow copper spiral coil thus charging the storage. A model for the collector/concentrator system is developed to enable simulation of the feedforward IMC structure. Using a Simulink block model, the simulation results reveal that a feedforward IMC structure performs better than a feedforward structure. The feedforward IMC structure is tested experimentally and the performance of the control structure is acceptable within a few degrees of the set temperatures. Experimental results are also compared with the simulation results. The simulated responses are found to relate closely to the experimental ones and any discrepancies between the two are discussed. Furthermore, the feedforward IMC structure is also compared experimentally with a combined feedforward and PID feedback structure. Results of the comparison indicate that the feedforward IMC structure performs better than the combined feedforward and PID feedback structure. The thermal profile of the storage during the charging experiment with the feedforward IMC structure is also presented and the results obtained from the storage profile indicate that the storage tank is thermally stratified

  15. Predicting Antitumor Activity of Peptides by Consensus of Regression Models Trained on a Small Data Sample

    Directory of Open Access Journals (Sweden)

    Ivanka Jerić

    2011-11-01

    Full Text Available Predicting antitumor activity of compounds using regression models trained on a small number of compounds with measured biological activity is an ill-posed inverse problem. Yet, it occurs very often within the academic community. To counteract, up to some extent, overfitting problems caused by a small training data, we propose to use consensus of six regression models for prediction of biological activity of virtual library of compounds. The QSAR descriptors of 22 compounds related to the opioid growth factor (OGF, Tyr-Gly-Gly-Phe-Met with known antitumor activity were used to train regression models: the feed-forward artificial neural network, the k-nearest neighbor, sparseness constrained linear regression, the linear and nonlinear (with polynomial and Gaussian kernel support vector machine. Regression models were applied on a virtual library of 429 compounds that resulted in six lists with candidate compounds ranked by predicted antitumor activity. The highly ranked candidate compounds were synthesized, characterized and tested for an antiproliferative activity. Some of prepared peptides showed more pronounced activity compared with the native OGF; however, they were less active than highly ranked compounds selected previously by the radial basis function support vector machine (RBF SVM regression model. The ill-posedness of the related inverse problem causes unstable behavior of trained regression models on test data. These results point to high complexity of prediction based on the regression models trained on a small data sample.

  16. Extracting functionally feedforward networks from a population of spiking neurons.

    Science.gov (United States)

    Vincent, Kathleen; Tauskela, Joseph S; Thivierge, Jean-Philippe

    2012-01-01

    Neuronal avalanches are a ubiquitous form of activity characterized by spontaneous bursts whose size distribution follows a power-law. Recent theoretical models have replicated power-law avalanches by assuming the presence of functionally feedforward connections (FFCs) in the underlying dynamics of the system. Accordingly, avalanches are generated by a feedforward chain of activation that persists despite being embedded in a larger, massively recurrent circuit. However, it is unclear to what extent networks of living neurons that exhibit power-law avalanches rely on FFCs. Here, we employed a computational approach to reconstruct the functional connectivity of cultured cortical neurons plated on multielectrode arrays (MEAs) and investigated whether pharmacologically induced alterations in avalanche dynamics are accompanied by changes in FFCs. This approach begins by extracting a functional network of directed links between pairs of neurons, and then evaluates the strength of FFCs using Schur decomposition. In a first step, we examined the ability of this approach to extract FFCs from simulated spiking neurons. The strength of FFCs obtained in strictly feedforward networks diminished monotonically as links were gradually rewired at random. Next, we estimated the FFCs of spontaneously active cortical neuron cultures in the presence of either a control medium, a GABA(A) receptor antagonist (PTX), or an AMPA receptor antagonist combined with an NMDA receptor antagonist (APV/DNQX). The distribution of avalanche sizes in these cultures was modulated by this pharmacology, with a shallower power-law under PTX (due to the prominence of larger avalanches) and a steeper power-law under APV/DNQX (due to avalanches recruiting fewer neurons) relative to control cultures. The strength of FFCs increased in networks after application of PTX, consistent with an amplification of feedforward activity during avalanches. Conversely, FFCs decreased after application of APV

  17. Feedforward Control of Magnetically Levitated Planar Actuators

    OpenAIRE

    Bloemers, T.; Proimadis, I.; Kasemsinsup, Y.; Tóth, R.

    2018-01-01

    The present report summarizes the work conducted during the internship on Feedforward Control of the Magnetic Levitation Setup. Different feedforward strategies, specifically tailored for this setup, are developed and reviewed. These feedforward methods explicitly take the intrinsic position-dependent behavior of the magnetic levitation setup into account. Additionally, closed-loop stability of the given setup is assessed. All investigations are carried out under the rigid-body assumption of ...

  18. Development of Feedforward Control in a Dynamic Manual Tracking Task

    Science.gov (United States)

    van Roon, Dominique; Caeyenberghs, Karen; Swinnen, Stephan P.; Smits-Engelsman, Bouwien C. M.

    2008-01-01

    To examine the development of feedforward control during manual tracking, 117 participants in 5 age groups (6 to 7, 8 to 9, 10 to 11, 12 to 14, and 15 to 17 years) tracked an accelerating dot presented on a monitor by moving an electronic pen on a digitizer. To remain successful at higher target velocities, they had to create a predictive model of…

  19. Application of parsimonious learning feedforward control to mechatronic systems

    NARCIS (Netherlands)

    de Vries, Theodorus J.A.; Velthuis, W.J.R.; Idema, L.J.

    2001-01-01

    For motion control, learning feedforward controllers (LFFCs) should be applied when accurate process modelling is difficult. When controlling such processes with LFFCs in the form of multidimensional B-spline networks, large network sizes and a poor generalising ability may result, known as the

  20. Results of adaptive feedforward on GTA

    International Nuclear Information System (INIS)

    Ziomek, C.D.; Denney, P.M.; Regan, A.H.; Lynch, M.T.; Jachim, S.P.; Eaton, L.E.; Natter, E.F.

    1993-01-01

    This paper presents the results of the adaptive feedforward system in use on the Ground Test Accelerator (GTA). The adaptive feedforward system was shown to correct repetitive, high-frequency errors in the amplitude and phase of the RF field of the pulsed accelerator. The adaptive feedforward system was designed as an augmentation to the RF field feedback control system and was able to extend the closed-loop bandwidth and disturbance rejection by a factor of ten. Within a second implementation, the adaptive feedforward hardware was implemented in place of the feedback control system and was shown to negate both beam transients and phase droop in the klystron amplifier

  1. Prediction of metal corrosion using feed-forward neural networks

    International Nuclear Information System (INIS)

    Mahjani, M.G.; Jalili, S.; Jafarian, M.; Jaberi, A.

    2004-01-01

    The reliable prediction of corrosion behavior for the effective control of corrosion is a fundamental requirement. Since real world corrosion never seems to involve quite the same conditions that have previously been tested, using corrosion literature does not provide the necessary answers. In order to provide a methodology for predicting corrosion in real and complex situations, artificial neural networks can be utilized. Feed-forward artificial neural network (FFANN) is an information-processing paradigm inspired by the way the densely interconnected, parallel structure of the human brain process information.The aim of the present work is to predict corrosion behavior in critical conditions, such as industrial applications, based on some laboratory experimental data. Electrochemical behavior of stainless steel in different conditions were studied, using polarization technique and Tafel curves. Back-propagation neural networks models were developed to predict the corrosion behavior. The trained networks result in predicted value in good comparison to the experimental data. They have generally been claimed to be successful in modeling the corrosion behavior. The results are presented in two tables. Table 1 gives corrosion behavior of stainless-steel as a function of pH and CuSO 4 concentration and table 2 gives corrosion behavior of stainless - steel as a function of electrode surface area and CuSO 4 concentration. (authors)

  2. Comparison of different modelling approaches of drive train temperature for the purposes of wind turbine failure detection

    Science.gov (United States)

    Tautz-Weinert, J.; Watson, S. J.

    2016-09-01

    Effective condition monitoring techniques for wind turbines are needed to improve maintenance processes and reduce operational costs. Normal behaviour modelling of temperatures with information from other sensors can help to detect wear processes in drive trains. In a case study, modelling of bearing and generator temperatures is investigated with operational data from the SCADA systems of more than 100 turbines. The focus is here on automated training and testing on a farm level to enable an on-line system, which will detect failures without human interpretation. Modelling based on linear combinations, artificial neural networks, adaptive neuro-fuzzy inference systems, support vector machines and Gaussian process regression is compared. The selection of suitable modelling inputs is discussed with cross-correlation analyses and a sensitivity study, which reveals that the investigated modelling techniques react in different ways to an increased number of inputs. The case study highlights advantages of modelling with linear combinations and artificial neural networks in a feedforward configuration.

  3. Intelligence rules of hysteresis in the feedforward trajectory control of piezoelectrically-driven nanostagers

    Science.gov (United States)

    Bashash, Saeid; Jalili, Nader

    2007-02-01

    Piezoelectrically-driven nanostagers have limited performance in a variety of feedforward and feedback positioning applications because of their nonlinear hysteretic response to input voltage. The hysteresis phenomenon is well known for its complex and multi-path behavior. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligence properties of hysteresis with the effects of non-local memories are discussed here. Through performing a set of experiments on a piezoelectrically-driven nanostager with a high resolution capacitive position sensor, it is shown that for the precise prediction of the hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of the hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the ever-present nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect, if memory units are sufficiently chosen for the inverse model.

  4. Effects of controlled element dynamics on human feedforward behavior in ramp-tracking tasks.

    Science.gov (United States)

    Laurense, Vincent A; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus René M; Mulder, Max

    2015-02-01

    In real-life manual control tasks, human controllers are often required to follow a visible and predictable reference signal, enabling them to use feedforward control actions in conjunction with feedback actions that compensate for errors. Little is known about human control behavior in these situations. This paper investigates how humans adapt their feedforward control dynamics to the controlled element dynamics in a combined ramp-tracking and disturbance-rejection task. A human-in-the-loop experiment is performed with a pursuit display and vehicle-like controlled elements, ranging from a single integrator through second-order systems with a break frequency at either 3, 2, or 1 rad/s, to a double integrator. Because the potential benefits of feedforward control increase with steeper ramp segments in the target signal, three steepness levels are tested to investigate their possible effect on feedforward control with the various controlled elements. Analyses with four novel models of the operator, fitted to time-domain data, reveal feedforward control for all tested controlled elements and both (nonzero) tested levels of ramp steepness. For the range of controlled element dynamics investigated, it is found that humans adapt to these dynamics in their feedforward response, with a close to perfect inversion of the controlled element dynamics. No significant effects of ramp steepness on the feedforward model parameters are found.

  5. Cerebellar contribution to feedforward control of locomotion.

    Science.gov (United States)

    Pisotta, Iolanda; Molinari, Marco

    2014-01-01

    The cerebellum is an important contributor to feedforward control mechanisms of the central nervous system, and sequencing-the process that allows spatial and temporal relationships between events to be recognized-has been implicated as the fundamental cerebellar mode of operation. By adopting such a mode and because cerebellar activity patterns are sensitive to a variety of sensorimotor-related tasks, the cerebellum is believed to support motor and cognitive functions that are encoded in the frontal and parietal lobes of the cerebral cortex. In this model, the cerebellum is hypothesized to make predictions about the consequences of a motor or cognitive command that originates from the cortex to prepare the entire system to cope with ongoing changes. In this framework, cerebellar predictive mechanisms for locomotion are addressed, focusing on sensorial and motoric sequencing. The hypothesis that sequence recognition is the mechanism by which the cerebellum functions in gait control is presented and discussed.

  6. Flying Training Capacity Model: Initial Results

    National Research Council Canada - National Science Library

    Lynch, Susan

    2005-01-01

    OBJECTIVE: (1) Determine the flying training capacity for 6 bases: * Sheppard AFB * Randolph AFB * Moody AFB * Columbus AFB * Laughlin AFB * Vance AFB * (2) Develop versatile flying training capacity simulation model for AETC...

  7. Fuzzy PID Feedback Control of Piezoelectric Actuator with Feedforward Compensation

    OpenAIRE

    Ziqiang Chi; Minping Jia; Qingsong Xu

    2014-01-01

    Piezoelectric actuator is widely used in the field of micro/nanopositioning. However, piezoelectric hysteresis introduces nonlinearity to the system, which is the major obstacle to achieve a precise positioning. In this paper, the Preisach model is employed to describe the hysteresis characteristic of piezoelectric actuator and an inverse Preisach model is developed to construct a feedforward controller. Considering that the analytical expression of inverse Preisach model is difficult to deri...

  8. Effects of topologies on signal propagation in feedforward networks

    Science.gov (United States)

    Zhao, Jia; Qin, Ying-Mei; Che, Yan-Qiu

    2018-01-01

    We systematically investigate the effects of topologies on signal propagation in feedforward networks (FFNs) based on the FitzHugh-Nagumo neuron model. FFNs with different topological structures are constructed with same number of both in-degrees and out-degrees in each layer and given the same input signal. The propagation of firing patterns and firing rates are found to be affected by the distribution of neuron connections in the FFNs. Synchronous firing patterns emerge in the later layers of FFNs with identical, uniform, and exponential degree distributions, but the number of synchronous spike trains in the output layers of the three topologies obviously differs from one another. The firing rates in the output layers of the three FFNs can be ordered from high to low according to their topological structures as exponential, uniform, and identical distributions, respectively. Interestingly, the sequence of spiking regularity in the output layers of the three FFNs is consistent with the firing rates, but their firing synchronization is in the opposite order. In summary, the node degree is an important factor that can dramatically influence the neuronal network activity.

  9. Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

    Directory of Open Access Journals (Sweden)

    Mehrshad Salmasi

    2012-07-01

    Full Text Available Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in noise attenuation are compared. We use Elman network as a recurrent neural network. For simulations, noise signals from a SPIB database are used. In order to compare the networks appropriately, equal number of layers and neurons are considered for the networks. Moreover, training and test samples are similar. Simulation results show that feedforward and recurrent neural networks present good performance in noise cancellation. As it is seen, the ability of recurrent neural network in noise attenuation is better than feedforward network.

  10. Frequency-weighted feedforward control for dynamic compensation in ionic polymer–metal composite actuators

    International Nuclear Information System (INIS)

    Shan, Yingfeng; Leang, Kam K

    2009-01-01

    Ionic polymer–metal composites (IPMCs) are innovative materials that offer combined sensing and actuating ability in lightweight and flexible package. IPMCs have been exploited in robotics and a wide variety of biomedical devices, for example, as sensors for teleoperation, as actuators for positioning in active endoscopy, as fins for propelling aquatic robots, and as an injector for drug delivery. In the actuation mode, one of the main challenges is precise position control. In particular, IPMC actuators exhibit relaxation behavior and nonlinearities; and at relatively high operating frequencies dynamic effects limit accuracy and positioning bandwidth. A frequency-weighted feedforward controller is designed to account for the IPMC's structural dynamics to enable fast positioning. The control method is applied to a custom-made Nafion-based IPMC actuator. The controller takes into account the magnitude of the control input to avoid generating excessively large voltages which can damage the IPMC actuator. To account for unmodeled effects not captured by the dynamics model, a feedback controller is integrated with the feedforward controller. Experimental results show a significant improvement in the tracking performance when feedforward control is used. For instance, the feedforward controller shows over 75% reduction in the tracking error compared to the case without feedforward compensation. Finally, the integrated feedforward and feedback control system reduces the tracking error to less than 10% for tracking an 18-Hz triangle-like trajectory. Some of the advantages of feedforward control as well as its limitations are also discussed

  11. Natural Language Processing with Small Feed-Forward Networks

    OpenAIRE

    Botha, Jan A.; Pitler, Emily; Ma, Ji; Bakalov, Anton; Salcianu, Alex; Weiss, David; McDonald, Ryan; Petrov, Slav

    2017-01-01

    We show that small and shallow feed-forward neural networks can achieve near state-of-the-art results on a range of unstructured and structured language processing tasks while being considerably cheaper in memory and computational requirements than deep recurrent models. Motivated by resource-constrained environments like mobile phones, we showcase simple techniques for obtaining such small neural network models, and investigate different tradeoffs when deciding how to allocate a small memory...

  12. Learning feedback and feedforward control in a mirror-reversed visual environment.

    Science.gov (United States)

    Kasuga, Shoko; Telgen, Sebastian; Ushiba, Junichi; Nozaki, Daichi; Diedrichsen, Jörn

    2015-10-01

    When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers. Copyright © 2015 the American Physiological Society.

  13. [Membrane-bound cytokine and feedforward regulation].

    Science.gov (United States)

    Wu, Ke-Fu; Zheng, Guo-Guang; Ma, Xiao-Tong; Song, Yu-Hua

    2013-10-01

    Feedback and feedforward widely exist in life system, both of them are the basic processes of control system. While the concept of feedback has been widely used in life science, feedforward regulation was systematically studied in neurophysiology, awaiting further evidence and mechanism in molecular biology and cell biology. The authors put forward a hypothesis about the feedforward regulation of membrane bound macrophage colony stimulation factor (mM-CSF) on the basis of their previous work. This hypothesis might provide a new direction for the study on the biological effects of mM-CSF on leukemia and solid tumors, and contribute to the study on other membrane bound cytokines.

  14. Design and Validation of Optimized Feedforward with Robust Feedback Control of a Nuclear Reactor

    International Nuclear Information System (INIS)

    Shaffer, Roman; He Weidong; Edwards, Robert M.

    2004-01-01

    Design applications for robust feedback and optimized feedforward control, with confirming results from experiments conducted on the Pennsylvania State University TRIGA reactor, are presented. The combination of feedforward and feedback control techniques complement each other in that robust control offers guaranteed closed-loop stability in the presence of uncertainties, and optimized feedforward offers an approach to achieving performance that is sometimes limited by overly conservative robust feedback control. The design approach taken in this work combines these techniques by first designing robust feedback control. Alternative methods for specifying a low-order linear model and uncertainty specifications, while seeking as much performance as possible, are discussed and evaluated. To achieve desired performance characteristics, the optimized feedforward control is then computed by using the nominal nonlinear plant model that incorporates the robust feedback control

  15. Predictive Feedback and Feedforward Control for Systems with Unknown Disturbances

    Science.gov (United States)

    Juang, Jer-Nan; Eure, Kenneth W.

    1998-01-01

    Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.

  16. Feedforward Nonlinear Control Using Neural Gas Network

    Directory of Open Access Journals (Sweden)

    Iván Machón-González

    2017-01-01

    Full Text Available Nonlinear systems control is a main issue in control theory. Many developed applications suffer from a mathematical foundation not as general as the theory of linear systems. This paper proposes a control strategy of nonlinear systems with unknown dynamics by means of a set of local linear models obtained by a supervised neural gas network. The proposed approach takes advantage of the neural gas feature by which the algorithm yields a very robust clustering procedure. The direct model of the plant constitutes a piece-wise linear approximation of the nonlinear system and each neuron represents a local linear model for which a linear controller is designed. The neural gas model works as an observer and a controller at the same time. A state feedback control is implemented by estimation of the state variables based on the local transfer function that was provided by the local linear model. The gradient vectors obtained by the supervised neural gas algorithm provide a robust procedure for feedforward nonlinear control, that is, supposing the inexistence of disturbances.

  17. Fuzzy PID Feedback Control of Piezoelectric Actuator with Feedforward Compensation

    Directory of Open Access Journals (Sweden)

    Ziqiang Chi

    2014-01-01

    Full Text Available Piezoelectric actuator is widely used in the field of micro/nanopositioning. However, piezoelectric hysteresis introduces nonlinearity to the system, which is the major obstacle to achieve a precise positioning. In this paper, the Preisach model is employed to describe the hysteresis characteristic of piezoelectric actuator and an inverse Preisach model is developed to construct a feedforward controller. Considering that the analytical expression of inverse Preisach model is difficult to derive and not suitable for practical application, a digital inverse model is established based on the input and output data of a piezoelectric actuator. Moreover, to mitigate the compensation error of the feedforward control, a feedback control scheme is implemented using different types of control algorithms in terms of PID control, fuzzy control, and fuzzy PID control. Extensive simulation studies are carried out using the three kinds of control systems. Comparative investigation reveals that the fuzzy PID control system with feedforward compensation is capable of providing quicker response and better control accuracy than the other two ones. It provides a promising way of precision control for piezoelectric actuator.

  18. Robust sequential learning of feedforward neural networks in the presence of heavy-tailed noise.

    Science.gov (United States)

    Vuković, Najdan; Miljković, Zoran

    2015-03-01

    Feedforward neural networks (FFNN) are among the most used neural networks for modeling of various nonlinear problems in engineering. In sequential and especially real time processing all neural networks models fail when faced with outliers. Outliers are found across a wide range of engineering problems. Recent research results in the field have shown that to avoid overfitting or divergence of the model, new approach is needed especially if FFNN is to run sequentially or in real time. To accommodate limitations of FFNN when training data contains a certain number of outliers, this paper presents new learning algorithm based on improvement of conventional extended Kalman filter (EKF). Extended Kalman filter robust to outliers (EKF-OR) is probabilistic generative model in which measurement noise covariance is not constant; the sequence of noise measurement covariance is modeled as stochastic process over the set of symmetric positive-definite matrices in which prior is modeled as inverse Wishart distribution. In each iteration EKF-OR simultaneously estimates noise estimates and current best estimate of FFNN parameters. Bayesian framework enables one to mathematically derive expressions, while analytical intractability of the Bayes' update step is solved by using structured variational approximation. All mathematical expressions in the paper are derived using the first principles. Extensive experimental study shows that FFNN trained with developed learning algorithm, achieves low prediction error and good generalization quality regardless of outliers' presence in training data. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Feedforward/feedback control synthesis for performance and robustness

    Science.gov (United States)

    Wie, Bong; Liu, Qiang

    1990-01-01

    Both feedforward and feedback control approaches for uncertain dynamical systems are investigated. The control design objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant modeling uncertainty. Preshapong of an ideal, time-optimal control input using a 'tapped-delay' filter is shown to provide a rapid maneuver with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. The proposed feedforward/feedback control approach is robust for a certain class of uncertain dynamical systems, since the control input command computed for a given desired output does not depend on the plant parameters.

  20. Training model for cerebral aneurysm clipping

    Directory of Open Access Journals (Sweden)

    Hiroshi Tenjin, M.D., Ph.D.

    2017-12-01

    Full Text Available Clipping of cerebral aneurysms is still an important skill in neurosurgery. We have made a training model for the clipping of cerebral aneurysms. The concepts for the model were 1: training model for beginners, 2: three dimensional manipulation using an operating microscope, 3: the aneurysm model is to be perfused by simulated blood causing premature rupture. The correct relationship between each tissue, and softness of the brain and vessels were characteristics of the model. The skull, brain, arteries, and veins were made using a 3D printer with data from DICOM. The brain and vessels were made from polyvinyl alcohol (PVA. One training course was held and this model was useful for training of cerebral aneurysm surgery for young neurosurgeons.

  1. Feedforward-feedback control of dissolved oxygen concentration in a predenitrification system.

    Science.gov (United States)

    Yong, Ma; Yongzhen, Peng; Shuying, Wang

    2005-07-01

    As the largest single energy-consuming component in most biological wastewater treatment systems, aeration control is of great interest from the point of view of saving energy and improving wastewater treatment plant efficiency. In this paper, three different strategies, including conventional constant dissolved oxygen (DO) set-point control, cascade DO set-point control, and feedforward-feedback DO set-point control were evaluated using the denitrification layout of the IWA simulation benchmark. Simulation studies showed that the feedforward-feedback DO set-point control strategy was better than the other control strategies at meeting the effluent standards and reducing operational costs. The control strategy works primarily by feedforward control based on an ammonium sensor located at the head of the aerobic process. It has an important advantage over effluent measurements in that there is no (or only a very short) time delay for information; feedforward control was combined with slow feedback control to compensate for model approximations. The feedforward-feedback DO control was implemented in a lab-scale wastewater treatment plant for a period of 60 days. Compared to operation with constant DO concentration, the required airflow could be reduced by up to 8-15% by employing the feedforward-feedback DO-control strategy, and the effluent ammonia concentration could be reduced by up to 15-25%. This control strategy can be expected to be accepted by the operating personnel in wastewater treatment plants.

  2. Biomechanical constraints on the feedforward regulation of endpoint stiffness.

    Science.gov (United States)

    Hu, Xiao; Murray, Wendy M; Perreault, Eric J

    2012-10-01

    Although many daily tasks tend to destabilize arm posture, it is still possible to have stable interactions with the environment by regulating the multijoint mechanics of the arm in a task-appropriate manner. For postural tasks, this regulation involves the appropriate control of endpoint stiffness, which represents the stiffness of the arm at the hand. Although experimental studies have been used to evaluate endpoint stiffness control, including the orientation of maximal stiffness, the underlying neural strategies remain unknown. Specifically, the relative importance of feedforward and feedback mechanisms has yet to be determined due to the difficulty separately identifying the contributions of these mechanisms in human experiments. This study used a previously validated three-dimensional musculoskeletal model of the arm to quantify the degree to which the orientation of maximal endpoint stiffness could be changed using only steady-state muscle activations, used to represent feedforward motor commands. Our hypothesis was that the feedforward control of endpoint stiffness orientation would be significantly constrained by the biomechanical properties of the musculoskeletal system. Our results supported this hypothesis, demonstrating substantial biomechanical constraints on the ability to regulate endpoint stiffness throughout the workspace. The ability to regulate stiffness orientation was further constrained by additional task requirements, such as the need to support the arm against gravity or exert forces on the environment. Together, these results bound the degree to which slowly varying feedforward motor commands can be used to regulate the orientation of maximum arm stiffness and provide a context for better understanding conditions in which feedback control may be needed.

  3. A Better Model for Management Training

    Science.gov (United States)

    Bobele, H. Kenneth; Buchanan, Peter J.

    1976-01-01

    Greater precision in appraising training needs, greater clarity in defining training objectives, and an emphasis on a practical, skills-oriented approach to management development can result from using Henry Mintzberg's model which describes managerial work in terms of 6 job characteristics and 10 interpersonal, informational, or decisional roles.…

  4. Hybrid Feedforward-Feedback Noise Control Using Virtual Sensors

    Science.gov (United States)

    Bean, Jacob; Fuller, Chris; Schiller, Noah

    2016-01-01

    Several approaches to active noise control using virtual sensors are evaluated for eventual use in an active headrest. Specifically, adaptive feedforward, feedback, and hybrid control structures are compared. Each controller incorporates the traditional filtered-x least mean squares algorithm. The feedback controller is arranged in an internal model configuration to draw comparisons with standard feedforward control theory results. Simulation and experimental results are presented that illustrate each controllers ability to minimize the pressure at both physical and virtual microphone locations. The remote microphone technique is used to obtain pressure estimates at the virtual locations. It is shown that a hybrid controller offers performance benefits over the traditional feedforward and feedback controllers. Stability issues associated with feedback and hybrid controllers are also addressed. Experimental results show that 15-20 dB reduction in broadband disturbances can be achieved by minimizing the measured pressure, whereas 10-15 dB reduction is obtained when minimizing the estimated pressure at a virtual location.

  5. Structural learning in feedforward and feedback control.

    Science.gov (United States)

    Yousif, Nada; Diedrichsen, Jörn

    2012-11-01

    For smooth and efficient motor control, the brain needs to make fast corrections during the movement to resist possible perturbations. It also needs to adapt subsequent movements to improve future performance. It is important that both feedback corrections and feedforward adaptation need to be made based on noisy and often ambiguous sensory data. Therefore, the initial response of the motor system, both for online corrections and adaptive responses, is guided by prior assumptions about the likely structure of perturbations. In the context of correcting and adapting movements perturbed by a force field, we asked whether these priors are hard wired or whether they can be modified through repeated exposure to differently shaped force fields. We found that both feedback corrections to unexpected perturbations and feedforward adaptation to a new force field changed, such that they were appropriate to counteract the type of force field that participants had experienced previously. We then investigated whether these changes were driven by a common mechanism or by two separate mechanisms. Participants experienced force fields that were either temporally consistent, causing sustained adaptation, or temporally inconsistent, causing little overall adaptation. We found that the consistent force fields modified both feedback and feedforward responses. In contrast, the inconsistent force field modified the temporal shape of feedback corrections but not of the feedforward adaptive response. These results indicate that responses to force perturbations can be modified in a structural manner and that these modifications are at least partly dissociable for feedback and feedforward control.

  6. Processing oscillatory signals by incoherent feedforward loops

    Science.gov (United States)

    Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

    From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

  7. Declarative Terrain Modeling for Military Training Games

    Directory of Open Access Journals (Sweden)

    Ruben M. Smelik

    2010-01-01

    Full Text Available Military training instructors increasingly often employ computer games to train soldiers in all sorts of skills and tactics. One of the difficulties instructors face when using games as a training tool is the creation of suitable content, including scenarios, entities, and corresponding terrain models. Terrain plays a key role in many military training games, as for example, in our case game Tactical Air Defense. However, current manual terrain editors are both too complex and too time-consuming to be useful for instructors; automatic terrain generation methods show a lot of potential, but still lack user control and intuitive editing capabilities. We present a novel way for instructors to model terrain for their training games: instead of constructing a terrain model using complex modeling tools, instructors can declare the required properties of their terrain using an advanced sketching interface. Our framework integrates terrain generation methods and manages dependencies between terrain features in order to automatically create a complete 3D terrain model that matches the sketch. With our framework, instructors can easily design a large variety of terrain models that meet their training requirements.

  8. Rapid prototyping model for percutaneous nephrolithotomy training.

    Science.gov (United States)

    Bruyère, Franck; Leroux, Cecile; Brunereau, Laurent; Lermusiaux, Patrick

    2008-01-01

    Rapid prototyping is a technique used for creating computer images in three dimensions more efficiently than classic techniques. Percutaneous nephrolithotomy (PCNL) is a popular method to remove kidney stones; however, broader use by the urologic community has been hampered by the morbidity associated with needle puncture to gain access to the renal calix (bleeding, pneumothorax, hydrothorax, inadvertent colon injury). A training model to improve technique and understanding of renal anatomy could improve complications related to renal puncture; however, no model currently exists for resident training. We created a training model using the rapid prototyping technique based on abdominal CT images of a patient scheduled to undergo PCNL. This allowed our staff and residents to train on the model before performing the operation. This model allowed anticipation of particular difficulties inherent to the patient's anatomy. After training, the procedure proceeded without complication, and the patient was discharged at postoperative day 1 without problems. We hypothesize that rapid prototyping could be useful for resident education, allowing the creation of numerous models for research and surgical training. In addition, we anticipate that experienced urologists could find this technique helpful in preparation for difficult PCNL operations.

  9. Developing a Successful Open Source Training Model

    Directory of Open Access Journals (Sweden)

    Belinda Lopez

    2010-01-01

    Full Text Available Training programs for open source software provide a tangible, and sellable, product. A successful training program not only builds revenue, it also adds to the overall body of knowledge available for the open source project. By gathering best practices and taking advantage of the collective expertise within a community, it may be possible for a business to partner with an open source project to build a curriculum that promotes the project and supports the needs of the company's training customers. This article describes the initial approach used by Canonical, the commercial sponsor of the Ubuntu Linux operating system, to engage the community in the creation of its training offerings. We then discuss alternate curriculum creation models and some of the conditions that are necessary for successful collaboration between creators of existing documentation and commercial training providers.

  10. Feedforward temperature control using a heat flux microsensor

    OpenAIRE

    Lartz, Douglas John

    1993-01-01

    The concept of using heat flux measurements to provide the input for a feedforward temperature control loop is investigated. The feedforward loop is added to proportional and integral feedback control to increase the speed of the response to a disturbance. Comparison is made between the feedback and the feedback plus feedforward control laws. The control law with the feedforward control loop is also compared to the conventional approach of adding derivative control to speed up ...

  11. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM

    Directory of Open Access Journals (Sweden)

    A. Cancelier

    Full Text Available Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, the network was trained on a recurring basis and only the technique of genetic algorithms was used. In this case, only the weights and bias of the output layer neuron were modified, starting from the parameters obtained from the offline training. From the experimental results obtained in a pilot plant, a good performance was observed for the proposed control system, with superior performance for the control algorithm with online adaptation of the model, particularly with respect to the presence of off-set for the case of the fixed parameters model.

  12. Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

    OpenAIRE

    Mehrshad Salmasi; Homayoun Mahdavi-Nasab

    2012-01-01

    Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in n...

  13. MODEL OF TRAINING OF SUCCESS IN LIFE

    Directory of Open Access Journals (Sweden)

    Екатерина Александровна Лежнева

    2014-04-01

    Full Text Available The article explains the importance of the development of motive to succeed in adolescence. It is determined the value of the motive to achieve success in the further development of the teenager: a motive to achieve effective internal forces mobilized for the implementation of successful operation ensures the active involvement of teenagers in social and interpersonal relationships. As the primary means of motive development success is considered training. The author provides a definition of "training for success in life," creates a model of training for success in life, and describes its units (targeted, informative, technological, productive, reveals the successful development of the technology life strategy used during the training (self-presentation, targets, incentives, subject-orientation. The author pays attention to the need for a future psychologist to develop teenagers’ motive to achieve success through the mastery of competence in constructing a model of training for success in life, and its implementation in the course of professional activities. The main means of training students of psychology to the use of training success in life identified the additional educational programs and psychological section.DOI: http://dx.doi.org/10.12731/2218-7405-2013-9-77

  14. Physically realistic modeling of maritime training simulation

    OpenAIRE

    Cieutat , Jean-Marc

    2003-01-01

    Maritime training simulation is an important matter of maritime teaching, which requires a lot of scientific and technical skills.In this framework, where the real time constraint has to be maintained, all physical phenomena cannot be studied; the most visual physical phenomena relating to the natural elements and the ship behaviour are reproduced only. Our swell model, based on a surface wave simulation approach, permits to simulate the shape and the propagation of a regular train of waves f...

  15. Position Control of Servo Systems Using Feed-Forward Friction Compensation

    International Nuclear Information System (INIS)

    Park, Min Gyu; Kim, Han Me; Shin, Jong Min; Kim, Jong Shik

    2009-01-01

    Friction is an important factor for precise position tracking control of servo systems. Servo systems with highly nonlinear friction are sensitive to the variation of operating condition. To overcome this problem, we use the LuGre friction model which can consider dynamic characteristics of friction. The LuGre friction model is used as a feed-forward compensator to improve tracking performance of servo systems. The parameters of the LuGre friction model are identified through experiments. The experimental result shows that the tracking performance of servo systems with higherly nonlinear friction can be improved by using feed-forward friction compensation

  16. Feed-forward segmentation of figure-ground and assignment of border-ownership.

    Directory of Open Access Journals (Sweden)

    Hans Supèr

    Full Text Available Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.

  17. Feed-forward segmentation of figure-ground and assignment of border-ownership.

    Science.gov (United States)

    Supèr, Hans; Romeo, August; Keil, Matthias

    2010-05-19

    Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.

  18. Differences in feedforward trunk muscle activity in subgroups of patients with mechanical low back pain.

    Science.gov (United States)

    Silfies, Sheri P; Mehta, Rupal; Smith, Sue S; Karduna, Andrew R

    2009-07-01

    To investigate alterations in trunk muscle timing patterns in subgroups of patients with mechanical low back pain (MLBP). Our hypothesis was that subjects with MLBP would demonstrate delayed muscle onset and have fewer muscles functioning in a feedforward manner than the control group. We further hypothesized that we would find differences between subgroups of our patients with MLBP, grouped according to diagnosis (segmental instability and noninstability). Case-control. Laboratory. Forty-three patients with chronic MLBP (25 instability, 18 noninstability) and 39 asymptomatic controls. Not applicable. Surface electromyography was used to measure onset time of 10 trunk muscles during a self-perturbation task. Trunk muscle onset latency relative to the anterior deltoid was calculated and the number of muscles functioning in feedforward determined. Activation timing patterns (Pfeedforward (P=.02; eta=.30; 1-beta=.83) were statistically different between patients with MLBP and controls. The control group activated the external oblique, lumbar multifidus, and erector spinae muscles in a feedforward manner. The heterogeneous MLBP group did not activate the trunk musculature in feedforward, but responded with significantly delayed activations. MLBP subgroups demonstrated significantly different timing patterns. The noninstability MLBP subgroup activated trunk extensors in a feedforward manner, similar to the control group, but significantly earlier than the instability subgroup. Lack of feedforward activation of selected trunk musculature in patients with MLBP may result in a period of inefficient muscular stabilization. Activation timing was more impaired in the instability than the noninstability MLBP subgroup. Training specifically for recruitment timing may be an important component of the rehabilitation program.

  19. Feedforward Coordinate Control of a Robotic Cell Injection Catheter.

    Science.gov (United States)

    Cheng, Weyland; Law, Peter K

    2017-08-01

    Remote and robotically actuated catheters are the stepping-stones toward autonomous catheters, where complex intravascular procedures may be performed with minimal intervention from a physician. This article proposes a concept for the positional, feedforward control of a robotically actuated cell injection catheter used for the injection of myogenic or undifferentiated stem cells into the myocardial infarct boundary zones of the left ventricle. The prototype for the catheter system was built upon a needle-based catheter with a single degree of deflection, a 3-D printed handle combined with actuators, and the Arduino microcontroller platform. A bench setup was used to mimic a left ventricle catheter procedure starting from the femoral artery. Using Matlab and the open-source video modeling tool Tracker, the planar coordinates ( y, z) of the catheter position were analyzed, and a feedforward control system was developed based on empirical models. Using the Student's t test with a sample size of 26, it was determined that for both the y- and z-axes, the mean discrepancy between the calibrated and theoretical coordinate values had no significant difference compared to the hypothetical value of µ = 0. The root mean square error of the calibrated coordinates also showed an 88% improvement in the z-axis and 31% improvement in the y-axis compared to the unmodified trial run. This proof of concept investigation leads to the possibility of further developing a feedfoward control system in vivo using catheters with omnidirectional deflection. Feedforward positional control allows for more flexibility in the design of an automated catheter system where problems such as systemic time delay may be a hindrance in instances requiring an immediate reaction.

  20. Advanced training simulator models. Implementation and validation

    International Nuclear Information System (INIS)

    Borkowsky, Jeffrey; Judd, Jerry; Belblidia, Lotfi; O'farrell, David; Andersen, Peter

    2008-01-01

    Modern training simulators are required to replicate plant data for both thermal-hydraulic and neutronic response. Replication is required such that reactivity manipulation on the simulator properly trains the operator for reactivity manipulation at the plant. This paper discusses advanced models which perform this function in real-time using the coupled code system THOR/S3R. This code system models the all fluids systems in detail using an advanced, two-phase thermal-hydraulic a model. The nuclear core is modeled using an advanced, three-dimensional nodal method and also by using cycle-specific nuclear data. These models are configured to run interactively from a graphical instructor station or handware operation panels. The simulator models are theoretically rigorous and are expected to replicate the physics of the plant. However, to verify replication, the models must be independently assessed. Plant data is the preferred validation method, but plant data is often not available for many important training scenarios. In the absence of data, validation may be obtained by slower-than-real-time transient analysis. This analysis can be performed by coupling a safety analysis code and a core design code. Such a coupling exists between the codes RELAP5 and SIMULATE-3K (S3K). RELAP5/S3K is used to validate the real-time model for several postulated plant events. (author)

  1. Binding and segmentation via a neural mass model trained with Hebbian and anti-Hebbian mechanisms.

    Science.gov (United States)

    Cona, Filippo; Zavaglia, Melissa; Ursino, Mauro

    2012-04-01

    Synchronization of neural activity in the gamma band, modulated by a slower theta rhythm, is assumed to play a significant role in binding and segmentation of multiple objects. In the present work, a recent neural mass model of a single cortical column is used to analyze the synaptic mechanisms which can warrant synchronization and desynchronization of cortical columns, during an autoassociation memory task. The model considers two distinct layers communicating via feedforward connections. The first layer receives the external input and works as an autoassociative network in the theta band, to recover a previously memorized object from incomplete information. The second realizes segmentation of different objects in the gamma band. To this end, units within both layers are connected with synapses trained on the basis of previous experience to store objects. The main model assumptions are: (i) recovery of incomplete objects is realized by excitatory synapses from pyramidal to pyramidal neurons in the same object; (ii) binding in the gamma range is realized by excitatory synapses from pyramidal neurons to fast inhibitory interneurons in the same object. These synapses (both at points i and ii) have a few ms dynamics and are trained with a Hebbian mechanism. (iii) Segmentation is realized with faster AMPA synapses, with rise times smaller than 1 ms, trained with an anti-Hebbian mechanism. Results show that the model, with the previous assumptions, can correctly reconstruct and segment three simultaneous objects, starting from incomplete knowledge. Segmentation of more objects is possible but requires an increased ratio between the theta and gamma periods.

  2. Small Business Training Models for Community Growth.

    Science.gov (United States)

    Jellison, Holly M., Ed.

    Nine successful community college programs for small business management training are described in this report in terms of their college and economic context, purpose, offerings, delivery modes, operating and marketing strategies, community outreach, support services, faculty and staff, evaluation, and future directions. The model programs are…

  3. Constructing Agent Model for Virtual Training Systems

    Science.gov (United States)

    Murakami, Yohei; Sugimoto, Yuki; Ishida, Toru

    Constructing highly realistic agents is essential if agents are to be employed in virtual training systems. In training for collaboration based on face-to-face interaction, the generation of emotional expressions is one key. In training for guidance based on one-to-many interaction such as direction giving for evacuations, emotional expressions must be supplemented by diverse agent behaviors to make the training realistic. To reproduce diverse behavior, we characterize agents by using a various combinations of operation rules instantiated by the user operating the agent. To accomplish this goal, we introduce a user modeling method based on participatory simulations. These simulations enable us to acquire information observed by each user in the simulation and the operating history. Using these data and the domain knowledge including known operation rules, we can generate an explanation for each behavior. Moreover, the application of hypothetical reasoning, which offers consistent selection of hypotheses, to the generation of explanations allows us to use otherwise incompatible operation rules as domain knowledge. In order to validate the proposed modeling method, we apply it to the acquisition of an evacuee's model in a fire-drill experiment. We successfully acquire a subject's model corresponding to the results of an interview with the subject.

  4. Identification of the feedforward component in manual control with predictable target signals.

    Science.gov (United States)

    Drop, Frank M; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus M; Mulder, Max

    2013-12-01

    In the manual control of a dynamic system, the human controller (HC) often follows a visible and predictable reference path. Compared with a purely feedback control strategy, performance can be improved by making use of this knowledge of the reference. The operator could effectively introduce feedforward control in conjunction with a feedback path to compensate for errors, as hypothesized in literature. However, feedforward behavior has never been identified from experimental data, nor have the hypothesized models been validated. This paper investigates human control behavior in pursuit tracking of a predictable reference signal while being perturbed by a quasi-random multisine disturbance signal. An experiment was done in which the relative strength of the target and disturbance signals were systematically varied. The anticipated changes in control behavior were studied by means of an ARX model analysis and by fitting three parametric HC models: two different feedback models and a combined feedforward and feedback model. The ARX analysis shows that the experiment participants employed control action on both the error and the target signal. The control action on the target was similar to the inverse of the system dynamics. Model fits show that this behavior can be modeled best by the combined feedforward and feedback model.

  5. Neural network feedforward control of a closed-circuit wind tunnel

    Science.gov (United States)

    Sutcliffe, Peter

    Accurate control of wind-tunnel test conditions can be dramatically enhanced using feedforward control architectures which allow operating conditions to be maintained at a desired setpoint through the use of mathematical models as the primary source of prediction. However, as the desired accuracy of the feedforward prediction increases, the model complexity also increases, so that an ever increasing computational load is incurred. This drawback can be avoided by employing a neural network that is trained offline using the output of a high fidelity wind-tunnel mathematical model, so that the neural network can rapidly reproduce the predictions of the model with a greatly reduced computational overhead. A novel neural network database generation method, developed through the use of fractional factorial arrays, was employed such that a neural network can accurately predict wind-tunnel parameters across a wide range of operating conditions whilst trained upon a highly efficient database. The subsequent network was incorporated into a Neural Network Model Predictive Control (NNMPC) framework to allow an optimised output schedule capable of providing accurate control of the wind-tunnel operating parameters. Facilitation of an optimised path through the solution space is achieved through the use of a chaos optimisation algorithm such that a more globally optimum solution is likely to be found with less computational expense than the gradient descent method. The parameters associated with the NNMPC such as the control horizon are determined through the use of a Taguchi methodology enabling the minimum number of experiments to be carried out to determine the optimal combination. The resultant NNMPC scheme was employed upon the Hessert Low Speed Wind Tunnel at the University of Notre Dame to control the test-section temperature such that it follows a pre-determined reference trajectory during changes in the test-section velocity. Experimental testing revealed that the

  6. Engineering teacher training models and experiences

    Science.gov (United States)

    González-Tirados, R. M.

