–The aim of this study was to compare the acute effects of low-intensity (LI) resistance exercise (RE) with continuous blood flow restriction (CBFR) and intermittent blood flow restriction (IBFR) on systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP). After a one-repetition maximum test, 10 normotensive recreationally trained men performed three exper...

Cascade-Correlation is a new architecture and supervised learning algorithm for artificial neural networks. Instead of just adjusting the weights in a network of fixed topology, Cascade-Correlation begins with a minimal network, then automatically trains and adds new hidden units one by one, creating a multi-layer structure. Once a new hidden unit has been added to the network, its input-side w...

In this paper we developed a new method for computing learning rate Back-propagation algorithm to train feed-forward neural networks. Our idea is based on the approximating inverse Hessian matrix error function originally suggested by Andrie. Experimental results show that proposed considerably improve convergence of chosen test problem.

Hypertension is a major public health problem in black populations worldwide.1,2 Although hypertension is usually asymptomatic, it may be associated with considerable morbidity and mortality. The higher the blood pressure, the greater the risk for adverse outcomes including development of coronary heart disease3. Hypertension treatment has been clearly shown to reduce this risk.3,4 A study cond...

In this paper, performance of three classifiers for classification of five mental tasks were investigated. Wavelet Packet Transform (WPT) was used for feature extraction of the relevant frequency bands from raw Electroencephalograph (EEG) signal. The three classifiers namely used were Multilayer Back propagation Neural Network, Support Vector Machine and Radial Basis Function Neural Network. In...

The equilibrium moisture content and specific gravity of Uludag fir (Abies bornmüelleriana Mattf.) hornbeam (Carpinus betulus L.) woods were investigated following heat treatment at different temperatures times. Two prediction models established based on the Aquila optimization algorithm back-propagation neural network model. To demonstrate effectiveness accuracy proposed model, it was compared...

The back propagation algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a training algorithm consisting of a learning rate and a momentum factor. The major drawbacks of above learning algorithm are the problems of local minima and slow convergence speeds. The addition of an extra term, called a proportional factor reduces the convergence of th...

a neural network is developed for the determination of leaky confined aquifer parameters. leakage into the aquifer takes place from the storage in the confining aquitard. the network is trained for the well function of leaky confined aquifers by the back propagation technique and adopting the levenberg–marquardt optimization algorithm. by applying the principal component analysis (pca) on the a...

important parameters on apple drying process are investigated experimentally and modeled employing artificial neural network and neuro-taguchi's method. experimental results show that the apple drying curve stands in the falling rate period of drying. temperature is the most important parameter that has a more pronounced effect on drying rate than the other two parameters i.e. air velocity and ...

Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched...