Methodology for Assessing the Level of Greenhouse Gas Emissions in Agricultural Crops Production by N. I. Dzhabborov, A. P. Mishanov, A. M. Zakharov, A. M. Dobrinov

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Research on Automatic Driving Control Strategy for Freight Locomotives in Key Scenarios by SHEN Ziyang, BAI Jinlei, ZHONG Puhua, ZHOU Huangbiao, YI Jie

“…Due to factors such as complex application scenarios, strong non-linearity and discreteness of control objects, some problems and challenges have arisen during the operation assessment, including impulsive and surging phenomena during train interval operation, non-compliance with station benchmark parking accuracy requirements, failure to start on steep slopes, and difficulty in evaluating air braking performance. …”
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Experimental and CFD study of a new design of a direct-flow cyclone by E. V. Flisyuk, V. S. Toptalov, O. M. Flisyuk, I. G. Likhachev, Yu. M. Kotsur

“…In the pharmaceutical industry solving such problems requires the use of compact, highly efficient devices, for the development and study of which CFD-modelling methods have recently been increasingly used. …”
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Research on a virtual-real fusion experimental system for the cutting part of a boom-type roadheader. by Jianzhuo Zhang, Ce Chen, Xiaoyu Ding, Tao Wang, Chuanxu Wan, Wenliang Li

“…Aiming at the problems of high safety risks, economic costs, and inefficiency in experimental research on boom-type roadheaders, this study proposes a virtual-real fusion experimental system for the cutting module. …”
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‌Rockburst intensity grading prediction based on the LOF-ENN-KNN model‌ by Haoran Ge, Jiyong Zhang, Congbo Ma, Kai Hui, Yicong Li, Ziniu Wu

“…Abstract Rockburst is a typical dynamic disaster in deep underground engineering, and its accurate prediction is of great significance to ensure the safety of engineering. Aiming at the key problems in rockburst prediction, such as insufficient analysis of nonlinear correlation characteristics, significant discreteness of small sample data and limited generalization ability of traditional models, this study innovatively constructs a LOF-ENN-KNN coupling prediction model. …”
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