    2009-04-01

    Education Area, we renewed the programme, content and methodology, teaching the course under the name of "Initial Teacher Training Course within the framework of the European Higher Education Area". Continuous Training means learning throughout one's life as an Engineering teacher. They are actions designed to update and improve teaching staff, and are systematically offered on the current issues of: Teaching Strategies, training for research, training for personal development, classroom innovations, etc. They are activities aimed at conceptual change, changing the way of teaching and bringing teaching staff up-to-date. At the same time, the Institution is at the disposal of all teaching staff as a meeting point to discuss issues in common, attend conferences, department meetings, etc. In this Congress we present a justification of both training models and their design together with some results obtained on: training needs, participation, how it is developing and to what extent students are profiting from it.

  7. Combined feedforward and feedback control of a redundant, nonlinear, dynamic musculoskeletal system.

    Science.gov (United States)

    Blana, Dimitra; Kirsch, Robert F; Chadwick, Edward K

    2009-05-01

    A functional electrical stimulation controller is presented that uses a combination of feedforward and feedback for arm control in high-level injury. The feedforward controller generates the muscle activations nominally required for desired movements, and the feedback controller corrects for errors caused by muscle fatigue and external disturbances. The feedforward controller is an artificial neural network (ANN) which approximates the inverse dynamics of the arm. The feedback loop includes a PID controller in series with a second ANN representing the nonlinear properties and biomechanical interactions of muscles and joints. The controller was designed and tested using a two-joint musculoskeletal model of the arm that includes four mono-articular and two bi-articular muscles. Its performance during goal-oriented movements of varying amplitudes and durations showed a tracking error of less than 4 degrees in ideal conditions, and less than 10 degrees even in the case of considerable fatigue and external disturbances.

  8. The Roles of Feedback and Feedforward as Humans Learn to Control Unknown Dynamic Systems.

    Science.gov (United States)

    Zhang, Xingye; Wang, Shaoqian; Hoagg, Jesse B; Seigler, T Michael

    2018-02-01

    We present results from an experiment in which human subjects interact with an unknown dynamic system 40 times during a two-week period. During each interaction, subjects are asked to perform a command-following (i.e., pursuit tracking) task. Each subject's performance at that task improves from the first trial to the last trial. For each trial, we use subsystem identification to estimate each subject's feedforward (or anticipatory) control, feedback (or reactive) control, and feedback time delay. Over the 40 trials, the magnitudes of the identified feedback controllers and the identified feedback time delays do not change significantly. In contrast, the identified feedforward controllers do change significantly. By the last trial, the average identified feedforward controller approximates the inverse of the dynamic system. This observation provides evidence that a fundamental component of human learning is updating the anticipatory control until it models the inverse dynamics.

  9. Slewing maneuvers and vibration control of space structures by feedforward/feedback moment-gyro controls

    Science.gov (United States)

    Yang, Li-Farn; Mikulas, Martin M., Jr.; Park, K. C.; Su, Renjeng

    1993-01-01

    This paper presents a moment-gyro control approach to the maneuver and vibration suppression of a flexible truss arm undergoing a constant slewing motion. The overall slewing motion is triggered by a feedforward input, and a companion feedback controller is employed to augment the feedforward input and subsequently to control vibrations. The feedforward input for the given motion requirement is determined from the combined CMG (Control Momentum Gyro) devices and the desired rigid-body motion. The rigid-body dynamic model has enabled us to identify the attendant CMG momentum saturation constraints. The task for vibration control is carried out in two stages; first in the search of a suitable CMG placement along the beam span for various slewing maneuvers, and subsequently in the development of Liapunov-based control algorithms for CMG spin-stabilization. Both analytical and numerical results are presented to show the effectiveness of the present approach.

  10. Robust wide-range control of nuclear reactors by using the feedforward-feedback concept

    International Nuclear Information System (INIS)

    Weng, C.K.; Edwards, R.M.; Ray, A.

    1994-01-01

    A robust feedforward-feedback controller is proposed for wide-range operations of nuclear reactors. This control structure provides (a) optimized performance over a wide operating range resulting form the feedforward element and (b) guaranteed robust stability and performance resulting from the feedback element. The feedforward control law is synthesized via nonlinear programming, which generates an optimal control sequence over a finite-time horizon under specified constraints. The feedback control is synthesized via the structured singular value μ approach to guarantee robustness in the presence of disturbances and modeling uncertainties. The results of simulation experiments are presented to demonstrate efficacy of the proposed control structure for a large rapid power reduction to avoid unnecessary plant trips

  11. Dialogic feedforward in group coaching

    DEFF Research Database (Denmark)

    Alrø, Helle; Dahl, Poul Nørgård

    2015-01-01

    The overall purpose of the article is to describe a joint learning process where both practicable and theoretically anchored knowledge are in the foreground. The empirical data derives from an EU project. In focus is a group of course leaders and their experiences of carrying out a training...... programme targeted for a group of individuals with a weak position on the labour market. The author brings out what happens when individuals try to understand perspectives from one another. The results demonstrate the knowledge that is developed when members of a project team are included in the entire...... research process, from the definition of problems to the analysis, presentation of results and suggestions of change. Further the outcome illustrates how an interactive research approach can be conducted in close co-operation with those concerned. Active participation, a structured learning process...

  12. Design Of Feedforward Controllers For Multivariable Plants

    Science.gov (United States)

    Seraji, Homayoun

    1989-01-01

    Controllers based on simple low-order transfer functions. Mathematical criteria derived for design of feedforward controllers for class of multiple-input/multiple-output linear plants. Represented by simple low-order transfer functions, obtained without reconstruction of states of commands and disturbances. Enables plant to track command while remaining unresponsive to disturbance in steady state. Feedback controller added independently to stabilize plant or to make control system less susceptible to variations in parameters of plant.

  13. Output Control Using Feedforward And Cascade Controllers

    Science.gov (United States)

    Seraji, Homayoun

    1990-01-01

    Report presents theoretical study of open-loop control elements in single-input, single-output linear system. Focus on output-control (servomechanism) problem, in which objective is to find control scheme that causes output to track certain command inputs and to reject certain disturbance inputs in steady state. Report closes with brief discussion of characteristics and relative merits of feedforward, cascade, and feedback controllers and combinations thereof.

  14. Feedback/feedforward control of hysteresis-compensated piezoelectric actuators for high-speed scanning applications

    International Nuclear Information System (INIS)

    Liu, Yanfang; Shan, Jinjun; Gabbert, Ulrich

    2015-01-01

    This paper presents the control system design for a piezoelectric actuator (PEA) for a high-speed trajectory scanning application. First nonlinear hysteresis is compensated for by using the Maxwell resistive capacitor model. Then the linear dynamics of the hysteresis-compensated piezoelectric actuator are identified. A proportional plus integral (PI) controller is designed based on the linear system, enhanced by feedforward hysteresis compensation. It is found that the feedback controller does not always improve tracking accuracy. When the input frequency exceeds a certain value, feedforward control only may result in better control performance. Experiments are conducted, and the results demonstrate the effectiveness of the proposed control approach. (paper)

  15. Fitting neuron models to spike trains

    Directory of Open Access Journals (Sweden)

    Cyrille eRossant

    2011-02-01

    Full Text Available Computational modeling is increasingly used to understand the function of neural circuitsin systems neuroscience.These studies require models of individual neurons with realisticinput-output properties.Recently, it was found that spiking models can accurately predict theprecisely timed spike trains produced by cortical neurons in response tosomatically injected currents,if properly fitted. This requires fitting techniques that are efficientand flexible enough to easily test different candidate models.We present a generic solution, based on the Brian simulator(a neural network simulator in Python, which allowsthe user to define and fit arbitrary neuron models to electrophysiological recordings.It relies on vectorization and parallel computing techniques toachieve efficiency.We demonstrate its use on neural recordings in the barrel cortex andin the auditory brainstem, and confirm that simple adaptive spiking modelscan accurately predict the response of cortical neurons. Finally, we show how a complexmulticompartmental model can be reduced to a simple effective spiking model.

  16. Model for behavior observation training programs

    International Nuclear Information System (INIS)

    Berghausen, P.E. Jr.

    1987-01-01

    Continued behavior observation is mandated by ANSI/ANS 3.3. This paper presents a model for behavior observation training that is in accordance with this standard and the recommendations contained in US NRC publications. The model includes seventeen major topics or activities. Ten of these are discussed: Pretesting of supervisor's knowledge of behavior observation requirements, explanation of the goals of behavior observation programs, why behavior observation training programs are needed (legal and psychological issues), early indicators of emotional instability, use of videotaped interviews to demonstrate significant psychopathology, practice recording behaviors, what to do when unusual behaviors are observed, supervisor rationalizations for noncompliance, when to be especially vigilant, and prevention of emotional instability

  17. Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks.

    Science.gov (United States)

    DeMarse, Thomas B; Pan, Liangbin; Alagapan, Sankaraleengam; Brewer, Gregory J; Wheeler, Bruce C

    2016-01-01

    Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized

  18. Low-order feedforward controllers: Optimal performance and practical considerations

    OpenAIRE

    Hast, Martin; Hägglund, Tore

    2014-01-01

    Feedforward control from measurable disturbances can significantly improve the performance in control loops. However, tuning rules for such controllers are scarce. In this paper design rules for how to choose optimal low-order feedforward controller parameter are presented. The parameters are chosen so that the integrated squared error, when the system is subject to a step disturbance, is minimized. The approach utilizes a controller structure that decouples the feedforward and the feedback c...

  19. Feedforward inhibition and synaptic scaling--two sides of the same coin?

    Directory of Open Access Journals (Sweden)

    Christian Keck

    Full Text Available Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

  20. Feedforward inhibition and synaptic scaling--two sides of the same coin?

    Science.gov (United States)

    Keck, Christian; Savin, Cristina; Lücke, Jörg

    2012-01-01

    Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

  1. Feedforward and Feedback Control in Apraxia of Speech: Effects of Noise Masking on Vowel Production

    Science.gov (United States)

    Maas, Edwin; Mailend, Marja-Liisa; Guenther, Frank H.

    2015-01-01

    Purpose: This study was designed to test two hypotheses about apraxia of speech (AOS) derived from the Directions Into Velocities of Articulators (DIVA) model (Guenther et al., 2006): the feedforward system deficit hypothesis and the feedback system deficit hypothesis. Method: The authors used noise masking to minimize auditory feedback during…

  2. Control of a local neural network by feedforward and feedback inhibition

    NARCIS (Netherlands)

    Remme, M.W.H.; Wadman, W.J.

    2004-01-01

    The signal transfer of a neuronal network is shaped by the local interactions between the excitatory principal cells and the inhibitory interneurons. We investigated with a simple lumped model how feedforward and feedback inhibition in.uence the steady-state network signal transfer. We analyze how

  3. Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?

    Science.gov (United States)

    Lücke, Jörg

    2012-01-01

    Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing. PMID:22457610

  4. Video Feedforward for Rapid Learning of a Picture-Based Communication System

    Science.gov (United States)

    Smith, Jemma; Hand, Linda; Dowrick, Peter W.

    2014-01-01

    This study examined the efficacy of video self modeling (VSM) using feedforward, to teach various goals of a picture exchange communication system (PECS). The participants were two boys with autism and one man with Down syndrome. All three participants were non-verbal with no current functional system of communication; the two children had long…

  5. Discriminative training of self-structuring hidden control neural models

    DEFF Research Database (Denmark)

    Sørensen, Helge Bjarup Dissing; Hartmann, Uwe; Hunnerup, Preben

    1995-01-01

    This paper presents a new training algorithm for self-structuring hidden control neural (SHC) models. The SHC models were trained non-discriminatively for speech recognition applications. Better recognition performance can generally be achieved, if discriminative training is applied instead. Thus...... we developed a discriminative training algorithm for SHC models, where each SHC model for a specific speech pattern is trained with utterances of the pattern to be recognized and with other utterances. The discriminative training of SHC neural models has been tested on the TIDIGITS database...

  6. Feedforward hysteresis compensation in trajectory control of piezoelectrically-driven nanostagers

    Science.gov (United States)

    Bashash, Saeid; Jalili, Nader

    2006-03-01

    Complex structural nonlinearities of piezoelectric materials drastically degrade their performance in variety of micro- and nano-positioning applications. From the precision positioning and control perspective, the multi-path time-history dependent hysteresis phenomenon is the most concerned nonlinearity in piezoelectric actuators to be analyzed. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligent properties of hysteresis with the effects of non-local memories are discussed. Through performing a set of experiments on a piezoelectrically-driven nanostager with high resolution capacitive position sensor, it is shown that for the precise prediction of hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the system everpresent nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect if memory units are sufficiently chosen for the inverse model.

  7. Comparison between hybrid feedforward-feedback, feedforward, and feedback structures for active noise control of fMRI noise.

    Science.gov (United States)

    Reddy, Rajiv M; Panahi, Issa M S

    2008-01-01

    The performance of FIR feedforward, IIR feedforward, FIR feedback, hybrid FIR feedforward--FIR feedback, and hybrid IIR feedforward - FIR feedback structures for active noise control (ANC) are compared for an fMRI noise application. The filtered-input normalized least squares (FxNLMS) algorithm is used to update the coefficients of the adaptive filters in all these structures. Realistic primary and secondary paths of an fMRI bore are used by estimating them on a half cylindrical acrylic bore of 0.76 m (D)x1.52 m (L). Detailed results of the performance of the ANC system are presented in the paper for each of these structures. We find that the IIR feedforward structure produces most of the performance improvement in the hybrid IIR feedforward - FIR feedback structure and adding the feedback structure becomes almost redundant in the case of fMRI noise.

  8. Training mode's influences on the relationships between training-load models during basketball conditioning.

    Science.gov (United States)

    Scanlan, Aaron T; Wen, Neal; Tucker, Patrick S; Borges, Nattai R; Dalbo, Vincent J

    2014-09-01

    To compare perceptual and physiological training-load responses during various basketball training modes. Eight semiprofessional male basketball players (age 26.3 ± 6.7 y, height 188.1 ± 6.2 cm, body mass 92.0 ± 13.8 kg) were monitored across a 10-wk period in the preparatory phase of their training plan. Player session ratings of perceived exertion (sRPE) and heart-rate (HR) responses were gathered across base, specific, and tactical/game-play training modes. Pearson correlations were used to determine the relationships between the sRPE model and 2 HR-based models: the training impulse (TRIMP) and summated HR zones (SHRZ). One-way ANOVAs were used to compare training loads between training modes for each model. Stronger relationships between perceptual and physiological models were evident during base (sRPE-TRIMP r = .53, P training load than the TRIMP (15-65 AU) and SHRZ models (27-170 AU) transitioning between training modes. While the training-load models were significantly correlated during each training mode, weaker relationships were observed during specific conditioning. Comparisons suggest that the HR-based models were less effective in detecting periodized increases in training load, particularly during court-based, intermittent, multidirectional drills. The practical benefits and sensitivity of the sRPE model support its use across different basketball training modes.

  9. Sliding-mode control combined with improved adaptive feedforward for wafer scanner

    Science.gov (United States)

    Li, Xiaojie; Wang, Yiguang

    2018-03-01

    In this paper, a sliding-mode control method combined with improved adaptive feedforward is proposed for wafer scanner to improve the tracking performance of the closed-loop system. Particularly, In addition to the inverse model, the nonlinear force ripple effect which may degrade the tracking accuracy of permanent magnet linear motor (PMLM) is considered in the proposed method. The dominant position periodicity of force ripple is determined by using the Fast Fourier Transform (FFT) analysis for experimental data and the improved feedforward control is achieved by the online recursive least-squares (RLS) estimation of the inverse model and the force ripple. The improved adaptive feedforward is given in a general form of nth-order model with force ripple effect. This proposed method is motivated by the motion controller design of the long-stroke PMLM and short-stroke voice coil motor for wafer scanner. The stability of the closed-loop control system and the convergence of the motion tracking are guaranteed by the proposed sliding-mode feedback and adaptive feedforward methods theoretically. Comparative experiments on a precision linear motion platform can verify the correctness and effectiveness of the proposed method. The experimental results show that comparing to traditional method the proposed one has better performance of rapidity and robustness, especially for high speed motion trajectory. And, the improvements on both tracking accuracy and settling time can be achieved.

  10. Noise destroys feedback enhanced figure-ground segmentation but not feedforward figure-ground segmentation

    Science.gov (United States)

    Romeo, August; Arall, Marina; Supèr, Hans

    2012-01-01

    Figure-ground (FG) segmentation is the separation of visual information into background and foreground objects. In the visual cortex, FG responses are observed in the late stimulus response period, when neurons fire in tonic mode, and are accompanied by a switch in cortical state. When such a switch does not occur, FG segmentation fails. Currently, it is not known what happens in the brain on such occasions. A biologically plausible feedforward spiking neuron model was previously devised that performed FG segmentation successfully. After incorporating feedback the FG signal was enhanced, which was accompanied by a change in spiking regime. In a feedforward model neurons respond in a bursting mode whereas in the feedback model neurons fired in tonic mode. It is known that bursts can overcome noise, while tonic firing appears to be much more sensitive to noise. In the present study, we try to elucidate how the presence of noise can impair FG segmentation, and to what extent the feedforward and feedback pathways can overcome noise. We show that noise specifically destroys the feedback enhanced FG segmentation and leaves the feedforward FG segmentation largely intact. Our results predict that noise produces failure in FG perception. PMID:22934028

  11. Conjugate descent formulation of backpropagation error in feedforward neural networks

    Directory of Open Access Journals (Sweden)

    NK Sharma

    2009-06-01

    Full Text Available The feedforward neural network architecture uses backpropagation learning to determine optimal weights between different interconnected layers. This learning procedure uses a gradient descent technique applied to a sum-of-squares error function for the given input-output pattern. It employs an iterative procedure to minimise the error function for a given set of patterns, by adjusting the weights of the network. The first derivates of the error with respect to the weights identify the local error surface in the descent direction. Hence the network exhibits a different local error surface for every different pattern presented to it, and weights are iteratively modified in order to minimise the current local error. The determination of an optimal weight vector is possible only when the total minimum error (mean of the minimum local errors for all patterns from the training set may be minimised. In this paper, we present a general mathematical formulation for the second derivative of the error function with respect to the weights (which represents a conjugate descent for arbitrary feedforward neural network topologies, and we use this derivative information to obtain the optimal weight vector. The local error is backpropagated among the units of hidden layers via the second order derivative of the error with respect to the weights of the hidden and output layers independently and also in combination. The new total minimum error point may be evaluated with the help of the current total minimum error and the current minimised local error. The weight modification processes is performed twice: once with respect to the present local error and once more with respect to the current total or mean error. We present some numerical evidence that our proposed method yields better network weights than those determined via a conventional gradient descent approach.

  12. The relationships between internal and external training load models during basketball training.

    Science.gov (United States)

    Scanlan, Aaron T; Wen, Neal; Tucker, Patrick S; Dalbo, Vincent J

    2014-09-01

    The present investigation described and compared the internal and external training loads during basketball training. Eight semiprofessional male basketball players (mean ± SD, age: 26.3 ± 6.7 years; stature: 188.1 ± 6.2 cm; body mass: 92.0 ± 13.8 kg) were monitored across a 7-week period during the preparatory phase of the annual training plan. A total of 44 total sessions were monitored. Player session ratings of perceived exertion (sRPE), heart rate, and accelerometer data were collected across each training session. Internal training load was determined using the sRPE, training impulse (TRIMP), and summated-heart-rate-zones (SHRZ) training load models. External training load was calculated using an established accelerometer algorithm. Pearson product-moment correlations with 95% confidence intervals (CIs) were used to determine the relationships between internal and external training load models. Significant moderate relationships were observed between external training load and the sRPE (r42 = 0.49, 95% CI = 0.23-0.69, p external training load and the SHRZ model (r42 = 0.61, 95% CI = 0.38-0.77, p internal and external training load models, the magnitude of the correlations and low commonality suggest that internal training load models measure different constructs of the training process than the accelerometer training load model in basketball settings. Basketball coaching and conditioning professionals should not assume a linear dose-response between accelerometer and internal training load models during training and are recommended to combine internal and external approaches when monitoring training load in players.

  13. Neural network hydrological modelling: on questions of over-fitting, over-training and over-parameterisation

    Science.gov (United States)

    Abrahart, R. J.; Dawson, C. W.; Heppenstall, A. J.; See, L. M.

    2009-04-01

    The most critical issue in developing a neural network model is generalisation: how well will the preferred solution perform when it is applied to unseen datasets? The reported experiments used far-reaching sequences of model architectures and training periods to investigate the potential damage that could result from the impact of several interrelated items: (i) over-fitting - a machine learning concept related to exceeding some optimal architectural size; (ii) over-training - a machine learning concept related to the amount of adjustment that is applied to a specific model - based on the understanding that too much fine-tuning might result in a model that had accommodated random aspects of its training dataset - items that had no causal relationship to the target function; and (iii) over-parameterisation - a statistical modelling concept that is used to restrict the number of parameters in a model so as to match the information content of its calibration dataset. The last item in this triplet stems from an understanding that excessive computational complexities might permit an absurd and false solution to be fitted to the available material. Numerous feedforward multilayered perceptrons were trialled and tested. Two different methods of model construction were also compared and contrasted: (i) traditional Backpropagation of Error; and (ii) state-of-the-art Symbiotic Adaptive Neuro-Evolution. Modelling solutions were developed using the reported experimental set ups of Gaume & Gosset (2003). The models were applied to a near-linear hydrological modelling scenario in which past upstream and past downstream discharge records were used to forecast current discharge at the downstream gauging station [CS1: River Marne]; and a non-linear hydrological modelling scenario in which past river discharge measurements and past local meteorological records (precipitation and evaporation) were used to forecast current discharge at the river gauging station [CS2: Le Sauzay].

  14. Feed-Forward Control in Resonant DC Link Inverter

    OpenAIRE

    Apinan Aurasopon; Worawat Sa-ngiavibool

    2008-01-01

    This paper proposes a feed-forward control in resonant dc link inverter. The feed-forward control configuration is based on synchronous sigma-delta modulation. The simulation results showing the proposed technique can reject non-ideal dc bus improving the total harmonic distortion.

  15. Feedforward signal prediction for accurate motion systems using digital filters

    NARCIS (Netherlands)

    Butler, H.

    2012-01-01

    A positioning system that needs to accurately track a reference can benefit greatly from using feedforward. When using a force actuator, the feedforward needs to generate a force proportional to the reference acceleration, which can be measured by means of an accelerometer or can be created by

  16. Feed-Forward versus Feedback Inhibition in a Basic Olfactory Circuit.

    Directory of Open Access Journals (Sweden)

    Tiffany Kee

    2015-10-01

    Full Text Available Inhibitory interneurons play critical roles in shaping the firing patterns of principal neurons in many brain systems. Despite difference in the anatomy or functions of neuronal circuits containing inhibition, two basic motifs repeatedly emerge: feed-forward and feedback. In the locust, it was proposed that a subset of lateral horn interneurons (LHNs, provide feed-forward inhibition onto Kenyon cells (KCs to maintain their sparse firing--a property critical for olfactory learning and memory. But recently it was established that a single inhibitory cell, the giant GABAergic neuron (GGN, is the main and perhaps sole source of inhibition in the mushroom body, and that inhibition from this cell is mediated by a feedback (FB loop including KCs and the GGN. To clarify basic differences in the effects of feedback vs. feed-forward inhibition in circuit dynamics we here use a model of the locust olfactory system. We found both inhibitory motifs were able to maintain sparse KCs responses and provide optimal odor discrimination. However, we further found that only FB inhibition could create a phase response consistent with data recorded in vivo. These findings describe general rules for feed-forward versus feedback inhibition and suggest GGN is potentially capable of providing the primary source of inhibition to the KCs. A better understanding of how inhibitory motifs impact post-synaptic neuronal activity could be used to reveal unknown inhibitory structures within biological networks.

  17. Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays.

    Science.gov (United States)

    Mejias, Jorge F; Payeur, Alexandre; Selin, Erik; Maler, Leonard; Longtin, André

    2014-01-01

    The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry-also known as "open-loop feedback"-, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves) via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.

  18. Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays

    Directory of Open Access Journals (Sweden)

    Jorge F Mejias

    2014-02-01

    Full Text Available The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry — also known as ’open-loop feedback’ —, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.

  19. Comparative experiments regarding approaches to feedforward hysteresis compensation for piezoceramic actuators

    International Nuclear Information System (INIS)

    Gu, Guo-Ying; Zhu, Li-Min

    2014-01-01

    Piezoceramic actuators (PCAs) are desired devices in many micro/nano-positioning applications. The performance of PCA-based applications is severely limited by the presence of hysteresis nonlinearity. To remedy the hysteresis nonlinearity in such systems, feedforward hysteresis compensation is the most common technique. In the literature, many different feedforward hysteresis compensation approaches have been developed, but there are no comparative studies of these approaches. Focusing on the modified Prandtl-Ishlinskii model (MPIM) for asymmetric hysteresis description of piezoceramic actuators, three feedforward hysteresis compensation approaches—inverse hysteresis compensation (IHC), without inverse hysteresis compensation (WIHC), and direct inverse hysteresis compensation (DIHC)—are developed and compared in this paper. Extensive comparative experiments were conducted on a PCA-actuated stage to verify the effectiveness of the three different feedforward control approaches to hysteresis compensation. The experimental results show that the performances among the three approaches are rather similar, and the main differences among them are due to the specific implementation of each approach. (paper)

  20. Adaptive Feedforward Cancellation of Sinusoidal Disturbances in Superconducting RF Cavities

    CERN Document Server

    Kandil, T H; Hartung, W; Khalil, H; Popielarski, J; Vincent, J; York, R C

    2004-01-01

    A control method, known as adaptive feedforward cancellation (AFC) is applied to damp sinusoidal disturbances due to microphonics in superconducting RF (SRF) cavities. AFC provides a method for damping internal, and external sinusoidal disturbances with known frequencies. It is preferred over other schemes because it uses rudimentary information about the frequency response at the disturbance frequencies, without the necessity of knowing an analytic model (transfer function) of the system. It estimates the magnitude and phase of the sinusoidal disturbance inputs and generates a control signal to cancel their effect. AFC, along with a frequency estimation process, is shown to be very successful in the cancellation of sinusoidal signals from different sources. The results of this research may significantly reduce the power requirements and increase the stability for lightly loaded continuous-wave SRF systems.

  1. The mechanism of synchronization in feed-forward neuronal networks

    International Nuclear Information System (INIS)

    Goedeke, S; Diesmann, M

    2008-01-01

    Synchronization in feed-forward subnetworks of the brain has been proposed to explain the precisely timed spike patterns observed in experiments. While the attractor dynamics of these networks is now well understood, the underlying single neuron mechanisms remain unexplained. Previous attempts have captured the effects of the highly fluctuating membrane potential by relating spike intensity f(U) to the instantaneous voltage U generated by the input. This article shows that f is high during the rise and low during the decay of U(t), demonstrating that the U-dot-dependence of f, not refractoriness, is essential for synchronization. Moreover, the bifurcation scenario is quantitatively described by a simple f(U,U-dot) relationship. These findings suggest f(U,U-dot) as the relevant model class for the investigation of neural synchronization phenomena in a noisy environment

  2. Boundedness and convergence of online gradient method with penalty for feedforward neural networks.

    Science.gov (United States)

    Zhang, Huisheng; Wu, Wei; Liu, Fei; Yao, Mingchen

    2009-06-01

    In this brief, we consider an online gradient method with penalty for training feedforward neural networks. Specifically, the penalty is a term proportional to the norm of the weights. Its roles in the method are to control the magnitude of the weights and to improve the generalization performance of the network. By proving that the weights are automatically bounded in the network training with penalty, we simplify the conditions that are required for convergence of online gradient method in literature. A numerical example is given to support the theoretical analysis.

  3. Degraded expression of learned feedforward control in movements released by startle.

    Science.gov (United States)

    Wright, Zachary A; Carlsen, Anthony N; MacKinnon, Colum D; Patton, James L

    2015-08-01

    Recent work has shown that preplanned motor programs can be rapidly released via fast conducting pathways using a startling acoustic stimulus. Our question was whether the startle-elicited response might also release a recently learned internal model, which draws on experience to predict and compensate for expected perturbations in a feedforward manner. Our initial investigation using adaptation to robotically produced forces showed some evidence of this, but the results were potentially confounded by co-contraction caused by startle. In this study, we eliminated this confound by asking subjects to make reaching movements in the presence of a visual distortion. Results show that a startle stimulus (1) decreased performance of the recently learned task and (2) reduced after-effect magnitude. Since the recall of learned control was reduced, but not eliminated during startle trials, we suggest that multiple neural centers (cortical and subcortical) are involved in such learning and adaptation. These findings have implications for motor training in areas such as piloting, teleoperation, sports, and rehabilitation.

  4. An Improved Walk Model for Train Movement on Railway Network

    International Nuclear Information System (INIS)

    Li Keping; Mao Bohua; Gao Ziyou

    2009-01-01

    In this paper, we propose an improved walk model for simulating the train movement on railway network. In the proposed method, walkers represent trains. The improved walk model is a kind of the network-based simulation analysis model. Using some management rules for walker movement, walker can dynamically determine its departure and arrival times at stations. In order to test the proposed method, we simulate the train movement on a part of railway network. The numerical simulation and analytical results demonstrate that the improved model is an effective tool for simulating the train movement on railway network. Moreover, it can well capture the characteristic behaviors of train scheduling in railway traffic. (general)

  5. Modeling and Solving the Train Pathing Problem

    Directory of Open Access Journals (Sweden)

    Chuen-Yih Chen

    2009-04-01

    Full Text Available In a railroad system, train pathing is concerned with the assignment of trains to links and tracks, and train timetabling allocates time slots to trains. In this paper, we present an optimization heuristic to solve the train pathing and timetabling problem. This heuristic allows the dwell time of trains in a station or link to be dependent on the assigned tracks. It also allows the minimum clearance time between the trains to depend on their relative status. The heuristic generates a number of alternative paths for each train service in the initialization phase. Then it uses a neighborhood search approach to find good feasible combinations of these paths. A linear program is developed to evaluate the quality of each combination that is encountered. Numerical examples are provided.

  6. Declarative terrain modeling for military training games

    NARCIS (Netherlands)

    Smelik, R.M.; Tutenel, T.; Kraker, J.K.. de; Bidarra, R.

    2010-01-01

    Military training instructors increasingly often employ computer games to train soldiers in all sorts of skills and tactics. One of the difficulties instructors face when using games as a training tool is the creation of suitable content, including scenarios, entities, and corresponding terrain

  7. Neural Dynamics of Feedforward and Feedback Processing in Figure-Ground Segregation

    OpenAIRE

    Oliver W. Layton; Ennio eMingolla; Arash eYazdanbakhsh

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedba...

  8. Measuring Feedforward Inhibition and Its Impact on Local Circuit Function.

    Science.gov (United States)

    Hull, Court

    2017-05-01

    This protocol describes a series of approaches to measure feedforward inhibition in acute brain slices from the cerebellar cortex. Using whole-cell voltage and current clamp recordings from Purkinje cells in conjunction with electrical stimulation of the parallel fibers, these methods demonstrate how to measure the relationship between excitation and inhibition in a feedforward circuit. This protocol also describes how to measure the impact of feedforward inhibition on Purkinje cell excitability, with an emphasis on spike timing. © 2017 Cold Spring Harbor Laboratory Press.

  9. Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

    Science.gov (United States)

    Sailamul, Pachaya; Jang, Jaeson; Paik, Se-Bum

    2017-12-01

    Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of convergent feedforward wiring. To address this question, we implemented computer simulations of model neural networks: a source and a target layer connected with different types of convergent wiring rules. In the Gaussian-Gaussian (GG) model, both the connection probability and the strength are given as Gaussian distribution as a function of spatial distance. In the Uniform-Constant (UC) and Uniform-Exponential (UE) models, the connection probability density is a uniform constant within a certain range, but the connection strength is set as a constant value or an exponentially decaying function, respectively. Then we examined how the spike transfer function is modulated under these conditions, while static or synchronized input patterns were introduced to simulate different levels of feedforward spike synchronization. We observed that the synchronization-dependent modulation of the transfer function appeared noticeably different for each convergence condition. The modulation of the spike transfer function was largest in the UC model, and smallest in the UE model. Our analysis showed that this difference was induced by the different spike weight distributions that was generated from convergent synapses in each model. Our results suggest that, the structure of the feedforward convergence is a crucial factor for correlation-dependent spike control, thus must be considered important to understand the mechanism of information transfer in the brain.

  10. A Model of the Antecedents of Training Transfer

    Science.gov (United States)

    Mohammed Turab, Ghaneemah; Casimir, Gian

    2015-01-01

    Many organizations have invested heavily in training. However, only a small percentage of what is learnt from training is applied or transferred to the workplace. This study examines factors that influence training transfer. A conceptual model based on the Theory of Reasoned Action is hypothesized and tested. The sample consisted of 123 full-time…

  11. Neural dynamics of feedforward and feedback processing in figure-ground segregation.

    Science.gov (United States)

    Layton, Oliver W; Mingolla, Ennio; Yazdanbakhsh, Arash

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure's interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells), and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells). Neurons (convex cells) that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up) information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation.

  12. Neural Dynamics of Feedforward and Feedback Processing in Figure-Ground Segregation

    Directory of Open Access Journals (Sweden)

    Oliver W. Layton

    2014-09-01

    Full Text Available Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure’s interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells, and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells. Neurons (convex cells that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation.

  13. Neural dynamics of feedforward and feedback processing in figure-ground segregation

    Science.gov (United States)

    Layton, Oliver W.; Mingolla, Ennio; Yazdanbakhsh, Arash

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure's interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells), and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells). Neurons (convex cells) that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up) information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation. PMID:25346703

  14. Feedback enhances feedforward figure-ground segmentation by changing firing mode.

    Science.gov (United States)

    Supèr, Hans; Romeo, August

    2011-01-01

    In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforward spiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses with the responses to a homogenous texture. We propose that feedback controls figure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons.

  15. Feedback enhances feedforward figure-ground segmentation by changing firing mode.

    Directory of Open Access Journals (Sweden)

    Hans Supèr

    Full Text Available In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforward spiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses with the responses to a homogenous texture. We propose that feedback controls figure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons.

  16. Experience with feedback and feedforward for plasma control in ASDEX

    International Nuclear Information System (INIS)

    Schneider, F.

    1983-01-01

    Experimental results of vertical and radial position feedback are shown and discussed. In particular, stability problems of vertical position control are studied in detail. A feedforward procedure for the process computer is described and proved by measurements. (author)

  17. Minimal-Inversion Feedforward-And-Feedback Control System

    Science.gov (United States)

    Seraji, Homayoun

    1990-01-01

    Recent developments in theory of control systems support concept of minimal-inversion feedforward-and feedback control system consisting of three independently designable control subsystems. Applicable to the control of linear, time-invariant plant.

  18. NREL Advances Feedforward Control in Turbines (Fact Sheet)

    Energy Technology Data Exchange (ETDEWEB)

    2015-01-01

    This NREL Highlight is being produced for the 2015 February Alliance S&T Board meeting, and describes research that uses lidar and feedforward algorithms to improve rotor speed regulation and reduce costs of maintenance and operation.

  19. Excised Abdominoplasty Material as a Systematic Plastic Surgical Training Model

    Directory of Open Access Journals (Sweden)

    M. Erol Demirseren

    2012-01-01

    Full Text Available Achieving a level of technical skill and confidence in surgical operations is the main goal of plastic surgical training. Operating rooms were accepted as the practical teaching venues of the traditional apprenticeship model. However, increased patient population, time, and ethical and legal considerations made preoperation room practical work a must for plastic surgical training. There are several plastic surgical teaching models and simulators which are very useful in preoperation room practical training and the evaluation of plastic surgery residents. The full thickness skin with its vascular network excised in abdominoplasty procedures is an easily obtainable real human tissue which could be used as a training model in plastic surgery.

  20. Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network

    Directory of Open Access Journals (Sweden)

    Mehmet Şimşir

    2016-01-01

    Full Text Available Low power hub motors are widely used in electromechanical systems such as electrical bicycles and solar vehicles due to their robustness and compact structure. Such systems driven by hub motors (in wheel motors encounter previously defined and undefined faults under operation. It may inevitably lead to the interruption of the electromechanical system operation; hence, economic losses take place at certain times. Therefore, in order to maintain system operation sustainability, the motor should be precisely monitored and the faults are diagnosed considering various significant motor parameters. In this study, the artificial feedforward backpropagation neural network approach is proposed to real-time monitor and diagnose the faults of the hub motor by measuring seven main system parameters. So as to construct a necessary model, we trained the model, using a data set consisting of 4160 samples where each has 7 parameters, by the MATLAB environment until the best model is obtained. The results are encouraging and meaningful for the specific motor and the developed model may be applicable to other types of hub motors. The prosperous model of the whole system was embedded into Arduino Due microcontroller card and the mobile real-time monitoring and fault diagnosis system prototype for hub motor was designed and manufactured.

  1. 3D Printed Pediatric Temporal Bone: A Novel Training Model.

    Science.gov (United States)

    Longfield, Evan A; Brickman, Todd M; Jeyakumar, Anita

    2015-06-01

    Temporal bone dissection is a fundamental element of otologic training. Cadaveric temporal bones (CTB) are the gold standard surgical training model; however, many institutions do not have ready access to them and their cost can be significant: $300 to $500. Furthermore, pediatric cadaveric temporal bones are not readily available. Our objective is to develop a pediatric temporal bone model. Temporal bone model. Tertiary Children's Hospital. Pediatric patient model. We describe the novel use of a 3D printer for the generation of a plaster training model from a pediatric high- resolution CT temporal bone scan of a normal pediatric temporal bone. Three models were produced and were evaluated. The models utilized multiple colors (white for bone, yellow for the facial nerve) and were of high quality. Two models were drilled as a proof of concept and found to be an acceptable facsimile of the patient's anatomy, rendering all necessary surgical landmarks accurately. The only negative comments pertaining to the 3D printed temporal bone as a training model were the lack of variation in hardness between cortical and cancellous bone, noting a tactile variation from cadaveric temporal bones. Our novel pediatric 3D temporal bone training model is a viable, low-cost training option for previously inaccessible pediatric temporal bone training. Our hope is that, as 3D printers become commonplace, these models could be rapidly reproduced, allowing for trainees to print models of patients before performing surgery on the living patient.

  2. Relative effectiveness of assertive training, modelling and their ...

    African Journals Online (AJOL)

    The study investigated the Relative Effectiveness of Assertive Training (AT), modelling (M) and a combination of Assertive Training and Modelling (AT & M) techniques in improving the social skills of primary school isolates and consequently reduce their isolate behaviour. The study is a quasi experimental research that ...

  3. Southwest University's No-Fee Teacher-Training Model

    Science.gov (United States)

    Chen, Shijian; Yang, Shuhan; Li, Linyuan

    2013-01-01

    The training model for Southwest University's no-fee teacher education program has taken shape over several years. Based on a review of the documentation and interviews with administrators and no-fee preservice students from different specialties, this article analyzes Southwest University's no-fee teacher-training model in terms of three main…

  4. Why vision is not both hierarchical and feedforward

    Directory of Open Access Journals (Sweden)

    Michael H Herzog

    2014-10-01

    Full Text Available In classical models of object recognition, first, basic features (e.g., edges and lines are analyzed by independent filters that mimic the receptive field profiles of V1 neurons. In a feedforward fashion, the outputs of these filters are fed to filters at the next processing stage, pooling information across several filters from the previous level, and so forth at subsequent processing stages. Low-level processing determines high-level processing. Information lost on lower stages is irretrievably lost. Models of this type have proven to be very successful in many fields of vision, but have failed to explain object recognition in general. Here, we present experiments that, first, show that, similar to demonstrations from the Gestaltists, figural aspects determine low-level processing (as much as the other way around. Second, performance on a single element depends on all the other elements in the visual scene. Small changes in the overall configuration can lead to large changes in performance. Third, grouping of elements is key. Only if we know how elements group across the entire visual field, we can determine performance on individual elements, i.e., challenging the classical stereotypical filtering approach, which is at the very heart of most vision models.

  5. 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

  6. Rasmussen's model of human behavior in laparoscopy training.

    Science.gov (United States)

    Wentink, M; Stassen, L P S; Alwayn, I; Hosman, R J A W; Stassen, H G

    2003-08-01

    Compared to aviation, where virtual reality (VR) training has been standardized and simulators have proven their benefits, the objectives, needs, and means of VR training in minimally invasive surgery (MIS) still have to be established. The aim of the study presented is to introduce Rasmussen's model of human behavior as a practical framework for the definition of the training objectives, needs, and means in MIS. Rasmussen distinguishes three levels of human behavior: skill-, rule-, and knowledge-based behaviour. The training needs of a laparoscopic novice can be determined by identifying the specific skill-, rule-, and knowledge-based behavior that is required for performing safe laparoscopy. Future objectives of VR laparoscopy trainers should address all three levels of behavior. Although most commercially available simulators for laparoscopy aim at training skill-based behavior, especially the training of knowledge-based behavior during complications in surgery will improve safety levels. However, the cost and complexity of a training means increases when the training objectives proceed from the training of skill-based behavior to the training of complex knowledge-based behavior. In aviation, human behavior models have been used successfully to integrate the training of skill-, rule-, and knowledge-based behavior in a full flight simulator. Understanding surgeon behavior is one of the first steps towards a future full-scale laparoscopy simulator.

  7. A Model for Multiple Competency Teacher Training

    Science.gov (United States)

    Gargiulo, Richard M.; Swartz, Stanley L.

    1977-01-01

    Project Merge is an undergraduate, preservice education program at Bowling Green University providing training and experience leading to dual or triple certification in elementary education plus educable mental retardation and/or learning disabilities behavior disorders. (MB)

  8. [Feedforward control strategy and its application in quality improvement of ethanol precipitation process of danhong injection].

    Science.gov (United States)

    Yan, Bin-Jun; Guo, Zheng-Tai; Qu, Hai-Bin; Zhao, Bu-Chang; Zhao, Tao

    2013-06-01

    In this work, a feedforward control strategy basing on the concept of quality by design was established for the manufacturing process of traditional Chinese medicine to reduce the impact of the quality variation of raw materials on drug. In the research, the ethanol precipitation process of Danhong injection was taken as an application case of the method established. Box-Behnken design of experiments was conducted. Mathematical models relating the attributes of the concentrate, the process parameters and the quality of the supernatants produced were established. Then an optimization model for calculating the best process parameters basing on the attributes of the concentrate was built. The quality of the supernatants produced by ethanol precipitation with optimized and non-optimized process parameters were compared. The results showed that using the feedforward control strategy for process parameters optimization can control the quality of the supernatants effectively. The feedforward control strategy proposed can enhance the batch-to-batch consistency of the supernatants produced by ethanol precipitation.

  9. Standardized training in nurse model travel clinics.

    Science.gov (United States)

    Sofarelli, Theresa A; Ricks, Jane H; Anand, Rahul; Hale, Devon C

    2011-01-01

    International travel plays a significant role in the emergence and redistribution of major human diseases. The importance of travel medicine clinics for preventing morbidity and mortality has been increasingly appreciated, although few studies have thus far examined the management and staff training strategies that result in successful travel-clinic operations. Here, we describe an example of travel-clinic operation and management coordinated through the University of Utah School of Medicine, Division of Infectious Diseases. This program, which involves eight separate clinics distributed statewide, functions both to provide patient consult and care services, as well as medical provider training and continuing medical education (CME). Initial training, the use of standardized forms and protocols, routine chart reviews and monthly continuing education meetings are the distinguishing attributes of this program. An Infectious Disease team consisting of one medical doctor (MD) and a physician assistant (PA) act as consultants to travel nurses who comprise the majority of clinic staff. Eight clinics distributed throughout the state of Utah serve approximately 6,000 travelers a year. Pre-travel medical services are provided by 11 nurses, including 10 registered nurses (RNs) and 1 licensed practical nurse (LPN). This trained nursing staff receives continuing travel medical education and participate in the training of new providers. All nurses have completed a full training program and 7 of the 11 (64%) of clinic nursing staff serve more than 10 patients a week. Quality assurance measures show that approximately 0.5% of charts reviewed contain a vaccine or prescription error which require patient notification for correction. Using an initial training program, standardized patient intake forms, vaccine and prescription protocols, preprinted prescriptions, and regular CME, highly trained nurses at travel clinics are able to provide standardized pre-travel care to

  10. Feedforward responses of transversus abdominis are directionally specific and act asymmetrically: implications for core stability theories.

