The progression towards smart grids, integrating renewable energy resources, has increased the integration of distributed generators (DGs) into power distribution networks. However, several economic and technical challenges can result from the unsuitable incorporation of DGs in existing distribution networks. Therefore, optimal placement and sizing of DGs are of paramount importance to improve ...

In a supply chain, cross-docking is one of the most innovative systems for ameliorating the operational performance at distribution centers. Cross-docking is a logistics strategy in which freight is unloaded from inbound trucks and (almost) directly loaded into outbound trucks, with little or no storage in between, thus no inventory remains at the distribution center. In this study, we consider...

large water distribution systems can be highly vulnerable to penetration of contaminant factors caused by different means including deliberate contamination injections. as contaminants quickly spread into a water distribution network, rapid characterization of the pollution source has a high measure of importance for early warning assessment and disaster management. in this paper, a methodology...

Linear and nonlinear quantitative structure-activity relationship (QSAR) models and docking score functions were developed for dihydrofolate reductase (DHFR) inhibition by cycloguanil derivatives using small molecule descriptors derived from MOE and in silico docking energies. The best QSAR models and docking score functions were identified when using artificial neural networks optimized by evo...

Cognate docking has been used as a test for pose prediction quality in docking engines for decades. In this paper, we report a statistically rigorous analysis of cognate docking performance using tools in the OpenEye docking suite. We address a number of critically important aspects of the cognate docking problem that are often handled poorly: data set quality, methods of comparison of the pred...

this paper presents a multi-objective formulation for optimal siting and sizing of distributed generation (dg) resources in distribution systems in order to minimize the cost of power losses and energy not supplied. the implemented technique is based on a genetic algorithm (ga) and weight method that employed to obtain the best compromise between these costs. simulation results on 33-bus distri...

key distribution is an important problem in wireless sensor networks where sensor nodesare randomly scattered in adversarial environments.due to the random deployment of sensors, a list of keys must be pre-distributed to each sensor node before deployment. to establish a secure communication, two nodes must share common key from their key-rings. otherwise, they can find a key- path in which ens...

A novel approach that combines neural networks, computer docking and quantum mechanical method is developed to design potent aldose reductase inhibitors (ARIs). Neural networks is employed to determine the quantitative structure-activity relationship (QSAR) among the known ARIs. The physical descriptors of the neural networks, such as electronegativity and molar volume, are evaluated with first...

Water distribution networks are one of the important and costly infrastructures of cities and many meta-heuristic algorithms in standard or hybrid forms were used for optimizing water distribution networks. These algorithms require a large amount of computational cost. Therefore, the converging speed of algorithms toward the optimization goal is as important as the goal itself. In this paper, a...