The training of supervisors in corrugated box plants: ten lesson plans.

Mode of access: Internet.

Education and training of American workers : paper prepared for the OECD National Experts Group on Training Statistics.

"June 1990."

The organization and training of joint task forces /

"April 1996."

The Universal standard speaker; a handbook of entertainment for all occassions; including rules for the training of the voice and the use of gesture.

Mode of access: Internet.

Regulations for the training of teachers for elementary schools

Mode of access: Internet.

Training of civil aircraft mechanics : hearing before a subcommittee of the Committee on Interstate and Foreign Commerce, House of Representatives, Seventy-seventh Congress, first session on H.R. 5695 a bill to amend the Civilian Pilot Training Act of 1939 so as to provide for the training of civilian aviation mechanics, December 8, 1941.

Mode of access: Internet.

The phonographic amanuensis.: A presentation of Pitman phonography, more especially adapted to the use of business and other schools devoted to the instruction and training of shorthand amanuenses.

Impression: 35th thousand.

Training of Teachers; Report, Statistics

Mode of access: Internet.

Age-related differences in rapid muscle activation after rate of force development training of the elbow flexors

In young adults, improvements in the rate of force development as a result of resistance training are accompanied by increases in neural drive in the very initial phase of muscle activation. The purpose of this experiment was to determine if older adults also exhibit similar adaptations in response to rate of force development (RFD) training. Eight young (21-35 years) and eight older (60-79 years) adults were assessed during the production of maximum rapid contractions, before and after four weeks of progressive resistance training for the elbow flexors. Young and older adults exhibited significant increases (P< 0.01) in peak RFD, of 25.6% and 28.6% respectively. For both groups the increase in RFD was accompanied by an increase in the root mean square (RMS) amplitude and in the rate of rise (RER) in the electromyogram (EMG) throughout the initial 100 ms of activation. For older adults, however, this training response was only apparent in the brachialis and brachioradialis muscles. This response was not observed in surface EMG recorded from the biceps brachii muscle during either RFD testing or throughout training, nor was it observed in the pronator teres muscle. The minimal adaptations observed for older adults in the bifunctional muscles biceps brachii and pronator teres are considered to indicate a compromise of the neural adaptations older adults might experience in response to resistance training.

Description and training of neural network dynamics

Attractor properties of a popular discrete-time neural network model are illustrated through numerical simulations. The most complex dynamics is found to occur within particular ranges of parameters controlling the symmetry and magnitude of the weight matrix. A small network model is observed to produce fixed points, limit cycles, mode-locking, the Ruelle-Takens route to chaos, and the period-doubling route to chaos. Training algorithms for tuning this dynamical behaviour are discussed. Training can be an easy or difficult task, depending whether the problem requires the use of temporal information distributed over long time intervals. Such problems require training algorithms which can handle hidden nodes. The most prominent of these algorithms, back propagation through time, solves the temporal credit assignment problem in a way which can work only if the relevant information is distributed locally in time. The Moving Targets algorithm works for the more general case, but is computationally intensive, and prone to local minima.

Efficient training of RBF networks for classification.

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. We show how RBFs with logistic and softmax outputs can be trained efficiently using the Fisher scoring algorithm. This approach can be used with any model which consists of a generalised linear output function applied to a model which is linear in its parameters. We compare this approach with standard non-linear optimisation algorithms on a number of datasets.

Bayesian training of mixture density networks

Mixture Density Networks (MDNs) are a well-established method for modelling the conditional probability density which is useful for complex multi-valued functions where regression methods (such as MLPs) fail. In this paper we extend earlier research of a regularisation method for a special case of MDNs to the general case using evidence based regularisation and we show how the Hessian of the MDN error function can be evaluated using R-propagation. The method is tested on two data sets and compared with early stopping.

Efficient training of RBF networks for classification

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. In this paper we show how RBFs with logistic and softmax outputs can be trained efficiently using algorithms derived from Generalised Linear Models. This approach is compared with standard non-linear optimisation algorithms on a number of datasets.