    Science.gov (United States)

    Allison, Garry T; Morris, Sue L; Lay, Brendan

    2008-05-01

    response. This is the first study to show that the feedforward activity of the TrA is specific to the direction of arm movement and not bilaterally symmetrical. The asymmetry of TrA activity during arm raising suggests that the interpretation of the role of TrA as a bilateral stabilizer during anticipatory postural adjustments needs to be revised. Future research needs to examine muscle synergies associated with the asymmetrical function of the TrA and the underlying mechanism associated with low-load stability training. Therapy, level 5.

  11. Controlling the chaotic discrete-Hénon system using a feedforward neural network with an adaptive learning rate

    OpenAIRE

    GÖKCE, Kürşad; UYAROĞLU, Yılmaz

    2013-01-01

    This paper proposes a feedforward neural network-based control scheme to control the chaotic trajectories of a discrete-Hénon map in order to stay within an acceptable distance from the stable fixed point. An adaptive learning back propagation algorithm with online training is employed to improve the effectiveness of the proposed method. The simulation study carried in the discrete-Hénon system verifies the validity of the proposed control system.

  12. An entrepreneurial training model to enhance undergraduate training in biomedical research.

    Science.gov (United States)

    Kamangar, Farin; Silver, Gillian; Hohmann, Christine; Hughes-Darden, Cleo; Turner-Musa, Jocelyn; Haines, Robert Trent; Jackson, Avis; Aguila, Nelson; Sheikhattari, Payam

    2017-01-01

    Undergraduate students who are interested in biomedical research typically work on a faculty member's research project, conduct one distinct task (e.g., running gels), and, step by step, enhance their skills. This "apprenticeship" model has been helpful in training many distinguished scientists over the years, but it has several potential drawbacks. For example, the students have limited autonomy, and may not understand the big picture, which may result in students giving up on their goals for a research career. Also, the model is costly and may greatly depend on a single mentor. The NIH Building Infrastructure Leading to Diversity (BUILD) Initiative has been established to fund innovative undergraduate research training programs and support institutional and faculty development of the recipient university. The training model at Morgan State University (MSU), namely " A S tudent- C entered En trepreneurship D evelopment training model" (ASCEND), is one of the 10 NIH BUILD-funded programs, and offers a novel, experimental "entrepreneurial" training approach. In the ASCEND training model, the students take the lead. They own the research, understand the big picture, and experience the entire scope of the research process, which we hypothesize will lead to a greater sense of self-efficacy and research competency, as well as an enhanced sense of science identity. They are also immersed in environments with substantial peer support, where they can exchange research ideas and share experiences. This is important for underrepresented minority students who might have fewer role models and less peer support in conducting research. In this article, we describe the MSU ASCEND entrepreneurial training model's components, rationale, and history, and how it may enhance undergraduate training in biomedical research that may be of benefit to other institutions. We also discuss evaluation methods, possible sustainability solutions, and programmatic challenges that can affect all

  13. Transfer Learning for OCRopus Model Training on Early Printed Books

    Directory of Open Access Journals (Sweden)

    Christian Reul

    2017-12-01

    Full Text Available A method is presented that significantly reduces the character error rates for OCR text obtained from OCRopus models trained on early printed books when only small amounts of diplomatic transcriptions are available. This is achieved by building from already existing models during training instead of starting from scratch. To overcome the discrepancies between the set of characters of the pretrained model and the additional ground truth the OCRopus code is adapted to allow for alphabet expansion or reduction. The character set is now capable of flexibly adding and deleting characters from the pretrained alphabet when an existing model is loaded. For our experiments we use a self-trained mixed model on early Latin prints and the two standard OCRopus models on modern English and German Fraktur texts. The evaluation on seven early printed books showed that training from the Latin mixed model reduces the average amount of errors by 43% and 26%, compared to training from scratch with 60 and 150 lines of ground truth, respectively. Furthermore, it is shown that even building from mixed models trained on standard data unrelated to the newly added training and test data can lead to significantly improved recognition results.

  14. Interactive training model of TRIZ for mechanical engineers in China

    Science.gov (United States)

    Tan, Runhua; Zhang, Huangao

    2014-03-01

    Innovation is a process of taking an original idea and converting it into a business value, in which the engineers face some inventive problems which can be solved hardly by experience. TRIZ, as a new theory for companies in China, provides both conceptual and procedural knowledge for finding and solving inventive problems. Because the government plays a leading role in the diffusion of TRIZ, too many companies from different industries are waiting to be trained, but the quantity of the trainers mastering TRIZ is incompatible with that requirement. In this context, to improve the training effect, an interactive training model of TRIZ for the mechanical engineers in China is developed and the implementation in the form of training classes is carried out. The training process is divided into 6 phases as follows: selecting engineers, training stage-1, finding problems, training stage-2, finding solutions and summing up. The government, TRIZ institutions and companies to join the programs interact during the process. The government initiates and monitors a project in form of a training class of TRIZ and selects companies to join the programs. Each selected companies choose a few engineers to join the class and supervises the training result. The TRIZ institutions design the training courses and carry out training curriculum. With the beginning of the class, an effective communication channel is established by means of interview, discussion face to face, E-mail, QQ and so on. After two years training practices, the results show that innovative abilities of the engineers to join and pass the final examinations increased distinctly, and most of companies joined the training class have taken congnizance of the power of TRIZ for product innovation. This research proposes an interactive training model of TRIZ for mechanical engineers in China to expedite the knowledge diffusion of TRIZ.

  15. Estimating feedforward vs. feedback control of speech production through kinematic analyses of unperturbed articulatory movements.

    Science.gov (United States)

    Kim, Kwang S; Max, Ludo

    2014-01-01

    To estimate the contributions of feedforward vs. feedback control systems in speech articulation, we analyzed the correspondence between initial and final kinematics in unperturbed tongue and jaw movements for consonant-vowel (CV) and vowel-consonant (VC) syllables. If movement extents and endpoints are highly predictable from early kinematic information, then the movements were most likely completed without substantial online corrections (feedforward control); if the correspondence between early kinematics and final amplitude or position is low, online adjustments may have altered the planned trajectory (feedback control) (Messier and Kalaska, 1999). Five adult speakers produced CV and VC syllables with high, mid, or low vowels while movements of the tongue and jaw were tracked electromagnetically. The correspondence between the kinematic parameters peak acceleration or peak velocity and movement extent as well as between the articulators' spatial coordinates at those kinematic landmarks and movement endpoint was examined both for movements across different target distances (i.e., across vowel height) and within target distances (i.e., within vowel height). Taken together, results suggest that jaw and tongue movements for these CV and VC syllables are mostly under feedforward control but with feedback-based contributions. One type of feedback-driven compensatory adjustment appears to regulate movement duration based on variation in peak acceleration. Results from a statistical model based on multiple regression are presented to illustrate how the relative strength of these feedback contributions can be estimated.

  16. Feedforward motor control in developmental dyslexia and developmental coordination disorder: Does comorbidity matter?

    Science.gov (United States)

    Cignetti, Fabien; Vaugoyeau, Marianne; Fontan, Aurelie; Jover, Marianne; Livet, Marie-Odile; Hugonenq, Catherine; Audic, Frédérique; Chabrol, Brigitte; Assaiante, Christine

    2018-05-01

    Feedforward and online controls are two facets of predictive motor control from internal models, which is suspected to be impaired in learning disorders. We examined whether the feedforward component is affected in children (8-12 years) with developmental dyslexia (DD) and/or with developmental coordination disorder (DCD) compared to typically developing (TD) children. Children underwent a bimanual unloading paradigm during which a load supported to one arm, the postural arm, was either unexpectedly unloaded by a computer or voluntary unloaded by the subject with the other arm. All children showed a better stabilization (lower flexion) of the postural arm and an earlier inhibition of the arm flexors during voluntary unloading, indicating anticipation of unloading. Between-group comparisons of kinematics and electromyographic activity of the postural arm revealed that the difference during voluntary unloading was between DD-DCD children and the other groups, with the former showing a delayed inhibition of the flexor muscles. Deficit of the feedforward component of motor control may particularly apply to comorbid subtypes, here the DD-DCD subtype. The development of a comprehensive framework for motor performance deficits in children with learning disorders will be achieved only by dissociating key components of motor prediction and focusing on subtypes and comorbidities. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Variable synaptic strengths controls the firing rate distribution in feedforward neural networks.

    Science.gov (United States)

    Ly, Cheng; Marsat, Gary

    2018-02-01

    Heterogeneity of firing rate statistics is known to have severe consequences on neural coding. Recent experimental recordings in weakly electric fish indicate that the distribution-width of superficial pyramidal cell firing rates (trial- and time-averaged) in the electrosensory lateral line lobe (ELL) depends on the stimulus, and also that network inputs can mediate changes in the firing rate distribution across the population. We previously developed theoretical methods to understand how two attributes (synaptic and intrinsic heterogeneity) interact and alter the firing rate distribution in a population of integrate-and-fire neurons with random recurrent coupling. Inspired by our experimental data, we extend these theoretical results to a delayed feedforward spiking network that qualitatively capture the changes of firing rate heterogeneity observed in in-vivo recordings. We demonstrate how heterogeneous neural attributes alter firing rate heterogeneity, accounting for the effect with various sensory stimuli. The model predicts how the strength of the effective network connectivity is related to intrinsic heterogeneity in such delayed feedforward networks: the strength of the feedforward input is positively correlated with excitability (threshold value for spiking) when firing rate heterogeneity is low and is negatively correlated with excitability with high firing rate heterogeneity. We also show how our theory can be used to predict effective neural architecture. We demonstrate that neural attributes do not interact in a simple manner but rather in a complex stimulus-dependent fashion to control neural heterogeneity and discuss how it can ultimately shape population codes.

  18. Measurable Disturbances Compensation: Analysis and Tuning of Feedforward Techniques for Dead-Time Processes

    Directory of Open Access Journals (Sweden)

    Andrzej Pawlowski

    2016-04-01

    Full Text Available In this paper, measurable disturbance compensation techniques are analyzed, focusing the problem on the input-output and disturbance-output time delays. The feedforward compensation method is evaluated for the common structures that appear between the disturbance and process dynamics. Due to the presence of time delays, the study includes causality and instability phenomena that can arise when a classical approach for disturbance compensation is used. Different feedforward configurations are analyzed for two feedback control techniques, PID (Proportional-Integral-Derivative and MPC (Model Predictive Control that are widely used for industrial process-control applications. The specific tuning methodology for the analyzed process structure is used to obtain improved disturbance rejection performance regarding classical approaches. The evaluation of the introduced disturbance rejection schemes is performed through simulation, considering process constraints in order to highlight the advantages and drawbacks in common scenarios. The performance of the analyzed structure is expressed with different indexes that allow us direct comparisons. The obtained results show that the proper design and tuning of the feedforward action helps to significantly improve the overall control performance in process control tasks.

  19. Modelling, simulation and applications of longitudinal train dynamics

    Science.gov (United States)

    Cole, Colin; Spiryagin, Maksym; Wu, Qing; Sun, Yan Quan

    2017-10-01

    Significant developments in longitudinal train simulation and an overview of the approaches to train models and modelling vehicle force inputs are firstly presented. The most important modelling task, that of the wagon connection, consisting of energy absorption devices such as draft gears and buffers, draw gear stiffness, coupler slack and structural stiffness is then presented. Detailed attention is given to the modelling approaches for friction wedge damped and polymer draft gears. A significant issue in longitudinal train dynamics is the modelling and calculation of the input forces - the co-dimensional problem. The need to push traction performances higher has led to research and improvement in the accuracy of traction modelling which is discussed. A co-simulation method that combines longitudinal train simulation, locomotive traction control and locomotive vehicle dynamics is presented. The modelling of other forces, braking propulsion resistance, curve drag and grade forces are also discussed. As extensions to conventional longitudinal train dynamics, lateral forces and coupler impacts are examined in regards to interaction with wagon lateral and vertical dynamics. Various applications of longitudinal train dynamics are then presented. As an alternative to the tradition single wagon mass approach to longitudinal train dynamics, an example incorporating fully detailed wagon dynamics is presented for a crash analysis problem. Further applications of starting traction, air braking, distributed power, energy analysis and tippler operation are also presented.

  20. Preliminary development of the Active Colonoscopy Training Model

    Directory of Open Access Journals (Sweden)

    Choi J

    2011-06-01

    Full Text Available JungHun Choi1, Kale Ravindra1, Randolph Robert1, David Drozek21Mechanical Engineering, Ohio University, Athens, OH, USA; 2College of Osteopathic Medicine, Ohio University, Athens, OH, USAAbstract: Formal colonoscopy training requires a significant amount of time and effort. In particular, it requires actual patients for a realistic learning experience. The quality of colonoscopy training varies, and includes didactic courses and procedures proctored by skilled surgeons. A colonoscopy training model is occasionally used as part of the training method, but the effects are minute due to both the simple and tedious training procedures. To enhance the educational effect of the colonoscopy training model, the Active Colonoscopy Training Model (ACTM has been developed. ACTM is an interactive colonoscopy training device which can create the environment of a real colonoscopy procedure as closely as possible. It comprises a configurable rubber colon, a human torso, sensors, a display, and the control part. The ACTM provides audio and visual interaction to the trainee by monitoring important factors, such as forces caused by the distal tip and the shaft of the colonoscope and the pressure to open up the lumen and the localization of the distal tip. On the computer screen, the trainee can easily monitor the status of the colonoscopy, which includes the localization of the distal tip, maximum forces, pressure inside the colon, and surgery time. The forces between the rubber colon and the constraints inside the ACTM are measured and the real time display shows the results to the trainee. The pressure sensors will check the pressure at different parts of the colon. The real-time localized distal tip gives the colonoscopy trainee easier and more confident operation without introducing an additional device in the colonoscope. With the current need for colonoscopists and physicians, the ACTM can play an essential role resolving the problems of the current

  1. Traffic Modelling for Moving-Block Train Control System

    International Nuclear Information System (INIS)

    Tang Tao; Li Keping

    2007-01-01

    This paper presents a new cellular automaton (CA) model for train control system simulation. In the proposed CA model, the driver reactions to train movements are captured by some updated rules. The space-time diagram of traffic flow and the trajectory of train movement is used to obtain insight into the characteristic behavior of railway traffic flow. A number of simulation results demonstrate that the proposed CA model can be successfully used for the simulations of railway traffic. Not only the characteristic behavior of railway traffic flow can be reproduced, but also the simulation values of the minimum time headway are close to the theoretical values.

  2. Modeling cultural behavior for military virtual training

    NARCIS (Netherlands)

    Kerbusch, P.; Schram, J.; Bosch, K. van den

    2011-01-01

    Soldiers on mission in areas with unfamiliar cultures must be able to take into account the norms of the local culture when assessing a situation, and must be able to adapt their behavior accordingly. Innovative technologies provide opportunity to train the required skills in an interactive and

  3. Modeling Cultural Behavior for Military Virtual Training

    NARCIS (Netherlands)

    Bosch, K. van den; Kerbusch, P.J.M.; Schram, J.

    2012-01-01

    Soldiers on mission in areas with unfamiliar cultures must be able to take into account the norms of the local culture when assessing a situation, and must be able to adapt their behavior accordingly. Innovative technologies provide opportunity to train the required skills in an interactive and

  4. Clinical Reasoning in Athletic Training Education: Modeling Expert Thinking

    Science.gov (United States)

    Geisler, Paul R.; Lazenby, Todd W.

    2009-01-01

    Objective: To address the need for a more definitive approach to critical thinking during athletic training educational experiences by introducing the clinical reasoning model for critical thinking. Background: Educators are aware of the need to teach students how to think critically. The multiple domains of athletic training are comprehensive and…

  5. An incoherent feedforward loop facilitates adaptive tuning of gene expression.

    Science.gov (United States)

    Hong, Jungeui; Brandt, Nathan; Abdul-Rahman, Farah; Yang, Ally; Hughes, Tim; Gresham, David

    2018-04-05

    We studied adaptive evolution of gene expression using long-term experimental evolution of Saccharomyces cerevisiae in ammonium-limited chemostats. We found repeated selection for non-synonymous variation in the DNA binding domain of the transcriptional activator, GAT1, which functions with the repressor, DAL80 in an incoherent type-1 feedforward loop (I1-FFL) to control expression of the high affinity ammonium transporter gene, MEP2. Missense mutations in the DNA binding domain of GAT1 reduce its binding to the GATAA consensus sequence. However, we show experimentally, and using mathematical modeling, that decreases in GAT1 binding result in increased expression of MEP2 as a consequence of properties of I1-FFLs. Our results show that I1-FFLs, one of the most commonly occurring network motifs in transcriptional networks, can facilitate adaptive tuning of gene expression through modulation of transcription factor binding affinities. Our findings highlight the importance of gene regulatory architectures in the evolution of gene expression. © 2018, Hong et al.

  6. Preparing radiology staff to meet service goals: a training model.

    Science.gov (United States)

    Ricciardone, E B; Stepanovich, P H; West, V T

    1994-01-01

    This article describes a model used to train radiology staff in customer service relations at a large southeastern medical center. Information about the needs of the radiology department and staff was acquired through quantitative and qualitative assessments. The primary goal of the training was twofold: 1) to develop employee awareness of customer expectations and 2) to develop problem-solving skills to respond to customer service related issues. Instructional methods compatible with adult learning were used and training results were assessed. Positive changes in employee attitudes and behaviors are described and recommendations for training development and implementation are discussed.

  7. Neural network based approach for tuning of SNS feedback and feedforward controllers

    International Nuclear Information System (INIS)

    Kwon, Sung-Il; Prokop, Mark S.; Regan, Amy H.

    2002-01-01

    The primary controllers in the SNS low level RF system are proportional-integral (PI) feedback controllers. To obtain the best performance of the linac control systems, approximately 91 individual PI controller gains should be optimally tuned. Tuning is time consuming and requires automation. In this paper, a neural network is used for the controller gain tuning. A neural network can approximate any continuous mapping through learning. In a sense, the cavity loop PI controller is a continuous mapping of the tracking error and its one-sample-delay inputs to the controller output. Also, monotonic cavity output with respect to its input makes knowing the detailed parameters of the cavity unnecessary. Hence the PI controller is a prime candidate for approximation through a neural network. Using mean square error minimization to train the neural network along with a continuous mapping of appropriate weights, optimally tuned PI controller gains can be determined. The same neural network approximation property is also applied to enhance the adaptive feedforward controller performance. This is done by adjusting the feedforward controller gains, forgetting factor, and learning ratio. Lastly, the automation of the tuning procedure data measurement, neural network training, tuning and loading the controller gain to the DSP is addressed.

  8. Simultaneous feedforward recruitment of the vasti in untrained postural tasks can be restored by physical therapy.

    Science.gov (United States)

    Cowan, Sallie M; Bennell, Kim L; Hodges, Paul W; Crossley, Kay M; McConnell, Jenny

    2003-05-01

    Physical therapy rehabilitation strategies are commonly directed at the alteration of muscle recruitment in functional movements. The aim of this study was to investigate whether feedforward strategies of the vasti in people with patellofemoral pain syndrome can be changed by a physical therapy treatment program in a randomised, double blind, placebo controlled trial. Forty (25 female, 15 male) subjects aged 40 yrs or less (27.2+/-7.8 yrs). Subjects were allocated to either a placebo treatment or a physical therapy intervention program. The postural challenge used as the outcome measure was not included in the training program. Electromyography (EMG) onsets of vastus medialis obliquus (VMO), vastus lateralis (VL), tibialis anterior and soleus were assessed before and after the six week standardised treatment programs. At baseline the EMG onset of VL occurred prior to that of VMO in both subject groups. Following physical therapy intervention there was a significant change in the time of onset of EMG of VMO compared to VL with the onsets occurring simultaneously. This change was associated with a reduction in symptoms. In contrast, following placebo intervention the EMG onset of VL still occurred prior to that of VMO. The results indicate that the feedforward strategy used by the central nervous system to control the patella can be restored. Importantly, the data suggest that this intervention produced a change that was transferred to a task that was not specifically included in the training program. Furthermore, the change in motor control was associated with clinical improvement in symptoms.

  9. Feedforward somatosensory inhibition is normal in cervical dystonia.

    Science.gov (United States)

    Ferrè, Elisa R; Ganos, Christos; Bhatia, Kailash P; Haggard, Patrick

    2015-03-01

    Insufficient cortical inhibition is a key pathophysiological finding in dystonia. Subliminal sensory stimuli were reported to transiently inhibit somatosensory processing. Here we investigated whether such subliminal feedforward inhibition is reduced in patients with cervical dystonia. Sixteen cervical dystonia patients and 16 matched healthy controls performed a somatosensory detection task. We measured the drop in sensitivity to detect a threshold-level digital nerve shock when it was preceded by a subliminal conditioning shock, compared to when it was not. Subliminal conditioning shocks reduced sensitivity to threshold stimuli to a similar extent in both patients and controls, suggesting that somatosensory subliminal feedforward inhibition is normal in cervical dystonia. Somatosensory feedforward inhibition was normal in this group of cervical dystonia patients. Our results qualify previous concepts of a general dystonic deficit in sensorimotor inhibitory processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Adopsi Model Competency Based Training dalam Kewirausahaan

    OpenAIRE

    I Ketut Santra

    2009-01-01

    The aim of the research is improving the teaching method in entrepreneurship subject. This research adopted the competency based training (CBT) into the entrepreneurship. The major task in this research is formulated and designed the entrepreneurship competency. Entrepreneurship competency indicated by Personal, Strategic and Situational and Business competence. All of entrepreneurship competences are described into sub topic of competence. After designing and formulating the game and simulat...

  11. Spreadsheet Decision Support Model for Training Exercise Material Requirements Planning

    National Research Council Canada - National Science Library

    Tringali, Arthur

    1997-01-01

    ... associated with military training exercises. The model combines the business practice of Material Requirements Planning and the commercial spreadsheet software capabilities of Lotus 1-2-3 to calculate the requirements for food, consumable...

  12. Flood routing modelling with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    R. Peters

    2006-01-01

    Full Text Available For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HEC-RAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resolution in space requires very small calculation time steps, which are some two orders of magnitude smaller than the input data resolution. This leads to quite high computation requirements seriously restricting the application – especially when dealing with real time operations such as online flood forecasting. In order to solve this problem we tested the application of Artificial Neural Networks (ANN. First studies show the ability of adequately trained multilayer feedforward networks (MLFN to reproduce the model performance.

  13. Feedforward Tracking Control of Flat Recurrent Fuzzy Systems

    International Nuclear Information System (INIS)

    Gering, Stefan; Adamy, Jürgen

    2014-01-01

    Flatness based feedforward control has proven to be a feasible solution for the problem of tracking control, which may be applied to a broad class of nonlinear systems. If a flat output of the system is known, the control is often based on a feedforward controller generating a nominal input in combination with a linear controller stabilizing the linearized error dynamics around the trajectory. We show in this paper that the very same idea may be incorporated for tracking control of MIMO recurrent fuzzy systems. Their dynamics is given by means of linguistic differential equations but may be converted into a hybrid system representation, which then serves as the basis for controller synthesis

  14. Feedforward Tracking Control of Flat Recurrent Fuzzy Systems

    Science.gov (United States)

    Gering, Stefan; Adamy, Jürgen

    2014-12-01

    Flatness based feedforward control has proven to be a feasible solution for the problem of tracking control, which may be applied to a broad class of nonlinear systems. If a flat output of the system is known, the control is often based on a feedforward controller generating a nominal input in combination with a linear controller stabilizing the linearized error dynamics around the trajectory. We show in this paper that the very same idea may be incorporated for tracking control of MIMO recurrent fuzzy systems. Their dynamics is given by means of linguistic differential equations but may be converted into a hybrid system representation, which then serves as the basis for controller synthesis.

  15. Feed-forward motor control of ultrafast, ballistic movements.

    Science.gov (United States)

    Kagaya, K; Patek, S N

    2016-02-01

    To circumvent the limits of muscle, ultrafast movements achieve high power through the use of springs and latches. The time scale of these movements is too short for control through typical neuromuscular mechanisms, thus ultrafast movements are either invariant or controlled prior to movement. We tested whether mantis shrimp (Stomatopoda: Neogonodactylus bredini) vary their ultrafast smashing strikes and, if so, how this control is achieved prior to movement. We collected high-speed images of strike mechanics and electromyograms of the extensor and flexor muscles that control spring compression and latch release. During spring compression, lateral extensor and flexor units were co-activated. The strike initiated several milliseconds after the flexor units ceased, suggesting that flexor activity prevents spring release and determines the timing of strike initiation. We used linear mixed models and Akaike's information criterion to serially evaluate multiple hypotheses for control mechanisms. We found that variation in spring compression and strike angular velocity were statistically explained by spike activity of the extensor muscle. The results show that mantis shrimp can generate kinematically variable strikes and that their kinematics can be changed through adjustments to motor activity prior to the movement, thus supporting an upstream, central-nervous-system-based control of ultrafast movement. Based on these and other findings, we present a shishiodoshi model that illustrates alternative models of control in biological ballistic systems. The discovery of feed-forward control in mantis shrimp sets the stage for the assessment of targets, strategic variation in kinematics and the role of learning in ultrafast animals. © 2016. Published by The Company of Biologists Ltd.

  16. Training of Evaluators in the Third World: Implementation of the Action Training Model (ATM) in Kenya and Botswana.

    Science.gov (United States)

    Bhola, H. S.

    The Action Training Model (ATM) was developed for the delivery of evaluation training to development workers in Kenya and Botswana and implemented under the aegis of the German Foundation for International Development. Training of evaluators is a challenge in any context, but in the Third World environment, evaluation training offers special…

  17. Train Dwell Time Models for Rail Passenger Service

    Directory of Open Access Journals (Sweden)

    San Hor Peay

    2016-01-01

    Full Text Available In recent years, more studies had been conducted about train dwell time as it is a key parameter of rail system performance and reliability. This paper draws an overview of train dwell time models for rail passenger service from various continents, namely Asia, North America, Europe and Australia. The factors affecting train dwell time are identified and analysed across some rail network operators. The dwell time models developed by various researches are also discussed and reviewed. Finally, the contributions from the outcomes of these models are briefly addressed. In conclusion, this paper suggests that there is a need to further study the factors with strong influence upon dwell time to improve the quality of the train services.

  18. A High-Speed Train Operation Plan Inspection Simulation Model

    Directory of Open Access Journals (Sweden)

    Yang Rui

    2018-01-01

    Full Text Available We developed a train operation simulation tool to inspect a train operation plan. In applying an improved Petri Net, the train was regarded as a token, and the line and station were regarded as places, respectively, in accordance with the high-speed train operation characteristics and network function. Location change and running information transfer of the high-speed train were realized by customizing a variety of transitions. The model was built based on the concept of component combination, considering the random disturbance in the process of train running. The simulation framework can be generated quickly and the system operation can be completed according to the different test requirements and the required network data. We tested the simulation tool when used for the real-world Wuhan to Guangzhou high-speed line. The results showed that the proposed model can be developed, the simulation results basically coincide with the objective reality, and it can not only test the feasibility of the high-speed train operation plan, but also be used as a support model to develop the simulation platform with more capabilities.

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

    Science.gov (United States)

    Cuper, Taryn

    2010-01-01

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

  20. IMPROVEMENT OF MATHEMATICAL MODELS FOR ESTIMATION OF TRAIN DYNAMICS

    Directory of Open Access Journals (Sweden)

    L. V. Ursulyak

    2017-12-01

    Full Text Available Purpose. Using scientific publications the paper analyzes the mathematical models developed in Ukraine, CIS countries and abroad for theoretical studies of train dynamics and also shows the urgency of their further improvement. Methodology. Information base of the research was official full-text and abstract databases, scientific works of domestic and foreign scientists, professional periodicals, materials of scientific and practical conferences, methodological materials of ministries and departments. Analysis of publications on existing mathematical models used to solve a wide range of problems associated with the train dynamics study shows the expediency of their application. Findings. The results of these studies were used in: 1 design of new types of draft gears and air distributors; 2 development of methods for controlling the movement of conventional and connected trains; 3 creation of appropriate process flow diagrams; 4 development of energy-saving methods of train driving; 5 revision of the Construction Codes and Regulations (SNiP ΙΙ-39.76; 6 when selecting the parameters of the autonomous automatic control system, created in DNURT, for an auxiliary locomotive that is part of a connected train; 7 when creating computer simulators for the training of locomotive drivers; 8 assessment of the vehicle dynamic indices characterizing traffic safety. Scientists around the world conduct numerical experiments related to estimation of train dynamics using mathematical models that need to be constantly improved. Originality. The authors presented the main theoretical postulates that allowed them to develop the existing mathematical models for solving problems related to the train dynamics. The analysis of scientific articles published in Ukraine, CIS countries and abroad allows us to determine the most relevant areas of application of mathematical models. Practicalvalue. The practical value of the results obtained lies in the scientific validity

  1. In vivo porcine training model for cranial neurosurgery.

    Science.gov (United States)

    Regelsberger, Jan; Eicker, Sven; Siasios, Ioannis; Hänggi, Daniel; Kirsch, Matthias; Horn, Peter; Winkler, Peter; Signoretti, Stefano; Fountas, Kostas; Dufour, Henry; Barcia, Juan A; Sakowitz, Oliver; Westermaier, Thomas; Sabel, Michael; Heese, Oliver

    2015-01-01

    Supplemental education is desirable for neurosurgical training, and the use of human cadaver specimen and virtual reality models is routine. An in vivo porcine training model for cranial neurosurgery was introduced in 2005, and our recent experience with this unique model is outlined here. For the first time, porcine anatomy is illustrated with particular respect to neurosurgical procedures. The pros and cons of this model are described. The aim of the course was to set up a laboratory scenery imitating an almost realistic operating room in which anatomy of the brain and neurosurgical techniques in a mentored environment free from time constraints could be trained. Learning objectives of the course were to learn about the microsurgical techniques in cranial neurosurgery and the management of complications. Participants were asked to evaluate the quality and utility of the programme via standardized questionnaires by a grading scale from A (best) to E (worst). In total, 154 residents have been trained on the porcine model to date. None of the participants regarded his own residency programme as structured. The bleeding and complication management (97%), the realistic laboratory set-up (89%) and the working environment (94%) were favoured by the vast majority of trainees and confirmed our previous findings. After finishing the course, the participants graded that their skills in bone drilling, dissecting the brain and preserving cerebral vessels under microscopic magnification had improved to level A and B. In vivo hands-on courses, fully equipped with microsurgical instruments, offer an outstanding training opportunity in which bleeding management on a pulsating, vital brain represents a unique training approach. Our results have shown that education programmes still lack practical training facilities in which in vivo models may act as a complementary approach in surgical training.

  2. The chicken foot digital replant training model.

    Science.gov (United States)

    Athanassopoulos, Thanassi; Loh, Charles Yuen Yung

    2015-01-01

    A simple, readily available digital replantation model in the chicken foot is described. This high fidelity model will hopefully allow trainees in hand surgery to gain further experience in replant surgery prior to clinical application.

  3. Cell cycle regulation by feed-forward loops coupling transcription and phosphorylation

    DEFF Research Database (Denmark)

    Csikász-Nagy, Attila; Kapuy, Orsolya; Tóth, Attila

    2009-01-01

    of these EPs. From genome-scale data sets of budding yeast, we identify 126 EPs that are regulated by Cdk1 both through direct phosphorylation of the EP and through phosphorylation of the transcription factors that control expression of the EP, so that each of these EPs is regulated by a feed-forward loop (FFL......) from Cdk1. By mathematical modelling, we show that such FFLs can activate EPs at different phases of the cell cycle depending of the effective signs (+ or -) of the regulatory steps of the FFL. We provide several case studies of EPs that are controlled by FFLs exactly as our models predict. The signal...

  4. Robust Position Tracking for Electro-Hydraulic Drives Based on Generalized Feedforward Compensation Approach

    DEFF Research Database (Denmark)

    Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.

    2012-01-01

    This paper presents a robust tracking control concept based on accurate feedforward compensation for hydraulic valve-cylinder drives. The proposed feedforward compensator is obtained utilizing a generalized description of the valve flow that takes into account any asymmetry of valves and...... constant gain type feedforward compensator, when subjected to strong perturbations in supply pressure and coulomb friction....

  5. Recovery Act. Development of a Model Energy Conservation Training Program

    Energy Technology Data Exchange (ETDEWEB)

    none,

    2012-07-05

    The overall objective of this project was to develop an updated model Energy Conservation training program for stationary engineers. This revision to the IUOE National Training Fund’s existing Energy Conservation training curriculum is designed to enable stationary engineers to incorporate essential energy management into routine building operation and maintenance tasks. The curriculum uses a blended learning approach that includes classroom, hands-on, computer simulation and web-based training in addition to a portfolio requirement for a workplace-based learning application. The Energy Conservation training program goal is development of a workforce that can maintain new and existing commercial buildings at optimum energy performance levels. The grant start date was July 6, 2010 and the project continued through September 30, 2012, including a three month non-funded extension.

  6. A dynamic feedforward neural network based on gaussian particle swarm optimization and its application for predictive control.

    Science.gov (United States)

    Han, Min; Fan, Jianchao; Wang, Jun

    2011-09-01

    A dynamic feedforward neural network (DFNN) is proposed for predictive control, whose adaptive parameters are adjusted by using Gaussian particle swarm optimization (GPSO) in the training process. Adaptive time-delay operators are added in the DFNN to improve its generalization for poorly known nonlinear dynamic systems with long time delays. Furthermore, GPSO adopts a chaotic map with Gaussian function to balance the exploration and exploitation capabilities of particles, which improves the computational efficiency without compromising the performance of the DFNN. The stability of the particle dynamics is analyzed, based on the robust stability theory, without any restrictive assumption. A stability condition for the GPSO+DFNN model is derived, which ensures a satisfactory global search and quick convergence, without the need for gradients. The particle velocity ranges could change adaptively during the optimization process. The results of a comparative study show that the performance of the proposed algorithm can compete with selected algorithms on benchmark problems. Additional simulation results demonstrate the effectiveness and accuracy of the proposed combination algorithm in identifying and controlling nonlinear systems with long time delays.

  7. A Novel Perforator Flap Training Model Using a Chicken Leg.

    Science.gov (United States)

    Cifuentes, Ignacio J; Yañez, Ricardo A; Salisbury, Maria C; Rodriguez, José R; Varas, Julian E; Dagnino, Bruno L

    2016-04-01

    Living animal models are frequently used for perforator flap dissection training, but no ex vivo models have been described. The aim of this study is to present a novel nonliving model for perforator flap training based on a constant perforator in the chicken leg. A total of 15 chicken legs were used in this study. Anatomical dissection of the perforator was performed after its identification using ink injection, and in four of these specimens a perforator-based flap was raised. The anatomical dissection revealed a constant intramuscular perforator with a median length of 5.7 cm. Median proximal and distal vessel diameters were 0.93 and 0.4 mm, respectively. The median dissection time was 77.5 minutes. This study introduces a novel, affordable, and reproducible model for the intramuscular dissection of a perforator-based flap using an ex vivo animal model. Its consistent perforator and appropriate-sized vessels make it useful for training.

  8. Aesthetic Surgery Training during Residency in the United States: A Comparison of the Integrated, Combined, and Independent Training Models

    OpenAIRE

    Momeni, Arash; Kim, Rebecca Y.; Wan, Derrick C.; Izadpanah, Ali; Lee, Gordon K.

    2014-01-01

    Background. Three educational models for plastic surgery training exist in the United States, the integrated, combined, and independent model. The present study is a comparative analysis of aesthetic surgery training, to assess whether one model is particularly suitable to provide for high-quality training in aesthetic surgery. Methods. An 18-item online survey was developed to assess residents’ perceptions regarding the quality of training in aesthetic surgery in the US. The survey had three...

  9. MODEL ON THE JOB TRAINING PENINGKATAN KETERAMPILAN MAHASISWA

    Directory of Open Access Journals (Sweden)

    Suranto

    2012-10-01

    Full Text Available Penelitian ini bertujuan untuk mengetahui apakah model on the job training (pelatihan kerja di industri mampu meningkatkan kemampuan keterampilan mahasiswa program studi vokasi bidang manufaktur di Universitas Tujuh Belas Agustus Surabaya. Penelitian ini mengambil data pada mahasiswa di Program Studi Vokasi bidang manufaktur sejumlah 20 orang untuk menguji validitas dan reliabilitas angket dan sejumlah 30 orang mahasiswa untuk menguji pengaruh on the job training terhadap kemampuan keterampilan mahasiswa yang meliputi aspek afektif, kognitif dan psikomotorik. Pengumpulan data melalui angket, observasi, dan wawancara. Metode analisis menggunakan regresi untuk mengetahui pengaruh antara variabel on the job training terhadap variabel kemampuan keterampilan mahasiswa. Diketahui hasil persamaan regresi bahwa semakin baik model on the job training diterapkan, maka semakin baik pula peningkatan kemampuan keterampilan yang dimiliki mahasiswa. Besarnya pengaruh model on the job training terhadap keterampilan sebesar 0.701 atau 70.1%. Dihasilkan model pembelajaran on the job training yang dilakukan mampu mempengaruhi peningkatan kemampuan keterampilan calon lulusan program studi vokasi bidang manufaktur

  10. Adopsi Model Competency Based Training dalam Kewirausahaan

    Directory of Open Access Journals (Sweden)

    I Ketut Santra

    2009-01-01

    Full Text Available The aim of the research is improving the teaching method in entrepreneurship subject. This research adopted the competency based training (CBT into the entrepreneurship. The major task in this research is formulated and designed the entrepreneurship competency. Entrepreneurship competency indicated by Personal, Strategic and Situational and Business competence. All of entrepreneurship competences are described into sub topic of competence. After designing and formulating the game and simulation the research continuing to implement the competency based training in the real class. The time consumed to implementing the CBT one semester, starting on September 2006 to early February 2007. The lesson learnt from the implementation period, the CBT could improve the student competence in Personal, Situational Strategic and Business. The three of the competencies are important for the success entrepreneur. It is a sign of application of “Kurikulum Berbasis Kompetensi”. There are many evidences to describe the achievement of the CBT in entrepreneurship subject. Firstly, physically achievement, that all of the student’s business plan could became the real business. The evidences are presented by picture of the student’s real business. Secondly theoretically achievement, that the Personal, Situational Strategic and Business competence statistically have significant relation with Business Plan even Real Business quality. The effect of the Personal, Situational Strategic and Business competence to Business Plan quality is 84.4%. and, to the Real Business quality 77.2%. The statistic’s evidence suggests that the redesign of the entrepreneurship subject is the right way. The content of the entrepreneur competence (Personal, Situational and Strategic and Business competence have impact to the student to conduct and running for own business.

  11. A stochastic optimal feedforward and feedback control methodology for superagility

    Science.gov (United States)

    Halyo, Nesim; Direskeneli, Haldun; Taylor, Deborah B.

    1992-01-01

    A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and feedback control laws. This approach places conflicting demands on the control law such as fast tracking versus noise atttenuation/disturbance rejection. In the SOFFT approach, two cost functions are defined. The feedforward control law is designed to optimize one cost function, the feedback optimizes the other. By separating the design objectives and decoupling the feedforward and feedback design processes, both objectives can be achieved fully. A new measure of command tracking performance, Z-plots, is also developed. By analyzing these plots at off-nominal conditions, the sensitivity or robustness of the system in tracking commands can be predicted. Z-plots provide an important tool for designing robust control systems. The Variable-Gain SOFFT methodology was used to design a flight control system for the F/A-18 aircraft. It is shown that SOFFT can be used to expand the operating regime and provide greater performance (flying/handling qualities) throughout the extended flight regime. This work was performed under the NASA SBIR program. ICS plans to market the software developed as a new module in its commercial CACSD software package: ACET.

  12. MIMO FIR feedforward design for zero error tracking control

    NARCIS (Netherlands)

    Heertjes, M.F.; Bruijnen, D.J.H.

    2014-01-01

    This paper discusses a multi-input multi-output (MIMO) finite impulse response (FIR) feedforward design. The design is intended for systems that have (non-)minimum phase zeros in the plant description. The zeros of the plant (either minimum or non-minimum phase) are used in the shaping of the

  13. Adaptive feedforward in the LANL rf control system

    International Nuclear Information System (INIS)

    Ziomek, C.D.

    1992-01-01

    This paper describes an adaptive feedforward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF field feedback control system can be eliminated with a feedforward system. Many RF field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feedforward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feedforward system are presented

  14. Classes of feedforward neural networks and their circuit complexity

    NARCIS (Netherlands)

    Shawe-Taylor, John S.; Anthony, Martin H.G.; Kern, Walter

    1992-01-01

    This paper aims to place neural networks in the context of boolean circuit complexity. We define appropriate classes of feedforward neural networks with specified fan-in, accuracy of computation and depth and using techniques of communication complexity proceed to show that the classes fit into a

  15. Feed-Forward Neural Networks and Minimal Search Space Learning

    Czech Academy of Sciences Publication Activity Database

    Neruda, Roman

    2005-01-01

    Roč. 4, č. 12 (2005), s. 1867-1872 ISSN 1109-2750 R&D Projects: GA ČR GA201/05/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : search space * feed-forward networks * genetic algorithm s Subject RIV: BA - General Mathematics

  16. Analysis of different training models for handball goalkeepers

    Directory of Open Access Journals (Sweden)

    Alejandro Muñoz Moreno

    2012-11-01

    Full Text Available The importance of the goalkeeper for the team performance is critical, however, publications on specific preparation are few in number, with no clear lines of work. The present study aims to analyze the different methodologies used in the specific training handball goalkeeper, by setting what the different training models as well as deepen the potential applications of each.For this purpose, it was conducted an extensive literature review, categorizing each document based on the performance factor on which prioritizes: physical-technical, perceptual and tactical. The analysis of results found that there were no other models than those categorized, being more numerous publications falling under physical and technical training, followed by the perceptive and very few exist on tactical training. In light of the results seems essential to conduct a specific training program for goalkeeper, taking into account the most relevant variables for optimal performance. No single factor seems more relevant to any stage of training, it being necessary to deepen it.Keywords: specific training, perception, decision making, tactical

  17. An animal model to train Lichtenstein inguinal hernia repair

    DEFF Research Database (Denmark)

    Rosenberg, J; Presch, I; Pommergaard, H C

    2013-01-01

    , thus complicating the procedure if operation should be done in the inguinal canal. The chain of lymph nodes resembles the human spermatic cord and can be used to perform Lichtenstein's hernia repair. RESULTS: This experimental surgical model has been tested on two adult male pigs and three adult female...... pigs, and a total of 55 surgeons have been educated to perform Lichtenstein's hernia repair in these animals. CONCLUSIONS: This new experimental surgical model for training Lichtenstein's hernia repair mimics the human inguinal anatomy enough to make it suitable as a training model. The operation...

  18. The Design of Model-Based Training Programs

    Science.gov (United States)

    Polson, Peter; Sherry, Lance; Feary, Michael; Palmer, Everett; Alkin, Marty; McCrobie, Dan; Kelley, Jerry; Rosekind, Mark (Technical Monitor)

    1997-01-01

    This paper proposes a model-based training program for the skills necessary to operate advance avionics systems that incorporate advanced autopilots and fight management systems. The training model is based on a formalism, the operational procedure model, that represents the mission model, the rules, and the functions of a modem avionics system. This formalism has been defined such that it can be understood and shared by pilots, the avionics software, and design engineers. Each element of the software is defined in terms of its intent (What?), the rationale (Why?), and the resulting behavior (How?). The Advanced Computer Tutoring project at Carnegie Mellon University has developed a type of model-based, computer aided instructional technology called cognitive tutors. They summarize numerous studies showing that training times to a specified level of competence can be achieved in one third the time of conventional class room instruction. We are developing a similar model-based training program for the skills necessary to operation the avionics. The model underlying the instructional program and that simulates the effects of pilots entries and the behavior of the avionics is based on the operational procedure model. Pilots are given a series of vertical flightpath management problems. Entries that result in violations, such as failure to make a crossing restriction or violating the speed limits, result in error messages with instruction. At any time, the flightcrew can request suggestions on the appropriate set of actions. A similar and successful training program for basic skills for the FMS on the Boeing 737-300 was developed and evaluated. The results strongly support the claim that the training methodology can be adapted to the cockpit.

  19. Assessing the limitations of the Banister model in monitoring training

    Science.gov (United States)

    Hellard, Philippe; Avalos, Marta; Lacoste, Lucien; Barale, Frédéric; Chatard, Jean-Claude; Millet, Grégoire P.

    2006-01-01

    The aim of this study was to carry out a statistical analysis of the Banister model to verify how useful it is in monitoring the training programmes of elite swimmers. The accuracy, the ill-conditioning and the stability of this model were thus investigated. Training loads of nine elite swimmers, measured over one season, were related to performances with the Banister model. Firstly, to assess accuracy, the 95% bootstrap confidence interval (95% CI) of parameter estimates and modelled performances were calculated. Secondly, to study ill-conditioning, the correlation matrix of parameter estimates was computed. Finally, to analyse stability, iterative computation was performed with the same data but minus one performance, chosen randomly. Performances were significantly related to training loads in all subjects (R2= 0.79 ± 0.13, P < 0.05) and the estimation procedure seemed to be stable. Nevertheless, the 95% CI of the most useful parameters for monitoring training were wide τa =38 (17, 59), τf =19 (6, 32), tn =19 (7, 35), tg =43 (25, 61). Furthermore, some parameters were highly correlated making their interpretation worthless. The study suggested possible ways to deal with these problems and reviewed alternative methods to model the training-performance relationships. PMID:16608765

  20. Tax Policy in a Model of Search with Training

    NARCIS (Netherlands)

    Boone, J.; de Mooij, R.A.

    2000-01-01

    This paper develops a model of search on the labour market with training. The model reveals how the tax system can restore the social optimum if the Hosios condition is not satisfied in the private equilibrium. Furthermore, the effects are explored of a second-best reform from average to marginal

  1. Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays

    OpenAIRE

    Mejias, Jorge F.; Payeur, Alexandre; Selin, Erik; Maler, Leonard; Longtin, André

    2014-01-01

    The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry—also known as “open-loop feedback”—, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different...

  2. On path generation and feedforward control for a class of surface sailing vessels

    DEFF Research Database (Denmark)

    Xiao, Lin; Jouffroy, Jerome

    2010-01-01

    Sailing vessels with wind as their main means of propulsion possess a unique property that the paths they take depend on the wind direction, which, in the literature, has attracted less attention than normal vehicles propelled by propellers or thrusters. This paper considers the problem of motion...... planning and controllability for sailing vehicles representing the no-sailing zone effect in sailing. Following our previous work, we present an extended algorithm for automatic path generation with a prescribed initial heading for a simple model of sailing vehicles, together with a feedforward controller...

  3. OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMS

    Directory of Open Access Journals (Sweden)

    V.S.S. Yadavalli

    2012-01-01

    Full Text Available In this paper, the optimal planning of manpower training programmes in a manpower system with two grades is discussed. The planning of manpower training within a given organization involves a trade-off between training costs and expected return. These planning problems are examined through models that reflect the random nature of manpower movement in two grades. To be specific, the system consists of two grades, grade 1 and grade 2. Any number of persons in grade 2 can be sent for training and after the completion of training, they will stay in grade 2 and will be given promotion as and when vacancies arise in grade 1. Vacancies arise in grade 1 only by wastage. A person in grade 1 can leave the system with probability p. Vacancies are filled with persons in grade 2 who have completed the training. It is assumed that there is a perfect passing rate and that the sizes of both grades are fixed. Assuming that the planning horizon is finite and is T, the underlying stochastic process is identified as a finite state Markov chain and using dynamic programming, a policy is evolved to determine how many persons should be sent for training at any time k so as to minimize the total expected cost for the entire planning period T.

  4. Control of CA3 output by feedforward inhibition despite developmental changes in the excitation-inhibition balance.

    Science.gov (United States)

    Torborg, Christine L; Nakashiba, Toshiaki; Tonegawa, Susumu; McBain, Chris J

    2010-11-17

    In somatosensory cortex, the relative balance of excitation and inhibition determines how effectively feedforward inhibition enforces the temporal fidelity of action potentials. Within the CA3 region of the hippocampus, glutamatergic mossy fiber (MF) synapses onto CA3 pyramidal cells (PCs) provide strong monosynaptic excitation that exhibit prominent facilitation during repetitive activity. We demonstrate in the juvenile CA3 that MF-driven polysynaptic IPSCs facilitate to maintain a fixed EPSC-IPSC ratio during short-term plasticity. In contrast, in young adult mice this MF-driven polysynaptic inhibitory input can facilitate or depress in response to short trains of activity. Transgenic mice lacking the feedback inhibitory loop continue to exhibit both facilitating and depressing polysynaptic IPSCs, indicating that this robust inhibition is not caused by the secondary engagement of feedback inhibition. Surprisingly, eliminating MF-driven inhibition onto CA3 pyramidal cells by blockade of GABA(A) receptors did not lead to a loss of temporal precision of the first action potential observed after a stimulus but triggered in many cases a long excitatory plateau potential capable of triggering repetitive action potential firing. These observations indicate that, unlike other regions of the brain, the temporal precision of single MF-driven action potentials is dictated primarily by the kinetics of MF EPSPs, not feedforward inhibition. Instead, feedforward inhibition provides a robust regulation of CA3 PC excitability across development to prevent excessive depolarization by the monosynaptic EPSP and multiple action potential firings.

  5. Direct adaptive control using feedforward neural networks

    OpenAIRE

    Cajueiro, Daniel Oliveira; Hemerly, Elder Moreira

    2003-01-01

    ABSTRACT: This paper proposes a new scheme for direct neural adaptive control that works efficiently employing only one neural network, used for simultaneously identifying and controlling the plant. The idea behind this structure of adaptive control is to compensate the control input obtained by a conventional feedback controller. The neural network training process is carried out by using two different techniques: backpropagation and extended Kalman filter algorithm. Additionally, the conver...

  6. Landscape self organisation: Modelling Sediment trains

    Science.gov (United States)

    Schoorl, J. M.; Temme, A. J. A. M.; Veldkamp, A.

    2012-04-01

    Rivers tend to develop towards an equilibrium length profile, independently of exogenous factors. In general, although still under debate, this so-called self-organisation is assumed to be caused by simple feedbacks between sedimentation and erosion. Erosion correlates positively with gradient and discharge and sedimentation negatively. With the LAPSUS model, which was run for the catchment of the Sabinal, a small river in the South of Spain, this interplay of erosion and sedimentation results in sediment pulses (sequences of incision and sedimentation through time). These pulses are visualised in a short movie ( see http://www.youtube.com/watch?v=V5LDUMvYZxU). In this case the LAPSUS model run did not take climate, base level nor tectonics into account. Therefore, these pulses can be considered independent of them. Furthermore, different scenarios show that the existence of the pulses is independent of precipitation, erodibility and sedimentation rate, although they control the number and shape of the pulses. A fieldwork check showed the plausibility of the occurrence of these sediment pulses. We conclude that the pulses as modelled with LAPSUS are indeed the consequence of the feedbacks between erosion and sedimentation and are not depending on exogenous factors. Keywords: Landscape self-organisation, Erosion, Deposition, LAPSUS, Modelling

  7. Stochastic models for spike trains of single neurons

    CERN Document Server

    Sampath, G

    1977-01-01

    1 Some basic neurophysiology 4 The neuron 1. 1 4 1. 1. 1 The axon 7 1. 1. 2 The synapse 9 12 1. 1. 3 The soma 1. 1. 4 The dendrites 13 13 1. 2 Types of neurons 2 Signals in the nervous system 14 2. 1 Action potentials as point events - point processes in the nervous system 15 18 2. 2 Spontaneous activi~ in neurons 3 Stochastic modelling of single neuron spike trains 19 3. 1 Characteristics of a neuron spike train 19 3. 2 The mathematical neuron 23 4 Superposition models 26 4. 1 superposition of renewal processes 26 4. 2 Superposition of stationary point processe- limiting behaviour 34 4. 2. 1 Palm functions 35 4. 2. 2 Asymptotic behaviour of n stationary point processes superposed 36 4. 3 Superposition models of neuron spike trains 37 4. 3. 1 Model 4. 1 39 4. 3. 2 Model 4. 2 - A superposition model with 40 two input channels 40 4. 3. 3 Model 4. 3 4. 4 Discussion 41 43 5 Deletion models 5. 1 Deletion models with 1nd~endent interaction of excitatory and inhibitory sequences 44 VI 5. 1. 1 Model 5. 1 The basic de...

  8. Gelatin model for training ultrasound-guided puncture

    Directory of Open Access Journals (Sweden)

    Alexandre Campos Moraes Amato

    2015-09-01

    Full Text Available BACKGROUND: It is indispensable that members of the medical profession receive the technical training needed to enable them to rapidly obtain effective vascular access. Training procedures should be used judiciously to familiarize students with the technique. However, existing models are expensive or ineffective, and models need to be developed that are similar to what will be encountered in real patients.OBJECTIVES: To demonstrate creation and application of a gelatin model for training ultrasound-guided puncture.METHOS: The model was made using a mixture of colorless gelatin and water in a transparent plastic receptacle with two pairs of orifices of different diameters, through which two plastic tubes were inserted, to simulate blood vessels.RESULTS: The model was a close approximation to the real medical procedure in several aspects, since gelatin has a similar consistency to human tissues, providing a more faithful reproduction of the tactile sensation at the moment when the needle reaches the interior of a vessel and its contents are aspirated.CONCLUSIONS: The method proposed here can be used to easily construct a low-cost model using everyday materials that is suitable for large-scale training of ultrasound-guided puncture.

  9. Modeling of power train by applying the virtual prototype concept; Kaso genkei ni yoru power train no model ka

    Energy Technology Data Exchange (ETDEWEB)

    Hiramatsu, S; Harada, Y; Arakawa, H; Komori, S [Mazda Motor Corp., Hiroshima (Japan); Sumida, S [U-Shin Corp., Tokyo (Japan)

    1997-10-01

    This paper describes the simulation of power train that includes the model developed by applying the virtual prototype concept. By this concept, subsystem models which consist of functional model and mechanism models are integrated into a total system model. This peculiarity in architecture of model, which is called the hierarchical structure, enables us to model a system of large scale with many units, systems and parts easily. Two kinds of computer simulations are performed. One is engine revolution fluctuation by accessory load input, and the other is changing gears by automatic transmission. They are verified to have sufficient accuracy. 2 refs., 12 figs.

  10. Microsurgical training on an in vitro chicken wing infusion model.

    Science.gov (United States)

    Olabe, Jon; Olabe, Javier

    2009-12-01

    Microneurovascular anastomosis and aneurysm clipping require extensive training before mastering the technique and are a surgical challenge. We developed the "infused chicken wing method" to provide a simple but realistic training method minimizing animal use and need for special facilities for animal care and anesthesia. Fresh chicken wings were used in this model. The main brachial artery was cannulated, and water was infused at 140 mm Hg followed by anatomical neurovascular dissection. Multiple microsurgical training exercises were performed under microscope vision including terminoterminal, lateroterminal, laterolateral vascular anastomosis, and nerve anastomosis. Different complexity aneurysms were created using venous patches, clipping, rupture, and vascular reconstruction techniques were performed. This novel training model is inexpensive, easily obtainable, and no live animals are required. The diameter and characteristics of arteries and veins used are similar to those of the human brain. Great microsurgical technique progress may be obtained. The infused chicken wing artery model presents a realistic microvascular training method. It is inexpensive and easy to set up. Such simplicity provides the adequate environment for developing microsurgical technique. Copyright 2009 Elsevier Inc. All rights reserved.

  11. Adaptive scenarios: a training model for today's public health workforce.

    Science.gov (United States)

    Uden-Holman, Tanya; Bedet, Jennifer; Walkner, Laurie; Abd-Hamid, Nor Hashidah

    2014-01-01

    With the current economic climate, money for training is scarce. In addition, time is a major barrier to participation in trainings. To meet the public health workforce's rising demand for training, while struggling with less time and fewer resources, the Upper Midwest Preparedness and Emergency Response Learning Center has developed a model of online training that provides the public health workforce with individually customized, needs-based training experiences. Adaptive scenarios are rooted in case-based reasoning, a learning approach that focuses on the specific knowledge needed to solve a problem. Proponents of case-based reasoning argue that learners benefit from being able to remember previous similar situations and reusing information and knowledge from that situation. Adaptive scenarios based on true-to-life job performance provide an opportunity to assess skills by presenting the user with choices to make in a problem-solving context. A team approach was used to develop the adaptive scenarios. Storylines were developed that incorporated situations aligning with the knowledge, skills, and attitudes outlined in the Public Health Preparedness and Response Core Competency Model. This article examines 2 adaptive scenarios: "Ready or Not? A Family Preparedness Scenario" and "Responding to a Crisis: Managing Emotions and Stress Scenario." The scenarios are available on Upper Midwest Preparedness and Emergency Response Learning Center's Learning Management System, the Training Source (http://training-source.org). Evaluation data indicate that users' experiences have been positive. Integrating the assessment and training elements of the scenarios so that the training experience is uniquely adaptive to each user is one of the most efficient ways to provide training. The opportunity to provide individualized, needs-based training without having to administer separate assessments has the potential to save time and resources. These adaptive scenarios continue to be

  12. Cumulative Training Dose's Effects on Interrelationships Between Common Training-Load Models During Basketball Activity.

    Science.gov (United States)

    Scanlan, Aaron T; Fox, Jordan L; Borges, Nattai R; Dascombe, Ben J; Dalbo, Vincent J

    2017-02-01

    The influence of various factors on training-load (TL) responses in basketball has received limited attention. This study aimed to examine the temporal changes and influence of cumulative training dose on TL responses and interrelationships during basketball activity. Ten state-level Australian male junior basketball players completed 4 × 10-min standardized bouts of simulated basketball activity using a circuit-based protocol. Internal TL was quantified using the session rating of perceived exertion (sRPE), summated heart-rate zones (SHRZ), Banister training impulse (TRIMP), and Lucia TRIMP models. External TL was assessed via measurement of mean sprint and circuit speeds. Temporal TL comparisons were performed between 10-min bouts, while Pearson correlation analyses were conducted across cumulative training doses (0-10, 0-20, 0-30, and 0-40 min). sRPE TL increased (P basketball activity. sRPE TL was only significantly related to Lucia TRIMP (r = .66-.69; P basketball training doses lasting beyond 20 min. Thus, the interchangeability of commonly used internal and external TL approaches appears dose-dependent during basketball activity, with various psychophysiological mediators likely underpinning temporal changes.

  13. A Robust Multivariable Feedforward/Feedback Controller Design for Integrated Power Control of Boiling Water Reactor Power Plants

    International Nuclear Information System (INIS)

    Shyu, S.-S.; Edwards, Robert M.

    2002-01-01

    In this paper, a methodology for synthesizing a robust multivariable feedforward/feedback control (FF/FBC) strategy is proposed for an integrated control of turbine power, throttle pressure, and reactor water level in a nuclear power plant. In the proposed method, the FBC is synthesized by the robust control approach. The feedforward control, which is generated via nonlinear programming, is added to the robust FBC system to further improve the control performance. The plant uncertainties, including unmodeled dynamics, linearization, and model reduction, are characterized and estimated. The comparisons of simulation responses based on a nonlinear reactor model demonstrate the achievement of the proposed controller with specified performance and endurance under uncertainty. It is also important to note that all input variables are manipulated in an orchestrated manner in response to a single output's setpoint change

  14. Training for laparoscopic Nissen fundoplication with a newly designed model: a replacement for animal tissue models?

    Science.gov (United States)

    Christie, Lorna; Goossens, Richard; Jakimowicz, Jack J.

    2010-01-01

    Background To bridge the early learning curve for laparoscopic Nissen fundoplication from the clinical setting to a safe environment, training models can be used. This study aimed to develop a reusable, low-cost model to be used for training in laparoscopic Nissen fundoplication procedure as an alternative to the use of animal tissue models. Methods From artificial organs and tissue, an anatomic model of the human upper abdomen was developed for training in performing laparoscopic Nissen fundoplication. The 20 participants and tutors in the European Association for Endoscopic Surgery (EAES) upper gastrointestinal surgery course completed four complementary tasks of laparoscopic Nissen fundoplication with the artificial model, then compared the realism, haptic feedback, and training properties of the model with those of animal tissue models. Results The main difference between the two training models was seen in the properties of the stomach. The wrapping of the stomach in the artificial model was rated significantly lower than that in the animal tissue model (mean, 3.6 vs. 4.2; p = 0.010). The main criticism of the stomach of the artificial model was that it was too rigid for making a proper wrap. The suturing of the stomach wall, however, was regarded as fairly realistic (mean, 3.6). The crura on the artificial model were rated better (mean, 4.3) than those on the animal tissue (mean, 4.0), although the difference was not significant. The participants regarded the model as a good to excellent (mean, 4.3) training tool. Conclusion The newly developed model is regarded as a good tool for training in laparoscopic Nissen fundoplication procedure. It is cheaper, more durable, and more readily available for training and can therefore be used in every training center. The stomach of this model, however, still needs improvement because it is too rigid for making the wrap. PMID:20526629

  15. Single-Iteration Learning Algorithm for Feed-Forward Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Barhen, J.; Cogswell, R.; Protopopescu, V.

    1999-07-31

    A new methodology for neural learning is presented, whereby only a single iteration is required to train a feed-forward network with near-optimal results. To this aim, a virtual input layer is added to the multi-layer architecture. The virtual input layer is connected to the nominal input layer by a specird nonlinear transfer function, and to the fwst hidden layer by regular (linear) synapses. A sequence of alternating direction singular vrdue decompositions is then used to determine precisely the inter-layer synaptic weights. This algorithm exploits the known separability of the linear (inter-layer propagation) and nonlinear (neuron activation) aspects of information &ansfer within a neural network.

  16. Vocational Training for Prison Inmates: A Treatment Model.

    Science.gov (United States)

    Uche, Greg N.

    1995-01-01

    Components of a treatment model are diagnosis of offenders' work history and training needs, in relation to labor market requirements; provision of appropriate job and entrepreneurial skills; and after care services. Focus is on vocational adjustment to ensure successful rehabilitation. (SK)

  17. Cognitive Modeling of Mindfulness Therapy by Autogenic Training

    NARCIS (Netherlands)

    Mohammadi Ziabari, S.S.; Treur, J.

    2018-01-01

    In this paper the effect of a mindfulness therapy based on a Network-Oriented Modeling approach is addressed. The considered therapy is Autogenic Training, that can be used when under stress; it has as two main goals to achieve feeling heavy and warm body parts (limbs). Mantra’s have been used in

  18. Design Of Combined Stochastic Feedforward/Feedback Control

    Science.gov (United States)

    Halyo, Nesim

    1989-01-01

    Methodology accommodates variety of control structures and design techniques. In methodology for combined stochastic feedforward/feedback control, main objectives of feedforward and feedback control laws seen clearly. Inclusion of error-integral feedback, dynamic compensation, rate-command control structure, and like integral element of methodology. Another advantage of methodology flexibility to develop variety of techniques for design of feedback control with arbitrary structures to obtain feedback controller: includes stochastic output feedback, multiconfiguration control, decentralized control, or frequency and classical control methods. Control modes of system include capture and tracking of localizer and glideslope, crab, decrab, and flare. By use of recommended incremental implementation, control laws simulated on digital computer and connected with nonlinear digital simulation of aircraft and its systems.

  19. Efficient Feedforward Linearization Technique Using Genetic Algorithms for OFDM Systems

    Directory of Open Access Journals (Sweden)

    García Paloma

    2010-01-01

    Full Text Available Feedforward is a linearization method that simultaneously offers wide bandwidth and good intermodulation distortion suppression; so it is a good choice for Orthogonal Frequency Division Multiplexing (OFDM systems. Feedforward structure consists of two loops, being necessary an accurate adjustment between them along the time, and when temperature, environmental, or operating changes are produced. Amplitude and phase imbalances of the circuit elements in both loops produce mismatched effects that lead to degrade its performance. A method is proposed to compensate these mismatches, introducing two complex coefficients calculated by means of a genetic algorithm. A full study is carried out to choose the optimal parameters of the genetic algorithm applied to wideband systems based on OFDM technologies, which are very sensitive to nonlinear distortions. The method functionality has been verified by means of simulation.

  20. A novel feedforward compensation canceling input filter-regulator interaction

    Science.gov (United States)

    Kelkar, S. S.; Lee, F. C.

    1983-01-01

    The interaction between the input and the control loop of switching regulators often results in deterimental effects, such as loop instability, degradation of transient response, and audiosusceptibility, etc. The concept of pole-zero cancelation is employed to mitigate some of these detrimental effects and is implemented using a novel feedforward loop, in addition to existing feedback loops of a buck regulator. Experimental results are presented which show excellent correlation with theory.

  1. Designing Robustness to Temperature in a Feedforward Loop Circuit

    OpenAIRE

    Sen, Shaunak; Kim, Jongmin; Murray, Richard M.

    2013-01-01

    Incoherent feedforward loops represent important biomolecular circuit elements capable of a rich set of dynamic behavior including adaptation and pulsed responses. Temperature can modulate some of these properties through its effect on the underlying reaction rate parameters. It is generally unclear how to design such a circuit where the properties are robust to variations in temperature. Here, we address this issue using a combination of tools from control and dynamical systems theory as wel...

  2. An Introduction to Feedforward Control of Electric Drives

    Directory of Open Access Journals (Sweden)

    Michal Malek

    2010-01-01

    Full Text Available The field of electric drives provides a broad spectrum of applications with different power demands, utilized motor types or different environment requirements. Lot of applications are characterized by very high demands on accuracy and dynamic properties and have attribute of servo applications. This means that they are fully subordinate to wishes of the master. This rigorous condition is fulfill (with tolerated errors mainly thanks to the feedforward utilization.

  3. Neural network training by Kalman filtering in process system monitoring

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.

    1996-03-01

    Kalman filtering approach for neural network training is described. Its extended form is used as an adaptive filter in a nonlinear environment of the form a feedforward neural network. Kalman filtering approach generally provides fast training as well as avoiding excessive learning which results in enhanced generalization capability. The network is used in a process monitoring application where the inputs are measurement signals. Since the measurement errors are also modelled in Kalman filter the approach yields accurate training with the implication of accurate neural network model representing the input and output relationships in the application. As the process of concern is a dynamic system, the input source of information to neural network is time dependent so that the training algorithm presents an adaptive form for real-time operation for the monitoring task. (orig.)

  4. Feed-Forward Control of Kite Power Systems

    International Nuclear Information System (INIS)

    Fechner, Uwe; Schmehl, Roland

    2014-01-01

    Kite power technology is a novel solution to harvest wind energy from altitudes that can not be reached by conventional wind turbines. The use of a lightweight but strong tether in place of an expensive tower provides an additional cost advantage, next to the higher capacity factor. This paper describes a method to estimate the wind velocity at the kite using measurement data at the kite and at the ground. Focussing on a kite power system, which is converting the traction power of a kite in a pumping mode of operation, a reel-out speed predictor is presented for use in feed-forward control of the tether reel-out speed of the winch. The results show, that the developed feedforward controller improves the force control accuracy by a factor of two compared to the previously used feedback controller. This allows to use a higher set force during the reel-out phase which in turn increases the average power output by more than 4%. Due to its straightforward implementation and low computational requirements feedforward control is considered a promising technique for the reliable and efficient operation of traction-based kite power systems

  5. A technique for improved stability of adaptive feedforward controllers without detailed uncertainty measurements

    International Nuclear Information System (INIS)

    Berkhoff, A P

    2012-01-01

    Model errors in adaptive controllers for the reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. Previous research on active structures with small damping has shown that the addition of a low-authority controller which increases damping in the system may lead to improved performance of an adaptive, high-authority controller. Other researchers have suggested the use of frequency dependent regularization based on measured uncertainties. In this paper an alternative method is presented that avoids the disadvantages of these methods, namely the additional complex hardware and the need to obtain detailed information on the uncertainties. An analysis is made of an adaptive feedforward controller in which a difference exists between the secondary path and the model as used in the controller. The real parts of the eigenvalues that determine the stability of the system are expressed in terms of the amount of uncertainty and the singular values of the secondary path. Modifications of the feedforward control scheme are suggested that aim to improve performance without requiring detailed uncertainty measurements. (paper)

  6. Communication Skills Training in Pediatric Oncology: Moving Beyond Role Modeling

    Science.gov (United States)

    Feraco, Angela M.; Brand, Sarah R.; Mack, Jennifer W.; Kesselheim, Jennifer C.; Block, Susan D.; Wolfe, Joanne

    2018-01-01

    Communication is central to pediatric oncology care. Pediatric oncologists disclose life-threatening diagnoses, explain complicated treatment options, and endeavor to give honest prognoses, to maintain hope, to describe treatment complications, and to support families in difficult circumstances ranging from loss of function and fertility to treatment-related or disease-related death. However, parents, patients, and providers report substantial communication deficits. Poor communication outcomes may stem, in part, from insufficient communication skills training, overreliance on role modeling, and failure to utilize best practices. This review summarizes evidence for existing methods to enhance communication skills and calls for revitalizing communication skills training within pediatric oncology. PMID:26822066

  7. Model of knowledge management in mobile systems used for training

    Directory of Open Access Journals (Sweden)

    Chadwick CARRETO ARELLANO

    2014-11-01

    Full Text Available This work shows the development of a Knowledge Management Model (MAC applied to the training process in mobile devices for ease of use and access of different types of users to relevant information (anywhere and anytime. The MAC permit to manage knowledge, so that helps in the process of collection, classification and search of information according to a profile and academic needs as well as services related to the transformation of data and information for knowledge generation. The MAC aims to provide users, tools for skills development and allow the development of the training process with the use of limited capacity device with Internet connection.

  8. Communication Skills Training in Pediatric Oncology: Moving Beyond Role Modeling.

    Science.gov (United States)

    Feraco, Angela M; Brand, Sarah R; Mack, Jennifer W; Kesselheim, Jennifer C; Block, Susan D; Wolfe, Joanne

    2016-06-01

    Communication is central to pediatric oncology care. Pediatric oncologists disclose life-threatening diagnoses, explain complicated treatment options, and endeavor to give honest prognoses, to maintain hope, to describe treatment complications, and to support families in difficult circumstances ranging from loss of function and fertility to treatment-related or disease-related death. However, parents, patients, and providers report substantial communication deficits. Poor communication outcomes may stem, in part, from insufficient communication skills training, overreliance on role modeling, and failure to utilize best practices. This review summarizes evidence for existing methods to enhance communication skills and calls for revitalizing communication skills training within pediatric oncology. © 2016 Wiley Periodicals, Inc.

  9. Modelling electric trains energy consumption using Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Martinez Fernandez, P.; Garcia Roman, C.; Insa Franco, R.

    2016-07-01

    Nowadays there is an evident concern regarding the efficiency and sustainability of the transport sector due to both the threat of climate change and the current financial crisis. This concern explains the growth of railways over the last years as they present an inherent efficiency compared to other transport means. However, in order to further expand their role, it is necessary to optimise their energy consumption so as to increase their competitiveness. Improving railways energy efficiency requires both reliable data and modelling tools that will allow the study of different variables and alternatives. With this need in mind, this paper presents the development of consumption models based on neural networks that calculate the energy consumption of electric trains. These networks have been trained based on an extensive set of consumption data measured in line 1 of the Valencia Metro Network. Once trained, the neural networks provide a reliable estimation of the vehicles consumption along a specific route when fed with input data such as train speed, acceleration or track longitudinal slope. These networks represent a useful modelling tool that may allow a deeper study of railway lines in terms of energy expenditure with the objective of reducing the costs and environmental impact associated to railways. (Author)

  10. A new training model for robot-assisted urethrovesical anastomosis and posterior muscle-fascial reconstruction: the Verona training technique.

    Science.gov (United States)

    Cacciamani, G; De Marco, V; Siracusano, S; De Marchi, D; Bizzotto, L; Cerruto, M A; Motton, G; Porcaro, A B; Artibani, W

    2017-06-01

    A training model is usually needed to teach robotic surgical technique successfully. In this way, an ideal training model should mimic as much as possible the "in vivo" procedure and allow several consecutive surgical simulations. The goal of this study was to create a "wet lab" model suitable for RARP training programs, providing the simulation of the posterior fascial reconstruction. The second aim was to compare the original "Venezuelan" chicken model described by Sotelo to our training model. Our training model consists of performing an anastomosis, reproducing the surgical procedure in "vivo" as in RARP, between proventriculus and the proximal portion of the esophagus. A posterior fascial reconstruction simulating Rocco's stitch is performed between the tissues located under the posterior surface of the esophagus and the tissue represented by the serosa of the proventriculus. From 2014 to 2015, during 6 different full-immersion training courses, thirty-four surgeons performed the urethrovesical anastomosis using our model and the Sotelo's one. After the training period, each surgeon was asked to fill out a non-validated questionnaire to perform an evaluation of the differences between the two training models. Our model was judged the best model, in terms of similarity with urethral tissue and similarity with the anatomic unit urethra-pelvic wall. Our training model as reported by all trainees is easily reproducible and anatomically comparable with the urethrovesical anastomosis as performed during radical prostatectomy in humans. It is suitable for performing posterior fascial reconstruction reported by Rocco. In this context, our surgical training model could be routinely proposed in all robotic training courses to develop specific expertise in urethrovesical anastomosis with the reproducibility of the Rocco stitch.

  11. AgMIP Training in Multiple Crop Models and Tools

    Science.gov (United States)

    Boote, Kenneth J.; Porter, Cheryl H.; Hargreaves, John; Hoogenboom, Gerrit; Thornburn, Peter; Mutter, Carolyn

    2015-01-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

  12. Limitations of Feedback, Feedforward and IMC Controller for a First Order Non-Linear Process with Dead Time

    Directory of Open Access Journals (Sweden)

    Maruthai Suresh

    2010-10-01

    Full Text Available A nonlinear process, the heat exchanger whose parameters vary with respect to the process variable, is considered. The time constant and gain of the chosen process vary as a function of temperature. The limitations of the conventional feedback controller tuned using Ziegler-Nichols settings for the chosen process are brought out. The servo and regulatory responses through simulation and experimentation for various magnitudes of set-point changes and load changes at various operating points with the controller tuned only at a chosen nominal operating point are obtained and analyzed. Regulatory responses for output load changes are studied. The efficiency of feedforward controller and the effects of modeling error have been brought out. An IMC based system is presented to understand clearly how variations of system parameters affect the performance of the controller. The present work illustrates the effectiveness of Feedforward and IMC controller.

  13. Feedforward Nonlinear Control Using Neural Gas Network

    OpenAIRE

    Machón-González, Iván; López-García, Hilario

    2017-01-01

    Nonlinear systems control is a main issue in control theory. Many developed applications suffer from a mathematical foundation not as general as the theory of linear systems. This paper proposes a control strategy of nonlinear systems with unknown dynamics by means of a set of local linear models obtained by a supervised neural gas network. The proposed approach takes advantage of the neural gas feature by which the algorithm yields a very robust clustering procedure. The direct model of the ...

  14. The French model of psychoanalytic training: Ethical conflicts.

    Science.gov (United States)

    François-Poncet, Claire-Marine

    2009-12-01

    Research on psychoanalytical education within the IPA may be clarified by reflecting on the ethic behind each of the three main models (Eitingonian, French and Uruguayan). In fact, the ethic underpinning psychoanalytical education, whatever the model, is confronted by irreducible conflicts between transmitting psychoanalysis by means of analytical experience or by means of academic teaching. Transmission by experience is essentially based on the ethic of psychoanalytic practice, which is difficult to regulate through institutional standards, whereas the academic aspect can be evaluated by objective and public criteria. The importance of both aspects and their relative weight in the training process depend on the conception of psychoanalysis underlying each model. This paper will look primarily at the French training model, the essentially analytical aspects of which favour the transmission of the very ethical foundations of psychoanalytic practice itself: the application of the method both as a working tool and as a tool of evaluation. It presupposes expanding the observation and analysis of transference beyond the framework of treatment to that of supervision. From this analysis, the paper will attempt to demonstrate how the French model proposes dealing with the inevitable conflicts between transmission by means of analysis and training by means of apprenticeship.

  15. Feedforward compensation control of rotor imbalance for high-speed magnetically suspended centrifugal compressors using a novel adaptive notch filter

    Science.gov (United States)

    Zheng, Shiqiang; Feng, Rui

    2016-03-01

    This paper introduces a feedforward control strategy combined with a novel adaptive notch filter to solve the problem of rotor imbalance in high-speed Magnetically Suspended Centrifugal Compressors (MSCCs). Unbalance vibration force of rotor in MSCC is mainly composed of current stiffness force and displacement stiffness force. In this paper, the mathematical model of the unbalance vibration with the proportional-integral-derivative (PID) control laws is presented. In order to reduce the unbalance vibration, a novel adaptive notch filter is proposed to identify the synchronous frequency displacement of the rotor as a compensation signal to eliminate the current stiffness force. In addition, a feedforward channel from position component to control output is introduced to compensate displacement stiffness force to achieve a better performance. A simplified inverse model of power amplifier is included in the feedforward channel to reject the degrade performance caused by its low-pass characteristic. Simulation and experimental results on a MSCC demonstrate a significant effect on the synchronous vibration suppression of the magnetically suspended rotor at a high speed.

  16. LIDAR Wind Speed Measurement Analysis and Feed-Forward Blade Pitch Control for Load Mitigation in Wind Turbines: January 2010--January 2011

    Energy Technology Data Exchange (ETDEWEB)

    Dunne, F.; Simley, E.; Pao, L.Y.

    2011-10-01

    This report examines the accuracy of measurements that rely on Doppler LIDAR systems to determine their applicability to wind turbine feed-forward control systems and discusses feed-forward control system designs that use preview wind measurements. Light Detection and Ranging (LIDAR) systems are able to measure the speed of incoming wind before it interacts with a wind turbine rotor. These preview wind measurements can be used in feed-forward control systems designed to reduce turbine loads. However, the degree to which such preview-based control techniques can reduce loads by reacting to turbulence depends on how accurately the incoming wind field can be measured. The first half of this report examines the accuracy of different measurement scenarios that rely on coherent continuous-wave or pulsed Doppler LIDAR systems to determine their applicability to feed-forward control. In particular, the impacts of measurement range and angular offset from the wind direction are studied for various wind conditions. A realistic case involving a scanning LIDAR unit mounted in the spinner of a wind turbine is studied in depth with emphasis on choices for scan radius and preview distance. The effects of turbulence parameters on measurement accuracy are studied as well. Continuous-wave and pulsed LIDAR models based on typical commercially available units were used in the studies present in this report. The second half of this report discusses feed-forward control system designs that use preview wind measurements. Combined feedback/feed-forward blade pitch control is compared to industry standard feedback control when simulated in realistic turbulent above-rated winds. The feed-forward controllers are designed to reduce fatigue loads, increasing turbine lifetime and therefore reducing the cost of energy. Three feed-forward designs are studied: non-causal series expansion, Preview Control, and optimized FIR filter. The input to the feed-forward controller is a measurement of

  17. System Dynamics and Feedforward Control for Tether-Net Space Robot System

    Directory of Open Access Journals (Sweden)

    Guang Zhai

    2009-06-01

    Full Text Available A new concept using flexible tether-net system to capture space debris is presented in this paper. With a mass point assumption the tether-net system dynamic model is established in orbital frame by applying Lagrange Equations. In order to investigate the net in-plane trajectories during after cast, the non-control R-bar and V-bar captures are simulated with ignoring the out-of-plane libration, the effect of in-plane libration on the trajectories of the capture net is demonstrated by simulation results. With an effort to damp the in-plane libration, the control scheme based on tether tension is investigated firstly, after that an integrated control scheme is proposed by introduced the thrusters into the system, the nonlinear close-loop dynamics is linearised by feedforward strategy, the simulation results show that feedforward controllor is effective for in-plane libration damping and enable the capture net to track an expected trajectory.

  18. Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses.

    Science.gov (United States)

    Lujan, J Luis; Crago, Patrick E

    2009-01-01

    This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-DOF, motor system neural prostheses. The design process is based on experimental measurement of the forward input/output properties of the neuromechanical system and numerical optimization of stimulation patterns to meet muscle coactivation criteria, thus resolving the muscle redundancy (i.e., overcontrol) and the coupled DOF problems inherent in neuromechanical systems. We designed feedforward controllers to control the isometric forces at the tip of the thumb in two directions during stimulation of three thumb muscles as a model system. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. Good control of isometric force in both DOFs was observed, with rms errors less than 10% of the force range in seven experiments and statistically significant correlations between the actual and target forces in all ten experiments. Systematic bias and slope errors were observed in a few experiments, likely due to the neuromuscular fatigue. Overall, the tests demonstrated the ability of a general design approach to satisfy both control and coactivation criteria in multiple-muscle, multiple-axis neuromechanical systems, which is applicable to a wide range of neuromechanical systems and stimulation electrodes.

  19. Perceptual decision-making difficulty modulates feedforward effective connectivity to the dorsolateral prefrontal cortex

    Directory of Open Access Journals (Sweden)

    Bidhan eLamichhane

    2015-09-01

    Full Text Available Diverse cortical structures are known to coordinate activity as a network in relaying and processing of visual information to discriminate visual objects. However, how this discrimination is achieved is still largely unknown. To contribute to answering this question, we used face-house categorization tasks with three levels of noise in face and house images in functional magnetic resonance imaging (fMRI experiments involving thirty-three participants. The behavioral performance error and response time (RT were correlated with noise in face-house images. We then built dynamical causal models (DCM of fMRI blood-oxygenation level dependent (BOLD signals from the face and house category-specific regions in ventral temporal cortex, the fusiform face area (FFA and parahippocampal place area (PPA, and the dorsolateral prefrontal cortex (dlPFC. We found a strong feed-forward intrinsic connectivity pattern from FFA and PPA to dlPFC. Importantly, the feed-forward connectivity to dlPFC was significantly modulated by the perception of both faces and houses. The dlPFC-BOLD activity, the connectivity from FFA and PPA to the dlPFC all increased with noise level. These results suggest that the FFA-PPA-dlPFC network plays an important role for relaying and integrating competing sensory information to arrive at perceptual decisions.

  20. Simulation of ammoniacal nitrogen effluent using feedforward ...

    African Journals Online (AJOL)

    Ammoniacal nitrogen in domestic wastewater treatment plants has recently been added as the monitoring parameter by the Department of Environment, Malaysia. It is necessary to obtain a suitable model for the simulation of ammonical nitrogen in the effluent stream of sewage treatment plant in order to meet the new ...

  1. Models for Train Passenger Forecasting of Java and Sumatra

    Science.gov (United States)

    Sartono

    2017-04-01

    People tend to take public transportation to avoid high traffic, especially in Java. In Jakarta, the number of railway passengers is over than the capacity of the train at peak time. This is an opportunity as well as a challenge. If it is managed well then the company can get high profit. Otherwise, it may lead to disaster. This article discusses models for the train passengers, hence, finding the reasonable models to make a prediction overtimes. The Box-Jenkins method is occupied to develop a basic model. Then, this model is compared to models obtained using exponential smoothing method and regression method. The result shows that Holt-Winters model is better to predict for one-month, three-month, and six-month ahead for the passenger in Java. In addition, SARIMA(1,1,0)(2,0,0) is more accurate for nine-month and twelve-month oversee. On the other hand, for Sumatra passenger forecasting, SARIMA(1,1,1)(0,0,2) gives a better approximation for one-month ahead, and ARIMA model is best for three-month ahead prediction. The rest, Trend Seasonal and Liner Model has the least of RMSE to forecast for six-month, nine-month, and twelve-month ahead.

  2. Consensus-based training and assessment model for general surgery.

    Science.gov (United States)

    Szasz, P; Louridas, M; de Montbrun, S; Harris, K A; Grantcharov, T P

    2016-05-01

    Surgical education is becoming competency-based with the implementation of in-training milestones. Training guidelines should reflect these changes and determine the specific procedures for such milestone assessments. This study aimed to develop a consensus view regarding operative procedures and tasks considered appropriate for junior and senior trainees, and the procedures that can be used as technical milestone assessments for trainee progression in general surgery. A Delphi process was followed where questionnaires were distributed to all 17 Canadian general surgery programme directors. Items were ranked on a 5-point Likert scale, with consensus defined as Cronbach's α of at least 0·70. Items rated 4 or above on the 5-point Likert scale by 80 per cent of the programme directors were included in the models. Two Delphi rounds were completed, with 14 programme directors taking part in round one and 11 in round two. The overall consensus was high (Cronbach's α = 0·98). The training model included 101 unique procedures and tasks, 24 specific to junior trainees, 68 specific to senior trainees, and nine appropriate to all. The assessment model included four procedures. A system of operative procedures and tasks for junior- and senior-level trainees has been developed along with an assessment model for trainee progression. These can be used as milestones in competency-based assessments. © 2016 BJS Society Ltd Published by John Wiley & Sons Ltd.

  3. Thalamocortical control of feed-forward inhibition in awake somatosensory 'barrel' cortex.

    OpenAIRE

    Swadlow, Harvey A

    2002-01-01

    Intracortical inhibition plays a role in shaping sensory cortical receptive fields and is mediated by both feed-forward and feedback mechanisms. Feed-forward inhibition is the faster of the two processes, being generated by inhibitory interneurons driven by monosynaptic thalamocortical (TC) input. In principle, feed-forward inhibition can prevent targeted cortical neurons from ever reaching threshold when TC input is weak. To do so, however, inhibitory interneurons must respond to TC input at...

  4. Basic models modeling resistance training: an update for basic scientists interested in study skeletal muscle hypertrophy.

    Science.gov (United States)

    Cholewa, Jason; Guimarães-Ferreira, Lucas; da Silva Teixeira, Tamiris; Naimo, Marshall Alan; Zhi, Xia; de Sá, Rafaele Bis Dal Ponte; Lodetti, Alice; Cardozo, Mayara Quadros; Zanchi, Nelo Eidy

    2014-09-01

    Human muscle hypertrophy brought about by voluntary exercise in laboratorial conditions is the most common way to study resistance exercise training, especially because of its reliability, stimulus control and easy application to resistance training exercise sessions at fitness centers. However, because of the complexity of blood factors and organs involved, invasive data is difficult to obtain in human exercise training studies due to the integration of several organs, including adipose tissue, liver, brain and skeletal muscle. In contrast, studying skeletal muscle remodeling in animal models are easier to perform as the organs can be easily obtained after euthanasia; however, not all models of resistance training in animals displays a robust capacity to hypertrophy the desired muscle. Moreover, some models of resistance training rely on voluntary effort, which complicates the results observed when animal models are employed since voluntary capacity is something theoretically impossible to measure in rodents. With this information in mind, we will review the modalities used to simulate resistance training in animals in order to present to investigators the benefits and risks of different animal models capable to provoke skeletal muscle hypertrophy. Our second objective is to help investigators analyze and select the experimental resistance training model that best promotes the research question and desired endpoints. © 2013 Wiley Periodicals, Inc.

  5. Grid-Voltage-Feedforward Active Damping for Grid-Connected Inverter with LCL Filter

    DEFF Research Database (Denmark)

    Lu, Minghui; Wang, Xiongfei; Blaabjerg, Frede

    2016-01-01

    For the grid-connected voltage source inverters, the feedforward scheme of grid voltage is commonly adopted to mitigate the current distortion caused by grid background voltages harmonics. This paper investigates the grid-voltage-feedforward active damping for grid connected inverter with LCL...... filter. It reveals that proportional feedforward control can not only fulfill the mitigation of grid disturbance, but also offer damping effects on the LCL filter resonance. Digital delays are intrinsic to digital controlled inverters; with these delays, the feedforward control can be equivalent...

  6. Feed-forward general-purpose computer

    Energy Technology Data Exchange (ETDEWEB)

    Yamada, H; Yoshioka, Y; Nakamura, T; Shigei, Y

    1983-08-01

    The feed forward machine (FFM) proposed by the authors has a CPU composed of many fixed arithmetic units and registers. Many features of the FFM which are compatible with concurrent operating and reduce the instruction requirement for store are reported. In order to evaluate the FFM, the minimum execution time of instructions is discussed by using the Petri Net model. From this it is predicted that the execution time will be 0.46-0.6 times the real execution time. Furthermore, it is concluded that the program for the FFM will be reduced in size with respect to the program for the Von Neumann computers. 12 references.

