When operating an equipment or a power system at the high voltage, problems associated with partial discharge (PD) can be tracked down to electromagnetic emission, acoustic emission or chemical reactions such as the formation of ozone and nitrous oxide gases. The high voltage equipment and high voltage installation owners have come to terms with the need for conditions monitoring the process of PD in the equipments such as power transformers, gas insulated substations (GIS), and cable installations. This paper reviews the available PD detection methods (involving high voltage equipment) such as electrical detection, chemical detection, acoustic detection, and optical detection. Advantages and disadvantages of each method have been explored and compared. The review suggests that optical detection techniques provide many advantages in the consideration of accuracy and suitability for the applications when compared to other techniques.

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This work was carried out in collaboration between all authors. Author MMY designed the study, wrote the protocol, and wrote the first draft of the manuscript. Author MAA managed the literature searches, analyses of the study performed the spectroscopy analysis and managed the experimental process.All authors read and approved the final manuscript.

Abstract:The purpose of this paper is to compare the performance of two spectrometers that are manufactured from the same company. In this work, heavy metals like lead Pb and copper Cu in the KBr matrix were analyzed using the laser induced breakdown spectroscopic technique. A Q-switched Nd:YAG laser with 90 mJ per pulse operating at the fundamental wavelength of 1064 nm and pulse duration of 10 ns was used to generate plasma at the focal region. The important experimental parameters such as the laser energy, integration time, distance between the lens and sample, distance and angle of the optical fiber from the target were optimized. Two spectrometers manufactured by Ocean Optics namely as Maya2000Pro and USB 4000 were employed for anlyzing the spectral lines. The experimental setup and conditions were remained the same for both experiments. The production of spectral lines from each of the interested elements was analyzed and compared with the NIST (National Institute of Standards and Technology) database. The sensitivity, repeatability and limit of detection for each of the systems are discussed in detail.

Human activity recognition (HAR) is recently used in numerous applications including smart homes to monitor human behavior, automate homes according to human activities, entertainment, falling detection, violence detection, and people care. Vision-based recognition is the most powerful method widely used in HAR systems implementation due to its characteristics in recognizing complex human activities. This paper addresses the design of a 3D convolutional neural network (3D-CNN) model that can be used in smart homes to identify several numbers of activities. The model is trained using KTH dataset that contains activities like (walking, running, jogging, handwaving handclapping, boxing). Despite the challenges of this method due to the effectiveness of the lamination, background variation, and human body variety, the proposed model reached an accuracy of 93.33%. The model was implemented, trained and tested using moderate computation machine and the results show that the proposal was successfully capable to recognize human activities with reasonable computations.

<p><span>The load shifting technique is widely implemented in electrical power generation due to its considerable impact on system reliability. The evaluation of load shifting benefits towards the adequacy of generation systems requires an accurate assessment. If the generation unit’s capacity is insufficient to meet the system load, then assistance is required from alternative sources. Load shifting, as a primary demand-side management technique, is used efficiently in electrical power networks given that the energy clipped/curtailed owing to load curtailment and peak clipping can be recovered during the off-peak period. The reliability of a generic framework for the prospective integration of a load shifting technique, with preventative and corrective actions as alternatives to peaking units, is investigated in this study. The optimal rate of load shifting in terms of expected energy not supplied is also investigated. Results show that preventive load shifting (PLS) can act as peaking units when the total generated capacity is within specific limits. Meanwhile, corrective load shifting can act as a better alternative than PLS and peaking units. To calculate expected energy not supplied, sequential Monte Carlo simulation is utilized. This study is conducted using the IEEE reliability test system.</span></p>

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