The Go-Back-N and Selective-Repeat automatic repeat request (ARQ) protocols are widely used for error control in computer-communication networks. They are nearly optimal for channels characterized by low error rates and small propagation delays, and thus suitable for many classical data transmission applications. However, these protocols are not eecient for modern non-conventional channels with...

Objective of this paper is to develop a new technique for solving Transportation Problems (TP) by considering uncertainty in deterministic case for multi periods. There are many obtainable techniques for solving TP for deterministic cases. But these techniques are not applicable to solve multi period TP when uncertainty arises. In this paper, a technique has proposed to handle this uncertainty ...

In this paper, an extended DBP (E DBP) scheme is studied for (m,k)-firm constraint. The basic idea of the proposed algorithm takes into account the distance to exit a failure state, which is a symmetrical notion of distance to fall into a failure state in DBP. Quality of Service (QoS) in terms of dynamic failure and delay is evaluated. Simulation results reveal the effectiveness of E DBP to pro...

In this paper a critical review of gradient-based training methods for recurrent neural networks is presented including Back Propagation Through Time (BPTT), Real Time Recurrent Learning (RTRL) and several specific learning algorithms for different locally recurrent architectures. From this survey it comes out the need for a unifying view of all the specific procedures proposed for networks wit...

We have previously reported that the administration of a large amount of di(n-blltyl)phthalftte (DBP) increased the conversion ratio of tryptophan to niacin in rats. In the present experiment, the effect of di(2-ethylhexyl)phthalate (DEHP) on the conyersion ratio and how altering the conversion ratio of tryptophan to niacin depended on the concentration of DEHP were inyestigated to elucidate th...

As traditional neural network consumes a significant amount of computing resources during back propagation, Sun et al. (2017) propose a simple yet effective technique to alleviate this problem. In this technique, only a small subset of the full gradients are computed to update the model parameters. In this paper we extend this technique into the Convolutional Neural Network(CNN) to reduce calcu...

This study explores a semi-supervised classification approach using random forest as a base classifier to classify the low-back disorders (LBDs) risk associated with the industrial jobs. Semi-supervised classification approach uses unlabeled data together with the small number of labelled data to create a better classifier. The results obtained by the proposed approach are compared with those o...

The cavability assessment of rock mass cavability and indicating the damage profile ahead of a cave-back is of great importance in the evaluation of a caving mine operation, which can influence all aspects of the mine operation. Due to the lack of access to the caved zones, our current knowledge about the damage profile in caved zones is very limited. Among the different approaches available, p...