  7. Train-to-Ground communications of a Train Control and Monitoring Systems: A simulation platform modelling approach

    DEFF Research Database (Denmark)

    Bouaziz, Maha; Yan, Ying; Kassab, Mohamed

    2018-01-01

    wireless technologies, e.g. Wi-Fi and LTE. Different T2G scenarios are defined in order to evaluate the performances of the Mobile Communication Gateway (managing train communications) and Quality of Services (QoS) offered to TCMS applications in the context of various environments (regular train lines......Under the SAFE4RAIL project, we are developing a simulation platform based on a discrete-events network simulator. This platform models the Train-to-Ground (T2G) link in the framework of a system-level simulation of Train Control Management System (TCMS). The modelled T2G link is based on existing...

  8. Music training and inhibitory control: a multidimensional model.

    Science.gov (United States)

    Moreno, Sylvain; Farzan, Faranak

    2015-03-01

    Training programs aimed to improve cognitive skills have either yielded mixed results or remain to be validated. The limited benefits of such regimens are largely attributable to weak understanding of (1) how (and which) interventions provide the most cognitive improvements; and (2) how brain networks and neural mechanisms that underlie specific cognitive abilities can be modified selectively. Studies indicate that music training leads to robust and long-lasting benefits to behavior. Importantly, behavioral advantages conferred by music extend beyond perceptual abilities to even nonauditory functions, such as inhibitory control (IC) and its neural correlates. Alternative forms of arts engagement or brain training do not appear to yield such enhancements, which suggests that music uniquely taps into brain networks subserving a variety of auditory as well as domain-general mechanisms such as IC. To account for such widespread benefits of music training, we propose a framework of transfer effects characterized by three dimensions: level of processing, nature of the transfer, and involvement of executive functions. We suggest that transfer of skills is mediated through modulation of general cognitive processes, in particular IC. We believe that this model offers a viable framework to test the extent and limitations of music-related changes. © 2014 New York Academy of Sciences.

  9. Feedforward and feedback inhibition in neostriatal GABAergic spiny neurons.

    Science.gov (United States)

    Tepper, James M; Wilson, Charles J; Koós, Tibor

    2008-08-01

    There are two distinct inhibitory GABAergic circuits in the neostriatum. The feedforward circuit consists of a relatively small population of GABAergic interneurons that receives excitatory input from the neocortex and exerts monosynaptic inhibition onto striatal spiny projection neurons. The feedback circuit comprises the numerous spiny projection neurons and their interconnections via local axon collaterals. This network has long been assumed to provide the majority of striatal GABAergic inhibition and to sharpen and shape striatal output through lateral inhibition, producing increased activity in the most strongly excited spiny cells at the expense of their less strongly excited neighbors. Recent results, mostly from recording experiments of synaptically connected pairs of neurons, have revealed that the two GABAergic circuits differ markedly in terms of the total number of synapses made by each, the strength of the postsynaptic response detected at the soma, the extent of presynaptic convergence and divergence and the net effect of the activation of each circuit on the postsynaptic activity of the spiny neuron. These data have revealed that the feedforward inhibition is powerful and widespread, with spiking in a single interneuron being capable of significantly delaying or even blocking the generation of spikes in a large number of postsynaptic spiny neurons. In contrast, the postsynaptic effects of spiking in a single presynaptic spiny neuron on postsynaptic spiny neurons are weak when measured at the soma, and unable to significantly affect spike timing or generation. Further, reciprocity of synaptic connections between spiny neurons is only rarely observed. These results suggest that the bulk of the fast inhibition that has the strongest effects on spiny neuron spike timing comes from the feedforward interneuronal system whereas the axon collateral feedback system acts principally at the dendrites to control local excitability as well as the overall level of

  10. Model-Based Reasoning in Humans Becomes Automatic with Training.

    Directory of Open Access Journals (Sweden)

    Marcos Economides

    2015-09-01

    Full Text Available Model-based and model-free reinforcement learning (RL have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.

  11. On spatial spillover in feedforward and feedback noise control

    Science.gov (United States)

    Xie, Antai; Bernstein, Dennis

    2017-03-01

    Active feedback noise control for rejecting broadband disturbances must contend with the Bode integral constraint, which implies that suppression over some frequency range gives rise to amplification over another range at the performance microphone. This is called spectral spillover. The present paper deals with spatial spillover, which refers to the amplification of noise at locations where no microphone is located. A spatial spillover function is defined, which is valid for both feedforward and feedback control with scalar and vector control inputs. This function is numerically analyzed and measured experimentally. Obstructions are introduced in the acoustic space to investigate their effect on spatial spillover.

  12. A Novel Memristive Multilayer Feedforward Small-World Neural Network with Its Applications in PID Control

    Directory of Open Access Journals (Sweden)

    Zhekang Dong

    2014-01-01

    Full Text Available In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.

  13. A novel memristive multilayer feedforward small-world neural network with its applications in PID control.

    Science.gov (United States)

    Dong, Zhekang; Duan, Shukai; Hu, Xiaofang; Wang, Lidan; Li, Hai

    2014-01-01

    In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN) inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.

  14. Simulation of Feedforward-Feedback Control of Dissolved Oxygen of Microbial Repeated Fed-batch Culture

    Directory of Open Access Journals (Sweden)

    Ling Gao

    2016-09-01

    Full Text Available Fed-batch culture is often used in industry, and dissolved oxygen (DO concentration control is important in fermentation process control. DO control is often applied by using feedback (FB control strategy. But, feedforward-feedback (FF-FB control has the advantage in dealing with the time-varying characteristics resulted from the cell growth during the fermentation process. Mathematical modeling and computer simulation is a useful tool in analysis of the control system.  In this research, the FF-FB DO control and FB substrate control of repeated fed-batch culture process is modeled and simulated. The results showed the feasibility of the control strategy. These results are useful for control system development and process analyses and optimization.

  15. Feedback Enhances Feedforward Figure-Ground Segmentation by Changing Firing Mode

    Science.gov (United States)

    Supèr, Hans; Romeo, August

    2011-01-01

    In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforwardspiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses withthe responses to a homogenous texture. We propose that feedback controlsfigure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons. PMID:21738747

  16. Andragogical Model in Language Training of Mining Specialists

    Science.gov (United States)

    Bondareva, Evgeniya; Chistyakova, Galina; Kleshevskyi, Yury; Sergeev, Sergey; Stepanov, Aleksey

    2017-11-01

    Nowadays foreign language competence is one of the main professional skills of mining engineers. Modern competitive conditions require the ability for meeting production challenges in a foreign language from specialists and managers of mining enterprises. This is the reason of high demand on foreign language training/retraining courses. Language training of adult learners fundamentally differs from children and adolescent education. The article describes the features of andragogical learning model. The authors conclude that distance learning is the most productive education form having a number of obvious advantages over traditional (in-class) one. Interactive learning method that involves active engagement of adult trainees appears to be of the greatest interest due to introduction of modern information and communication technologies for distance learning.

  17. Phase I to II cross-induction of xenobiotic metabolizing enzymes: A feedforward control mechanism for potential hormetic responses

    International Nuclear Information System (INIS)

    Zhang Qiang; Pi Jingbo; Woods, Courtney G.; Andersen, Melvin E.

    2009-01-01

    Hormetic responses to xenobiotic exposure likely occur as a result of overcompensation by the homeostatic control systems operating in biological organisms. However, the mechanisms underlying overcompensation that leads to hormesis are still unclear. A well-known homeostatic circuit in the cell is the gene induction network comprising phase I, II and III metabolizing enzymes, which are responsible for xenobiotic detoxification, and in many cases, bioactivation. By formulating a differential equation-based computational model, we investigated in this study whether hormesis can arise from the operation of this gene/enzyme network. The model consists of two feedback and one feedforward controls. With the phase I negative feedback control, xenobiotic X activates nuclear receptors to induce cytochrome P450 enzyme, which bioactivates X into a reactive metabolite X'. With the phase II negative feedback control, X' activates transcription factor Nrf2 to induce phase II enzymes such as glutathione S-transferase and glutamate cysteine ligase, etc., which participate in a set of reactions that lead to the metabolism of X' into a less toxic conjugate X''. The feedforward control involves phase I to II cross-induction, in which the parent chemical X can also induce phase II enzymes directly through the nuclear receptor and indirectly through transcriptionally upregulating Nrf2. As a result of the active feedforward control, a steady-state hormetic relationship readily arises between the concentrations of the reactive metabolite X' and the extracellular parent chemical X to which the cell is exposed. The shape of dose-response evolves over time from initially monotonically increasing to J-shaped at the final steady state-a temporal sequence consistent with adaptation-mediated hormesis. The magnitude of the hormetic response is enhanced by increases in the feedforward gain, but attenuated by increases in the bioactivation or phase II feedback loop gains. Our study suggests a

  18. Phase I to II cross-induction of xenobiotic metabolizing enzymes: a feedforward control mechanism for potential hormetic responses.

    Science.gov (United States)

    Zhang, Qiang; Pi, Jingbo; Woods, Courtney G; Andersen, Melvin E

    2009-06-15

    Hormetic responses to xenobiotic exposure likely occur as a result of overcompensation by the homeostatic control systems operating in biological organisms. However, the mechanisms underlying overcompensation that leads to hormesis are still unclear. A well-known homeostatic circuit in the cell is the gene induction network comprising phase I, II and III metabolizing enzymes, which are responsible for xenobiotic detoxification, and in many cases, bioactivation. By formulating a differential equation-based computational model, we investigated in this study whether hormesis can arise from the operation of this gene/enzyme network. The model consists of two feedback and one feedforward controls. With the phase I negative feedback control, xenobiotic X activates nuclear receptors to induce cytochrome P450 enzyme, which bioactivates X into a reactive metabolite X'. With the phase II negative feedback control, X' activates transcription factor Nrf2 to induce phase II enzymes such as glutathione S-transferase and glutamate cysteine ligase, etc., which participate in a set of reactions that lead to the metabolism of X' into a less toxic conjugate X''. The feedforward control involves phase I to II cross-induction, in which the parent chemical X can also induce phase II enzymes directly through the nuclear receptor and indirectly through transcriptionally upregulating Nrf2. As a result of the active feedforward control, a steady-state hormetic relationship readily arises between the concentrations of the reactive metabolite X' and the extracellular parent chemical X to which the cell is exposed. The shape of dose-response evolves over time from initially monotonically increasing to J-shaped at the final steady state-a temporal sequence consistent with adaptation-mediated hormesis. The magnitude of the hormetic response is enhanced by increases in the feedforward gain, but attenuated by increases in the bioactivation or phase II feedback loop gains. Our study suggests a

  19. Inexpensive homemade models for ultrasound-guided vein cannulation training.

    Science.gov (United States)

    Di Domenico, Stefano; Santori, Gregorio; Porcile, Elisa; Licausi, Martina; Centanaro, Monica; Valente, Umberto

    2007-11-01

    To test the hypothesis that low-cost homemade models may be used to acquire the basic skills for ultrasound-guided central vein puncture. Training study. University transplantation department. Training was performed using three different homemade models (A, B, and C). Segments of a common rubber tourniquet (V1) and Silastic tube (V2) were used to simulate vessels within agar-based models. Overall cost for each model was less than 5 euro (US$7). For each test (test I, A-V1; II, A-V2; III, B-V1; IV, C-V2), the number of punctures and attempts needed to locate the needle inside the lumen were recorded. Each test was considered completed when participants punctured the vessels at the first attempt for three consecutive times. In test I, the mean number of punctures and attempts were 3.85 +/- 1.26 and 4.95 +/- 3.05; in test II, 4.60 +/- 1.14 and 6.30 +/- 2.51; in test III, 4.80 +/- 1.06 and 4.65 +/- 2.21; and in test IV, 4.45 +/- 1.23 and 6.05 +/- 2.92, respectively. For each test, no statistical difference was found by comparison of number of punctures and attempts for anesthesiologists versus nonanesthesiologists, men versus women, or previous experience versus no experience with central vein cannulation (CVC). Video game users obtained better results than did nonusers in test I (punctures, P = 0.033; attempts, P = 0.038), test II (punctures, P = 0.052; attempts, P = 0.011), and test IV (punctures, P = 0.001; attempts, P = 0.003). A posttraining questionnaire showed favorable opinions about the clarity of the instructions, aptness of the models, and adequacy of the training. In our operative unit, the use of ultrasound guidance for CVC increased from 2% to 23% in the first month after training. Low-cost homemade models are useful in acquiring basic coordination skills for ultrasound-guided CVC.

  20. Training and Validation of the Fast PCRTM_Solar Model

    Science.gov (United States)

    Yang, Q.; Liu, X.; Wu, W.; Yang, P.; Wang, C.

    2015-12-01

    Fast and accurate radiative transfer model is the key for satellite data assimilation for remote sensing application. The simulation of the satellite remote sensing radiances is very complicated since many physical processes, such as absorption, emission, and scattering, are involved due to the interactions between electromagnetic radiation and earth surface, water vapor, clouds, aerosols, and gas molecules in the sky. The principal component-based radiative transfer model (PCRTM) has been developed for various passive IR and MW instruments. In this work, we extended PCRTM to including the contribution from solar radiation. The cloud/aerosol bidirectional reflectances have been carefully calculated using the well-known Discrete-Ordinate-Method Radiative Transfer (DISORT) model under over 10 millions of diverse conditions with varying cloud particle size, wavelength, satellite viewing direction, and solar angles. The obtained results were compressed significantly using principal component analysis and used in the mono domain radiance calculation. We used 1352 different atmosphere profiles, each of them has different surface skin temperatures and surface pressures in our training. Different surface emissivity spectra were derived from ASTER database and emissivity models. Some artificially generated emissivity spectra were also used to account for diverse surface types of the earth. Concentrations of sixteen trace gases were varied systematically in the training and the remaining trace gas contributions were accounted for as a fixed gas. Training was done in both clear and cloudy skies conditions. Finally the nonlocal thermal equilibrium (NLTE) induced radiance change was included for daytime conditions. We have updated the PCRTM model for instruments such as IASI, NASTI, CrIS, AIRS, and SHIS. The training results show that the PCRTM model can calculate thousands of channel radiances by computing only a few hundreds of mono radiances. This greatly increased the

  1. Training Spiking Neural Models Using Artificial Bee Colony

    Science.gov (United States)

    Vazquez, Roberto A.; Garro, Beatriz A.

    2015-01-01

    Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644

  2. Training Post-9/11 Police Officers with a Counter-Terrorism Reality-Based Training Model: A Case Study

    Science.gov (United States)

    Biddle, Christopher J.

    2013-01-01

    The purpose of this qualitative holistic multiple-case study was to identify the optimal theoretical approach for a Counter-Terrorism Reality-Based Training (CTRBT) model to train post-9/11 police officers to perform effectively in their counter-terrorism assignments. Post-9/11 police officers assigned to counter-terrorism duties are not trained…

  3. A Feed-forward Geometrical Compensation and Adaptive Feedback Control Algorithm for Hydraulic Robot Manipulators

    DEFF Research Database (Denmark)

    Conrad, Finn; Zhou, Jianjun; Gabacik, Andrzej

    1998-01-01

    Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control.......Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control....

  4. Enhancing feedforward controller tuning via instrumental variables: with application to nanopositioning

    NARCIS (Netherlands)

    Boeren, F.A.J.; Bruijnen, D.J.H.; Oomen, T.A.E.

    2017-01-01

    Feedforward control enables high performance of a motion system. Recently, algorithms have been proposed that eliminate bias errors in tuning the parameters of a feedforward controller. The aim of this paper is to develop a new algorithm that combines unbiased parameter estimates with optimal

  5. MIMO feed-forward design in wafer scanners using a gradient approximation-based algorithm

    NARCIS (Netherlands)

    Heertjes, M.F.; Hennekens, D.W.T.; Steinbuch, M.

    2010-01-01

    An experimental demonstration is given of a data-based multi-input multi-output (MIMO) feed-forward control design applied to the motion systems of a wafer scanner. Atop a nominal single-input single-output (SISO) feed-forward controller, a MIMO controller is designed having a finite impulse

  6. Reference-tracking feedforward control design for linear dynamical systems through signal decomposition

    NARCIS (Netherlands)

    Kasemsinsup, Y.; Romagnoli, R.; Heertjes, M.F.; Weiland, S.; Butler, H.

    2017-01-01

    In this work, we study a novel approach towards the reference-tracking feedforward control design for linear dynamical systems. By utilizing the superposition property and exploiting signal decomposition together with a quadratic optimization process, we obtain a feedforward design procedure for

  7. Self-tuning disturbance feedforward control with drift prevention for air mount systems

    NARCIS (Netherlands)

    Beijen, M.A.; Heertjes, M.F.; Butler, H.

    2015-01-01

    A MIMO disturbance feedforward control strategy is presented to isolate an industrial active vibration isolation system with air mounts from broadband floor vibrations. The feedforward controller compensates for the static damping and stiffness of the air mount suspension, leading to significant

  8. Anticipatory synergy adjustments reflect individual performance of feedforward force control.

    Science.gov (United States)

    Togo, Shunta; Imamizu, Hiroshi

    2016-10-06

    We grasp and dexterously manipulate an object through multi-digit synergy. In the framework of the uncontrolled manifold (UCM) hypothesis, multi-digit synergy is defined as the coordinated control mechanism of fingers to stabilize variable important for task success, e.g., total force. Previous studies reported anticipatory synergy adjustments (ASAs) that correspond to a drop of the synergy index before a quick change of the total force. The present study compared ASA's properties with individual performances of feedforward force control to investigate a relationship of those. Subjects performed a total finger force production task that consisted of a phase in which subjects tracked target line with visual information and a phase in which subjects produced total force pulse without visual information. We quantified their multi-digit synergy through UCM analysis and observed significant ASAs before producing total force pulse. The time of the ASA initiation and the magnitude of the drop of the synergy index were significantly correlated with the error of force pulse, but not with the tracking error. Almost all subjects showed a significant increase of the variance that affected the total force. Our study directly showed that ASA reflects the individual performance of feedforward force control independently of target-tracking performance and suggests that the multi-digit synergy was weakened to adjust the multi-digit movements based on a prediction error so as to reduce the future error. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  9. Biomimetic Hybrid Feedback Feedforward Neural-Network Learning Control.

    Science.gov (United States)

    Pan, Yongping; Yu, Haoyong

    2017-06-01

    This brief presents a biomimetic hybrid feedback feedforward neural-network learning control (NNLC) strategy inspired by the human motor learning control mechanism for a class of uncertain nonlinear systems. The control structure includes a proportional-derivative controller acting as a feedback servo machine and a radial-basis-function (RBF) NN acting as a feedforward predictive machine. Under the sufficient constraints on control parameters, the closed-loop system achieves semiglobal practical exponential stability, such that an accurate NN approximation is guaranteed in a local region along recurrent reference trajectories. Compared with the existing NNLC methods, the novelties of the proposed method include: 1) the implementation of an adaptive NN control to guarantee plant states being recurrent is not needed, since recurrent reference signals rather than plant states are utilized as NN inputs, which greatly simplifies the analysis and synthesis of the NNLC and 2) the domain of NN approximation can be determined a priori by the given reference signals, which leads to an easy construction of the RBF-NNs. Simulation results have verified the effectiveness of this approach.

  10. Neural networks for feedback feedforward nonlinear control systems.

    Science.gov (United States)

    Parisini, T; Zoppoli, R

    1994-01-01

    This paper deals with the problem of designing feedback feedforward control strategies to drive the state of a dynamic system (in general, nonlinear) so as to track any desired trajectory joining the points of given compact sets, while minimizing a certain cost function (in general, nonquadratic). Due to the generality of the problem, conventional methods are difficult to apply. Thus, an approximate solution is sought by constraining control strategies to take on the structure of multilayer feedforward neural networks. After discussing the approximation properties of neural control strategies, a particular neural architecture is presented, which is based on what has been called the "linear-structure preserving principle". The original functional problem is then reduced to a nonlinear programming one, and backpropagation is applied to derive the optimal values of the synaptic weights. Recursive equations to compute the gradient components are presented, which generalize the classical adjoint system equations of N-stage optimal control theory. Simulation results related to nonlinear nonquadratic problems show the effectiveness of the proposed method.

  11. Outage Analysis of Train-to-Train Communication Model over Nakagami-m Channel in High-Speed Railway

    Directory of Open Access Journals (Sweden)

    Pengyu Liu

    2013-01-01

    Full Text Available This paper analyzes the end-to-end outage performance of high-speed-railway train-to-train communication model in high-speed railway over independent identical and nonidentical Nakagami-m channels. The train-to-train communication is inter-train communication without an aid of infrastructure (for base station. Source train uses trains on other rail tracks as relays to transmit signals to destination train on the same track. The mechanism of such communication among trains can be divided into three cases based on occurrence of possible-occurrence relay trains. We first present a new closed form for the sum of squared independent Nakagami-m variates and then derive an expression for the outage probability of the identical and non-identical Nakagami-m channels in three cases. In particular, the problem is improved by the proposed formulation that statistic for sum of squared Nakagami-m variates with identical m tends to be infinite. Numerical analysis indicates that the derived analytic results are reasonable and the outage performance is better over Nakagami-m channel in high-speed railway scenarios.

  12. Feedback and feedforward adaptation to visuomotor delay during reaching and slicing movements.

    Science.gov (United States)

    Botzer, Lior; Karniel, Amir

    2013-07-01

    It has been suggested that the brain and in particular the cerebellum and motor cortex adapt to represent the environment during reaching movements under various visuomotor perturbations. It is well known that significant delay is present in neural conductance and processing; however, the possible representation of delay and adaptation to delayed visual feedback has been largely overlooked. Here we investigated the control of reaching movements in human subjects during an imposed visuomotor delay in a virtual reality environment. In the first experiment, when visual feedback was unexpectedly delayed, the hand movement overshot the end-point target, indicating a vision-based feedback control. Over the ensuing trials, movements gradually adapted and became accurate. When the delay was removed unexpectedly, movements systematically undershot the target, demonstrating that adaptation occurred within the vision-based feedback control mechanism. In a second experiment designed to broaden our understanding of the underlying mechanisms, we revealed similar after-effects for rhythmic reversal (out-and-back) movements. We present a computational model accounting for these results based on two adapted forward models, each tuned for a specific modality delay (proprioception or vision), and a third feedforward controller. The computational model, along with the experimental results, refutes delay representation in a pure forward vision-based predictor and suggests that adaptation occurred in the forward vision-based predictor, and concurrently in the state-based feedforward controller. Understanding how the brain compensates for conductance and processing delays is essential for understanding certain impairments concerning these neural delays as well as for the development of brain-machine interfaces. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  13. Propagation of spiking regularity and double coherence resonance in feedforward networks.

    Science.gov (United States)

    Men, Cong; Wang, Jiang; Qin, Ying-Mei; Deng, Bin; Tsang, Kai-Ming; Chan, Wai-Lok

    2012-03-01

    We investigate the propagation of spiking regularity in noisy feedforward networks (FFNs) based on FitzHugh-Nagumo neuron model systematically. It is found that noise could modulate the transmission of firing rate and spiking regularity. Noise-induced synchronization and synfire-enhanced coherence resonance are also observed when signals propagate in noisy multilayer networks. It is interesting that double coherence resonance (DCR) with the combination of synaptic input correlation and noise intensity is finally attained after the processing layer by layer in FFNs. Furthermore, inhibitory connections also play essential roles in shaping DCR phenomena. Several properties of the neuronal network such as noise intensity, correlation of synaptic inputs, and inhibitory connections can serve as control parameters in modulating both rate coding and the order of temporal coding.

  14. Incoherent feedforward control governs adaptation of activated ras in a eukaryotic chemotaxis pathway.

    Science.gov (United States)

    Takeda, Kosuke; Shao, Danying; Adler, Micha; Charest, Pascale G; Loomis, William F; Levine, Herbert; Groisman, Alex; Rappel, Wouter-Jan; Firtel, Richard A

    2012-01-03

    Adaptation in signaling systems, during which the output returns to a fixed baseline after a change in the input, often involves negative feedback loops and plays a crucial role in eukaryotic chemotaxis. We determined the dynamical response to a uniform change in chemoattractant concentration of a eukaryotic chemotaxis pathway immediately downstream from G protein-coupled receptors. The response of an activated Ras showed near-perfect adaptation, leading us to attempt to fit the results using mathematical models for the two possible simple network topologies that can provide perfect adaptation. Only the incoherent feedforward network accurately described the experimental results. This analysis revealed that adaptation in this Ras pathway is achieved through the proportional activation of upstream components and not through negative feedback loops. Furthermore, these results are consistent with a local excitation, global inhibition mechanism for gradient sensing, possibly with a Ras guanosine triphosphatase-activating protein acting as a global inhibitor.

  15. Joint input shaping and feedforward for point-to-point motion : automated tuning for an industrial nanopositioning system

    NARCIS (Netherlands)

    Boeren, F.A.J.; Bruijnen, D.J.H.; Dijk, van N.J.M.; Oomen, T.A.E.

    2014-01-01

    Feedforward control can effectively compensate for the servo error induced by the reference signal if it is tuned appropriately. This paper aims to introduce a new joint input shaping and feedforward parametrization in iterative feedforward control. Such a parametrization has the potential to

  16. Mitigation of ground motion effects in linear accelerators via feed-forward control

    Directory of Open Access Journals (Sweden)

    J. Pfingstner

    2014-12-01

    Full Text Available Ground motion is a severe problem for many particle accelerators, since it excites beam oscillations, which decrease the beam quality and create beam-beam offset (at colliders. Orbit feedback systems can only compensate ground motion effects at frequencies significantly smaller than the beam repetition rate. In linear colliders, where the repetition rate is low, additional counter measures have to be put in place. For this reason, a ground motion mitigation method based on feed-forward control is presented in this paper. It has several advantages compared to other techniques (stabilization systems and intratrain feedback systems such as cost reduction and potential performance improvement. An analytical model is presented that allows the derivation of hardware specification and performance estimates for a specific accelerator and ground motion model. At the Accelerator Test Facility (ATF2, ground motion sensors have been installed to verify the feasibility of important parts of the mitigation strategy. In experimental studies, it has been shown that beam excitations due to ground motion can be predicted from ground motion measurements on a pulse-to-pulse basis. Correlations of up to 80% between the estimated and measured orbit jitter have been observed. Additionally, an orbit jitter source was identified and has been removed, which halved the orbit jitter power at ATF2 and shows that the feed-forward scheme is also very useful for the detection of installation issues. We believe that the presented mitigation method has the potential to reduce costs and improve the performance of linear colliders and potentially other linear accelerators.

  17. The Conceptual Model of Future Teachers Training to Dual Education in VET (Vocational Education & Training)

    Science.gov (United States)

    Zholdasbekova, Saule; Nurzhanbayeva, Zhanat; Karatayev, Galymzhan; Akhmet, Laura Smatullaevna; Anarmetov, Bahitzhan

    2016-01-01

    In the article the author presents the theoretical understanding of research problems of training of the future teachers-organizers of the dual training system in vocational education & training (VET) in the conditions of the credit technology of education. The author's vision of way to solve the problem is discussed in the description of the…

  18. Reaction to the Major Contribution: Training for Skills Competency in Counseling Psychology--Integrating Models

    Science.gov (United States)

    Nutt, Roberta L.

    2011-01-01

    The authors of the Major Contribution have developed a complex and elegant three-level training model on which they suggest advanced microskills may be built. Prior to the description of their model, they have built a case that current microskills training has proved foundationally important but insufficient to training needs. They then invite…

  19. Nonlinear adaptive inverse control via the unified model neural network

    Science.gov (United States)

    Jeng, Jin-Tsong; Lee, Tsu-Tian

    1999-03-01

    In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

  20. Comparative performance of high-fidelity training models for flexible ureteroscopy: Are all models effective?

    Directory of Open Access Journals (Sweden)

    Shashikant Mishra

    2011-01-01

    Full Text Available Objective: We performed a comparative study of high-fidelity training models for flexible ureteroscopy (URS. Our objective was to determine whether high-fidelity non-virtual reality (VR models are as effective as the VR model in teaching flexible URS skills. Materials and Methods: Twenty-one trained urologists without clinical experience of flexible URS underwent dry lab simulation practice. After a warm-up period of 2 h, tasks were performed on a high-fidelity non-VR (Uro-scopic Trainer TM ; Endo-Urologie-Modell TM and a high-fidelity VR model (URO Mentor TM . The participants were divided equally into three batches with rotation on each of the three stations for 30 min. Performance of the trainees was evaluated by an expert ureteroscopist using pass rating and global rating score (GRS. The participants rated a face validity questionnaire at the end of each session. Results: The GRS improved statistically at evaluation performed after second rotation (P<0.001 for batches 1, 2 and 3. Pass ratings also improved significantly for all training models when the third and first rotations were compared (P<0.05. The batch that was trained on the VR-based model had more improvement on pass ratings on second rotation but could not achieve statistical significance. Most of the realistic domains were higher for a VR model as compared with the non-VR model, except the realism of the flexible endoscope. Conclusions: All the models used for training flexible URS were effective in increasing the GRS and pass ratings irrespective of the VR status.

  1. Development of a computer-based training (CBT) course for the FSUTMS comprehensive modeling workshop.

    Science.gov (United States)

    2008-09-01

    FSUTMS training is a major activity of the Systems Planning Office of the Florida Department of : Transportation (FDOT). The training aims to establish and maintain quality assurance for consistent : statewide modeling standards and provide up-to-dat...

  2. Building Customer Relationships: A Model for Vocational Education and Training Delivery.

    Science.gov (United States)

    Jarratt, Denise G.; Murphy, Tom; Lowry, Diannah

    1997-01-01

    Review of the theory of relational marketing and interviews with training providers identified a training delivery model that includes elements of trust and commitment, investment by relationship partners, and knowledge exchange, supporting relationship longevity. (SK)

  3. Character Recognition Using Genetically Trained Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Diniz, C.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-10-01

    Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfid recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the

  4. Modeling the Responses to Resistance Training in an Animal Experiment Study

    Directory of Open Access Journals (Sweden)

    Antony G. Philippe

    2015-01-01

    Full Text Available The aim of the present study was to test whether systems models of training effects on performance in athletes can be used to explore the responses to resistance training in rats. 11 Wistar Han rats (277 ± 15 g underwent 4 weeks of resistance training consisting in climbing a ladder with progressive loads. Training amount and performance were computed from total work and mean power during each training session. Three systems models relating performance to cumulated training bouts have been tested: (i with a single component for adaptation to training, (ii with two components to distinguish the adaptation and fatigue produced by exercise bouts, and (iii with an additional component to account for training-related changes in exercise-induced fatigue. Model parameters were fitted using a mixed-effects modeling approach. The model with two components was found to be the most suitable to analyze the training responses (R2=0.53; P<0.001. In conclusion, the accuracy in quantifying training loads and performance in a rodent experiment makes it possible to model the responses to resistance training. This modeling in rodents could be used in future studies in combination with biological tools for enhancing our understanding of the adaptive processes that occur during physical training.

  5. In vivo temporal property of GABAergic neural transmission in collateral feed-forward inhibition system of hippocampal-prefrontal pathway.

    Science.gov (United States)

    Takita, Masatoshi; Kuramochi, Masahito; Izaki, Yoshinori; Ohtomi, Michiko

    2007-05-30

    Anatomical evidence suggests that rat CA1 hippocampal afferents collaterally innervate excitatory projecting pyramidal neurons and inhibitory interneurons, creating a disynaptic, feed-forward inhibition microcircuit in the medial prefrontal cortex (mPFC). We investigated the temporal relationship between the frequency of paired synaptic transmission and gamma-aminobutyric acid (GABA)ergic receptor-mediated modulation of the microcircuit in vivo under urethane anesthesia. Local perfusions of a GABAa antagonist (-)-bicuculline into the mPFC via microdialysis resulted in a statistically significant disinhibitory effect on intrinsic GABA action, increasing the first and second mPFC responses following hippocampal paired stimulation at interstimulus intervals of 100-200 ms, but not those at 25-50 ms. This (-)-bicuculline-induced disinhibition was compensated by the GABAa agonist muscimol, which itself did not attenuate the intrinsic oscillation of the local field potentials. The perfusion of a sub-minimal concentration of GABAb agonist (R)-baclofen slightly enhanced the synaptic transmission, regardless of the interstimulus interval. In addition to the tonic control by spontaneous fast-spiking GABAergic neurons, it is clear the sequential transmission of the hippocampal-mPFC pathway can phasically drive the collateral feed-forward inhibition system through activation of a GABAa receptor, bringing an active signal filter to the various types of impulse trains that enter the mPFC from the hippocampus in vivo.

  6. Time series prediction by feedforward neural networks - is it difficult?

    International Nuclear Information System (INIS)

    Rosen-Zvi, Michal; Kanter, Ido; Kinzel, Wolfgang

    2003-01-01

    The difficulties that a neural network faces when trying to learn from a quasi-periodic time series are studied analytically using a teacher-student scenario where the random input is divided into two macroscopic regions with different variances, 1 and 1/γ 2 (γ >> 1). The generalization error is found to decrease as ε g ∝ exp(-α/γ 2 ), where α is the number of examples per input dimension. In contradiction to this very slow vanishing generalization error, the next output prediction is found to be almost free of mistakes. This picture is consistent with learning quasi-periodic time series produced by feedforward neural networks, which is dominated by enhanced components of the Fourier spectrum of the input. Simulation results are in good agreement with the analytical results

  7. Protecting nonlocality of multipartite states by feed-forward control

    Science.gov (United States)

    Li, Xiao-Gang; Zou, Jian; Shao, Bin

    2018-06-01

    Nonlocality is a useful resource in quantum communication and quantum information processing. In practical quantum communication, multipartite entangled states must be distributed between different users in different places through a channel. However, the channel is usually inevitably disturbed by the environment in quantum state distribution processing and then the nonlocality of states will be weakened and even lost. In this paper, we use a feed-forward control scheme to protect the nonlocality of the Bell and GHZ states against dissipation. We find that this protection scheme is very effective, specifically, for the Bell state, we can increase the noise threshold from 0.5 to 0.98, and for GHZ state from 0.29 to 0.96. And we also find that entanglement is relatively easier to be protected than nonlocality. For our scheme, protecting entanglement is equivalent to protecting the state in the case of Bell state, while protecting nonlocality is not.

  8. PWR plant operator training used full scope simulator incorporated MAAP model

    International Nuclear Information System (INIS)

    Matsumoto, Y.; Tabuchi, T.; Yamashita, T.; Komatsu, Y.; Tsubouchi, K.; Banka, T.; Mochizuki, T.; Nishimura, K.; Iizuka, H.

    2015-01-01

    NTC makes an effort with the understanding of plant behavior of core damage accident as part of our advanced training. For the Fukushima Daiichi Nuclear Power Station accident, we introduced the MAAP model into PWR operator training full scope simulator and also made the Severe Accident Visual Display unit. From 2014, we will introduce new training program for a core damage accident with PWR operator training full scope simulator incorporated the MAAP model and the Severe Accident Visual Display unit. (author)

  9. Adaptive feedforward control for improving output power response of CO2 laser; Tekiogata feedforward ni yoru laser shutsuryoku oto no kaizen

    Energy Technology Data Exchange (ETDEWEB)

    Imai, Y.; Takahashi, t.; Morita, A. [Mitsubishi Electric Corp., Tokyo (Japan)

    1998-03-31

    Feedback control has been used to stabilize the steady-state output power of a CO2 laser to overcome the problems caused by the change in the temperature/deterioration of CO2 gas. The transient response, however, is as slow as a few hundred milliseconds because of the slow dynamics of a thermopile power sensor. When machining conditions of a CO2 laser are changed, this rather slow response requires an extra dwell time, resulting in low productivity of the machining. To cope with this problem, the authors have developed adaptive feedforward control for a CO2 laser in addition to conventional feedback control. The model of a CO2 laser is described as a gain, which is varied by the setting parameters; laser power, pulse frequency and duty factor, as well as gas conditions. In this paper, two new variables, effective discharge power and threshold discharge power, are introduced to obtain a compact and adjustable model. With the proposed control system, the step response time of a laser power is reduced to less than ten milliseconds without overshoot, and can be set to desired constant time. The effects of such a fast and stable response on the machining speed and machining quality are examined. The experimental results show that for thin metal line-cutting, neither the melt-off area nor dross is observed even in the no-dwell time case. For thin metal hole-cutting, the machining speed is improved by 30%. 11 refs., 14 figs., 3 tabs.

  10. IMPLEMENTATION MODEL OF MOTOR TRACTION FORCE OF MAGLEV TRAIN

    Directory of Open Access Journals (Sweden)

    V. O. Polyakov

    2016-08-01

    Full Text Available Purpose. Traction force implementation (TFI by the motor of magnetic levitation train (MLT occurs in the process of electric-to-kinetic energy transformation at interaction of inductor and armature magnetic fields. Ac-cordingly, the aim of this study is to obtain a correct description of such energy transformation. Methodology. At the present stage, a mathematical and, in particular, computer simulation is the main and most universal tool for analysis and synthesis of processes and systems. At the same time, radical advantages of this tool make the precision of selection of a particular research methodology even more important. It is especially important for such a large and complex system as MLT. Therefore the special attention in the work is given to the rationale for choosing the research paradigm selective features. Findings. The analysis results of existing TFI process model versions indicate that each of them has both advantages and disadvantages. Therefore, one of the main results of this study was the creation of a mathematical model for such process that would preserve the advantages of previous versions, but would be free from their disadvantages. The work provides rationale for application (for the purposes of research of train motor TFI of the integrative holistic paradigm, which assimilates the advantages of the theory of electric circuit and magnetic field. Originality. The priority of creation of such paradigm and corresponding version of FI model constitute the originality of the research. Practical value. The main manifestation of practical value of this research in the opportunity, in case of use of its results, for significant increase in efficiency of MLT dynamic studies, on the condition that their generalized costs will not rise.

  11. A train dispatching model based on fuzzy passenger demand forecasting during holidays

    Directory of Open Access Journals (Sweden)

    Fei Dou Dou

    2013-03-01

    Full Text Available Abstract: Purpose: The train dispatching is a crucial issue in the train operation adjustment when passenger flow outbursts. During holidays, the train dispatching is to meet passenger demand to the greatest extent, and ensure safety, speediness and punctuality of the train operation. In this paper, a fuzzy passenger demand forecasting model is put up, then a train dispatching optimization model is established based on passenger demand so as to evacuate stranded passengers effectively during holidays. Design/methodology/approach: First, the complex features and regularity of passenger flow during holidays are analyzed, and then a fuzzy passenger demand forecasting model is put forward based on the fuzzy set theory and time series theory. Next, the bi-objective of the train dispatching optimization model is to minimize the total operation cost of the train dispatching and unserved passenger volume during holidays. Finally, the validity of this model is illustrated with a case concerned with the Beijing-Shanghai high-speed railway in China. Findings: The case study shows that the fuzzy passenger demand forecasting model can predict outcomes more precisely than ARIMA model. Thus train dispatching optimization plan proves that a small number of trains are able to serve unserved passengers reasonably and effectively. Originality/value: On the basis of the passenger demand predictive values, the train dispatching optimization model is established, which enables train dispatching to meet passenger demand in condition that passenger flow outbursts, so as to maximize passenger demand by offering the optimal operation plan.

  12. How many doctors should we train for Sri Lanka? System dynamics modelling for training needs

    Science.gov (United States)

    De Silva, D

    2017-12-26

    Over the years, Sri Lanka has achieved remarkable health gains for the money spent on health. Currently about 1450 doctors enter the health system annually. While some advocate opening up of new medical schools to address an apparent shortage of doctors in the country, others argue against it. To identify the number of doctors Sri Lanka need. System dynamics, an analytical modelling approach and a methodology for studying complex feedback systems was used. Two sub models of “need” and “supply” were developed and simulated for a period of 15 years from 2017 to 2032 At present the doctor to population ratio is 1:671 and 91% of the need has been met. This study shows that currently there is a shortage of doctors in the country. However, the supply will match the need by 2025/26. Increasing the number of doctors, will result in oversupply of doctors towards the latter part of the next decade. There is no acute necessity to open up new Medical Schools. However comprehensive health workforce analysis needs to be done once in 5 years and the number of doctors to be trained, decided accordingly.

  13. Artery Soft-Tissue Modelling for Stent Implant Training System

    Directory of Open Access Journals (Sweden)

    Giovanni Aloisio

    2004-08-01

    Full Text Available Virtual reality technology can be utilised to provide new systematic training methods for surgical procedures. Our aim is to build a simulator that allows medical students to practice the coronary stent implant procedure and avoids exposing patients to risks. The designed simulation system consists of a virtual environment and a haptic interface, in order to provide both the visualization of the coronary arteries and the tactile and force feedback generated during the interactions of the surgical instruments in the virtual environment. Since the arteries are soft tissues, their shape may change during an operation; for this reason physical modelling of the organs is necessary to render their behaviour under the influence of surgeon's instruments. The idea is to define a model that computes the displacement of the tissue versus time; from the displacement it is possible to calculate the response of the tissue to the surgical tool external stimuli. Information about tools displacements and tissue responses are also used to graphically model the artery wall and virtual surgical instrument deformations generated as a consequence of their coming into contact. In order to obtain a realistic simulation, the Finite Element Method has been used to model the soft tissues of the artery, using linear elasticity to reduce computational time and speed up interaction rates.

  14. Metadynamics for training neural network model chemistries: A competitive assessment

    Science.gov (United States)

    Herr, John E.; Yao, Kun; McIntyre, Ryker; Toth, David W.; Parkhill, John

    2018-06-01

    Neural network model chemistries (NNMCs) promise to facilitate the accurate exploration of chemical space and simulation of large reactive systems. One important path to improving these models is to add layers of physical detail, especially long-range forces. At short range, however, these models are data driven and data limited. Little is systematically known about how data should be sampled, and "test data" chosen randomly from some sampling techniques can provide poor information about generality. If the sampling method is narrow, "test error" can appear encouragingly tiny while the model fails catastrophically elsewhere. In this manuscript, we competitively evaluate two common sampling methods: molecular dynamics (MD), normal-mode sampling, and one uncommon alternative, Metadynamics (MetaMD), for preparing training geometries. We show that MD is an inefficient sampling method in the sense that additional samples do not improve generality. We also show that MetaMD is easily implemented in any NNMC software package with cost that scales linearly with the number of atoms in a sample molecule. MetaMD is a black-box way to ensure samples always reach out to new regions of chemical space, while remaining relevant to chemistry near kbT. It is a cheap tool to address the issue of generalization.

  15. Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex.

    Science.gov (United States)

    Mejias, Jorge F; Murray, John D; Kennedy, Henry; Wang, Xiao-Jing

    2016-11-01

    Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.

  16. Teacher training by means of a school-based model

    African Journals Online (AJOL)

    21172714

    teacher shortage; teacher training; university-school partnerships; workplace learning ... (Department of Higher Education & Training, Republic of South Africa, 2011:8), which is an ..... http://www.researchgate.net/profile/Lynda_Wiest/p.

  17. Modelling the training effects of kinaesthetic acuity measurement in children.

    Science.gov (United States)

    Sims, K; Morton, J

    1998-07-01

    In previous papers (Sims, Henderson, Hulme, & Morton, 1996a; Sims, Henderson, Morton, & Hulme, 1996b) we have found that the motor skills of clumsy children are capable of significant improvement following relatively brief interventions. Most remarkably, this included a 10-minute intervention while testing the kinaesthetic acuity of the children using a staircase method (Pest). In this paper, we show that Pest testing improves the kinaesthetic acuity of normal children as well. We analyse the available data on the development and improvement of motor skills and kinaesthetic acuity and derive a causal model for the underlying skills. We show that at least three independent cognitive/biological components are required to account for the data. These three components are affected differently by the various interventions that have been tried. We deduce that improvement on a general test of motor impairment can be found as a result of training in kinaesthetic acuity or through other, independent factors.

  18. Hypermedia for Training: A Software and Instructional Engineering Model.

    Science.gov (United States)

    Cortinovis, Renato

    1992-01-01

    Presents an engineering environment oriented to the development of hypermedia applications for training. Training trends are described; requirements for a computer-based training (CBT) strategy are outlined; a hypermedia course structure is examined; microinstructional events (MIEs) are explained; and technology requirements and selection are…

  19. The Training Resource Unit--An Outreach Model.

    Science.gov (United States)

    Martin, Meredith A.

