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Investigational analysis and evaluation of cooperative learning phenomenon is a challenging educational issue. Recently, educationalists have adopted interesting research work concerned with realistic modeling of human's cooperative learning phenomenon. That's by investigation of its analogy with natural behavioral learning aspects, observed by swarm intelligence of social insects colonies. Herein,...
This paper addresses an interdisciplinary solution for one of the problems associated with computerized educational disciplines. Addressed problem basically concerned with realistic computer-based educational simulations (e-Sims). More specifically, it searches for optimal software learning package(s) applied for teaching of specified curriculum(s) in classroom(s). Herein, quantitative evaluation...
Searching for the next hop node in mobile sparse wireless sensor networks for data exchange is a challenging task. This involves frequently sending radio beacons that drain battery power and reduces the life of the sensor node. This work proposes a novel energy efficient approach of adaptively sampling the network connectivity. The adaptive sampling starts with random sampling of the network to collect...
This paper presents an investigation into the performance of system identification using Backpropagation Multi-layer Perceptron Neural Networks algorithm for identification of a flexible plate system. Details of the implementation and the experimental studies are given and analyzed in the paper. The input-output data of the system were first acquired through the experimental studies using National...
This study presents the application of artificial neural networks for modeling the parameters of Lewis-Kostiakov infiltration under conventional tillage systems on a clay soil. The conventional tillage systems were moldboard, chisel and rotary plows. Water infiltration rate was defined experimentally by double ring infiltrometer. Artificial neural network estimation indicated strong correlations (R...
This paper considers the problem of real time adaptive control of nonlinear multivariable systems. Two neural networks techniques are presented to solve the problem mentioned above. The first technique combines the ability of a single-layer feedforward neural network for modeling purposes and a linear control law to design the controller. The second technique combines the ability of dynamic recurrent...
In the following paper we present a complete analytical model that predicts the band-gap (Eg) of single-walled carbon nanotubes (SWCNTs) directly from their diameter (d) and chiral angle (thetas). The proposed analytical model is based on two mathematical expressions that have been derived by curve-fitting the outcome generated from the third-nearest-neighbor tight-binding (TB) method in conjunction...
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