In this paper we describe and compare two different methods to reduce the cardinality of the set of candidates nodules, characterized by an high sensitivity ratio, and extracted from PA chest radiographs by a fully automatized method. The methods are a rule based system and a feed-forward neural network trained by back-propagation. Both the systems allow to recognize almost the 021 % of false p...

There is little consensus on the corporate diversification-efficiency relationship in the diversification literature. According to the corporate diversification, firms have a tendency to get more market share with diversifying in the local segment or in the international market. Theoretically, a contradictory exists between the profitable strategy and the value reducing strategy in the diversif...

In this paper a nonparametric neural network (NN) technique for prediction of future values of a signal based on its past history is presented. This approach bypasses modeling, identification, and parameter estimation phases that are required by conventional parametric techniques. A multi-layer feed forward NN is employed. It develops an internal model of the signal through a training operation...

Supervisor’s feedback is both a naysaying and a puzzling concern that has always tormented academics in higher education. Particularly, written feedback on pre-final or final versions of a submitted doctoral dissertation is indisputably the most significant step toward granting a doctoral student supervisee the right to defend his/her research project. It also constitutes a rich source on how s...

Common heat transfer fluids such as water, ethylene glycol, and engine oil have limited heat transfer capabilities due to their low heat transfer properties. Nanofluids are suspensions of nanoparticles in base fluids, a new challenge for thermal sciences provided by nanotechnology. In this study, we are to optimize and report the effects of various parameters such as the ratio of the thermal co...

Simultaneous spectrophotometric estimation of Fluoxetine and Sertraline in tablets were performed using UV–Vis spectroscopic and Artificial Neural Networks (ANN). Absorption spectra of two components were recorded in 200–300 (nm) wavelengths region with an interval of 1 nm. The calibration models were thoroughly evaluated at several concentration levels using the spectra of synthetic binary mix...

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.