    1991-01-01

    The Training Resource Unit is a New South Wales (Australia) community services initiative that provides services such as direct client training, career training, and consultation to individuals with severe intellectual disability and severe challenging behaviors. The service is provided in the person's place of residence, workplace, or school…

  20. Urology residents training in laparoscopic surgery. Development of a virtual reality model.

    Science.gov (United States)

    Gutiérrez-Baños, J L; Ballestero-Diego, R; Truan-Cacho, D; Aguilera-Tubet, C; Villanueva-Peña, A; Manuel-Palazuelos, J C

    2015-11-01

    The training and learning of residents in laparoscopic surgery has legal, financial and technological limitations. Simulation is an essential tool in the training of residents as a supplement to their training in laparoscopic surgery. The training should be structured in an appropriate environment, with previously established and clear objectives, taught by professionals with clinical and teaching experience in simulation. The training should be conducted with realistic models using animals and ex-vivo tissue from animals. It is essential to incorporate mechanisms to assess the objectives during the residents' training progress. We present the training model for laparoscopic surgery for urology residents at the University Hospital Valdecilla. The training is conducted at the Virtual Hospital Valdecilla, which is associated with the Center for Medical Simulation in Boston and is accredited by the American College of Surgeons. The model is designed in 3 blocks, basic for R1, intermediate for R2-3 and advanced for R4-5, with 9 training modules. The training is conducted in 4-hour sessions for 4 afternoons, for 3 weeks per year of residence. Residents therefore perform 240 hours of simulated laparoscopic training by the end of the course. For each module, we use structured objective assessments to measure each resident's training progress. Since 2003, 9 urology residents have been trained, in addition to the 5 who are currently in training. The model has undergone changes according to the needs expressed in the student feedback. The acquisition of skills in a virtual reality model has enabled the safe transfer of those skills to actual practice. A laparoscopic surgery training program designed in structured blocks and with progressive complexity provides appropriate training for transferring the skills acquired using this model to an actual scenario while maintaining patient safety. Copyright © 2015 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

  1. Training courses on integrated safety assessment modelling for waste repositories

    International Nuclear Information System (INIS)

    Mallants, D.

    2007-01-01

    Near-surface or deep repositories of radioactive waste are being developed and evaluated all over the world. Also, existing repositories for low- and intermediate-level waste often need to be re-evaluated to extend their license or to obtain permission for final closure. The evaluation encompasses both a technical feasibility as well as a safety analysis. The long term safety is usually demonstrated by means of performance or safety assessment. For this purpose computer models are used that calculate the migration of radionuclides from the conditioned radioactive waste, through engineered barriers to the environment (groundwater, surface water, and biosphere). Integrated safety assessment modelling addresses all relevant radionuclide pathways from source to receptor (man), using in combination various computer codes in which the most relevant physical, chemical, mechanical, or even microbiological processes are mathematically described. SCK-CEN organizes training courses in Integrated safety assessment modelling that are intended for individuals who have either a controlling or supervising role within the national radwaste agencies or regulating authorities, or for technical experts that carry out the actual post-closure safety assessment for an existing or new repository. Courses are organised by the Department of Waste and Disposal

  2. Modeling Broadband Microwave Structures by Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    V. Otevrel

    2004-06-01

    Full Text Available The paper describes the exploitation of feed-forward neural networksand recurrent neural networks for replacing full-wave numerical modelsof microwave structures in complex microwave design tools. Building aneural model, attention is turned to the modeling accuracy and to theefficiency of building a model. Dealing with the accuracy, we describea method of increasing it by successive completing a training set.Neural models are mutually compared in order to highlight theiradvantages and disadvantages. As a reference model for comparisons,approximations based on standard cubic splines are used. Neural modelsare used to replace both the time-domain numeric models and thefrequency-domain ones.

  3. A fast and accurate online sequential learning algorithm for feedforward networks.

    Science.gov (United States)

    Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N

    2006-11-01

    In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.

  4. A Risk and Prevention Counselor Training Program Model: Theory and Practice

    Science.gov (United States)

    Mason, Michael J.; Nakkula, Michael J.

    2008-01-01

    The need for training mental health counselors in risk and prevention is presented, and justification of the development of an innovative and integrative prevention training program is offered. Theoretical underpinnings that connect the counseling discipline to the field of prevention are described. A risk and prevention training model from…

  5. Applied Research Consultants (ARC): A Vertical Practicum Model of Training Applied Research

    Science.gov (United States)

    Nadler, Joel T.; Cundiff, Nicole L.

    2009-01-01

    The demand for highly trained evaluation consultants is increasing. Furthermore, the gap between job seekers' evaluation competencies and job recruiters' expectations suggests a need for providing practical training experiences. A model using a vertical practicum (advanced students assisting in the training of newer students) is suggested as an…

  6. The predictability of frequency-altered auditory feedback changes the weighting of feedback and feedforward input for speech motor control.

    Science.gov (United States)

    Scheerer, Nichole E; Jones, Jeffery A

    2014-12-01

    Speech production requires the combined effort of a feedback control system driven by sensory feedback, and a feedforward control system driven by internal models. However, the factors that dictate the relative weighting of these feedback and feedforward control systems are unclear. In this event-related potential (ERP) study, participants produced vocalisations while being exposed to blocks of frequency-altered feedback (FAF) perturbations that were either predictable in magnitude (consistently either 50 or 100 cents) or unpredictable in magnitude (50- and 100-cent perturbations varying randomly within each vocalisation). Vocal and P1-N1-P2 ERP responses revealed decreases in the magnitude and trial-to-trial variability of vocal responses, smaller N1 amplitudes, and shorter vocal, P1 and N1 response latencies following predictable FAF perturbation magnitudes. In addition, vocal response magnitudes correlated with N1 amplitudes, vocal response latencies, and P2 latencies. This pattern of results suggests that after repeated exposure to predictable FAF perturbations, the contribution of the feedforward control system increases. Examination of the presentation order of the FAF perturbations revealed smaller compensatory responses, smaller P1 and P2 amplitudes, and shorter N1 latencies when the block of predictable 100-cent perturbations occurred prior to the block of predictable 50-cent perturbations. These results suggest that exposure to large perturbations modulates responses to subsequent perturbations of equal or smaller size. Similarly, exposure to a 100-cent perturbation prior to a 50-cent perturbation within a vocalisation decreased the magnitude of vocal and N1 responses, but increased P1 and P2 latencies. Thus, exposure to a single perturbation can affect responses to subsequent perturbations. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  7. Implementing a new model for on-the-job training: critical success factors.

    NARCIS (Netherlands)

    van Zolingen, S.J.; Streumer, Jan; van der Klink, Marcel; de Jong, Rolinda

    2000-01-01

    Post Offices Inc. in The Netherlands has developed and implemented a new instruction model for the training of desk employees. The quality of the new instruction model was assessed by means of the evaluation model of Jacobs and Jones for on-the-job training. It is concluded that the implementation

  8. A Frequency Matching Method for Generation of a Priori Sample Models from Training Images

    DEFF Research Database (Denmark)

    Lange, Katrine; Cordua, Knud Skou; Frydendall, Jan

    2011-01-01

    This paper presents a Frequency Matching Method (FMM) for generation of a priori sample models based on training images and illustrates its use by an example. In geostatistics, training images are used to represent a priori knowledge or expectations of models, and the FMM can be used to generate...... new images that share the same multi-point statistics as a given training image. The FMM proceeds by iteratively updating voxel values of an image until the frequency of patterns in the image matches the frequency of patterns in the training image; making the resulting image statistically...... indistinguishable from the training image....

  9. Accurate estimation of CO2 adsorption on activated carbon with multi-layer feed-forward neural network (MLFNN algorithm

    Directory of Open Access Journals (Sweden)

    Alireza Rostami

    2018-03-01

    Full Text Available Global warming due to greenhouse effect has been considered as a serious problem for many years around the world. Among the different gases which cause greenhouse gas effect, carbon dioxide is of great difficulty by entering into the surrounding atmosphere. So CO2 capturing and separation especially by adsorption is one of the most interesting approaches because of the low equipment cost, ease of operation, simplicity of design, and low energy consumption.In this study, experimental results are presented for the adsorption equilibria of carbon dioxide on activated carbon. The adsorption equilibrium data for carbon dioxide were predicted with two commonly used isotherm models in order to compare with multi-layer feed-forward neural network (MLFNN algorithm for a wide range of partial pressure. As a result, the ANN-based algorithm shows much better efficiency and accuracy than the Sips and Langmuir isotherms. In addition, the applicability of the Sips and Langmuir models are limited to isothermal conditions, even though the ANN-based algorithm is not restricted to the constant temperature condition. Consequently, it is proved that MLFNN algorithm is a promising model for calculation of CO2 adsorption density on activated carbon. Keywords: Global warming, CO2 adsorption, Activated carbon, Multi-layer feed-forward neural network algorithm, Statistical quality measures

  10. On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation

    OpenAIRE

    He, Tianxing; Zhang, Yu; Droppo, Jasha; Yu, Kai

    2016-01-01

    We propose to train bi-directional neural network language model(NNLM) with noise contrastive estimation(NCE). Experiments are conducted on a rescore task on the PTB data set. It is shown that NCE-trained bi-directional NNLM outperformed the one trained by conventional maximum likelihood training. But still(regretfully), it did not out-perform the baseline uni-directional NNLM.

  11. A Model for Behavioral Management and Relationship Training for Parents in Groups,

    Science.gov (United States)

    Behavior, Human relations, *Training, *Families(Human), Symposia, Models, Children, Psychotherapy, Problem solving, Management, Control, Learning, Skills, Decision making , Group dynamics, Military psychology, Military medicine

  12. Glucocorticoid and cytokine crosstalk: Feedback, feedforward, and co-regulatory interactions determine repression or resistance.

    Science.gov (United States)

    Newton, Robert; Shah, Suharsh; Altonsy, Mohammed O; Gerber, Antony N

    2017-04-28

    Inflammatory signals induce feedback and feedforward systems that provide temporal control. Although glucocorticoids can repress inflammatory gene expression, glucocorticoid receptor recruitment increases expression of negative feedback and feedforward regulators, including the phosphatase, DUSP1, the ubiquitin-modifying enzyme, TNFAIP3, or the mRNA-destabilizing protein, ZFP36. Moreover, glucocorticoid receptor cooperativity with factors, including nuclear factor-κB (NF-κB), may enhance regulator expression to promote repression. Conversely, MAPKs, which are inhibited by glucocorticoids, provide feedforward control to limit expression of the transcription factor IRF1, and the chemokine, CXCL10. We propose that modulation of feedback and feedforward control can determine repression or resistance of inflammatory gene expression toglucocorticoid. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  13. Notions of local controllability and optimal feedforward control for quantum systems

    International Nuclear Information System (INIS)

    Chakrabarti, Raj

    2011-01-01

    Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

  14. Feedforward control of a closed-loop piezoelectric translation stage for atomic force microscope.

    Science.gov (United States)

    Li, Yang; Bechhoefer, John

    2007-01-01

    Simple feedforward ideas are shown to lead to a nearly tenfold increase in the effective bandwidth of a closed-loop piezoelectric positioning stage used in scanning probe microscopy. If the desired control signal is known in advance, the feedforward filter can be acausal: the information about the future can be used to make the output of the stage have almost no phase lag with respect to the input. This keeps in register the images assembled from right and left scans. We discuss the design constraints imposed by the need for the feedforward filter to work robustly under a variety of circumstances. Because the feedforward needs only to modify the input signal, it can be added to any piezoelectric stage, whether closed or open loop.

  15. Notions of local controllability and optimal feedforward control for quantum systems

    Energy Technology Data Exchange (ETDEWEB)

    Chakrabarti, Raj, E-mail: rchakra@purdue.edu [School of Chemical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

    2011-05-06

    Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

  16. Communication skills training: describing a new conceptual model.

    Science.gov (United States)

    Brown, Richard F; Bylund, Carma L

    2008-01-01

    Current research in communication in physician-patient consultations is multidisciplinary and multimethodological. As this research has progressed, a considerable body of evidence on the best practices in physician-patient communication has been amassed. This evidence provides a foundation for communication skills training (CST) at all levels of medical education. Although the CST literature has demonstrated that communication skills can be taught, one critique of this literature is that it is not always clear which skills are being taught and whether those skills are matched with those being assessed. The Memorial Sloan-Kettering Cancer Center Comskil Model for CST seeks to answer those critiques by explicitly defining the important components of a consultation, based on Goals, Plans, and Actions theories and sociolinguistic theory. Sequenced guidelines as a mechanism for teaching about particular communication challenges are adapted from these other methods. The authors propose that consultation communication can be guided by an overarching goal, which is achieved through the use of a set of predetermined strategies. Strategies are common in CST; however, strategies often contain embedded communication skills. These skills can exist across strategies, and the Comskil Model seeks to make them explicit in these contexts. Separate from the skills are process tasks and cognitive appraisals that need to be addressed in teaching. The authors also describe how assessment practices foster concordance between skills taught and those assessed through careful coding of trainees' communication encounters and direct feedback.

  17. Off-the-job microsurgical training on dry models: Siberian experience.

    Science.gov (United States)

    Belykh, Evgenii; Byvaltsev, Vadim

    2014-01-01

    Microsurgical training has become an obligatory part of many neurosurgical training programs. To assess the cost and effectiveness of acquiring and maintaining microneurosurgical skills by training on an off-the-job basis using dry models. A dry off-the-job microneurosurgical training module was set up. Training exercises involved microdissection in a deep operation field, suturing and tying on gauze, untying, pushing of thread end, and microanastomosis. The time to complete the task and success rate were evaluated. The total cost of all necessary equipment and expendables for the training module was US$910. Fifteen residents participated in the continuous off-the-job training. The average time taken to perform the anastomosis decreased after the month of training from 90 to 20 minutes. Authors revealed that at 2 months, the total time and time to complete anastomosis increased significantly for the participants who discontinued practice after the first month, compared with those who just practiced suturing on gauze after the first month (P job training showed to be readily available and can be helpful for microsurgical training in the low-income regions of the world. Our data suggest that microsurgical training should be continuous and repetitive. Simulation training may benefit from models for repetitive training of relevant technical part-skills. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. On the approximation by single hidden layer feedforward neural networks with fixed weights

    OpenAIRE

    Guliyev, Namig J.; Ismailov, Vugar E.

    2017-01-01

    International audience; Feedforward neural networks have wide applicability in various disciplines of science due to their universal approximation property. Some authors have shown that single hidden layer feedforward neural networks (SLFNs) with fixed weights still possess the universal approximation property provided that approximated functions are univariate. But this phenomenon does not lay any restrictions on the number of neurons in the hidden layer. The more this number, the more the p...

  19. Cortical feedback signals generalise across different spatial frequencies of feedforward inputs

    OpenAIRE

    Revina, Yulia; Petro, Lucy S.; Muckli, Lars

    2017-01-01

    Visual processing in cortex relies on feedback projections contextualising feedforward information flow. Primary visual cortex (V1) has small receptive fields and processes feedforward information at a fine-grained spatial scale, whereas higher visual areas have larger, spatially invariant receptive fields. Therefore, feedback could provide coarse information about the global scene structure or alternatively recover fine-grained structure by targeting small receptive fields in V1. We tested i...

  20. Modeling of the radiation belt megnetosphere in decisional timeframes

    Science.gov (United States)

    Koller, Josef; Reeves, Geoffrey D; Friedel, Reiner H.W.

    2013-04-23

    Systems and methods for calculating L* in the magnetosphere with essentially the same accuracy as with a physics based model at many times the speed by developing a surrogate trained to be a surrogate for the physics-based model. The trained model can then beneficially process input data falling within the training range of the surrogate model. The surrogate model can be a feedforward neural network and the physics-based model can be the TSK03 model. Operatively, the surrogate model can use parameters on which the physics-based model was based, and/or spatial data for the location where L* is to be calculated. Surrogate models should be provided for each of a plurality of pitch angles. Accordingly, a surrogate model having a closed drift shell can be used from the plurality of models. The feedforward neural network can have a plurality of input-layer units, there being at least one input-layer unit for each physics-based model parameter, a plurality of hidden layer units and at least one output unit for the value of L*.

  1. Mathematical models of human paralyzed muscle after long-term training.

    Science.gov (United States)

    Law, L A Frey; Shields, R K

    2007-01-01

    Spinal cord injury (SCI) results in major musculoskeletal adaptations, including muscle atrophy, faster contractile properties, increased fatigability, and bone loss. The use of functional electrical stimulation (FES) provides a method to prevent paralyzed muscle adaptations in order to sustain force-generating capacity. Mathematical muscle models may be able to predict optimal activation strategies during FES, however muscle properties further adapt with long-term training. The purpose of this study was to compare the accuracy of three muscle models, one linear and two nonlinear, for predicting paralyzed soleus muscle force after exposure to long-term FES training. Further, we contrasted the findings between the trained and untrained limbs. The three models' parameters were best fit to a single force train in the trained soleus muscle (N=4). Nine additional force trains (test trains) were predicted for each subject using the developed models. Model errors between predicted and experimental force trains were determined, including specific muscle force properties. The mean overall error was greatest for the linear model (15.8%) and least for the nonlinear Hill Huxley type model (7.8%). No significant error differences were observed between the trained versus untrained limbs, although model parameter values were significantly altered with training. This study confirmed that nonlinear models most accurately predict both trained and untrained paralyzed muscle force properties. Moreover, the optimized model parameter values were responsive to the relative physiological state of the paralyzed muscle (trained versus untrained). These findings are relevant for the design and control of neuro-prosthetic devices for those with SCI.

  2. ISC feedforward control of gasoline engine. Adaptive system using neural network; Jidoshayo gasoline engine no ISC feedforward seigyo. Neural network wo mochiita tekioka

    Energy Technology Data Exchange (ETDEWEB)

    Kinugawa, N; Morita, S; Takiyama, T [Osaka City University, Osaka (Japan)

    1997-10-01

    For fuel economy and a good driver`s feeling, it is necessary for idle-speed to keep at a constant low speed. But keeping low speed has danger of engine stall when the engine torque is disturbed by the alternator, and so on. In this paper, adaptive feedforward idle-speed control system against electrical loads was investigated. This system was based on the reversed tansfer functions of the object system, and a neural network was used to adapt this system for aging. Then, this neural network was also used for creating feedforward table map. Good experimental results were obtained. 2 refs., 11 figs.

  3. Proinflammatory Cytokine Infusion Attenuates LH's Feedforward on Testosterone Secretion: Modulation by Age

    Science.gov (United States)

    Yang, Rebecca; Roelfsema, Ferdinand; Takahashi, Paul

    2016-01-01

    Context: In the experimental animal, inflammatory signals quench LH's feedforward drive of testosterone (T) secretion and appear to impair GnRH-LH output. The degree to which such suppressive effects operate in the human is not known. Objective: To test the hypothesis that IL-2 impairs LH's feedforward drive on T and T's feedback inhibition of LH secretion in healthy men. Setting: Mayo Center for Translational Science Activities. Patients or Other Participants: A total of 35 healthy men, 17 young and 18 older. Interventions: Randomized prospective double-blind saline-controlled study of IL-2 infusion in 2 doses with concurrent 10-minute blood sampling for 24 hours. Main Outcome Measures: Deconvolution analysis of LH and T secretion. Results: After saline injection, older compared with young men exhibited reduced LH feedforward drive on T secretion (P feedback inhibition of LH secretion (P feedforward onto T secretion declined markedly especially in young subjects (P feedback on LH secretion especially in older volunteers. Conclusion: This investigation confirms combined feedforward and feedback deficits in older relative to young men given saline and demonstrates 1) joint mechanisms by which IL-2 enforces biochemical hypogonadism, viz, combined feedforward block and feedback amplification; and 2) unequal absolute inhibition of T and LH secretion by IL-2 in young and older men. These outcomes establish that the male gonadal axis is susceptible to dual-site suppression by a prototypic inflammatory mediator. Thus, we postulate that selected ILs might also enforce male hypogonadism in chronic systemic inflammation. PMID:26600270

  4. Short-term Synaptic Depression in the Feedforward Inhibitory Circuit in the Dorsal Lateral Geniculate Nucleus.

    Science.gov (United States)

    Augustinaite, Sigita; Heggelund, Paul

    2018-05-24

    Synaptic short-term plasticity (STP) regulates synaptic transmission in an activity-dependent manner and thereby has important roles in the signal processing in the brain. In some synapses, a presynaptic train of action potentials elicits post-synaptic potentials that gradually increase during the train (facilitation), but in other synapses, these potentials gradually decrease (depression). We studied STP in neurons in the visual thalamic relay, the dorsal lateral geniculate nucleus (dLGN). The dLGN contains two types of neurons: excitatory thalamocortical (TC) neurons, which transfer signals from retinal afferents to visual cortex, and local inhibitory interneurons, which form an inhibitory feedforward loop that regulates the thalamocortical signal transmission. The overall STP in the retino-thalamic relay is short-term depression, but the distinct kind and characteristics of the plasticity at the different types of synapses are unknown. We studied STP in the excitatory responses of interneurons to stimulation of retinal afferents, in the inhibitory responses of TC neurons to stimulation of afferents from interneurons, and in the disynaptic inhibitory responses of TC neurons to stimulation of retinal afferents. Moreover, we studied STP at the direct excitatory input to TC neurons from retinal afferents. The STP at all types of the synapses showed short-term depression. This depression can accentuate rapid changes in the stream of signals and thereby promote detectability of significant features in the sensory input. In vision, detection of edges and contours is essential for object perception, and the synaptic short-term depression in the early visual pathway provides important contributions to this detection process. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

  5. Improving real-time train dispatching : Models, algorithms and applications

    NARCIS (Netherlands)

    D'Ariano, A.

    2008-01-01

    Traffic controllers monitor railway traffic sequencing train movements and setting routes with the aim of ensuring smooth train behaviour and limiting as much as existing delays. Due to the strict time limit available for computing a new timetable during operations, which so far is rather infeasible

  6. The Applicant Based Training Model Setting Conditions for Recruiting Success

    Science.gov (United States)

    2002-07-01

    the RS XO is another critical 32. function that falls into the scope of their responsibly and requires specific training in marketing and advertising . During...Phase I require a solid working knowledge of marketing and advertising . OpsO: Phase II actions require the OpsO receive advanced training in data

  7. Effective Employment-Based Training Models for Childcare Workers

    Science.gov (United States)

    Choy, Sarojni; Haukka, Sandra

    2010-01-01

    Childcare workers play a significant role in the learning and development of children in their care. This has major implications for the training of workers. Under new reforms of the childcare industry, the Australian government now requires all workers to obtain qualifications from a vocational education and training provider (e.g. Technical and…

  8. Learning to breathe? Feedforward regulation of the inspiratory motor drive.

    Science.gov (United States)

    Zaman, Jonas; Van den Bergh, Omer; Fannes, Stien; Van Diest, Ilse

    2014-09-15

    Claims have been made that breathing is in part controlled by feedforward regulation. In a classical conditioning paradigm, we investigated anticipatory increases in the inspiratory motor drive as measured by inspiratory occlusion pressure (P100). In an acquisition phase, an experimental group (N=13) received a low-intensity resistive load (5 cmH2O/l/s) for three consecutive inspirations as Conditioned Stimulus (CS), preceding a load of a stronger intensity (20 cmH2O/l/s) for three subsequent inspirations as unconditioned stimulus (US). The control group (N=11) received the low-intensity load for six consecutive inspirations. In a post-acquisition phase both groups received the low-intensity load for six consecutive inspirations. Responses to the CS-load only differed between groups during the first acquisition trials and a strong increase in P100 during the US-loads was observed, which habituated across the experiment. Our results suggest that the disruption caused by adding low to moderate resistive loads to three consecutive inspirations results in a short-lasting anticipatory increase in inspiratory motor drive. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Adaptive Feed-Forward Control of Low Frequency Interior Noise

    CERN Document Server

    Kletschkowski, Thomas

    2012-01-01

    This book presents a mechatronic approach to Active Noise Control (ANC). It describes the required elements of system theory, engineering acoustics, electroacoustics and adaptive signal processing in a comprehensive, consistent and systematic manner using a unified notation. Furthermore, it includes a design methodology for ANC-systems, explains its application and describes tools to be used for ANC-system design. From the research point of view, the book presents new approaches to sound source localization in weakly damped interiors. One is based on the inverse finite element method, the other is based on a sound intensity probe with an active free field. Furthermore, a prototype of an ANC-system able to reach the physical limits of local (feed-forward) ANC is described. This is one example for applied research in ANC-system design. Other examples are given for (i) local ANC in a semi-enclosed subspace of an aircraft cargo hold and (ii) for the combination of audio entertainment with ANC.

  10. Multivisceral transplantation in pigs: a model for research and training

    Directory of Open Access Journals (Sweden)

    André Ibrahim David

    2011-09-01

    Full Text Available Objective: To present a model for research and training inmultivisceral transplantation in pigs. Methods: Eight LargeWhite pigs (four donors and four recipients were operated. Themultivisceral transplant with stomach, duodenum, pancreas,liver and intestine was performed similarly to transplantation inhumans with a few differences, described below. Anastomoseswere performed as follows: end-to-end from the supra-hepaticvena cava of the graft to the recipient juxta diaphragmatic venacava; end-to-end from the infra-hepatic vena cava of the graftto the inferior (suprarenal vena cava of the recipient; and endto-side patch of the aorta of the graft to the infrarenal aortaof the recipient plus digestive reconstruction. Results: Theperformance of the multivisceral transplantion was possible inall four animals. Reperfusions of the multivisceral graft led to asevere ischemia-reperfusion syndrome, despite flushing of thegraft. The animals presented with hypotension and the need forhigh doses of vasoactive drugs, and all of them were sacrificedafter discontinuing these drugs. Conclusion: Some alternativesto minimize the ischemia-reperfusion syndrome, such as the useof another vasoactive drug, use of a third pig merely for bloodtransfusion, presence of an anesthesia team in the operatingroom, and reduction of the graft, will be the next steps to enableexperimental studies.

  11. Constructing Teaching Model for Training English Guides of Stone In-scription Relics

    Institute of Scientific and Technical Information of China (English)

    李慧

    2016-01-01

    A teaching model based on constructivism is proposed in this paper. The model contains five teaching steps, e.g. inter-pretation teaching, questioning-dialogue, knowledge and skills teaching, discussion-collaboration and field training. Practice proves that it can effectively improve the training efficiency of the training of English guides of stone inscription relics and en-hance their interpretation quality and English skills.

  12. Testing an empirically derived mental health training model featuring small groups, distributed practice and patient discussion.

    Science.gov (United States)

    Murrihy, Rachael C; Byrne, Mitchell K; Gonsalvez, Craig J

    2009-02-01

    Internationally, family doctors seeking to enhance their skills in evidence-based mental health treatment are attending brief training workshops, despite clear evidence in the literature that short-term, massed formats are not likely to improve skills in this complex area. Reviews of the educational literature suggest that an optimal model of training would incorporate distributed practice techniques; repeated practice over a lengthy time period, small-group interactive learning, mentoring relationships, skills-based training and an ongoing discussion of actual patients. This study investigates the potential role of group-based training incorporating multiple aspects of good pedagogy for training doctors in basic competencies in brief cognitive behaviour therapy (BCBT). Six groups of family doctors (n = 32) completed eight 2-hour sessions of BCBT group training over a 6-month period. A baseline control design was utilised with pre- and post-training measures of doctors' BCBT skills, knowledge and engagement in BCBT treatment. Family doctors' knowledge, skills in and actual use of BCBT with patients improved significantly over the course of training compared with the control period. This research demonstrates preliminary support for the efficacy of an empirically derived group training model for family doctors. Brief CBT group-based training could prove to be an effective and viable model for future doctor training.

  13. Microsurgical Bypass Training Rat Model: Part 2-Anastomosis Configurations.

    Science.gov (United States)

    Tayebi Meybodi, Ali; Lawton, Michael T; Yousef, Sonia; Mokhtari, Pooneh; Gandhi, Sirin; Benet, Arnau

    2017-11-01

    Mastery of microsurgical anastomosis is key to achieving good outcomes in cerebrovascular bypass procedures. Animal models (especially rodents) provide an optimal preclinical bypass training platform. However, the existing models for practicing different anastomosis configurations have several limitations. We sought to optimize the use of the rat's abdominal aorta and common iliac arteries (CIA) for practicing the 3 main anastomosis configurations commonly used in cerebrovascular surgery. Thirteen male Sprague-Dawley rats underwent inhalant anesthesia. The abdominal aorta and the CIAs were exposed. The distances between the major branches of the aorta were measured to find the optimal location for an end-to-end anastomosis. Also, the feasibility of performing side-to-side and end-to-side anastomoses between the CIAs was assessed. All bypass configurations could be performed between the left renal artery and the CIA bifurcation. The longest segments of the aorta without major branches were 1) between the left renal and left iliolumbar arteries (16.9 mm ± 4.6), and 2) between the right iliolumbar artery and the aortic bifurcation (9.7 mm ± 4.7). The CIAs could be juxtaposed for an average length of 7.6 mm ± 1.3, for a side-to-side anastomosis. The left CIA could be successfully reimplanted on to the right CIA at an average distance of 9.1 mm ± 1.6 from the aortic bifurcation. Our results show that rat's abdominal aorta and CIAs may be effectively used for all the anastomosis configurations used in cerebral revascularization procedures. We also provide technical nuances and anatomic descriptions to plan for practicing each bypass configuration. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability

    International Nuclear Information System (INIS)

    Ouyang, Min; Zhao, Lijing; Hong, Liu; Pan, Zhezhe

    2014-01-01

    Recently numerous studies have applied complex network based models to study the performance and vulnerability of infrastructure systems under various types of attacks and hazards. But how effective are these models to capture their real performance response is still a question worthy of research. Taking the Chinese railway system as an example, this paper selects three typical complex network based models, including purely topological model (PTM), purely shortest path model (PSPM), and weight (link length) based shortest path model (WBSPM), to analyze railway accessibility and flow-based vulnerability and compare their results with those from the real train flow model (RTFM). The results show that the WBSPM can produce the train routines with 83% stations and 77% railway links identical to the real routines and can approach the RTFM the best for railway vulnerability under both single and multiple component failures. The correlation coefficient for accessibility vulnerability from WBSPM and RTFM under single station failures is 0.96 while it is 0.92 for flow-based vulnerability; under multiple station failures, where each station has the same failure probability fp, the WBSPM can produce almost identical vulnerability results with those from the RTFM under almost all failures scenarios when fp is larger than 0.62 for accessibility vulnerability and 0.86 for flow-based vulnerability

  15. A new beating-heart off-pump coronary artery bypass grafting training model

    NARCIS (Netherlands)

    Bouma, Wobbe; Kuijpers, Michiel; Bijleveld, Aanke; De Maat, Gijs E.; Koene, Bart M.; Erasmus, Michiel E.; Natour, Ehsan; Mariani, Massimo A.

    OBJECTIVES: Training models are essential in mastering the skills required for off-pump coronary artery bypass grafting (OPCAB). We describe a new, high-fidelity, effective and reproducible beating-heart OPCAB training model in human cadavers. METHODS: Human cadavers were embalmed according to the

  16. An Effective Procedure for Training Early Special Education Teams to Implement a Model Program.

    Science.gov (United States)

    Rogers, Sally J.; And Others

    1987-01-01

    Training of early special education teams (serving 11 autistic and 10 developmentally-delayed children) to use the Playschool model resulted in: positive perception of the training's value; increases in knowledge about child development, infantile autism, and the model; increased use of Playschool techniques; and positive developmental changes in…

  17. Optimizing Intermodal Train Schedules with a Design Balanced Network Design Model

    DEFF Research Database (Denmark)

    Pedersen, Michael Berliner; Crainic, Teodor Gabriel

    We present a modeling approach for optimizing intermodal trains schedules based on an infrastructure divided into time-dependent train paths. The formulation can be generalized to a capacitated multi commodity network design model with additional design balance constraints. We present a Tabu Search...

  18. Study on Innovation of Teacher Training Model in Basic Education from the Perspective of "Blended Learning"

    Science.gov (United States)

    Bu, Huabai; Bu, Shizhen

    2012-01-01

    Gradual integration of synergetic technology, P2P technology and online learning community furnishes a new research field for innovation of teacher training model in a knowledge economy era. This article proposes the innovative model of "whole of three lines" in teacher training in basic education from the perspective of "blended…

  19. Development of an Accurate Feed-Forward Temperature Control Tankless Water Heater

    Energy Technology Data Exchange (ETDEWEB)

    David Yuill

    2008-06-30

    The following document is the final report for DE-FC26-05NT42327: Development of an Accurate Feed-Forward Temperature Control Tankless Water Heater. This work was carried out under a cooperative agreement from the Department of Energy's National Energy Technology Laboratory, with additional funding from Keltech, Inc. The objective of the project was to improve the temperature control performance of an electric tankless water heater (TWH). The reason for doing this is to minimize or eliminate one of the barriers to wider adoption of the TWH. TWH use less energy than typical (storage) water heaters because of the elimination of standby losses, so wider adoption will lead to reduced energy consumption. The project was carried out by Building Solutions, Inc. (BSI), a small business based in Omaha, Nebraska. BSI partnered with Keltech, Inc., a manufacturer of electric tankless water heaters based in Delton, Michigan. Additional work was carried out by the University of Nebraska and Mike Coward. A background study revealed several advantages and disadvantages to TWH. Besides using less energy than storage heaters, TWH provide an endless supply of hot water, have a longer life, use less floor space, can be used at point-of-use, and are suitable as boosters to enable alternative water heating technologies, such as solar or heat-pump water heaters. Their disadvantages are their higher cost, large instantaneous power requirement, and poor temperature control. A test method was developed to quantify performance under a representative range of disturbances to flow rate and inlet temperature. A device capable of conducting this test was designed and built. Some heaters currently on the market were tested, and were found to perform quite poorly. A new controller was designed using model predictive control (MPC). This control method required an accurate dynamic model to be created and required significant tuning to the controller before good control was achieved. The MPC

  20. Using an electrohydraulic ankle foot orthosis to study modifications in feedforward control during locomotor adaptation to force fields applied in stance.

    Science.gov (United States)

    Noel, Martin; Fortin, Karine; Bouyer, Laurent J

    2009-06-03

    locomotion. Our data suggest that, for short duration exposure, a feedforward modification in torque output occurs during mid-stance but not during push-off. These findings are important for the design of novel rehabilitation methods, as they suggest that the ability to use resistive force fields for training may depend on targeted gait phases.

  1. Using an electrohydraulic ankle foot orthosis to study modifications in feedforward control during locomotor adaptation to force fields applied in stance

    Directory of Open Access Journals (Sweden)

    Bouyer Laurent J

    2009-06-01

    control of the ankle during locomotion. Our data suggest that, for short duration exposure, a feedforward modification in torque output occurs during mid-stance but not during push-off. These findings are important for the design of novel rehabilitation methods, as they suggest that the ability to use resistive force fields for training may depend on targeted gait phases.

  2. Using an electrohydraulic ankle foot orthosis to study modifications in feedforward control during locomotor adaptation to force fields applied in stance

    Science.gov (United States)

    Noel, Martin; Fortin, Karine; Bouyer, Laurent J

    2009-01-01

    during locomotion. Our data suggest that, for short duration exposure, a feedforward modification in torque output occurs during mid-stance but not during push-off. These findings are important for the design of novel rehabilitation methods, as they suggest that the ability to use resistive force fields for training may depend on targeted gait phases. PMID:19493356

  3. Modeling the residual effects and threshold saturation of training: a case study of Olympic swimmers.

    Science.gov (United States)

    Hellard, Philippe; Avalos, Marta; Millet, Gregoire; Lacoste, Lucien; Barale, Frederic; Chatard, Jean-Claude

    2005-02-01

    The aim of this study was to model the residual effects of training on the swimming performance and to compare a model that includes threshold saturation (MM) with the Banister model (BM). Seven Olympic swimmers were studied over a period of 4 +/- 2 years. For 3 training loads (low-intensity w(LIT), high-intensity w(HIT), and strength training w(ST)), 3 residual training effects were determined: short-term (STE) during the taper phase (i.e., 3 weeks before the performance [weeks 0, 1, and 2]), intermediate-term (ITE) during the intensity phase (weeks 3, 4, and 5), and long-term (LTE) during the volume phase (weeks 6, 7, and 8). ITE and LTE were positive for w(HIT) and w(LIT), respectively (p measures indicated that MM compares favorably with BM. Identifying individual training thresholds may help individualize the distribution of training loads.

  4. A generic model for evaluation of the Federal Aviation Administration air traffic control specialist training programs.

    Science.gov (United States)

    1982-03-01

    The Systems Analysis Research Unit at the Civil Aeromedical Institute (CAMI) has developed a generic model for Federal Aviation Administration (FAA) Academy training program evaluation. The model will serve as a basis for integrating the total data b...

  5. Reduction in training time of a deep learning model in detection of lesions in CT

    Science.gov (United States)

    Makkinejad, Nazanin; Tajbakhsh, Nima; Zarshenas, Amin; Khokhar, Ashfaq; Suzuki, Kenji

    2018-02-01

    Deep learning (DL) emerged as a powerful tool for object detection and classification in medical images. Building a well-performing DL model, however, requires a huge number of images for training, and it takes days to train a DL model even on a cutting edge high-performance computing platform. This study is aimed at developing a method for selecting a "small" number of representative samples from a large collection of training samples to train a DL model for the could be used to detect polyps in CT colonography (CTC), without compromising the classification performance. Our proposed method for representative sample selection (RSS) consists of a K-means clustering algorithm. For the performance evaluation, we applied the proposed method to select samples for the training of a massive training artificial neural network based DL model, to be used for the classification of polyps and non-polyps in CTC. Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance equivalent to the model trained using the full training set. We compare the performance using area under the receiveroperating- characteristic curve (AUC).

  6. Train flow chaos analysis based on an improved cellular automata model

    International Nuclear Information System (INIS)

    Meng, Xuelei; Xiang, Wanli; Jia, Limin; Xu, Jie

    2015-01-01

    To control the chaos in the railway traffic flow and offer valuable information for the dispatchers of the railway system, an improved cellular model is presented to detect and analyze the chaos in the traffic flow. We first introduce the working mechanism of moving block system, analyzing the train flow movement characteristics. Then we improve the cellular model on the evolution rules to adjust the train flow movement. We give the train operation steps from three cases: the trains running on a railway section, a train will arrive in a station and a train will departure from a station. We simulate 4 trains to run on a high speed section fixed with moving block system and record the distances between the neighbor trains and draw the Poincare section to analyze the chaos in the train operation. It is concluded that there is not only chaos but order in the train operation system with moving blocking system and they can interconvert to each other. The findings have the potential value in train dispatching system construction and offer supporting information for the daily dispatching work.

  7. Houston, We Have a Problem Solving Model for Training

    Science.gov (United States)

    Schmidt, Lacey; Slack, Kelley; Keeton, Kathryn; Barshi, Immanuel; Martin, Lynne; Mauro, Robert; O'Keefe, William; Baldwin, Evelyn; Huning, Therese

    2011-01-01

    In late 2006, the Mission Operations Directorate (MOD) at NASA began looking at ways to make training more efficient for the flight controllers who support the International Space Station. The average certification times for flight controllers spanned from 18 months to three years and the MOD, responsible for technical training, was eager to develop creative solutions that would reduce the time to 12 months. Additionally, previously trained flight controllers sometimes participated in more than 50 very costly, eight-hour integrated simulations before becoming certified. New trainees needed to gain proficiency with far fewer lessons and training simulations than their predecessors. This poster presentation reviews the approach and the process that is currently in development to accomplish this goal.

  8. TRAINING OF NUMERICAL CONTROL MACHINES OPERATORS: MODEL OF SYNTHESIS

    Directory of Open Access Journals (Sweden)

    A. M. Silvestrov

    2016-09-01

    Full Text Available There are topical issues of development of the automated system intended for assessment of level of competence of industrial enterprises divisions for planning of training actions of specialists in automation of engineering processes are determined in article.

  9. Training Community Modeling and Simulation Business Plan: 2008 Edition

    Science.gov (United States)

    2009-12-01

    and Cyber Constructive Environment– Information Operations System ASCOT Airspace Control and Operations Trainer ASDA Advanced Seal Delivery System...Advanced Seal Delivery System ( ASDA ). Simulates a submarine training system for providing stealthy submerged transportation for insertion into Special

  10. EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

    OpenAIRE

    Hayati .; Retno Dwi Suyanti

    2013-01-01

    The objective in this research: (1) Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2) Determine the level of motivation to learn in affects physics student learning outcomes. (3) Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all s...

  11. Disorder Identification in Hysteresis Data: Recognition Analysis of the Random-Bond-Random-Field Ising Model

    International Nuclear Information System (INIS)

    Ovchinnikov, O. S.; Jesse, S.; Kalinin, S. V.; Bintacchit, P.; Trolier-McKinstry, S.

    2009-01-01

    An approach for the direct identification of disorder type and strength in physical systems based on recognition analysis of hysteresis loop shape is developed. A large number of theoretical examples uniformly distributed in the parameter space of the system is generated and is decorrelated using principal component analysis (PCA). The PCA components are used to train a feed-forward neural network using the model parameters as targets. The trained network is used to analyze hysteresis loops for the investigated system. The approach is demonstrated using a 2D random-bond-random-field Ising model, and polarization switching in polycrystalline ferroelectric capacitors.

  12. Active vibration control for piezoelectricity cantilever beam: an adaptive feedforward control method

    Science.gov (United States)

    Zhu, Qiao; Yue, Jun-Zhou; Liu, Wei-Qun; Wang, Xu-Dong; Chen, Jun; Hu, Guang-Di

    2017-04-01

    This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Due to that the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is employed to put an equivalent disturbance into the input channel. In this situation, the vibration control can be achieved by setting the control input be the identified EID. Then, for the EID with known multiple frequencies, the AFC is introduced to perfectly reject the vibration but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of EID in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis (TFA) method is employed to precisely identify the unknown frequencies. Consequently, a TFA-based AFC algorithm is proposed to the active vibration control with unknown frequencies. Finally, four cases are given to illustrate the efficiency of the proposed TFA-based AFC algorithm by experiment.

  13. Limits to the development of feed-forward structures in large recurrent neuronal networks

    Directory of Open Access Journals (Sweden)

    Susanne Kunkel

    2011-02-01

    Full Text Available Spike-timing dependent plasticity (STDP has traditionally been of great interest to theoreticians, as it seems to provide an answer to the question of how the brain can develop functional structure in response to repeated stimuli. However, despite this high level of interest, convincing demonstrations of this capacity in large, initially random networks have not been forthcoming. Such demonstrations as there are typically rely on constraining the problem artificially. Techniques include employing additional pruning mechanisms or STDP rules that enhance symmetry breaking, simulating networks with low connectivity that magnify competition between synapses, or combinations of the above. In this paper we first review modeling choices that carry particularly high risks of producing non-generalizable results in the context of STDP in recurrent networks. We then develop a theory for the development of feed-forward structure in random networks and conclude that an unstable fixed point in the dynamics prevents the stable propagation of structure in recurrent networks with weight-dependent STDP. We demonstrate that the key predictions of the theory hold in large-scale simulations. The theory provides insight into the reasons why such development does not take place in unconstrained systems and enables us to identify candidate biologically motivated adaptations to the balanced random network model that might enable it.

  14. Short-Term Load Forecasting Model Based on Quantum Elman Neural Networks

    Directory of Open Access Journals (Sweden)

    Zhisheng Zhang

    2016-01-01

    Full Text Available Short-term load forecasting model based on quantum Elman neural networks was constructed in this paper. The quantum computation and Elman feedback mechanism were integrated into quantum Elman neural networks. Quantum computation can effectively improve the approximation capability and the information processing ability of the neural networks. Quantum Elman neural networks have not only the feedforward connection but also the feedback connection. The feedback connection between the hidden nodes and the context nodes belongs to the state feedback in the internal system, which has formed specific dynamic memory performance. Phase space reconstruction theory is the theoretical basis of constructing the forecasting model. The training samples are formed by means of K-nearest neighbor approach. Through the example simulation, the testing results show that the model based on quantum Elman neural networks is better than the model based on the quantum feedforward neural network, the model based on the conventional Elman neural network, and the model based on the conventional feedforward neural network. So the proposed model can effectively improve the prediction accuracy. The research in the paper makes a theoretical foundation for the practical engineering application of the short-term load forecasting model based on quantum Elman neural networks.

  15. EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

    Directory of Open Access Journals (Sweden)

    Hayati .

