Research on Actuator Control System Based on Improved MPC by Qingjian Zhao, Qinghai Zhang, Shuang Zhao, Xiaoqian Zhang, Shilei Lu, Yang Guo, Liqiang Song, Zhengxu Zhao

“…Experimental and test results show that, under electromagnetic interference and mechanical vibration conditions, the system’s stability and robustness are significantly enhanced, with error fluctuations of less than 0.03 mm, dynamic response time of 4.82 s, overshoot of 1.5%, steady-state error of 0.14 mm, and energy consumption reduced by 15%, all better than MPC, fuzzy control, and PID control methods under similar conditions. This research provides a comprehensive solution for hardware design and algorithm optimization in actuator control for industrial automation and precision manufacturing.…”
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Research on Automatic Recovery Strategy for Metro Train Delay by QING Guangming, LI Jianghong, ZHANG Zhaoyang, ZHANG Yu

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Research and Application of Embedded Control Software Security Design by DAI Jisheng, WANG Chengjie, LI Yi, CHEN Junbo, LI Cheng

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Research on the Converter for Large Scale S-UPQC and Its Control by ZHAO Li, WEI Yingdong, JIANG Qirong

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Research on Dynamic Performance of Autonomous-rail Rapid Tram by ZHONG Hanwen, LI Xiaoguang, XIAO Lei, YANG Yong, ZHANG Chenlin, HUANG Ruipeng, YUAN Xiwen

“…Autonomous-rail rapid tram which has multiple articulations and rubber tires is a kind of new vehicle automatically following the digital virtual central line. In order to research the dynamic performance of the tram, a mathematical model based simulation research was carried out to support the algorithm design and to verify the strategies adopted by the central virtual track line following controller and the automatic tracking steering controller. …”
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Research on spectrum sensing technologies based on goodness of fit by Guangyue LU, Cai XU, Yinghui YE, Yin MI

“…Cognitive radio technology has achieved the dynamic allocation of spectrum resources,and improves the utilization rate of spectrum resources.Accurate and efficient spectrum sensing is the key step in cognitive radio.Developing a fast and high-performance spectrum sensing method has become an urgent problem to be solved.In recent years,goodness of fit（GOF）theory has been applied widely in the field of spectrum sensing and the effective spectrum sensing technology under small sample point has been implemented.Therefore,the research on spectrum sensing technology based on GOF has very significant value.The development process of GOF in areas of cognitive radio spectrum sensing was summarized,its basic principle common fitting criterion and fitting object were introduced.The simulation comparison of the algorithm was carried under the Gaussian channel and its prospects of further research was forecasted finally.…”
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Research on deep differential fault analysis against MIBS by ZHAO Xin-jie1, WANG Tao 1, WANG Su-zhen2, WU Yang1

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Research on the invulnerability of regional network based on topology analysis by Changqing AN, Yujia LIU, Hui WANG, Zhiyan ZHENG, Tao YU, Jilong WANG

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Research on the invulnerability of regional network based on topology analysis by Changqing AN, Yujia LIU, Hui WANG, Zhiyan ZHENG, Tao YU, Jilong WANG

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Research on deep differential fault analysis against MIBS by ZHAO Xin-jie1, WANG Tao 1, WANG Su-zhen2, WU Yang1

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Research on Health Evaluation Method of Tank Diesel Engine by X.-M. Zhang, D. X. Zhou, M. Chen

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Research on test strategy for randomness based on deep learning by Dongyu CHEN, Hua CHEN, Limin FAN, Yifang FU, Jian WANG

“…In order to achieve better test performance, researches on the randomness test strategies based on deep learning were conducted, including the batch average strategy proposed by EUROCRYPT 2021 and the selection strategy for data unit size.By introducing the randomness statistical test model based on deep learning methods, the statistical distribution and test power expression of two test strategies were theoretically derived, and it was pointed out that: (i) the batch average strategy could amplify the prediction accuracy of the model, but it was prone to an increase in the probability of the second type of error in statistics, instead reducing the statistical test power; (ii) the smaller data units of the deep model generally obtained the more powerful statistical tests.Based on the above understanding, a new bit-level deep learning model was proposed for randomness statistical tests, which gained the advantage of prediction with 80 times fewer parameters and 50% samples, compared with the previous work on linear congruent generator (LCG) algorithm, and achieved significant prediction advantages with 10～20 times fewer parameters by extending the model to apply to 5～7 rounds of Speck, compared with the model proposed by Gohr.…”
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Research of methods for evaluating the effectiveness of public relations activities by A. A. Sazonov

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Research on the application of digital twin technology for intelligent substations by GAO Yang, ZHAO Kuangyi, FU Yuhong, ZHANG Jinwei, LIU Hongyu, GUO Jia

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Research on test strategy for randomness based on deep learning by Dongyu CHEN, Hua CHEN, Limin FAN, Yifang FU, Jian WANG

“…In order to achieve better test performance, researches on the randomness test strategies based on deep learning were conducted, including the batch average strategy proposed by EUROCRYPT 2021 and the selection strategy for data unit size.By introducing the randomness statistical test model based on deep learning methods, the statistical distribution and test power expression of two test strategies were theoretically derived, and it was pointed out that: (i) the batch average strategy could amplify the prediction accuracy of the model, but it was prone to an increase in the probability of the second type of error in statistics, instead reducing the statistical test power; (ii) the smaller data units of the deep model generally obtained the more powerful statistical tests.Based on the above understanding, a new bit-level deep learning model was proposed for randomness statistical tests, which gained the advantage of prediction with 80 times fewer parameters and 50% samples, compared with the previous work on linear congruent generator (LCG) algorithm, and achieved significant prediction advantages with 10～20 times fewer parameters by extending the model to apply to 5～7 rounds of Speck, compared with the model proposed by Gohr.…”
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Approaches to automation of the preanalytical phase of large-scale research in the biobank of the National Medical Research Center for Therapy and Preventive Medicine of the Minist... by M. S. Pokrovskaya, A. L. Borisova, V. A. Kondratskaya, I. A. Efimova, A. I. Ershova, O. M. Drapkina

“…To create and validate an algorithm for automatic aliquoting of serum and plasma samples for biobanking as part of a large-scale study.Material and methods. …”
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A robotic system for researching social integration in honeybees. by Karlo Griparić, Tomislav Haus, Damjan Miklić, Marsela Polić, Stjepan Bogdan

“…In this paper, we present a novel robotic system developed for researching collective social mechanisms in a biohybrid society of robots and honeybees. …”
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Research on image generation technology based on deep learning by Li Jinchen

“…Image generation has emerged as a prominent research area in contemporary academia, with a high possibility of exploration and practice.…”
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Are Dating App Algorithms Making Men Lonely and Does This Present a Public Health Concern? by Eric Balki

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The Crossover strategy integrated Secretary Bird Optimization Algorithm and its application in engineering design problems by Xiongfa Mai, Yan Zhong, Ling Li

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