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arXiv 2024年

作者： Yu Xuan Tan, Ashton Yang, Yingkai Zhang, Xiaofei Li, Bowen Gao, Xiaorong Zheng, Sifa Wang, Jianqiang Gu, Xinyu Li, Jun Zhao, Yang Zhang, Yuxin Stathaki, Tania Wang, Hong School of Vehicle and Mobility Tsinghua University Beijing100084 China Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom School of Medicine Tsinghua University Beijing100084 China School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China State Key Laboratory of Automotive Simulation and Control Jilin University Changchun130025 China

Enhancing the safety of autonomous vehicles is crucial, especially given recent accidents involving automated systems. As passengers in these vehicles, humans’ sensory perception and decision-making can be integrated with autonomous systems to improve safety. This study explores neural mechanisms in passenger-vehicle interactions, leading to the development of a Passenger Cognitive Model (PCM) and the Passenger EEG Decoding Strategy (PEDS). Central to PEDS is a novel Convolutional Recurrent Neural Network (CRNN) that captures spatial and temporal EEG data patterns. The CRNN, combined with stacking algorithms, achieves an accuracy of 85.0%±3.18%. Our findings highlight the predictive power of pre-event EEG data, enhancing the detection of hazardous scenarios and offering a network-driven framework for safer autonomous vehicles. © 2024, CC BY.

关键词： Convolutional neural networks

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Application of genetic algorithm for broad learning system optimization 7

Application of genetic algorithm for broad learning system o...

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7th International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2020

作者： Li, Jiawei Zuo, Yi Li, Yiliang Wang, Yang Li, Tieshan Philip Chen, C.L. Navigation College Dalian Maritime University Dalian Liaoning China School of Automation Engineering University of Electronic Science and Technology of China Chengdu Sichuan China Fauctly of Science and Technology South China University of Technology Macau China

ISBN: (纸本)9781728162461

In order to solve the problem of waste of resources and low monitoring efficiency caused by Container Freight Station (CFS) safety helmet detection mainly relying on manual operations. The Broad Learning System (BLS) optimized by Genetic Algorithm (GA) is selected as the image recognition classifier for helmet detection, which accurately and quickly marks the images of CFS workers who do not wear safety helmet in the video and issues an early warning. GA is a method of searching for the optimal solution by simulating the natural evolution process. While comparing it with initial BLS, BLS optimized by GA (GA-BLS) can automatically constructs network structure and tunes hyperparameters. Furthermore, using proposed method in safety helmet data set reaches a lower error, reduces operation time than initial BLS and other image detection method, such as support vector machine (SVM). © 2020 IEEE.

关键词： Genetic algorithms

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Synergistic dispersion strengthening of Fe-Cr alloys by oxides and carbides: Microstructure and mechanical property enhancement

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Journal of Alloys and Compounds 2025年 1035卷

作者： Tuowen Chen Jingyi Tuo Yihao Wu Hui Wang Yongduo Sun Xuefei Huang College of Materials Science and Engineering Sichuan University Chengdu 610065 China National Key Laboratory of Nuclear Reactor Technology Nuclear Power Institute of China Chengdu Sichuan 610213 China

Fe-Cr alloys were fabricated using powder metallurgy (PM) with varying additions of ZrC (0–1.5 wt%) to investigate the influence on microstructure and mechanical properties. The resulting alloys exhibited a bimodal grain structure with dispersed nano-oxides (TaO, ZrO 2 ) and carbides (ZrC). The alloy containing 1.5 wt% ZrC demonstrated the most favourable combination of properties, achieving a yield strength of 1373 MPa and an elongation of 11.9 % at room temperature, which is attributed to synergistic dispersion strengthening. At 700°C, this alloy retained a yield strength of 470 MPa, surpassing that of many oxide dispersion-strengthened alloys. Incorporating ZrC refined the microstructure, promoted phase transformations, and inhibited the formation of coarse oxides, enhancing strength and ductility.

关键词： Fe-Cr alloy Mechanical properties Microstructure Nanoparticles Oxides and carbides synergistically dispersion strengthened

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Direct Ink Writing of Bi2te3-Based Thermoelectric Materials Induced by Rheological Design

SSRN

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SSRN 2022年

作者： Wang, Zhengshang Cui, Wen Yuan, Hao Kang, Xiaoli Zheng, Zhou Hu, Qiujun Qiu, Wenbin Tang, Jun Cui, Xudong Sichuan Research Center of New Materials 596 Yinhe Road Shuangliu Chengdu610200 China Institute of Chemical Materials China Academy of Engineering Physics Mianyang621900 China Key Laboratory of Radiation Physics and Technology of Ministry of Education Institute of Nuclear Science and Technology Sichuan University Chengdu610064 China College of Physics Sichuan University Chengdu610065 China