    2013-06-01

    Full Text Available The objective in this research: (1 Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2 Determine the level of motivation to learn in affects physics student learning outcomes. (3 Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all students in class XI SMA Negeri 1 T.P Sunggal Semester I 2012/2013. The sample of this research was consisted of two classes with a sample of 70 peoples who are determined by purposive sampling, the IPA XI-2 as a class experiment using a model-based multimedia learning Training Inquiry as many as 35 peoples and XI IPA-3 as a control class using learning model Inquiry Training 35 peoples. Hypotheses were analyzed using the GLM at significant level of 0.05 using SPSS 17.0 for Windows. Based on data analysis and hypothesis testing conducted found that: (1 Training Inquiry-based multimedia learning model in improving student learning outcomes rather than learning model physics Inquiry Training. (2 The results of studying physics students who have high motivation to learn better than students who have a low learning motivation. (3 From this research there was an interaction between learning model inquiry-based multimedia training and motivation to study on learning outcomes of students.

  16. Training community mental health staff in Guangzhou, China: evaluation of the effect of a new training model.

    Science.gov (United States)

    Li, Jie; Li, Juan; Thornicroft, Graham; Yang, Hui; Chen, Wen; Huang, Yuanguang

    2015-10-26

    Increasing numbers of people with mental disorders receive services at primary care in China. The aims of this study are to evaluate impact of a new training course and supervision for community mental health staff to enhance their levels of mental health knowledge and to reduce their stigmatization toward people with mental illness. A total of 77 community mental health staff from eight regions in Guangzhou in China were recruited for the study.4 regions were randomly allocated to the new training model group, and 4 to the old training model group. Levels of mental health knowledge were measured by purpose-made assessment schedule and by the Mental Health Knowledge Schedule (MAKS). Stigma was evaluated by the Mental Illness: Clinicians' Attitudes Scale (MICA) and the Reported and Intended Behavior Scale (RIBS). Evaluation questionnaires were given at the beginning of course, at the end, and at 6 month and at 12 month follow-up. After the training period, the 6-month, and the 12-month, knowledge scores of the intervention group were higher than the control group. At 6-month and 12-month follow-up, means scores of MAKS of the intervention group increased more than the control group (both p training, at 6-months, and at 12-months, mean scores of RIBS of the intervention group increased more than the control (p training course and supervision, the new course improved community mental health staff knowledge of mental disorders, improving their attitudes toward people with mental disorder, and increasing their willingness to have contact with people with mental disorder.

  17. A self-adaptive feedforward rf control system for linacs

    International Nuclear Information System (INIS)

    Zhang Renshan; Ben-Zvi, I.; Xie Jialin

    1993-01-01

    The design and performance of a self-adaptive feedforward rf control system are reported. The system was built for the linac of the Accelerator Test Facility (ATF) at Brookhaven National Laboratory. Variables of time along the linac macropulse, such as field or phase are discretized and represented as vectors. Upon turn-on or after a large change in the operating-point, the control system acquires the response of the system to test signal vectors and generates a linearized system response matrix. During operation an error vector is generated by comparing the linac variable vectors and a target vector. The error vector is multiplied by the inverse of the system's matrix to generate a correction vector is added to an operating point vector. This control system can be used to control a klystron to produce flat rf amplitude and phase pulses, to control a rf cavity to reduce the rf field fluctuation, and to compensate the energy spread among bunches in a rf linac. Beam loading effects can be corrected and a programmed ramp can be produced. The performance of the control system has been evaluated on the control of a klystron's output as well as an rf cavity. Both amplitude and phase have been regulated simultaneously. In initial tests, the rf output from a klystron has been regulated to an amplitude fluctuation of less than ±0.3% and phase variation of less than ±0.6deg. The rf field of the ATF's photo-cathode microwave gun cavity has been regulated to ±5% in amplitude and simultaneously to ±1deg in phase. Regulating just the rf field amplitude in the rf gun cavity, we have achieved amplitude fluctuation of less than ±2%. (orig.)

  18. Feedforward neural control of toe walking in humans.

    Science.gov (United States)

    Lorentzen, Jakob; Willerslev-Olsen, Maria; Hüche Larsen, Helle; Svane, Christian; Forman, Christian; Frisk, Rasmus; Farmer, Simon Francis; Kersting, Uwe; Nielsen, Jens Bo

    2018-03-23

    Activation of ankle muscles at ground contact during toe walking is unaltered when sensory feedback is blocked or the ground is suddenly dropped. Responses in the soleus muscle to transcranial magnetic stimulation, but not peripheral nerve stimulation, are facilitated at ground contact during toe walking. We argue that toe walking is supported by feedforward control at ground contact. Toe walking requires careful control of the ankle muscles in order to absorb the impact of ground contact and maintain a stable position of the joint. The present study aimed to clarify the peripheral and central neural mechanisms involved. Fifteen healthy adults walked on a treadmill (3.0 km h -1 ). Tibialis anterior (TA) and soleus (Sol) EMG, knee and ankle joint angles, and gastrocnemius-soleus muscle fascicle lengths were recorded. Peripheral and central contributions to the EMG activity were assessed by afferent blockade, H-reflex testing, transcranial magnetic brain stimulation (TMS) and sudden unloading of the planter flexor muscle-tendon complex. Sol EMG activity started prior to ground contact and remained high throughout stance. TA EMG activity, which is normally seen around ground contact during heel strike walking, was absent. Although stretch of the Achilles tendon-muscle complex was observed after ground contact, this was not associated with lengthening of the ankle plantar flexor muscle fascicles. Sol EMG around ground contact was not affected by ischaemic blockade of large-diameter sensory afferents, or the sudden removal of ground support shortly after toe contact. Soleus motor-evoked potentials elicited by TMS were facilitated immediately after ground contact, whereas Sol H-reflexes were not. These findings indicate that at the crucial time of ankle stabilization following ground contact, toe walking is governed by centrally mediated motor drive rather than sensory driven reflex mechanisms. These findings have implications for our understanding of the control of

  19. An Active Seat Controller with Vehicle Suspension Feedforward and Feedback States: An Experimental Study

    Directory of Open Access Journals (Sweden)

    Abdulaziz Alfadhli

    2018-04-01

    Full Text Available Active seat suspensions can be used to reduce the harmful vertical vibration of a vehicle’s seat by applying an external force using a closed loop controller. Many of the controllers found in the literature are difficult to implement practically, because they are based on using unavailable or difficult and costly measurements. This paper presents both simulation and experimental studies of five novel, simple, and cost-effective control strategies to be used for an active seat suspension in order to improve ride comfort at low frequencies below 20 Hz. These strategies use available and measurable feedforward (preview information states from the vehicle secondary suspension, as well as feedback states from the seat suspension, together with gains optimised to minimise the occupant vibration. The gains were optimised using a genetic algorithm (GA, with a fitness function based on the seat effective amplitude transmissibility (SEAT factor. Constraints on the control force and the seat suspension stroke were also included in the optimisation algorithm. Simulation and laboratory experimental tests were carried out to assess the performance of the proposed controllers according to the ISO 2631-1 standard, in both the frequency and time domains with a range of different road profiles. The experimental tests were performed using a multi-axis simulation table (MAST and a physical active seat suspension configured as a hardware-in-loop (HIL simulation with a virtual linear quarter vehicle model (QvM. The results demonstrate that the proposed controllers substantially attenuate the vertical vibration at the driver’s seat compared with both a passive and a proportional-integral-derivative (PID active seat suspension and thus improve ride comfort together with reducing vibration-linked health risks. Moreover, experimental results show that employing both feedforward information and feedback vehicle body and seat acceleration signals in the controller

  20. Simulating train movement in an urban railway based on an improved car-following model

    International Nuclear Information System (INIS)

    Ye Jing-Jing; Jin Xin-Min; Li Ke-Ping

    2013-01-01

    Based on the optimal velocity car-following model, in this paper, we propose an improved model for simulating train movement in an urban railway in which the regenerative energy of a train is considered. Here a new additional term is introduced into a traditional car-following model. Our aim is to analyze and discuss the dynamic characteristics of the train movement when the regenerative energy is utilized by the electric locomotive. The simulation results indicate that the improved car-following model is suitable for simulating the train movement. Further, some qualitative relationships between regenerative energy and dynamic characteristics of a train are investigated, such as the measurement data of regenerative energy presents a power-law distribution. Our results are useful for optimizing the design and plan of urban railway systems. (general)

  1. A Model Train-The-Trainer Program for HACCP-Based Food Safety Training in the Retail/Food Service Industry: An Evaluation.

    Science.gov (United States)

    Martin, Kenneth E.; Knabel, Steve; Mendenhall, Von

    1999-01-01

    A survey showed states are adopting higher training and certification requirements for food-service workers. A train-the-trainer model was developed to prepare extension agents, health officers, and food-service managers to train others in food-safety procedures. (SK)

  2. Integrating molecular diagnostics into histopathology training: the Belfast model.

    Science.gov (United States)

    Flynn, C; James, J; Maxwell, P; McQuaid, S; Ervine, A; Catherwood, M; Loughrey, M B; McGibben, D; Somerville, J; McManus, D T; Gray, M; Herron, B; Salto-Tellez, M

    2014-07-01

    Molecular medicine is transforming modern clinical practice, from diagnostics to therapeutics. Discoveries in research are being incorporated into the clinical setting with increasing rapidity. This transformation is also deeply changing the way we practise pathology. The great advances in cell and molecular biology which have accelerated our understanding of the pathogenesis of solid tumours have been embraced with variable degrees of enthusiasm by diverse medical professional specialties. While histopathologists have not been prompt to adopt molecular diagnostics to date, the need to incorporate molecular pathology into the training of future histopathologists is imperative. Our goal is to create, within an existing 5-year histopathology training curriculum, the structure for formal substantial teaching of molecular diagnostics. This specialist training has two main goals: (1) to equip future practising histopathologists with basic knowledge of molecular diagnostics and (2) to create the option for those interested in a subspecialty experience in tissue molecular diagnostics to pursue this training. It is our belief that this training will help to maintain in future the role of the pathologist at the centre of patient care as the integrator of clinical, morphological and molecular information. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  3. MODELLING AND SIMULATING RISKS IN THE TRAINING OF THE HUMAN RESOURCES BY APPLYING THE CHAOS THEORY

    OpenAIRE

    Eugen ROTARESCU

    2012-01-01

    The article approaches the modelling and simulation of risks in the training of the human resources, as well as the forecast of the degree of human resources training impacted by risks by applying the mathematical tools offered by the Chaos Theory and mathematical statistics. We will highlight that the level of knowledge, skills and abilities of the human resources from an organization are autocorrelated in time and they depend on the level of a previous moment of the training, as well as on ...

  4. Support surface related changes in feedforward and feedback control of standing posture.

    Science.gov (United States)

    Mohapatra, Sambit; Kukkar, Komal K; Aruin, Alexander S

    2014-02-01

    The aim of the study was to investigate the effect of different support surfaces on feedforward and feedback components of postural control. Nine healthy subjects were exposed to external perturbations applied to their shoulders while standing on a rigid platform, foam, and wobble board with eyes open or closed. Electrical activity of nine trunk and leg muscles and displacements of the center of pressure were recorded and analyzed during the time frames typical of feedforward and feedback postural adjustments. Feedforward control of posture was characterized by earlier activation of anterior muscles when the subjects stood on foam compared to a wobble board or a firm surface. In addition, the magnitude of feedforward muscle activity was the largest when the foam was used. During the feedback control, anterior muscles were activated prior to posterior muscles irrespective of the nature of surface. Moreover, the largest muscle activity was seen when the supporting surface was foam. Maximum CoP displacement occurred when subjects were standing on a rigid surface. Altering support surface affects both feedforward and feedback components of postural control. This information should be taken into consideration in planning rehabilitation interventions geared towards improvement of balance. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. A combined stochastic feedforward and feedback control design methodology with application to autoland design

    Science.gov (United States)

    Halyo, Nesim

    1987-01-01

    A combined stochastic feedforward and feedback control design methodology was developed. The objective of the feedforward control law is to track the commanded trajectory, whereas the feedback control law tries to maintain the plant state near the desired trajectory in the presence of disturbances and uncertainties about the plant. The feedforward control law design is formulated as a stochastic optimization problem and is embedded into the stochastic output feedback problem where the plant contains unstable and uncontrollable modes. An algorithm to compute the optimal feedforward is developed. In this approach, the use of error integral feedback, dynamic compensation, control rate command structures are an integral part of the methodology. An incremental implementation is recommended. Results on the eigenvalues of the implemented versus designed control laws are presented. The stochastic feedforward/feedback control methodology is used to design a digital automatic landing system for the ATOPS Research Vehicle, a Boeing 737-100 aircraft. The system control modes include localizer and glideslope capture and track, and flare to touchdown. Results of a detailed nonlinear simulation of the digital control laws, actuator systems, and aircraft aerodynamics are presented.

  6. A comprehensive inversion approach for feedforward compensation of piezoactuator system at high frequency

    Science.gov (United States)

    Tian, Lizhi; Xiong, Zhenhua; Wu, Jianhua; Ding, Han

    2016-09-01

    Motion control of the piezoactuator system over broadband frequencies is limited due to its inherent hysteresis and system dynamics. One of the suggested ways is to use feedforward controller to linearize the input-output relationship of the piezoactuator system. Although there have been many feedforward approaches, it is still a challenge to develop feedforward controller for the piezoactuator system at high frequency. Hence, this paper presents a comprehensive inversion approach in consideration of the coupling of hysteresis and dynamics. In this work, the influence of dynamics compensation on the input-output relationship of the piezoactuator system is investigated first. With system dynamics compensation, the input-output relationship of the piezoactuator system will be further represented as rate-dependent nonlinearity due to the inevitable dynamics compensation error, especially at high frequency. Base on this result, the feedforward controller composed by a cascade of linear dynamics inversion and rate-dependent nonlinearity inversion is developed. Then, the system identification of the comprehensive inversion approach is proposed. Finally, experimental results show that the proposed approach can improve the performance on tracking of both periodic and non-periodic trajectories at medium and high frequency compared with the conventional feedforward approaches.

  7. Pupil size directly modulates the feedforward response in human primary visual cortex independently of attention.

    Science.gov (United States)

    Bombeke, Klaas; Duthoo, Wout; Mueller, Sven C; Hopf, Jens-Max; Boehler, C Nico

    2016-02-15

    Controversy revolves around the question of whether psychological factors like attention and emotion can influence the initial feedforward response in primary visual cortex (V1). Although traditionally, the electrophysiological correlate of this response in humans (the C1 component) has been found to be unaltered by psychological influences, a number of recent studies have described attentional and emotional modulations. Yet, research into psychological effects on the feedforward V1 response has neglected possible direct contributions of concomitant pupil-size modulations, which are known to also occur under various conditions of attentional load and emotional state. Here we tested the hypothesis that such pupil-size differences themselves directly affect the feedforward V1 response. We report data from two complementary experiments, in which we used procedures that modulate pupil size without differences in attentional load or emotion while simultaneously recording pupil-size and EEG data. Our results confirm that pupil size indeed directly influences the feedforward V1 response, showing an inverse relationship between pupil size and early V1 activity. While it is unclear in how far this effect represents a functionally-relevant adaptation, it identifies pupil-size differences as an important modulating factor of the feedforward response of V1 and could hence represent a confounding variable in research investigating the neural influence of psychological factors on early visual processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Neural Networks For Electrohydrodynamic Effect Modelling

    Directory of Open Access Journals (Sweden)

    Wiesław Wajs

    2004-01-01

    Full Text Available This paper presents currently achieved results concerning methods of electrohydrodynamiceffect used in geophysics simulated with feedforward networks trained with backpropagation algorithm, radial basis function networks and generalized regression networks.

  9. Periodic spring–mass running over uneven terrain through feedforward control of landing conditions

    International Nuclear Information System (INIS)

    III, Luther R Palmer; Eaton, Caitrin E

    2014-01-01

    This work pursues a feedforward control algorithm for high-speed legged locomotion over uneven terrain. Being able to rapidly negotiate uneven terrain without visual or a priori information about the terrain will allow legged systems to be used in time-critical applications and alongside fast-moving humans or vehicles. The algorithm is shown here implemented on a spring-loaded inverted pendulum model in simulation, and can be configured to approach fixed running height over uneven terrain or self-stable terrain following. Offline search identifies unique landing conditions that achieve a desired apex height with a constant stride period over varying ground levels. Because the time between the apex and touchdown events is directly related to ground height, the landing conditions can be computed in real time as continuous functions of this falling time. Enforcing a constant stride period reduces the need for inertial sensing of the apex event, which is nontrivial for physical systems, and allows for clocked feedfoward control of the swing leg. (paper)

  10. Dead beat filling and feedforward rf control for the spallation neutron source SNQ

    International Nuclear Information System (INIS)

    Schulze, D.

    1982-01-01

    For the 1.1 GeV-100 mA Spallation Neutron Source SNQ operation costs and beam losses ask for the possible potential of rf control improvements. Two novel methods are investigated. First, in order to increase the overall rf efficiency, the cavity field is built up as fast as possible in the open loop state of feedback control and in detuned position of the cavity in such a manner that the cavity with beam is matched to the generator. It is shown that this requires the simulataneous application of a generator amplitude and a generator phase step. Secondly, a feedforward control system is proposed, which reduces the amplitude and phase control error caused by an arbitrary beam transient into the limits of +-0.1% and +-0.1 0 and maintains these error limits also in the presence of parameter drift. This is done by an adaptive parameter adjustment procedure using a digital model of the control system. The system structure and a promising digital simulation are discussed

  11. Fast-Spiking Interneurons Supply Feedforward Control of Bursting, Calcium, and Plasticity for Efficient Learning.

    Science.gov (United States)

    Owen, Scott F; Berke, Joshua D; Kreitzer, Anatol C

    2018-02-08

    Fast-spiking interneurons (FSIs) are a prominent class of forebrain GABAergic cells implicated in two seemingly independent network functions: gain control and network plasticity. Little is known, however, about how these roles interact. Here, we use a combination of cell-type-specific ablation, optogenetics, electrophysiology, imaging, and behavior to describe a unified mechanism by which striatal FSIs control burst firing, calcium influx, and synaptic plasticity in neighboring medium spiny projection neurons (MSNs). In vivo silencing of FSIs increased bursting, calcium transients, and AMPA/NMDA ratios in MSNs. In a motor sequence task, FSI silencing increased the frequency of calcium transients but reduced the specificity with which transients aligned to individual task events. Consistent with this, ablation of FSIs disrupted the acquisition of striatum-dependent egocentric learning strategies. Together, our data support a model in which feedforward inhibition from FSIs temporally restricts MSN bursting and calcium-dependent synaptic plasticity to facilitate striatum-dependent sequence learning. Copyright © 2018 Elsevier Inc. All rights reserved.

  12. Load speed regulation in compliant mechanical transmission systems using feedback and feedforward control actions.

    Science.gov (United States)

    Raul, P R; Dwivedula, R V; Pagilla, P R

    2016-07-01

    The problem of controlling the load speed of a mechanical transmission system consisting of a belt-pulley and gear-pair is considered. The system is modeled as two inertia (motor and load) connected by a compliant transmission. If the transmission is assumed to be rigid, then using either the motor or load speed feedback provides the same result. However, with transmission compliance, due to belts or long shafts, the stability characteristics and performance of the closed-loop system are quite different when either motor or load speed feedback is employed. We investigate motor and load speed feedback schemes by utilizing the singular perturbation method. We propose and discuss a control scheme that utilizes both motor and load speed feedback, and design an adaptive feedforward action to reject load torque disturbances. The control algorithms are implemented on an experimental platform that is typically used in roll-to-roll manufacturing and results are shown and discussed. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  13. Periodic spring-mass running over uneven terrain through feedforward control of landing conditions.

    Science.gov (United States)

    Palmer, Luther R; Eaton, Caitrin E

    2014-09-01

    This work pursues a feedforward control algorithm for high-speed legged locomotion over uneven terrain. Being able to rapidly negotiate uneven terrain without visual or a priori information about the terrain will allow legged systems to be used in time-critical applications and alongside fast-moving humans or vehicles. The algorithm is shown here implemented on a spring-loaded inverted pendulum model in simulation, and can be configured to approach fixed running height over uneven terrain or self-stable terrain following. Offline search identifies unique landing conditions that achieve a desired apex height with a constant stride period over varying ground levels. Because the time between the apex and touchdown events is directly related to ground height, the landing conditions can be computed in real time as continuous functions of this falling time. Enforcing a constant stride period reduces the need for inertial sensing of the apex event, which is nontrivial for physical systems, and allows for clocked feedfoward control of the swing leg.

  14. Dynamic Feedforward Control of a Diesel Engine Based on Optimal Transient Compensation Maps

    Directory of Open Access Journals (Sweden)

    Giorgio Mancini

    2014-08-01

    Full Text Available To satisfy the increasingly stringent emission regulations and a demand for an ever lower fuel consumption, diesel engines have become complex systems with many interacting actuators. As a consequence, these requirements are pushing control and calibration to their limits. The calibration procedure nowadays is still based mainly on engineering experience, which results in a highly iterative process to derive a complete engine calibration. Moreover, automatic tools are available only for stationary operation, to obtain control maps that are optimal with respect to some predefined objective function. Therefore, the exploitation of any leftover potential during transient operation is crucial. This paper proposes an approach to derive a transient feedforward (FF control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. A partially physics-based model is thereby used to replace the engine. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient. These maps complement the static control maps by accounting for the dynamic behavior of the engine. The procedure is implemented on a real engine and experimental results are presented along with the development of the methodology.

  15. Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex

    Science.gov (United States)

    Markov, Nikola T; Vezoli, Julien; Chameau, Pascal; Falchier, Arnaud; Quilodran, René; Huissoud, Cyril; Lamy, Camille; Misery, Pierre; Giroud, Pascale; Ullman, Shimon; Barone, Pascal; Dehay, Colette; Knoblauch, Kenneth; Kennedy, Henry

    2013-01-01

    The laminar location of the cell bodies and terminals of interareal connections determines the hierarchical structural organization of the cortex and has been intensively studied. However, we still have only a rudimentary understanding of the connectional principles of feedforward (FF) and feedback (FB) pathways. Quantitative analysis of retrograde tracers was used to extend the notion that the laminar distribution of neurons interconnecting visual areas provides an index of hierarchical distance (percentage of supragranular labeled neurons [SLN]). We show that: 1) SLN values constrain models of cortical hierarchy, revealing previously unsuspected areal relations; 2) SLN reflects the operation of a combinatorial distance rule acting differentially on sets of connections between areas; 3) Supragranular layers contain highly segregated bottom-up and top-down streams, both of which exhibit point-to-point connectivity. This contrasts with the infragranular layers, which contain diffuse bottom-up and top-down streams; 4) Cell filling of the parent neurons of FF and FB pathways provides further evidence of compartmentalization; 5) FF pathways have higher weights, cross fewer hierarchical levels, and are less numerous than FB pathways. Taken together, the present results suggest that cortical hierarchies are built from supra- and infragranular counterstreams. This compartmentalized dual counterstream organization allows point-to-point connectivity in both bottom-up and top-down directions. PMID:23983048

  16. Feedback-linearization and feedback-feedforward decentralized control for multimachine power system

    Energy Technology Data Exchange (ETDEWEB)

    De Tuglie, Enrico [Dipartimento di Ingegneria dell' Ambiente, e per lo Sviluppo Sostenibile - DIASS, Politecnico di Bari, Viale del Turismo 8, 74100 Taranto (Italy); Iannone, Silvio Marcello; Torelli, Francesco [Dipartimento di Elettrotecnica, ed Elettronica - DEE, Politecnico di Bari, Via Re David 200, 70125 Bari (Italy)

    2008-03-15

    In this paper a decentralized nonlinear controller for large-scale power systems is investigated. The proposed controller design is based on the input-output feedback linearization methodology. In order to overcome computational difficulties in adopting such methodology, the overall interconnected nonlinear system, given as n-order, is analyzed as a cascade connection of an n{sub 1}-order nonlinear subsystem and an n{sub 2}-order linear subsystem. The controller design is obtained by applying input-output feedback linearization to the nonlinear subsystem and adopting a tracking control scheme, based on feedback-feedforward technique, for the linear subsystem. In the assumed system model, which is characterised by an interconnected structure between generating units, a decentralised adaptive controller is implemented by decentralizing these constraints. The use of a totally decentralised controller implies a system performance decay with respect to performance when the system is equipped with a centralised controller. Fortunately, the robustness of the proposed controller, based on input-output feedback procedure, guarantees good performance in terms of disturbance even when disturbances are caused by decentralization of interconnection constraints. Test results, provided on the IEEE 30 bus test system, demonstrate the effectiveness and practical applicability of proposed methodology. (author)

  17. Domain Modeling for Adaptive Training and Education in Support of the US Army Learning Model-Research Outline

    Science.gov (United States)

    2015-06-01

    Definitions are provided for this section to distinguish between adaptive training and education elements and also to highlight their relationships ...illustrate this point Franke (2011) asserts that through the use of case study examples, instruction can provide the pedagogical foundation for decision...a prime example of an adaptive training and education system: a learner or trainee model, an instructional or pedagogical model, a domain model

  18. Modelling of word usage frequency dynamics using artificial neural network

    International Nuclear Information System (INIS)

    Maslennikova, Yu S; Bochkarev, V V; Voloskov, D S

    2014-01-01

    In this paper the method for modelling of word usage frequency time series is proposed. An artificial feedforward neural network was used to predict word usage frequencies. The neural network was trained using the maximum likelihood criterion. The Google Books Ngram corpus was used for the analysis. This database provides a large amount of data on frequency of specific word forms for 7 languages. Statistical modelling of word usage frequency time series allows finding optimal fitting and filtering algorithm for subsequent lexicographic analysis and verification of frequency trend models

  19. Model of training of computer science teachers by means of distant education technologies

    Directory of Open Access Journals (Sweden)

    Т А Соловьева

    2009-03-01

    Full Text Available Training of future computer science teachers in conditions of informatization of education is analyzed. Distant educational technologies (DET and traditional process of training, their advantages and disadvantages are considered, active functions of DET as the basis of the model of training by means of DET is stressed. It is shown that mixed education combining both distant ant traditional technologies takes place on the basis of the created model. Practical use of the model is shown on the example of the course «Recursion» for future computer science teachers.

  20. River scale model of an training dam using lightweight granulates

    NARCIS (Netherlands)

    Vermeulen, B.; Boersema, M.P.; Hoitink, A.J.F.; Sieben, J.; Sloff, C.J.; Wal, van der M.F.

    2014-01-01

    Replacing existing river groynes with longitudinal training dams is considered as a promising flood mitigation measure in the main Dutch rivers, which can also serve to guarantee navigability during low flows and to create conditions favourable for ecological development. Whereas the bed response in

  1. A collision dynamics model of a multi-level train

    Science.gov (United States)

    2006-11-05

    In train collisions, multi-level rail passenger vehicles can deform in modes that are different from the behavior of single level cars. The deformation in single level cars usually occurs at the front end during a collision. In one particular inciden...

  2. Training Vocational Rehabilitation Counselors in Group Dynamics: A Psychoeducational Model.

    Science.gov (United States)

    Elliott, Timothy R.

    1990-01-01

    Describes a six-session psychoeducational program for training vocational rehabilitation counselors in group dynamics. Presents evaluation of program by counselors (N=15) in which leadership styles, conflict management, and typology of group tasks concepts were rated as most beneficial. (Author/ABL)

  3. Bayesian model ensembling using meta-trained recurrent neural networks

    NARCIS (Netherlands)

    Ambrogioni, L.; Berezutskaya, Y.; Gü ç lü , U.; Borne, E.W.P. van den; Gü ç lü tü rk, Y.; Gerven, M.A.J. van; Maris, E.G.G.

    2017-01-01

    In this paper we demonstrate that a recurrent neural network meta-trained on an ensemble of arbitrary classification tasks can be used as an approximation of the Bayes optimal classifier. This result is obtained by relying on the framework of e-free approximate Bayesian inference, where the Bayesian

  4. Counseling Psychology Model Training Values Statement Addressing Diversity

    Science.gov (United States)

    Counseling Psychologist, 2009

    2009-01-01

    Respect for diversity and for values different from one's own is a central value of counseling psychology training programs. The valuing of diversity is also consistent with the profession of psychology as mandated by the American Psychological Association's (APA's) Ethical Principles and Code of Conduct and as discussed in the Guidelines and…

  5. Building Multicultural Residential Communities: A Model for Training Student Staff

    Science.gov (United States)

    Petryk, Taryn; Thompson, Monita C.; Boynton, Trelawny

    2013-01-01

    The growing diversity and changing demographics within the United States increases the importance of students developing skills to engage across identity difference. The purpose of this chapter is to describe how a pre-employment course for student staff members is used as a multicultural intervention training to provide students with the…

  6. Mesostructure, contemporary training model of the Cuban boxing school

    Directory of Open Access Journals (Sweden)

    Juan Hernández Sierra

    2018-01-01

    Full Text Available The present work aims to convey the experiences on the development and application of a meso-structure of 3-4 microcycles that allowed maintaining a long state of the sport form (5-6 months on a scientific-technical and methodological basis in the planning of the Sports training of the national boxing team, who participated in the 4th World Boxing Series (WSB. The investigated sample consisted of 21 boxers, representing 58%, of a population made up of 36 athletes / students belonging to the National School of Boxing. The importance of the research is that it exposes the use of new planning concepts and the current modifications in the training structure, as well as the contribution of science to the adaptation of training loads, which allows to obtain positive results during a long period of time. state of the sport form, factors on which it is necessary to reflect for an effective planning of modern sports training.

  7. A Conceptual Model for Employer Training to Manage Employee Counter-Productive Behaviors

    Science.gov (United States)

    Rock, Naomi Spickard

    2011-01-01

    The purpose of this study was to develop a model for employer training to manage employees who possess counter-productive behaviors. With the increasing encouragement for employers to hire without discriminating, the number of individuals with disabilities in the workforce will rise. There is limited training in universities and businesses to…

  8. In-Service Training of Teachers in Multicultural Urban Schools: A Systematic Model.

    Science.gov (United States)

    Nickolai-Mays, Susanne; Davis, Jerry L.

    1986-01-01

    Presents seven guidelines for developing effective teacher in-service training programs. Describes a training model for multicultural urban schools which addresses these topics: instructional methods; curriculum; interpersonal relations in the classroom; classroom management and discipline; parent-teacher-student involvement; and multicultural…

  9. Multicultural Grand Rounds: Competency-Based Training Model for Clinical Psychology Graduate Students

    Science.gov (United States)

    Stites, Shana D.; Warholic, Christina L.

    2014-01-01

    Preparing students to enter the field of psychology as competent professionals requires that multicultural practices be infused into all areas of training. This article describes how the Grand Rounds model was adapted to a graduate clinical psychology training program to foster applied learning in multicultural competence. This extension of Grand…

  10. Rationale and Resources for Teaching the Mathematical Modeling of Athletic Training and Performance

    Science.gov (United States)

    Clarke, David C.; Skiba, Philip F.

    2013-01-01

    A number of professions rely on exercise prescription to improve health or athletic performance, including coaching, fitness/personal training, rehabilitation, and exercise physiology. It is therefore advisable that the professionals involved learn the various tools available for designing effective training programs. Mathematical modeling of…

  11. Going beyond Kirkpatrick's Training Evaluation Model: The Role of Workplace Factors in Distance Learning Transfer

    Science.gov (United States)

    Aluko, F. R.; Shonubi, O. K.

    2014-01-01

    This article emanates from a longitudinal study of the impact of a distance education programme for teacher training on graduates' job performance, in which the authors built on the findings of a previous pilot study. After using Kirkpatrick's Training Evaluation Model in a previous study, one of the authors found there to be a strong relationship…

  12. Effectiveness of Training Model Capacity Building for Entrepreneurship Women Based Empowerment Community

    Science.gov (United States)

    Idawati; Mahmud, Alimuddin; Dirawan, Gufran Darma

    2016-01-01

    The purpose of this research was to determine the effectiveness of a training model for capacity building of women entrepreneurship community-based. Research type approach Research and Development Model, which refers to the model of development research that developed by Romiszowki (1996) combined with a model of development Sugiono (2011) it was…

  13. Low-Latency Digital Signal Processing for Feedback and Feedforward in Quantum Computing and Communication

    Science.gov (United States)

    Salathé, Yves; Kurpiers, Philipp; Karg, Thomas; Lang, Christian; Andersen, Christian Kraglund; Akin, Abdulkadir; Krinner, Sebastian; Eichler, Christopher; Wallraff, Andreas

    2018-03-01

    Quantum computing architectures rely on classical electronics for control and readout. Employing classical electronics in a feedback loop with the quantum system allows us to stabilize states, correct errors, and realize specific feedforward-based quantum computing and communication schemes such as deterministic quantum teleportation. These feedback and feedforward operations are required to be fast compared to the coherence time of the quantum system to minimize the probability of errors. We present a field-programmable-gate-array-based digital signal processing system capable of real-time quadrature demodulation, a determination of the qubit state, and a generation of state-dependent feedback trigger signals. The feedback trigger is generated with a latency of 110 ns with respect to the timing of the analog input signal. We characterize the performance of the system for an active qubit initialization protocol based on the dispersive readout of a superconducting qubit and discuss potential applications in feedback and feedforward algorithms.

  14. Performance assessment of static lead-lag feedforward controllers for disturbance rejection in PID control loops.

    Science.gov (United States)

    Yu, Zhenpeng; Wang, Jiandong

    2016-09-01

    This paper assesses the performance of feedforward controllers for disturbance rejection in univariate feedback plus feedforward control loops. The structures of feedback and feedforward controllers are confined to proportional-integral-derivative and static-lead-lag forms, respectively, and the effects of feedback controllers are not considered. The integral squared error (ISE) and total squared variation (TSV) are used as performance metrics. A performance index is formulated by comparing the current ISE and TSV metrics to their own lower bounds as performance benchmarks. A controller performance assessment (CPA) method is proposed to calculate the performance index from measurements. The proposed CPA method resolves two critical limitations in the existing CPA methods, in order to be consistent with industrial scenarios. Numerical and experimental examples illustrate the effectiveness of the obtained results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Hypocortisolemic clamp unmasks jointly feedforward- and feedback-dependent control of overnight ACTH secretion.

    Science.gov (United States)

    Iranmanesh, Ali; Veldhuis, Johannes D

    2008-11-01

    ACTH secretion is under hypothalamic stimulatory (feedforward) and adrenal inhibitory (feedback) control. Assessment of overnight ACTH secretion during a hypocortisolemic clamp will permit the estimation of changing feedforward and feedback. Seven healthy men. An oral dose of placebo (PLAC), metyrapone (METY, 3 g), or ketoconazole (KTCZ, 1.2 g) was given at midnight (MN) to block glucocorticoid synthesis. Plasma ACTH was sampled every 10 min (MN to 0800 h). Variable-waveform deconvolution analysis of ACTH secretion and approximate entropy (ApEn) analysis of pattern regularity. Compared with PLAC, administration of METY and KTCZ reduced morning cortisol concentrations by >or=77 and 54% respectively (Pfeedforward coordination. The combined data predict overnight amplification and coordination of hypothalamic feedforward drive onto ACTH release. Therefore, disruption of either mechanism might contribute to clinical pathophysiology, such as late-day elevations of cortisol output in fasting, alcoholism, depression, or aging.

  16. Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

    International Nuclear Information System (INIS)

    Jie, Li; Wan-Qing, Yu; Ding, Xu; Feng, Liu; Wei, Wang

    2009-01-01

    Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin–Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τ syn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τ syn , suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks. (cross-disciplinary physics and related areas of science and technology)

  17. Development and Validity of a Silicone Renal Tumor Model for Robotic Partial Nephrectomy Training.

    Science.gov (United States)

    Monda, Steven M; Weese, Jonathan R; Anderson, Barrett G; Vetter, Joel M; Venkatesh, Ramakrishna; Du, Kefu; Andriole, Gerald L; Figenshau, Robert S

    2018-04-01

    To provide a training tool to address the technical challenges of robot-assisted laparoscopic partial nephrectomy, we created silicone renal tumor models using 3-dimensional printed molds of a patient's kidney with a mass. In this study, we assessed the face, content, and construct validity of these models. Surgeons of different training levels completed 4 simulations on silicone renal tumor models. Participants were surveyed on the usefulness and realism of the model as a training tool. Performance was measured using operation-specific metrics, self-reported operative demands (NASA Task Load Index [NASA TLX]), and blinded expert assessment (Global Evaluative Assessment of Robotic Surgeons [GEARS]). Twenty-four participants included attending urologists, endourology fellows, urology residents, and medical students. Post-training surveys of expert participants yielded mean results of 79.2 on the realism of the model's overall feel and 90.2 on the model's overall usefulness for training. Renal artery clamp times and GEARS scores were significantly better in surgeons further in training (P ≤.005 and P ≤.025). Renal artery clamp times, preserved renal parenchyma, positive margins, NASA TLX, and GEARS scores were all found to improve across trials (P <.001, P = .025, P = .024, P ≤.020, and P ≤.006, respectively). Face, content, and construct validity were demonstrated in the use of a silicone renal tumor model in a cohort of surgeons of different training levels. Expert participants deemed the model useful and realistic. Surgeons of higher training levels performed better than less experienced surgeons in various study metrics, and improvements within individuals were observed over sequential trials. Future studies should aim to assess model predictive validity, namely, the association between model performance improvements and improvements in live surgery. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. Spaced training rescues memory and ERK1/2 signaling in fragile X syndrome model mice.

    Science.gov (United States)

    Seese, Ronald R; Wang, Kathleen; Yao, Yue Qin; Lynch, Gary; Gall, Christine M

    2014-11-25

    Recent studies have shown that short, spaced trains of afferent stimulation produce much greater long-term potentiation (LTP) than that obtained with a single, prolonged stimulation episode. The present studies demonstrate that spaced training regimens, based on these LTP timing rules, facilitate learning in wild-type (WT) mice and can offset learning and synaptic signaling impairments in the fragile X mental retardation 1 (Fmr1) knockout (KO) model of fragile X syndrome. We determined that 5 min of continuous training supports object location memory (OLM) in WT but not Fmr1 KO mice. However, the same amount of training distributed across three short trials, spaced by one hour, produced robust long-term memory in the KOs. At least three training trials were needed to realize the benefit of spacing, and intertrial intervals shorter or longer than 60 min were ineffective. Multiple short training trials also rescued novel object recognition in Fmr1 KOs. The spacing effect was surprisingly potent: just 1 min of OLM training, distributed across three trials, supported robust memory in both genotypes. Spacing also rescued training-induced activation of synaptic ERK1/2 in dorsal hippocampus of Fmr1 KO mice. These results show that a spaced training regimen designed to maximize synaptic potentiation facilitates recognition memory in WT mice and can offset synaptic signaling and memory impairments in a model of congenital intellectual disability.

  19. Model training curriculum for Low-Level Radioactive Waste Disposal Facility Operations

    Energy Technology Data Exchange (ETDEWEB)

    Tyner, C.J.; Birk, S.M.

    1995-09-01

    This document is to assist in the development of the training programs required to be in place for the operating license for a low-level radioactive waste disposal facility. It consists of an introductory document and four additional appendixes of individual training program curricula. This information will provide the starting point for the more detailed facility-specific training programs that will be developed as the facility hires and trains new personnel and begins operation. This document is comprehensive and is intended as a guide for the development of a company- or facility-specific program. The individual licensee does not need to use this model training curriculum as written. Instead, this document can be used as a menu for the development, modification, or verification of customized training programs.

  20. Model training curriculum for Low-Level Radioactive Waste Disposal Facility Operations

    International Nuclear Information System (INIS)

    Tyner, C.J.; Birk, S.M.

    1995-09-01

    This document is to assist in the development of the training programs required to be in place for the operating license for a low-level radioactive waste disposal facility. It consists of an introductory document and four additional appendixes of individual training program curricula. This information will provide the starting point for the more detailed facility-specific training programs that will be developed as the facility hires and trains new personnel and begins operation. This document is comprehensive and is intended as a guide for the development of a company- or facility-specific program. The individual licensee does not need to use this model training curriculum as written. Instead, this document can be used as a menu for the development, modification, or verification of customized training programs

  1. Artificial Neural Network Model for Monitoring Oil Film Regime in Spur Gear Based on Acoustic Emission Data

    Directory of Open Access Journals (Sweden)

    Yasir Hassan Ali

    2015-01-01

    Full Text Available The thickness of an oil film lubricant can contribute to less gear tooth wear and surface failure. The purpose of this research is to use artificial neural network (ANN computational modelling to correlate spur gear data from acoustic emissions, lubricant temperature, and specific film thickness (λ. The approach is using an algorithm to monitor the oil film thickness and to detect which lubrication regime the gearbox is running either hydrodynamic, elastohydrodynamic, or boundary. This monitoring can aid identification of fault development. Feed-forward and recurrent Elman neural network algorithms were used to develop ANN models, which are subjected to training, testing, and validation process. The Levenberg-Marquardt back-propagation algorithm was applied to reduce errors. Log-sigmoid and Purelin were identified as suitable transfer functions for hidden and output nodes. The methods used in this paper shows accurate predictions from ANN and the feed-forward network performance is superior to the Elman neural network.

  2. Incorporating the life course model into MCH nutrition leadership education and training programs.

    Science.gov (United States)

    Haughton, Betsy; Eppig, Kristen; Looney, Shannon M; Cunningham-Sabo, Leslie; Spear, Bonnie A; Spence, Marsha; Stang, Jamie S

    2013-01-01

    Life course perspective, social determinants of health, and health equity have been combined into one comprehensive model, the life course model (LCM), for strategic planning by US Health Resources and Services Administration's Maternal and Child Health Bureau. The purpose of this project was to describe a faculty development process; identify strategies for incorporation of the LCM into nutrition leadership education and training at the graduate and professional levels; and suggest broader implications for training, research, and practice. Nineteen representatives from 6 MCHB-funded nutrition leadership education and training programs and 10 federal partners participated in a one-day session that began with an overview of the models and concluded with guided small group discussions on how to incorporate them into maternal and child health (MCH) leadership training using obesity as an example. Written notes from group discussions were compiled and coded emergently. Content analysis determined the most salient themes about incorporating the models into training. Four major LCM-related themes emerged, three of which were about training: (1) incorporation by training grants through LCM-framed coursework and experiences for trainees, and similarly framed continuing education and skills development for professionals; (2) incorporation through collaboration with other training programs and state and community partners, and through advocacy; and (3) incorporation by others at the federal and local levels through policy, political, and prevention efforts. The fourth theme focused on anticipated challenges of incorporating the model in training. Multiple methods for incorporating the LCM into MCH training and practice are warranted. Challenges to incorporating include the need for research and related policy development.

  3. Fixed structure feedforward controller design exploiting iterative trials: application to a wafer stage and a desktop printer

    NARCIS (Netherlands)

    Meulen, van der S.H.; Tousain, R.L.; Bosgra, O.H.

    2008-01-01

    In this paper, the feedforward controller design problem for high-precision electromechanical servo systems that execute finite time tasks is addressed. The presented procedure combines the selection of the fixed structure of the feedforward controller and the optimization of the controller

  4. 53 MHZ Feedforward beam loading compensation in the Fermilab main injector

    International Nuclear Information System (INIS)

    Joseph E Dey et al.

    2003-01-01

    53 MHz feedforward beam loading compensation is crucial to all operations of the Main Injector. Recently a system using a fundamental frequency down converter mixer, a digital bucket delay module and a fundamental frequency up converter mixer were used to produce a one-turn-delay feedforward signal. This signal was then combined with the low level RF signal to the cavities to cancel the transient beam induced voltage. During operation they have shown consistently over 20 dB reduction in side-band voltage around the fundamental frequency during Proton coalescing and over 14 dB in multi-batch antiproton coalescing

  5. Movement goals and feedback and feedforward control mechanisms in speech production.

    Science.gov (United States)

    Perkell, Joseph S

    2012-09-01

    Studies of speech motor control are described that support a theoretical framework in which fundamental control variables for phonemic movements are multi-dimensional regions in auditory and somatosensory spaces. Auditory feedback is used to acquire and maintain auditory goals and in the development and function of feedback and feedforward control mechanisms. Several lines of evidence support the idea that speakers with more acute sensory discrimination acquire more distinct goal regions and therefore produce speech sounds with greater contrast. Feedback modification findings indicate that fluently produced sound sequences are encoded as feedforward commands, and feedback control serves to correct mismatches between expected and produced sensory consequences.

  6. Performance improvement of VAV air conditioning system through feedforward compensation decoupling and genetic algorithm

    International Nuclear Information System (INIS)

    Wang Jun; Wang Yan

    2008-01-01

    VAV (variable air volume) control system has the feature of multi-control loops. While all the control loops are working together, they interfere and influence each other. This paper designs the decoupling compensation unit in VAV system in the method of feedforward compensation. This paper also designs the controller parameters of VAV system by means of inverse deducing and the genetic algorithm. Experimental results demonstrate that the combination of the feedforward compensation decoupling and the controller optimization by genetic algorithm can improve the performance of the VAV control system

  7. Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration.

