Amira Mohamed, Shady S. Refaat and Haitham Abu-Rub
Smart grid (SG) is the solution to solve existing problems of energy security from generation to utilization. Examples of such problems are disruptions in the electric grid and disturbances in the transmission. SG is a premium source of Big Data. The data should be processed to reveal hidden patterns and secret correlations to extrapolate the needed values. Such useful information obtained by the so-called data analytics is an essential element for energy management and control decision towards improving energy security, efficiency, and decreasing costs of energy use. For that reason, different techniques have been developed to process Big Data. This paper presents an overview of these techniques and discusses their advantages and challenges. The contribution of this paper is building a recommender system using different techniques to overcome the most obstacles encountering the Big Data processes in SG. The proposed system achieves the goals of the future SG by (i) analyzing data and executing values as accurately as possible, (ii) helping in decision-making to improve the efficiency of the grid, (iii) reducing cost and time, (iv) managing operating parameters, (v) allowing predicting and preventing equipment failures, and (vi) increasing customer satisfaction. Big Data process enables benefits that were never achieved for the SG application.
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For precise indoor localization accurate synchronization is necessary. In this paper we propose a new synchronization method for direct sequence spread spectrum modulation based systems, which enables a more accurate correlation peak detection. We provide comprehensive statistical analysis and numerical results for the decision error probability assuming both coherent and non-coherent receiving via an AWGN channel. The essence of the proposed method is the two overlapping correlators, which allows taking into account the statistically not independent noise components to reduce the error probability of the correlation peak detection.
It is well known that straight teethed shaper cutters present a theoretical profile error. The side edges are situated on a common conical rack face with the result that they and their projection in the generating plane can’t be involute curves. The optimization of the cutter requires such a correlation of the edge defining parameters that the potential theoretical profile error is kept to the minimum possible. Thus the relevance of the edge equations is of great importance. This paper deals with the analysis of the edge equations, presenting two different forms of it. The comparison between the two different forms is realized by applying the numerical evaluation, by substitution of the edge point coordinates in the implicit equations of the originating surfaces. The obtained results present a difference of magnitude 10-E3. Finally, it can be concluded that the two forms of the edge equations cannot be used randomly but only in correlation with the goal proposed by the running application.
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