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As a component to effectively improve the overall lateral stiffness of the structure, the shear wall accurately simulates the mechanical behavior after entering the nonlinear state and is very important for evaluating the seismic safety of the structure. Taking the "Blind Test Competition of the Ninth National Earthquake Engineering Conference" as an example, based on OpenSees, four elements were used to simulate the behavior of shear wall, and the factors affecting the simulation accuracy of the four elements were summarized. The results show that the force-based beam-column element is sensitive to the number of integration points. For the displacement-based beam- column element, a reasonable number of element should be selected to simulate accurately. The flexure-shear interaction displacement-based beam-column element and Thushell element are used to simulate the performance of the shear wall, and the calculation time is relatively long and the parameters are involved.

The paper provides a methodology for substation loading curve optimization for power losses reduction and power network development deferral. The objective function of the problem provides costs minimization, however the optimization process is based on technical criteria, taking into account power system operation modes, electric energy consumers behavior and power equipment loading capacity. The mathematical calculations are carried out using genetic algorithms, because they prove to be effective for finite-solution optimization tasks. Proposed methodology was verified using real practical problem formulation.

A feature extraction method for Epilepsy diagnosis is proposed in this paper, which can be incorporated in automatic/semi-automatic epilepsy diagnosis systems to improve diagnosis efficiency from multi-channel Electroencephalogram signals. This method calculates the Robust Generalized Synchrony between pairs of Electroencephalogram channels in the first step. Then six character parameters are extracted from the Robust Generalized Synchrony values for the whole brain and the sub-brain regions. A set of Electroencephalogram data including 20 normal objects and 20 epileptic patients in interictal states were used to test the proposed method The results demonstrate that these features are effective to differentiate between epilepsy patients and the normal objects with the p-values smaller than 0.01.