    Science.gov (United States)

    Parrell, Benjamin; Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B

    2017-09-20

    The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of

  8. Dynamic Optimization of Feedforward Automatic Gauge Control Based on Extended Kalman Filter

    Institute of Scientific and Technical Information of China (English)

    YANG Bin-hu; YANG Wei-dong; CHEN Lian-gui; QU Lei

    2008-01-01

    Automatic gauge control is an essentially nonlinear process varying with time delay, and stochastically varying input and process noise always influence the target gauge control accuracy. To improve the control capability of feedforward automatic gauge control, Kalman filter was employed to filter the noise signal transferred from one stand to another. The linearized matrix that the Kalman filter algorithm needed was concluded; thus, the feedforward automatic gauge control architecture was dynamically optimized. The theoretical analyses and simulation show that the proposed algorithm is reasonable and effective.

  9. Cost Comparison Model: Blended eLearning versus traditional training of community health workers.

    Science.gov (United States)

    Sissine, Mysha; Segan, Robert; Taylor, Mathew; Jefferson, Bobby; Borrelli, Alice; Koehler, Mohandas; Chelvayohan, Meena

    2014-01-01

    Another one million community healthcare workers are needed to address the growing global population and increasing demand of health care services. This paper describes a cost comparison between two training approaches to better understand costs implications of training community health workers (CHWs) in Sub-Saharan Africa. Our team created a prospective model to forecast and compare the costs of two training methods as described in the Dalburge Report - (1) a traditional didactic training approach ("baseline") and (2) a blended eLearning training approach ("blended"). After running the model for training 100,000 CHWs, we compared the results and scaled up those results to one million CHWs. A substantial difference exists in total costs between the baseline and blended training programs. RESULTS indicate that using a blended eLearning approach for training community health care workers could provide a total cost savings of 42%. Scaling the model to one million CHWs, the blended eLearning training approach reduces total costs by 25%. The blended eLearning savings are a result of decreased classroom time, thereby reducing the costs associated with travel, trainers and classroom costs; and using a tablet with WiFi plus a feature phone rather than a smartphone with data plan. The results of this cost analysis indicate significant savings through using a blended eLearning approach in comparison to a traditional didactic method for CHW training by as much as 67%. These results correspond to the Dalberg publication which indicates that using a blended eLearning approach is an opportunity for closing the gap in training community health care workers.

  10. Enhancing Users' Participation in Business Process Modeling through Ontology-Based Training

    Science.gov (United States)

    Macris, A.; Malamateniou, F.; Vassilacopoulos, G.

    Successful business process design requires active participation of users who are familiar with organizational activities and business process modelling concepts. Hence, there is a need to provide users with reusable, flexible, agile and adaptable training material in order to enable them instil their knowledge and expertise in business process design and automation activities. Knowledge reusability is of paramount importance in designing training material on process modelling since it enables users participate actively in process design/redesign activities stimulated by the changing business environment. This paper presents a prototype approach for the design and use of training material that provides significant advantages to both the designer (knowledge - content reusability and semantic web enabling) and the user (semantic search, knowledge navigation and knowledge dissemination). The approach is based on externalizing domain knowledge in the form of ontology-based knowledge networks (i.e. training scenarios serving specific training needs) so that it is made reusable.

  11. Unsupervised acoustic model training: comparing South African English and isiZulu

    CSIR Research Space (South Africa)

    Kleynhans, N

    2015-11-01

    Full Text Available and requires funding, time and expertise. Lightly-supervised training techniques, however, provide a means to rapidly transcribe audio, thus reducing the initial resource investment to begin the modelling process. Our findings suggest that the lightly...

  12. Training surgical residents for a career in academic global surgery: a novel training model.

    Science.gov (United States)

    Swain, JaBaris D; Matousek, Alexi C; Scott, John W; Cooper, Zara; Smink, Douglas S; Bolman, Ralph Morton; Finlayson, Samuel R G; Zinner, Michael J; Riviello, Robert

    2015-01-01

    Academic global surgery is a nascent field focused on improving surgical care in resource-poor settings through a broad-based scholarship agenda. Although there is increasing momentum to expand training opportunities in low-resource settings among academic surgical programs, most focus solely on establishing short-term elective rotations rather than fostering research or career development. Given the complex nature of surgical care delivery and programmatic capacity building in the resource-poor settings, many challenges remain before global surgery is accepted as an academic discipline and an established career path. Brigham and Women's Hospital has established a specialized global surgery track within the general surgery residency program to develop academic leaders in this growing area of need and opportunity. Here we describe our experience with the design and development of the program followed by practical applications and lessons learned from our early experiences. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  13. The application of artificial neural network in radon disaster model of uranium mining

    International Nuclear Information System (INIS)

    Zhu Yufeng; Zhu Guogen; Zhou Shijian

    2012-01-01

    The structural features, data analysis and learning process of feed-forward neural network (BP ANN) were analyzed at first. Rodon sample from Fuzhou Jinan Uranium Industry Limited Company were used to training the network and make the forecast then, and a forecasting model was established for the radon disaster in uranium mines. The method and effectiveness of BP neural network in predicting radon disaster was discussed. The test of training samples showed that the BP network had gotten fairly satisfied result in predicting mine radon disaster. (authors)

  14. Training trajectories by continuous recurrent multilayer networks.

    Science.gov (United States)

    Leistritz, L; Galicki, M; Witte, H; Kochs, E

    2002-01-01

    This paper addresses the problem of training trajectories by means of continuous recurrent neural networks whose feedforward parts are multilayer perceptrons. Such networks can approximate a general nonlinear dynamic system with arbitrary accuracy. The learning process is transformed into an optimal control framework where the weights are the controls to be determined. A training algorithm based upon a variational formulation of Pontryagin's maximum principle is proposed for such networks. Computer examples demonstrating the efficiency of the given approach are also presented.

  15. [THE ALTERNATIVE MODEL IN TRAINING FOR OPERATION MANAGEMENT ON LUMBAR SPINE].

    Science.gov (United States)

    Zakondyrin, D E

    2015-01-01

    The authors proposed to use a lumbar part of calf carcass as a new biological model for training of basic practical skills in order to perform the neurosurgical operative interventions on the spine. The proximity of anatomico-surgical parameters of given model and human cavader lumbar spine was estimated. The study proved the possibility of use of lumbar part of calf carcass for training techniques of transpedicular fixation and microdiskectomy in lumbar part.

  16. An improved cellular automata model for train operation simulation with dynamic acceleration

    Science.gov (United States)

    Li, Wen-Jun; Nie, Lei

    2018-03-01

    Urban rail transit plays an important role in the urban public traffic because of its advantages of fast speed, large transport capacity, high safety, reliability and low pollution. This study proposes an improved cellular automaton (CA) model by considering the dynamic characteristic of the train acceleration to analyze the energy consumption and train running time. Constructing an effective model for calculating energy consumption to aid train operation improvement is the basis for studying and analyzing energy-saving measures for urban rail transit system operation.

  17. INNOVATIVE MODELS OF EDUCATION AND TRAINING OF SKILLED PERSONNEL FOR HIGH TECH INDUSTRIES IN UKRAINE

    Directory of Open Access Journals (Sweden)

    M.Shyshkina

    2013-03-01

    Full Text Available The problems of development of innovative learning environment of continuous education and training of skilled personnel for high-tech industry are described. Aspects of organization of ICT based learning environment of vocational and technical school on the basis of cloud computing and outsourcing are revealed. The three-stage conceptual model for perspective education and training of workers for high-tech industries is proposed. The model of cloud-based solution for design of learning environment for vocational education and training of skilled workers is introduced.

  18. INTELLECTUAL MODEL FORMATION OF RAILWAY STATION WORK DURING THE TRAIN OPERATION EXECUTION

    Directory of Open Access Journals (Sweden)

    O. V. Lavrukhin

    2014-11-01

    Full Text Available Purpose. The aim of this research work is to develop an intelligent technology for determination of the optimal route of freight trains administration on the basis of the technical and technological parameters. This will allow receiving the operational informed decisions by the station duty officer regarding to the train operation execution within the railway station. Metodology. The main elements of the research are the technical and technological parameters of the train station during the train operation. The methods of neural networks in order to form the self-teaching automated system were put in the basis of the generated model of train operation execution. Findings. The presented model of train operation execution at the railway station is realized on the basis of artificial neural networks using learning algorithm with a «teacher» in Matlab environment. The Matlab is also used for the immediate implementation of the intelligent automated control system of the train operation designed for the integration into the automated workplace of the duty station officer. The developed system is also useful to integrate on workplace of the traffic controller. This proposal is viable in case of the availability of centralized traffic control on the separate section of railway track. Originality. The model of train station operation during the train operation execution with elements of artificial intelligence was formed. It allows providing informed decisions to the station duty officer concerning a choice of rational and a safe option of reception and non-stop run of the trains with the ability of self-learning and adaptation to changing conditions. This condition is achieved by the principles of the neural network functioning. Practical value. The model of the intelligent system management of the process control for determining the optimal route receptionfor different categories of trains was formed.In the operational mode it offers the possibility

  19. Modelling of optimal training load patterns during the 11 weeks preceding major competition in elite swimmers.

    Science.gov (United States)

    Hellard, Philippe; Scordia, Charlotte; Avalos, Marta; Mujika, Inigo; Pyne, David B

    2017-10-01

    Periodization of swim training in the final training phases prior to competition and its effect on performance have been poorly described. We modeled the relationships between the final 11 weeks of training and competition performance in 138 elite sprint, middle-distance, and long-distance swimmers over 20 competitive seasons. Total training load (TTL), strength training (ST), and low- to medium-intensity and high-intensity training variables were monitored. Training loads were scaled as a percentage of the maximal volume measured at each intensity level. Four training periods (meso-cycles) were defined: the taper (weeks 1 to 2 before competition), short-term (weeks 3 to 5), medium-term (weeks 6 to 8), and long-term (weeks 9 to 11). Mixed-effects models were used to analyze the association between training loads in each training meso-cycle and end-of-season major competition performance. For sprinters, a 10% increase between ∼20% and 70% of the TTL in medium- and long-term meso-cycles was associated with 0.07 s and 0.20 s faster performance in the 50 m and 100 m events, respectively (p training yielded faster competition performance (e.g., a 10% increase in TTL was associated with improvements of 0.1-1.0 s in 200 m events and 0.3-1.6 s in 400 m freestyle, p < 0.01). For sprinters, a 60%-70% maximal ST load 6-8 weeks before competition induced the largest positive effects on performance (p < 0.01). An increase in TTL during the medium- and long-term preparation (6-11 weeks to competition) was associated with improved performance. Periodization plans should be adapted to the specialty of swimmers.

  20. Knowledge model of trainee for training support system of plant operation

    Energy Technology Data Exchange (ETDEWEB)

    Furuhama, Yutaka; Furuta, Kazuo; Kondo, Shunsuke [Tokyo Univ. (Japan). Faculty of Engineering

    1996-10-01

    We have already proposed a knowledge model of a trainee, which model consists of two layers: hierarchical function and qualitative structure. We developed a method to generate normative operator knowledge based on this knowledge model structure, and to identify trainee`s intention by means of truth maintenance. The methods were tested by cognitive experiment using a prototype of training support system. (author)

  1. Wages, Training, and Job Turnover in a Search-Matching Model

    DEFF Research Database (Denmark)

    Rosholm, Michael; Nielsen, Michael Svarer

    1999-01-01

    In this paper we extend a job search-matching model with firm-specific investments in training developed by Mortensen (1998) to allow for different offer arrival rates in employment and unemployment. The model by Mortensen changes the original wage posting model (Burdett and Mortensen, 1998) in two...

  2. Models for Multidimensional Tests and Hierarchically Structured Training Materials.

    Science.gov (United States)

    1985-05-01

    NAVOP 01B7 Washington, DC 20370 Dr. Hans Crombag University of Leyden Mr. Raymond E. Christal Education Research Center AFHRL/MOE Boerhaavelaan 2 Brooks...AFB, TX 78235 2334 EN Leyden The NETHERLANDS Dr. Norman Cliff Department of Psychology CTB/McGraw-Hill Library Univ. of So. Californ.a 2500 Garden Road...Diego, CA 92152 A[USTRALIA Ms. Kathleen Moreno Dr. William L. Maloy (02) Navy Personnel R&D Center Chief of Naval Education Code 62 and Training San Diego

  3. The Madrid Train Bombings: A Decision-Making Model Analysis

    Science.gov (United States)

    2009-12-11

    3T. K. Lawson Managing Editor, ―Madrid Bombing and Attacks on Trains, Subways ,‖ U.S. Department of State, Diplomatic Security Command Center (17 March...Alfred De Montesquiou, ―Official: Al-Qaeda Like A Fast Food Franchise ‗For Terrorism‘,‖ USA Today, 7 June 2009, http://www.usatoday.com/news/world/2009...Fort Leavenworth, KS, 2007): 78; De Montesquiou, ―Official: Al- Qaeda Like A Fast Food Franchise ‗For Terrorism‘.‖ 39Wilson, ―The Evolution of al

  4. A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

    Science.gov (United States)

    Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

    2016-06-01

    There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

  5. 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.)

  6. Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training.

    Science.gov (United States)

    Saggar, Manish; Zanesco, Anthony P; King, Brandon G; Bridwell, David A; MacLean, Katherine A; Aichele, Stephen R; Jacobs, Tonya L; Wallace, B Alan; Saron, Clifford D; Miikkulainen, Risto

    2015-07-01

    Meditation training has been shown to enhance attention and improve emotion regulation. However, the brain processes associated with such training are poorly understood and a computational modeling framework is lacking. Modeling approaches that can realistically simulate neurophysiological data while conforming to basic anatomical and physiological constraints can provide a unique opportunity to generate concrete and testable hypotheses about the mechanisms supporting complex cognitive tasks such as meditation. Here we applied the mean-field computational modeling approach using the scalp-recorded electroencephalogram (EEG) collected at three assessment points from meditating participants during two separate 3-month-long shamatha meditation retreats. We modeled cortical, corticothalamic, and intrathalamic interactions to generate a simulation of EEG signals recorded across the scalp. We also present two novel extensions to the mean-field approach that allow for: (a) non-parametric analysis of changes in model parameter values across all channels and assessments; and (b) examination of variation in modeled thalamic reticular nucleus (TRN) connectivity over the retreat period. After successfully fitting whole-brain EEG data across three assessment points within each retreat, two model parameters were found to replicably change across both meditation retreats. First, after training, we observed an increased temporal delay between modeled cortical and thalamic cells. This increase provides a putative neural mechanism for a previously observed reduction in individual alpha frequency in these same participants. Second, we found decreased inhibitory connection strength between the TRN and secondary relay nuclei (SRN) of the modeled thalamus after training. This reduction in inhibitory strength was found to be associated with increased dynamical stability of the model. Altogether, this paper presents the first computational approach, taking core aspects of physiology and

  7. A complementary model for medical subspecialty training in South ...

    African Journals Online (AJOL)

    research was to develop a business model to complement the current academic ... larger-scale potential public-private partnerships (PPPs). The model ... complementary system, which will benefit both the private and the public sectors.

  8. Application of a feedforward neural network in the search for kuroko deposits in the hokuroku district, Japan

    Science.gov (United States)

    Singer, D.A.; Kouda, R.

    1996-01-01

    A feedforward neural network with one hidden layer and five neurons was trained to recognize the distance to kuroko mineral deposits. Average amounts per hole of pyrite, sericite, and gypsum plus anhydrite as measured by X-rays in 69 drillholes were used in train the net. Drillholes near and between the Fukazawa, Furutobe, and Shakanai mines were used. The training data were selected carefully to represent well-explored areas where some confidence of the distance to ore was assured. A logarithmic transform was applied to remove the skewness of distance and each variable was scaled and centered by subtracting the median and dividing by the interquartile range. The learning algorithm of annealing plus conjugate gradients was used to minimise the mean squared error of the sealed distance to ore. The trained network then was applied to all of the 152 drillholes that had measured gypsum, sericite, and pyrite. A contour plot of the neural net predicted distance to ore shows fairly wide areas of 1 km or less to ore; each of the known deposit groups is within the 1 km contour. The high and htw distances on the margins of the contoured distance plot are in part the result of boundary effects of the contouring algorithm. For example, the short distances to ore predicted west of the Shakanai (Hanaoka) deposits are in basement. However, the short distances to ore predicted northeast of Furotobe, just off the figure, coincide with the location of the Nurukawa kuroko deposit and the Omaki deposit, south of the Shakanai-Hanaoka deposits, seems to be on an extension of short distance to ore contour, but is beyond the 3 km limit from drillholes. Also of interest are some areas only a few kilometers from the Fukazawa and Shakanai groups of deposits that are estimated to be many kilometers from ore, apparently reflecting the network's recognition of the extreme local variability of the geology near some deposits. 1996 International Association for Mathematical Geology.

  9. A general scheme for training and optimization of the Grenander deformable template model

    DEFF Research Database (Denmark)

    Fisker, Rune; Schultz, Nette; Duta, N.

    2000-01-01

    parameters, a very fast general initialization algorithm and an adaptive likelihood model based on local means. The model parameters are trained by a combination of a 2D shape learning algorithm and a maximum likelihood based criteria. The fast initialization algorithm is based on a search approach using...... for applying the general deformable template model proposed by (Grenander et al., 1991) to a new problem with minimal manual interaction, beside supplying a training set, which can be done by a non-expert user. The main contributions compared to previous work are a supervised learning scheme for the model...

  10. TEKNIK JARINGAN SYARAF TIRUAN FEEDFORWARD UNTUK PREDIKSI HARGA SAHAM PADA PASAR MODAL INDONESIA

    Directory of Open Access Journals (Sweden)

    Budi Bambang DP.

    1999-01-01

    , beberapa model analisa teknik telah dipakai dan dikembangkan, beberapa analisa tersebut seperti : MACD , Fourier Transform, Accumulator Swing Index, Stochastic Oscilator dan lain lain. Sebagai masukannya digunakan beberapa macam kombinasi harga seperti : harga pembukaan, tertinggi, terendah, penutupan kemarin dan penutupan hari ini serta volume perdagangan. Dan sebagai keluaran adalah suatu grafik yang menampilkan suatu keputusan beli atau jual. Suatu cara lain dalam menentukan harga saham adalah dengan menggunakan metoda 'Fundamental Analysis', yaitu suatu analisa dimana penampilan dari suatu kinerja perusahaan didasarkan atas ratio-ratio / laporan keuangan yang ada. Teknologi sistem jaringan syaraf tiruan telah di-implementasikan dalam berbagai aplikasi terutama dalam hal pengenalan pola. Kemampuan inilah yang telah menarik beberapa kalangan dalam menggunakan jaringan syaraf tiruan untuk keperluan kesehatan, keuangan , investasi, marketing dan lain lain. Pada makalah ini akan dibahas penggunaan Jaringan syaraf tiruan Feedforward/Backpropagarion. Data dari harga saham dapat diperlakukan secara 'time series' . Jika kita mempunyai data harian selama perioda tertentu, misal : Xt (t=1,2,......, maka harga saham pada perioda berikutnya (t+h dapat diprediksi (waktu yang digunakan bisa jam, harian, mingguan , bulanan ataupun tahunan . Demikian seterusnya dilakukan suatu iterasi berulang hingan N hari kerja. Untuk mendapatkan hasil prediksi yang baik maka pada jaringan syaraf buatan hasus di-umpankan suatu masukan yang mewakili dari beberapa aspek atau segi penunjang harga suatu saham. Kemudian dilakukan prinsip pembobotan yang diadaptasikan untuk meminimumkan kesalahan prediksi pada satu langkah kedepan. Dengan menggunakan bobot akhir dilakukan suatu tindakan untuk meminimumkan kesalahan total untuk iterasi berikutnya. Saham yang akan dibahas adalah saham Semen Gresik (SMGR dan Gudang Garam (GGRM Kata kunci: prediksi harga saham, jaringan syaraf tiruan, time series feedforward

  11. Realistic Creativity Training for Innovation Practitioners: The Know-Recognize-React Model

    DEFF Research Database (Denmark)

    Valgeirsdóttir, Dagný; Onarheim, Balder

    2017-01-01

    As creativity becomes increasingly recognized as important raw material for innovation, the importance of identifying ways to increase practitioners’ creativity through rigorously designed creativity training programs is highlighted. Therefore we sat out to design a creativity training program sp...... the transdisciplinary study described in this paper. Co-creation was employed as a method to ensure the three layers of focus would be taken into consideration. The result is a program called Creative Awareness Training which is based on the new Know-Recognize-React model.......As creativity becomes increasingly recognized as important raw material for innovation, the importance of identifying ways to increase practitioners’ creativity through rigorously designed creativity training programs is highlighted. Therefore we sat out to design a creativity training program...

  12. Reflexions on feedforward control strategies for a class of sailing vehicles

    DEFF Research Database (Denmark)

    Xiao, Lin; Jouffroy, Jerome

    2010-01-01

    Sailing vehicles, whether they are sea or land-based, share the unique property of exhibiting totally different trajectories depending on where their direction of travel is with respect to the wind. Following our previous work, this paper discusses a few points related to feedforward control...

  13. A novel controller for bipedal locomotion integrating feed-forward and feedback mechanisms

    NARCIS (Netherlands)

    Xiong, Xiaofeng; Sartori, Massimo; Dosen, Strahinja; González-Vargas, José; Wörgötter, Florentin; Farina, Dario; Ibanez, J.; González-Vargas, J.; Azorin, J.M.; Akay, M.; Pons, J.L.

    2017-01-01

    It has been recognized that bipedal locomotion is controlled using feed-forward (e.g., patterned) and feedback (e.g., reflex) control schemes. However, most current controllers fail to integrate the two schemes to simplify speed control of bipedal locomotion. To solve this problem, we here propose a

  14. Performance trade-offs in disturbance feedforward compensation of active hard-mounted vibration isolators

    NARCIS (Netherlands)

    Beijen, M.A.; Heertjes, M.F.; Butler, H.; Steinbuch, M.

    2015-01-01

    With disturbance feedforward compensation (DFC), input disturbances are measured and compensated to cancel the effect of the disturbance. Perfect cancellation is not possible in practice due to the causal nature of DFC, in which the compensation generally comes too late. Therefore, non-perfect plant

  15. Global output feedback stabilisation of stochastic high-order feedforward nonlinear systems with time-delay

    Science.gov (United States)

    Zhang, Kemei; Zhao, Cong-Ran; Xie, Xue-Jun

    2015-12-01

    This paper considers the problem of output feedback stabilisation for stochastic high-order feedforward nonlinear systems with time-varying delay. By using the homogeneous domination theory and solving several troublesome obstacles in the design and analysis, an output feedback controller is constructed to drive the closed-loop system globally asymptotically stable in probability.

  16. A low-complexity feed-forward I/Q imbalance compensation algorithm

    NARCIS (Netherlands)

    Moseley, N.A.; Slump, Cornelis H.

    2006-01-01

    This paper presents a low-complexity adaptive feed- forward I/Q imbalance compensation algorithm. The feed-forward so- lution has guaranteed stability. Due to its blind nature the algorithm is easily incorporated into an existing receiver design. The algorithm uses three estimators to obtain the

  17. Precision requirements for single-layer feed-forward neural networks

    NARCIS (Netherlands)

    Annema, Anne J.; Hoen, K.; Hoen, Klaas; Wallinga, Hans

    1994-01-01

    This paper presents a mathematical analysis of the effect of limited precision analog hardware for weight adaptation to be used in on-chip learning feedforward neural networks. Easy-to-read equations and simple worst-case estimations for the maximum tolerable imprecision are presented. As an

  18. Different glutamate receptors convey feedforward and recurrent processing in macaque V1

    NARCIS (Netherlands)

    Self, M.W.; Kooijmans, R.N.; Super, H.; Lamme, V.A.F.; Roelfsema, P.R.

    2012-01-01

    Neurons in the primary visual cortex (V1) receive feedforward input from the thalamus, which shapes receptive-field properties. They additionally receive recurrent inputs via horizontal connections within V1 and feedback from higher visual areas that are thought to be important for conscious visual

  19. High-speed linear optics quantum computing using active feed-forward.

    Science.gov (United States)

    Prevedel, Robert; Walther, Philip; Tiefenbacher, Felix; Böhi, Pascal; Kaltenbaek, Rainer; Jennewein, Thomas; Zeilinger, Anton

    2007-01-04

    As information carriers in quantum computing, photonic qubits have the advantage of undergoing negligible decoherence. However, the absence of any significant photon-photon interaction is problematic for the realization of non-trivial two-qubit gates. One solution is to introduce an effective nonlinearity by measurements resulting in probabilistic gate operations. In one-way quantum computation, the random quantum measurement error can be overcome by applying a feed-forward technique, such that the future measurement basis depends on earlier measurement results. This technique is crucial for achieving deterministic quantum computation once a cluster state (the highly entangled multiparticle state on which one-way quantum computation is based) is prepared. Here we realize a concatenated scheme of measurement and active feed-forward in a one-way quantum computing experiment. We demonstrate that, for a perfect cluster state and no photon loss, our quantum computation scheme would operate with good fidelity and that our feed-forward components function with very high speed and low error for detected photons. With present technology, the individual computational step (in our case the individual feed-forward cycle) can be operated in less than 150 ns using electro-optical modulators. This is an important result for the future development of one-way quantum computers, whose large-scale implementation will depend on advances in the production and detection of the required highly entangled cluster states.

  20. Cortical feedback signals generalise across different spatial frequencies of feedforward inputs.

    Science.gov (United States)

    Revina, Yulia; Petro, Lucy S; Muckli, Lars

    2017-09-22

    Visual processing in cortex relies on feedback projections contextualising feedforward information flow. Primary visual cortex (V1) has small receptive fields and processes feedforward information at a fine-grained spatial scale, whereas higher visual areas have larger, spatially invariant receptive fields. Therefore, feedback could provide coarse information about the global scene structure or alternatively recover fine-grained structure by targeting small receptive fields in V1. We tested if feedback signals generalise across different spatial frequencies of feedforward inputs, or if they are tuned to the spatial scale of the visual scene. Using a partial occlusion paradigm, functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA) we investigated whether feedback to V1 contains coarse or fine-grained information by manipulating the spatial frequency of the scene surround outside an occluded image portion. We show that feedback transmits both coarse and fine-grained information as it carries information about both low (LSF) and high spatial frequencies (HSF). Further, feedback signals containing LSF information are similar to feedback signals containing HSF information, even without a large overlap in spatial frequency bands of the HSF and LSF scenes. Lastly, we found that feedback carries similar information about the spatial frequency band across different scenes. We conclude that cortical feedback signals contain information which generalises across different spatial frequencies of feedforward inputs. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  1. Investigating transfer gate potential barrier by feed-forward effect measurement

    NARCIS (Netherlands)

    Xu, Y.; Ge, X.; Theuwissen, A.J.P.

    2015-01-01

    In a 4T pixel, the transfer gate (TG) “OFF” surface potential is one of the important parameters, which determines the pinned photodiode (PPD) full well capacity. The feed-forward effect measurement is a powerful tool to characterize the relationship of the PPD injection potential and the

  2. Active gust load alleviation system for flexible aircraft: Mixed feedforward/feedback approach

    DEFF Research Database (Denmark)

    Alam, Mushfiqul; Hromcik, Martin; Hanis, Tomas

    2015-01-01

    Lightweight flexible blended-wing-body (BWB) aircraft concept seems as a highly promising configuration for future high capacity airliners which suffers from reduced stiffness for disturbance loads such as gusts. A robust feedforward gust load alleviation system (GLAS) was developed to alleviate ...

  3. Causal feedforward control of a stochastically excited fuselage structure with active sidewall panel.

    Science.gov (United States)

    Misol, Malte; Haase, Thomas; Monner, Hans Peter; Sinapius, Michael

    2014-10-01

    This paper provides experimental results of an aircraft-relevant double panel structure mounted in a sound transmission loss facility. The primary structure of the double panel system is excited either by a stochastic point force or by a diffuse sound field synthesized in the reverberation room of the transmission loss facility. The secondary structure, which is connected to the frames of the primary structure, is augmented by actuators and sensors implementing an active feedforward control system. Special emphasis is placed on the causality of the active feedforward control system and its implications on the disturbance rejection at the error sensors. The coherence of the sensor signals is analyzed for the two different disturbance excitations. Experimental results are presented regarding the causality, coherence, and disturbance rejection of the active feedforward control system. Furthermore, the sound transmission loss of the double panel system is evaluated for different configurations of the active system. A principal result of this work is the evidence that it is possible to strongly influence the transmission of stochastic disturbance sources through double panel configurations by means of an active feedforward control system.

  4. Proinflammatory Cytokine Infusion Attenuates LH's Feedforward on Testosterone Secretion: Modulation by Age.

    Science.gov (United States)

    Veldhuis, Johannes; Yang, Rebecca; Roelfsema, Ferdinand; Takahashi, Paul

    2016-02-01

    In the experimental animal, inflammatory signals quench LH's feedforward drive of testosterone (T) secretion and appear to impair GnRH-LH output. The degree to which such suppressive effects operate in the human is not known. To test the hypothesis that IL-2 impairs LH's feedforward drive on T and T's feedback inhibition of LH secretion in healthy men. Mayo Center for Translational Science Activities. A total of 35 healthy men, 17 young and 18 older. Randomized prospective double-blind saline-controlled study of IL-2 infusion in 2 doses with concurrent 10-minute blood sampling for 24 hours. Deconvolution analysis of LH and T secretion. After saline injection, older compared with young men exhibited reduced LH feedforward drive on T secretion (P enforces biochemical hypogonadism, viz, combined feedforward block and feedback amplification; and 2) unequal absolute inhibition of T and LH secretion by IL-2 in young and older men. These outcomes establish that the male gonadal axis is susceptible to dual-site suppression by a prototypic inflammatory mediator. Thus, we postulate that selected ILs might also enforce male hypogonadism in chronic systemic inflammation.

  5. Development of a Base Model for the New Fire PSA Training

    International Nuclear Information System (INIS)

    Kim, Kilyoo; Kang, Daeil; Kim, Wee Kyong; Do, Kyu Sik

    2013-01-01

    US NRC/EPRI issued a new fire PSA method represented by NUREG/CR 6850, and have been training many operators and inspectors to widely spread the new method. However, there is a limitation in time and efficiency for many foreigners, who generally have communication problem, to participate in the EPRI/NRC training to learn the new method. Since it is about time to introduce the new fire PSA method as a regulatory requirement for the fire protection in Korea, a simple and easy-understandable base model for the fire PSA training is required, and KAERI-KINS is jointly preparing the base model for the new fire PSA training. This paper describes how the base model is developed. Using an imaginary simple NPP, a base model of fire PSA following the new fire PSA method was developed in two ways from the internal PSA model. Since we have the base model and know the process of making the fire PSA model, the training for the new fire PSA method can be in detail performed in Korea

  6. A biologically inspired neural model for visual and proprioceptive integration including sensory training.

    Science.gov (United States)

    Saidi, Maryam; Towhidkhah, Farzad; Gharibzadeh, Shahriar; Lari, Abdolaziz Azizi

    2013-12-01

    Humans perceive the surrounding world by integration of information through different sensory modalities. Earlier models of multisensory integration rely mainly on traditional Bayesian and causal Bayesian inferences for single causal (source) and two causal (for two senses such as visual and auditory systems), respectively. In this paper a new recurrent neural model is presented for integration of visual and proprioceptive information. This model is based on population coding which is able to mimic multisensory integration of neural centers in the human brain. The simulation results agree with those achieved by casual Bayesian inference. The model can also simulate the sensory training process of visual and proprioceptive information in human. Training process in multisensory integration is a point with less attention in the literature before. The effect of proprioceptive training on multisensory perception was investigated through a set of experiments in our previous study. The current study, evaluates the effect of both modalities, i.e., visual and proprioceptive training and compares them with each other through a set of new experiments. In these experiments, the subject was asked to move his/her hand in a circle and estimate its position. The experiments were performed on eight subjects with proprioception training and eight subjects with visual training. Results of the experiments show three important points: (1) visual learning rate is significantly more than that of proprioception; (2) means of visual and proprioceptive errors are decreased by training but statistical analysis shows that this decrement is significant for proprioceptive error and non-significant for visual error, and (3) visual errors in training phase even in the beginning of it, is much less than errors of the main test stage because in the main test, the subject has to focus on two senses. The results of the experiments in this paper is in agreement with the results of the neural model

  7. Integrating Soft Set Theory and Fuzzy Linguistic Model to Evaluate the Performance of Training Simulation Systems.

    Science.gov (United States)

    Chang, Kuei-Hu; Chang, Yung-Chia; Chain, Kai; Chung, Hsiang-Yu

    2016-01-01

    The advancement of high technologies and the arrival of the information age have caused changes to the modern warfare. The military forces of many countries have replaced partially real training drills with training simulation systems to achieve combat readiness. However, considerable types of training simulation systems are used in military settings. In addition, differences in system set up time, functions, the environment, and the competency of system operators, as well as incomplete information have made it difficult to evaluate the performance of training simulation systems. To address the aforementioned problems, this study integrated analytic hierarchy process, soft set theory, and the fuzzy linguistic representation model to evaluate the performance of various training simulation systems. Furthermore, importance-performance analysis was adopted to examine the influence of saving costs and training safety of training simulation systems. The findings of this study are expected to facilitate applying military training simulation systems, avoiding wasting of resources (e.g., low utility and idle time), and providing data for subsequent applications and analysis. To verify the method proposed in this study, the numerical examples of the performance evaluation of training simulation systems were adopted and compared with the numerical results of an AHP and a novel AHP-based ranking technique. The results verified that not only could expert-provided questionnaire information be fully considered to lower the repetition rate of performance ranking, but a two-dimensional graph could also be used to help administrators allocate limited resources, thereby enhancing the investment benefits and training effectiveness of a training simulation system.

  8. Functional and muscular adaptations in an experimental model for isometric strength training in mice.

    Directory of Open Access Journals (Sweden)

    Karsten Krüger

    Full Text Available Exercise training induces muscular adaptations that are highly specific to the type of exercise. For a systematic study of the differentiated exercise adaptations on a molecular level mouse models have been used successfully. The aim of the current study was to develop a suitable mouse model of isometric strength exercise training characterized by specific adaptations known from strength training. C57BL/6 mice performed an isometric strength training (ST for 10 weeks 5 days/week. Additionally, either a sedentary control group (CT or a regular endurance training group (ET groups were used as controls. Performance capacity was determined by maximum holding time (MHT and treadmill spirometry, respectively. Furthermore, muscle fiber types and diameter, muscular concentration of phosphofructokinase 1 (PFK, succinate dehydrogenase (SDHa, and glucose transporter type 4 (GLUT4 were determined. In a further approach, the effect of ST on glucose intolerance was tested in diabetic mice. In mice of the ST group we observed an increase of MHT in isometric strength tests, a type II fiber hypertrophy, and an increased GLUT4 protein content in the membrane fraction. In contrast, in mice of the ET group an increase of VO(2max, a shift to oxidative muscle fiber type and an increase of oxidative enzyme content was measured. Furthermore strength training was effective in reducing glucose intolerance in mice fed a high fat diet. An effective murine strength training model was developed and evaluated, which revealed marked differences in adaptations known from endurance training. This approach seems also suitable to test for therapeutical effects of strength training.

  9. Discrete event model-based simulation for train movement on a single-line railway

    International Nuclear Information System (INIS)

    Xu Xiao-Ming; Li Ke-Ping; Yang Li-Xing

    2014-01-01

    The aim of this paper is to present a discrete event model-based approach to simulate train movement with the considered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of the traffic flow and demonstrate the effectiveness of the proposed approach. The simulation results indicate that the proposed discrete event model-based simulation approach is suitable for characterizing the movements of a group of trains on a single railway line with less iterations and CPU time. Additionally, some other qualitative and quantitative characteristics are investigated. In particular, because of the cumulative influence from the previous trains, the following trains should be accelerated or braked frequently to control the headway distance, leading to more energy consumption. (general)

  10. Realistic Creativity Training for Innovation Practitioners: The Know-Recognize-React Model

    DEFF Research Database (Denmark)

    Valgeirsdóttir, Dagný; Onarheim, Balder

    2017-01-01

    As creativity becomes increasingly recognized as important raw material for innovation, the importance of identifying ways to increase practitioners’ creativity through rigorously designed creativity training programs is highlighted. Therefore we sat out to design a creativity training program...... the transdisciplinary study described in this paper. Co-creation was employed as a method to ensure the three layers of focus would be taken into consideration. The result is a program called Creative Awareness Training which is based on the new Know-Recognize-React model....

  11. The role of incoherent microRNA-mediated feedforward loops in noise buffering.

    Directory of Open Access Journals (Sweden)

    Matteo Osella

    2011-03-01

    Full Text Available MicroRNAs are endogenous non-coding RNAs which negatively regulate the expression of protein-coding genes in plants and animals. They are known to play an important role in several biological processes and, together with transcription factors, form a complex and highly interconnected regulatory network. Looking at the structure of this network, it is possible to recognize a few overrepresented motifs which are expected to perform important elementary regulatory functions. Among them, a special role is played by the microRNA-mediated feedforward loop in which a master transcription factor regulates a microRNA and, together with it, a set of target genes. In this paper we show analytically and through simulations that the incoherent version of this motif can couple the fine-tuning of a target protein level with an efficient noise control, thus conferring precision and stability to the overall gene expression program, especially in the presence of fluctuations in upstream regulators. Among the other results, a nontrivial prediction of our model is that the optimal attenuation of fluctuations coincides with a modest repression of the target expression. This feature is coherent with the expected fine-tuning function and in agreement with experimental observations of the actual impact of a wide class of microRNAs on the protein output of their targets. Finally, we describe the impact on noise-buffering efficiency of the cross-talk between microRNA targets that can naturally arise if the microRNA-mediated circuit is not considered as isolated, but embedded in a larger network of regulations.

  12. Top-down modulation on perceptual decision with balanced inhibition through feedforward and feedback inhibitory neurons.

    Directory of Open Access Journals (Sweden)

    Cheng-Te Wang

    Full Text Available Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.

  13. Top-down modulation on perceptual decision with balanced inhibition through feedforward and feedback inhibitory neurons.

    Science.gov (United States)

    Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

    2013-01-01

    Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.

  14. Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model

    Science.gov (United States)

    Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.

    2012-12-01

    The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that

  15. Outreach training model for accredited colorectal specialists in laparoscopic colorectal surgery: feasibility and evaluation of challenges.

    Science.gov (United States)

    Hamdan, M F; Day, A; Millar, J; Carter, F J C; Coleman, M G; Francis, N K

    2015-07-01

    The aim of this study was to explore the feasibility and safety of an outreach model of laparoscopic colorectal training of accredited specialists in advanced laparoscopic techniques and to explore the challenges of this model from the perspective of a National Training Programme (NTP) trainer. Prospective data were collected for unselected laparoscopic colorectal training procedures performed by five laparoscopic colorectal NTP trainees supervised by a single NTP trainer with an outreach model between 2009 and 2012. The operative and postoperative outcomes were compared with standard laparoscopic colorectal training procedures performed by six senior colorectal trainees under the supervision of the same NTP trainer within the same study period. The primary outcome was 30-day mortality. The Mann-Whitney test was used to compare continuous variables and the Chi squared or Fisher's exact tests were applied for the analysis of categorical variables. The level of statistical significance was set at P groups. Seventy-eight per cent of the patients operated on by the NTP trainees had had no previous abdominal surgery, compared with 50% in the supervised trainees' group (P = 0.0005). There were no significant differences in 30-day mortality or the operative and postoperative outcome between both groups. There were, however, difficulties in training an already established consultant in his or her own hospital and these were overcome by certain adjustments to the programme. Outreach laparoscopic training of colorectal surgeons is a feasible and safe model of training accredited specialists and does not compromise patient care. The challenges encountered can be overcome with optimum training and preparation. Colorectal Disease © 2015 The Association of Coloproctology of Great Britain and Ireland.

  16. Development of Innovative Tools and Models for Vocational Education and Training in Central and Western Romania

    Directory of Open Access Journals (Sweden)

    Liviu Moldovan

    2009-12-01

    Full Text Available This paper presents an initiative developed by two partner universities from Romania and Norway entitled „Innovative Tools and models for Vocational Education and Training in Central and western Romania” (MoVE-IT financed by SEE mechanism [1]. It has the priority to develop human resource through promotion of education and training, by means of distance learning. The objective, legal issues, outcome and results and envisaged impact of the project are presented.

  17. Does rational selection of training and test sets improve the outcome of QSAR modeling?

    Science.gov (United States)

    Martin, Todd M; Harten, Paul; Young, Douglas M; Muratov, Eugene N; Golbraikh, Alexander; Zhu, Hao; Tropsha, Alexander

    2012-10-22

    Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods can divide data sets into training and test sets in an intelligent fashion. The purpose of this study was to determine whether rational division methods lead to more predictive models compared to random division. A special data splitting procedure was used to facilitate the comparison between random and rational division methods. For each toxicity end point, the overall data set was divided into a modeling set (80% of the overall set) and an external evaluation set (20% of the overall set) using random division. The modeling set was then subdivided into a training set (80% of the modeling set) and a test set (20% of the modeling set) using rational division methods and by using random division. The Kennard-Stone, minimal test set dissimilarity, and sphere exclusion algorithms were used as the rational division methods. The hierarchical clustering, random forest, and k-nearest neighbor (kNN) methods were used to develop QSAR models based on the training sets. For kNN QSAR, multiple training and test sets were generated, and multiple QSAR models were built. The results of this study indicate that models based on rational division methods generate better statistical results for the test sets than models based on random division, but the predictive power of both types of models are comparable.

  18. Development of structural model of adaptive training complex in ergatic systems for professional use

    Science.gov (United States)

    Obukhov, A. D.; Dedov, D. L.; Arkhipov, A. E.

    2018-03-01

    The article considers the structural model of the adaptive training complex (ATC), which reflects the interrelations between the hardware, software and mathematical model of ATC and describes the processes in this subject area. The description of the main components of software and hardware complex, their interaction and functioning within the common system are given. Also the article scrutinizers a brief description of mathematical models of personnel activity, a technical system and influences, the interactions of which formalize the regularities of ATC functioning. The studies of main objects of training complexes and connections between them will make it possible to realize practical implementation of ATC in ergatic systems for professional use.

  19. Video modeling to train staff to implement discrete-trial instruction.

    Science.gov (United States)

    Catania, Cynthia N; Almeida, Daniel; Liu-Constant, Brian; DiGennaro Reed, Florence D

    2009-01-01

    Three new direct-service staff participated in a program that used a video model to train target skills needed to conduct a discrete-trial session. Percentage accuracy in completing a discrete-trial teaching session was evaluated using a multiple baseline design across participants. During baseline, performances ranged from a mean of 12% to 63% accuracy. During video modeling, there was an immediate increase in accuracy to a mean of 98%, 85%, and 94% for each participant. Performance during maintenance and generalization probes remained at high levels. Results suggest that video modeling can be an effective technique to train staff to conduct discrete-trial sessions.

  20. [Design and validation of a training model on paediatric and neonatal surgery].

    Science.gov (United States)

    Pérez-Duarte, F J; Díaz-Güemes, I; Sánchez-Hurtado, M A; Cano Novillo, I; Berchi García, F J; García Vázquez, A; Sánchez-Margallo, F M

    2012-07-01

    We present our experience in the design and development of a training program in paediatric and neonatal laparoscopic surgery, and the determination of face validity by the attendants. Data included in the present study was obtained from five consecutive editions of our Neonatal and Paediatric Laparoscopic Surgery Course. Our training model, with a total duration of 21 hours, begins with acquisition of knowledge in ergonomics and instrument concepts, after which the attendants develop basic laparoscopic dexterity through the performance of hands-on physical simulator tasks. During the second and third days of the course, surgeons undertook various surgical techniques hands-on animal model. At the end of the training program, a subjective evaluation questionnaire was handed out to the attendants, in which different didactic and organizational aspects were considered. We obtained a highly positive score on all questions concerning the different topics and techniques included in the training program (> or = 9 points over 10). 78,5% of the 54 attendants was in accordance with the course total duration, whilst 21,5% considered that it should be of longer duration. Regarding abilities' self assessment, 79,1% considered themselves capacitated to perform trained procedures on live patients. The presented training model has obtained a very positive valuation score, leading to an increase in the attendants' self confidence in the application of learned techniques to their clinical practice.