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This paper proposes an innovative algorithm for predicting short-term electrical maximum demand by using historical demand data. The ability to recognize in peak demand pattern for commercial or industrial customers would propose numerous direct and indirect benefits to the customers and utility providers in terms of demand reduction, cost control, and system stability. Prior works in electrical maximum demand forecasting have been mainly focused on seasonal effects, which is not a feasible approach for industrial manufacturing facilities in short-term load forecasting. The proposed algorithm, denoted as the Adaptive Rate of Change (ARC), determines the logarithmic rate-of-change in load profile prior to a peak by postulating the demand curve as a stochastic, mean-reverting process. The rationale behind this analysis, is that the energy efficient program requires not only demand estimation but also to warn the user of imminent maximum peak occurrence. This paper analyzes demand trend data and incorporates stochastic model and mean reverting half-life to develop an electrical maximum demand forecasting algorithm, which is statistically evaluated by cross-table and F-score for three different manufacturing facilities. The aggregate results show an overall accuracy of 0.91 and a F-score of 0.43, which indicates that the algorithm is effective predicting peak demand in predicting peak demand.

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A novel data hiding method for covert communication via the QR code image based on adjustments of the shapes of the QR code modules using image processing techniques is proposed. A module block consisting of two module pairs is taken as the unit for message-bit embedding by adjusting the vertical and horizontal internal boundaries in the module pairs. Eliminations of the resulting boundary line zigzaggedness and irregular overlapping and holing phenomena in the module block are also carried out. The resulting stego-image with secret bits embedded can be scanned by a barcode reader to obtain the facial data recorded in the QR code while a program implementing the message extraction process of the proposed method can process the stego-image to extract the hidden secret message. Good experimental results, tests of stego-image readability by QR code scanners and resistance to noise attacks, and a comparison with other methods from the viewpoint of data embedding rate show the feasibility and superiority of the proposed method for real covert communication applications. INDEX TERMS Covert communication, data hiding, QR code, module shape adjustment, image processing.