Multi-Timescale Battery-Charging Optimization for Electric Heavy-Duty Truck Battery-Swapping Stations, Considering Source–Load–Storage Uncertainty by Peijun Shi, Guojian Ni, Rifeng Jin, Haibo Wang, Jinsong Wang, Zhongwei Sun, Guizhi Qiu

“…First, a model incorporating uncertainties in renewable energy output, time-of-use pricing, and grid load fluctuations is developed for the battery-swapping station. Second, based on day-ahead and intra-day timescales, the optimization problem for battery-charging strategies at battery-swapping stations is decomposed into day-ahead and intra-day optimization problems. …”
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Measurement-Based Prediction of mmWave Channel Parameters Using Deep Learning and Point Cloud by Hang Mi, Bo Ai, Ruisi He, Anuraag Bodi, Raied Caromi, Jian Wang, Jelena Senic, Camillo Gentile, Yang Miao

“…Furthermore, a fusion method between the point clouds and images is proposed based on geometric relationship between the LiDAR and camera, to compress the size of the data collected. Second, based on a classic point cloud classification model (PointNet), we propose a novel regression PointNet model applied to channel parameter prediction. …”
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A method for evaluating the accessibility of underground auxiliary transportation vehicles in coal mines based on multi feature fusion by Fan JIANG, Yifan LIU, Zhencai ZHU, Chaofan ZHANG, Gongbo ZHOU, Yuxing PENG

“…Progressive probability Hough transform and Catmull Rom spline curve with improved feature point selection are used to fit the straight track and curved track separately, forming a railway track detection method based on a switchable model; Secondly, based on the color attributes of coal mine underground tunnel wall pipelines, a pipeline feature detection strategy is constructed through HSV color space transformation, edge detection, and least squares fitting algorithms; Once again, a weighted fusion method based on pipeline and rail feature points is proposed to extract the centerline trajectory of auxiliary transportation vehicles, and to construct rules for generating safe passage areas for auxiliary transportation vehicles; Then, for the over-segmentation problem in the traditional watershed algorithm, two-dimensional edge and area feature extraction of static obstacles is carried out by using improved watershed segmentation based on markers and GraphCut algorithm, and a small-sample classification support vector mechanism is selected to build a pedestrian detection model based on the fusion of HOG (Histograms of Oriented Gradients)features and LBP(Local Binary Pattern) features for underground coal mine, so as to realize the comprehensive detection of dynamic and static obstacles in front of auxiliary transportation vehicles; Finally, the positional relationship between obstacles and safe passage area is judged by Euclidean distance to determine the obstacle invasion, and the results of auxiliary transportation vehicle passability assessment are obtained. …”
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Penerapan Mekanisme Continuous Deployment dalam Pengembangan dan Pembaruan Perangkat Lunak Sistem Benam Berbasis Internet of Things by Yohanna Fransiska Aladina, Adhitya Bhawiyuga, Reza Andria Siregar, Primantara Hari Trisnawan

“…The average time it takes to perform an update is only 63.5 seconds. Based on the results of these tests, this solution can answer the problem of updating IoT device software which is still done manually. …”
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