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In this study, a pulse sequence analysis (PSA) method is presented, which does not measure the voltage signal for the defect-type recognition of power cable joints based on partial discharges (PDs) using convolutional neural networks (CNNs). The PSA showed effective results in comparison to a conventional phase-resolved PD (PRPD) pattern, which is a combination of a PD and voltage signals. The optimal drawing formats of the PSA patterns, including the size, type, color, and marker size of the images, which influence the recognition accuracy, were evaluated. In total, 12 sets of PD data, consisting of three types of cable joint defects, were trained and tested using CNN-based models. The results show that the performance of the PSA-based CNN model is as good as that of a PRPD even when the voltage signal is lost, whereas PRPD mostly fails under such cases. The total recognition accuracy obtained from a PSA-based CNN was 95.3%, whereas that of the PRPD-based CNN was 90.6%. In addition, an advanced and useful application of a PSA pattern is discussed herein. [ABSTRACT FROM AUTHOR]

This paper investigates smart home energy management in consideration of tradeoffs between residential privacy and energy costs. A multiobjective approach that minimizes energy costs and maximizes privacy protection is proposed. The approach leads to a multiobjective optimization problem in which the two objectives are addressed in separate dimensions. A hybrid algorithm that employs a stochastic search for power scheduling of home appliances and uses deterministic battery control is developed accordingly. The proposed approach can avoid some drawbacks faced by conventional weighted-sum methods for multiobjective optimization: the combination of objectives in different units, heuristic assignment of weighting coefficients, and possible misrepresentation of user preference. In contrast with existing studies on residential user privacy that assume limited controllability of appliances to facilitate algorithm development, this approach addresses the use of flexible appliances in smart homes. Simulations reveal that the proposed approach can maintain a reasonable energy cost while robustly preserving user privacy at a sensible level; its convergence rate is comparable to existing multiobjective evolutionary algorithms while the proposed approach yields a better level of convergence; the proposed approach is scalable to a group of smart houses, achieving a superior peak-to-average ratio that is beneficial to the stability of the underlying power grid. [ABSTRACT FROM AUTHOR]

Residue stuffed quadratic congruence (RSQC) codes are proposed for radio-over-fiber (RoF) scheme based on spectral-amplitude-coding (SAC) optical code-division multiple-access (OCDMA) networks. These new codes generated from residue method can enlarge the code space, and the decoder of this new code is cost-effective and suitable for realization. The error rate performance of the proposed RSQC code (two-code keying) and the original SQC code (on-off keying) are analyzed. [ABSTRACT FROM PUBLISHER]