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hybrid training

Therapeutic effect of hybrid training of voluntary and electrical muscle contractions in middle-aged obese women with nonalcoholic fatty liver disease: a pilot trial

Therapeutic effect of hybrid training of voluntary and electrical muscle contractions in middle-aged obese women with nonalcoholic fatty liver disease: a pilot trial

... Exercise training is an effective therapy for nonalcoholic fatty liver disease ...(NAFLD). Hybrid training (HYB) of voluntary and electrical muscle contractions was developed to prevent disuse ...

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Licensed Chemical Dependency Counselor California Hybrid Training Program

Licensed Chemical Dependency Counselor California Hybrid Training Program

... It is important to note that the ICDS – Sober College Hybrid Training Program is based on rolling admissions. This means that you may be starting anywhere between Course 1 through Course 4. This does not ...

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Manifold absolute pressure estimation using neural network with hybrid training algorithm

Manifold absolute pressure estimation using neural network with hybrid training algorithm

... experimental training data, the estimator network that trained with the sec­ ond variant of the hybrid algorithm (LM+BR+PSOb) showed the best performance, with MSE of ...

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A Hybrid Differential Evolution and Back Propagation Algorithm for Feedforward Neural Network Training

A Hybrid Differential Evolution and Back Propagation Algorithm for Feedforward Neural Network Training

... non-Lamarckian hybrid approach by utilizing both evolutionary and gradient ...This hybrid training of FNN using the differential evolution to do global search in the beginning of training, and ...

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Hybrid generative-discriminative training of Gaussian mixture models

Hybrid generative-discriminative training of Gaussian mixture models

... the hybrid CLL objective used in this paper, but they did not con- sider ...the hybrid LM objective used in this ...GMM training using the hybrid LM objective intrinsically more di ffi ...a ...

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A FASTER ESTIMATION ALGORITHM APPLIED TO POWER QUALITY PROBLEMS

A FASTER ESTIMATION ALGORITHM APPLIED TO POWER QUALITY PROBLEMS

... for training the weights of neural network namely gradient descent (GD), Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and hybrid of Particle Swarm Optimization (PSO) and gradient descend (GD) ...

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How to Speak a Language without Knowing It

How to Speak a Language without Knowing It

... Finally, we repeat the last experiment, but re- moving the human from the loop, using both automatic Chinese speech synthesis and English speech recognition. Results are shown in Table 8. Speech recognition is more ...

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MACOMB COUNTY CTE ADVISORY COMMITTEE MEETING MINUTES ENGINEERING / MANUFACTURING AND INDUSTRIAL TECHNOLOGY PATHWAY

MACOMB COUNTY CTE ADVISORY COMMITTEE MEETING MINUTES ENGINEERING / MANUFACTURING AND INDUSTRIAL TECHNOLOGY PATHWAY

... • Hybrid training classes; hybrid tools/technology; seminars - as instructors hard to get into classes; they are during work hours, weekends, too time consuming; expensive to get into hybrid ...

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Training with Hybrid Assistive Limb for walking function after total knee arthroplasty

Training with Hybrid Assistive Limb for walking function after total knee arthroplasty

... HAL training in stroke patients, improvements in walking speed accompanied by improvements in gait symmetry and increase in step length were observed ...HAL training for post-TKA patients seems to be a ...

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Online Medical Data Stream Mining Based on Adaptive Neuro-Fuzzy Approaches

Online Medical Data Stream Mining Based on Adaptive Neuro-Fuzzy Approaches

... into training and testing sets (126 patients were in the training set, 62 patients were in the testing ...the training and testing errors of multidimensional neo-fuzzy neuron and the value of the ...

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Hybrid Selection of Language Model Training Data Using Linguistic Information and Perplexity

Hybrid Selection of Language Model Training Data Using Linguistic Information and Perplexity

... This paper has explored the use of linguistic infor- mation (lemmas and named entities) for the task of training data selection for LMs. We have intro- duced three linguistically motivated models, and compared ...

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Joint Training Methods for Tandem and Hybrid Speech Recognition Systems using Deep Neural Networks

Joint Training Methods for Tandem and Hybrid Speech Recognition Systems using Deep Neural Networks

... DNN training configuration is listed in Table ...MPE training, and is used throughout the ...MPE training was ...MPE training performance, and all results presented later in this chapter were ...

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Neural Network based Intrusion Detection Systems

Neural Network based Intrusion Detection Systems

... used a combination of RBF Networks and SOM in the IDS for easy extension so as to automatically adapt to classification results of an human expert without complete re-training, this experiment resulted in very ...

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Fast and Effective Network Anomaly Detection Technique Using Hybrid Sequential Pattern algorithms

Fast and Effective Network Anomaly Detection Technique Using Hybrid Sequential Pattern algorithms

... The traffic data sets is considered in this work consists of attributes like protocol type, service, flag, duration such data are collected from the repositories. To avoid the imbalance of the dataset, the sample set are ...

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Patient-centric implementation of an electronic medication management system at a tertiary hospital in Western Sydney

Patient-centric implementation of an electronic medication management system at a tertiary hospital in Western Sydney

... administration. Training was commenced 6 weeks prior to go-live, though the majority of staff were trained in the latter 3 ...Go-live training, superuser and incident statistics are shown in Table ...

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Millimeter-Wave Beam Training Acceleration through Low-Complexity Hybrid Transceivers

Millimeter-Wave Beam Training Acceleration through Low-Complexity Hybrid Transceivers

... beam training protocol which exploits the parallel, multi-directional scanning capabilities of hybrid analog-digital ...beam training phase, enabled by the ability of hybrid transceivers to ...

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Random neural network learning heuristics

Random neural network learning heuristics

... Gelenbe introduced the GD algorithm for recurrent RNN in Gelenbe [30] which can be applied to a feed forward RNN model. Gelenbe and Timotheou [48] developed an extension of RNN to the case of synchronous interactions in ...

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Short Term Load Forecasting Using A Hybrid Model Based On Support Vector Regression

Short Term Load Forecasting Using A Hybrid Model Based On Support Vector Regression

... This paper proposed a hybrid method based on SVR and KH algorithm to predict the load data with more accuracy. The proposed method uses the KH algorithm to adjust the kernel function (σ) and the optimal hyper ...

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Developing guidance for the appropriate use of computed tomography within a hybrid imaging environment  “CT Competencies”

Developing guidance for the appropriate use of computed tomography within a hybrid imaging environment “CT Competencies”

... skills, competencies and evidence of appropriate training to safely utilise CT within hybrid imaging in modern practice.. This is taken from current UWE/Society of Radiographers researc[r] ...

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A new approach to fuzzy random forest generation

A new approach to fuzzy random forest generation

... This hybrid scheme was denoted as rule and condition selection (RCS) in ...the training set is pre-processed by transforming each continuous variable into a categorical and ordered ...transformed ...

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