Waste heat recovery systems built with thermoelectric (TE) materials offer promising means to generate electricity from waste heat directly, if TE materials or devices with controllable shapes are created, through direct ink writing (DIW). However, the nature of TE inks used for DIW must be modified with appropriate rheology to maintain stability and facilitate extrusion, as well as proper mechanical properties to resist deformation. Here, we report Bi2Te3-based inks modified with additives that allow direct printing of tunable architectures. The polyelectrolyte additives-induced adsorbed layers on the surface of TE particles are shown to significantly improve the stability and viscoelasticity of inks. Besides, the improved inks modified with methylcellulose additives exhibit an apparent enhancement of strength properties, thereby enabling the predesigned shapes to hold the successive layers printed above. Using charge control and framework reinforcement, the Bi2Te3-based inks print a series of architectures with porous structures, which largely reduce thermal conductivities. As a result, our 3D-printed materials display high figures of merit ZT of 0.65 and 0.53 for p- and n-type. This work explores how additives can influence both rheological properties, printability, and microstructures, which pave the way to construct complex architectures and improve TE performance for structural and functional applications. © 2022, The Authors. All rights reserved.

关键词： Additives

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Prediction of nexus among ESG disclosure and firm Performance: Applicability, explainability and implications

Innovation and Green Development

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Innovation and Green Development 2025年第4期4卷

作者： Joel Victor Dossa Chiagoziem C. Ukwuoma Dara Thomas James Mhoja Dossa Aamir Ali Gopang Business School Sichuan University Sichuan P.R. 610064 China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan P.R. 610059 China Sichuan Engineering Technology Research Center for Industrial Internet Intelligent Monitoring and Application Chengdu University of Technology Sichuan P.R. 610059 China Water Institute Tanzania

This study investigates the nexus between ESG disclosure and firm performance using advanced machine learning models (MLs) to capture complex, non-linear interactions. Analyzing data from Chinese A-share firms (2012–2022), it employs Explainable AI (XAI) tools such as SHAP, heat maps, and Williams plots to enhance model transparency and interpretability. Among several models, the Extra Trees model demonstrated the best predictive performance, revealing that ESG disclosure positively correlates with firm performance, with environmental disclosure exerting the strongest influence. Policymakers are urged to promote standardized, transparent ESG disclosures, particularly focusing on environmental practices while addressing greenwashing to enhance credibility. Investors can prioritize firms with strong environmental practices and use predictive models to refine decision-making. Corporate managers are encouraged to embed sustainability into long-term strategies and utilize ML techniques for improved governance. The study contributes by showcasing the utility of MLs in exploring ESG-performance relationships, offering actionable insights for stakeholders, and providing a foundation for future research. Researchers are encouraged to investigate non-linear ESG impacts across diverse contexts, using broader samples and incorporating market-based measures and ESG rating agencies to improve generalizability. This approach advances understanding of ESG's role in driving firm performance while addressing methodological gaps.

关键词： Machine learning ESG disclosure Extra tree Williams plots

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Data Mining and Business Intelligence in SME Customer Relationship Value Analysis 3

Data Mining and Business Intelligence in SME Customer Relati...

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3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021

作者： Jia, Siyuan Pan, Minming Sun, Wenlong Joyce, Harubwira Nyampinga Wang, Yan Zheng, Wenfeng Shanghai Urban Construction Vocational College Shanghai201415 China The Indiana University Kelley School of Business BloomingtonIN47405 United States Accounting School Shanghai University of International Business and Economics Shanghai201620 China School of Automation Engineering University of Electronic Science and Technology Chengdu611731 China

ISBN: (纸本)9781665417327

As a tool and system, business intelligence plays a vital role in the strategic planning process of a business company. Business intelligence provides companies with functions such as collecting, storing, accessing, and analyzing company data. In the traditional business model, most companies use human resources to track these large amounts of data and information. And business intelligence provides an automated data processing method that significantly improves efficiency. During a customer relationship management service system, a large amount of data will be generated and stored. With this natural data advantage, data analysis has more possibilities in customer relationship management service systems. Based on the business intelligence system, this paper analyzes the data of the customer system. It puts forward the K-means clustering method to analyze the customer quality, the fuzzy set clustering algorithm to examine whether the customer is active. The rough set algorithm to judge to improve the user activity decision analysis. The proposed intelligent business system brings new technical solutions to the maintenance of current corporate customer relationships. © 2021 IEEE.

关键词： Sales

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Research progress of glass scintillators with high density and high light yield 42

Research progress of glass scintillators with high density a...

