This research uses a comprehensive method to solve a combinatorial problem of distribution network expansion planning (DNEP) problem. The proposed multi-objective scheme aims to improve power system's accountability and system performance parameters, simultaneously, in the lowest possible costs. The dynamic programming approach is implemented in order to find the optimal sizing, siting and timi...

During the last decade, reverse logistics networks received a considerable attention due to economic importance and environmental regulations and customer awareness. Integration of leading and reverse logistics networks during logistical network design is one of the most important factors in supply chain. In this research, an Integer Linear Programming model is presented to design a multi-layer...

Gesture recognition is getting more and popular due to various application possibilities in human-machine interaction. Existing multi-modal gesture systems take data as input improve accuracy, but such methods require modality sensors, which will greatly limit their scenarios. Therefore we propose an end-to-end multi-task learning framework training 2D convolutional neural networks. The can use...

many performance evaluations for ieee 802.11distributed coordination function (dcf) have been previouslyreported in the literature. some of them have clearly indicatedthat 802.11 mac protocol has poor performance in multi-hopwireless ad hoc networks due to exposed and hidden nodeproblems. although rts/cts transmission scheme mitigatesthese phenomena, it has not been successful in thoroughlyomit...

in this paper we have discussed the main features of a finite clement program which we have developed for nonlinear dynamic analysis of plates and shells with material and geometric nonlinear behaviour. for this purpose, initially, the finite element model which we have used is briefly described. afterwards, the nonlinear viscoplastic material model in one-dimensional and multi-dimensional medi...

We describe various industrial and business applications of a common approach for learning the probability distributions and the structure of Bayesian networks. After describing the Bayesian learning theory, we explain how the parameters learned with this method can be used for prediction tasks in various application domains. In the first domain we learn the structure and the probability distri...

Epistemic planning can be used for decision making in multi-agent situations with distributed knowledge and capabilities. Recently, Dynamic Epistemic Logic (DEL) has been shown to provide a very natural and expressive framework for epistemic planning. We extend the DEL-based epistemic planning framework to include perspective shifts, allowing us to define new notions of sequential and condition...

Extractive style query oriented multi document summariza tion generates the summary by extracting a proper set of sentences from multiple documents based on the pre given query. This paper proposes a novel multi document summa rization framework via deep learning model. This uniform framework consists of three parts: concepts extraction, summary generation, and reconstruction validation, which ...

The performance of video tone-mapping operators is investigated in a rating experiment using two criteria: overall quality and fidelity to real-world experience. The study includes a tone-curve used in commercial cameras, rarely considered in tone-mapping evaluation studies. The quality is measured for a range of parameter settings, revealing the importance of parameter fine-tuning and often un...