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42nd International Conference on High Energy Physics, ICHEP 2024

作者： Sui, Zexuan Ren, Jing Qian, Sen Du, Dejing Fan, Ruirui Fan, Ruirui Han, Jifeng Hu, Peng Hua, Zhehao Li, Weichang Liu, Shan Liu, Yong Ma, Lishuang Qin, Laishun Liu, Yong Sun, Xinyuan Tang, Gao Wang, Zhile Yang, Dong Yin, Shenghua Zhang, Minghui Zhu, Yao Zhu, Yao Cai, Hua Chen, Danping Key Laboratory of In-Fiber Integrated Optics of Ministry of Education College of Physics and Optoelectronic Engineering Harbin Engineering University 145 Nantong Street Nangang District Harbin150001 China Key Laboratory of Photonic Materials and Devices Physics for Oceanic Applications Ministry of Industry and Information Technology of China College of Physics and Optoelectronic Engineering 145 Nantong Street Nangang District Harbin150001 China Institute of High Energy Physics Chinese Academy of Sciences Yuquan Road 19A Beijing100049 China State Key Laboratory of Particle Detection and Electronics Yuquan Road 19A Beijing100049 China China Building Materials Academy Guanzhuang East No.1 Beijing100024 China Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Qinghe Road 390 Shanghai201800 China Neutron source Road 1 Dongguan523803 China Institute of Nuclear Science and Technology Sichuan University No. 24 Section 1 South of Ring Road 1 Chengdu610065 China Nuclear Instrument Co. Ltd. Hongda South Road 3 Beijing100176 China Beijing Glass Research Institute East Tai Street 1 Beijing101111 China College of Materials and Chemistry China Jiliang University Xueyuan Road 258 Hangzhou310018 China Department of Physics Jinggangshan University Xueyuan Road 28 Ji'an343009 China School of Astronautics Harbin Institute of Technology West Tai Chi Street 92 Harbin150001 China Shanghai Institute of Ceramics Chinese Academy of Sciences Heshuo Road 585 Shanghai201899 China

Glass scintillators (GS), with their tunable composition, large-scale fabrication capabilities, and cost-effectiveness, have emerged as a novel choice for solid scintillation materials. The density of glasses can close to those of scintillation crystals (∼6 g/cm3) at a lower cost, making it the preferred light-emitting device for scintillation detectors. Since 2021, the High-Density Glass Scintillator Collaboration Group (GS group) has been working on the development of large-sized, high-density (∼6 g/cm3), high light output (>1000 ph/MeV), fast decay ( © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

关键词： Scintillation counters

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Nonlinear Model Predictive Control of Shipboard Boom Cranes with Ship Roll Motion

Nonlinear Model Predictive Control of Shipboard Boom Cranes ...

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Chinese automation Congress (CAC)

作者： Yuchi Cao Xiangjie Zhao Tieshan Li Navigation College Dalian Maritime University Dalian China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781665426480

In this paper, a nonlinear model predictive controller for shipboard boom cranes is proposed, while considering the ship roll motion caused by sea waves. After coordination transformation, the ship roll motion becomes part of new state variable, which can simplify the controller design significantly by making the time-varying reference value to be constants. All physical state constraints and input saturation are well considered and handled simultaneously by resorting to the virtues of nonlinear model predictive control (NMPC). CasADi and multiple shooting technique are employed to improve the computation efficiency of NMPC, thus the real-time implementation for shipboard boom cranes can be carried out. Moreover, simulations are elaborately designed to verity the effectiveness of the proposed controllers, satisfied performances are obtained.

关键词： Cranes automation Computational modeling Simulation Predictive models Real-time systems Computational efficiency

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Portable Optical Two-way Time Transfer in Outdoor Atmospheric Link with CPLD-based Time Codec

Portable Optical Two-way Time Transfer in Outdoor Atmospheri...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Junwei Ren Bisong Pan Ze Li Ke Liu Jianye Zhao Dong Hou School of Automation Engineering University of Electronic Science and Technology of China Chengdu China College of Electronics Engineering and Computer Science Peking University Beijing China

We demonstrated a portable optical two-way time transfer scheme over a 120-m outdoor atmospheric link. The measured root-mean-square (RMS) fluctuation of the time deference between the two sites is about 81 ps within ... 详细信息

ISBN: (纸本)9781943580910

关键词： Fluctuations Atmospheric measurements Optical propagation Sea measurements Measurement by laser beam Optical variables measurement Optical fiber communication

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Direct measurement of the 19F(p,αγ)16O reaction in JUNA 16

Direct measurement of the 19F(p,αγ)16O reaction in JUNA

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16th Symposium on Nuclei in the Cosmos, NIC-XVI 2021

作者： Zhang, L.Y. Su, J. He, J.J. Wiescher, M. deBoer, R.J. Kahl, D. Chen, Y.J. Li, X.Y. Wang, J.G. Zhang, L. Cao, F.Q. Zhang, H. Zhang, Z.C. Jiao, T.Y. Sheng, Y.D. Wang, L.H. Song, L.Y. Jiang, X.Z. Li, Z.M. Li, E.T. Wang, S. Lian, G. Li, Z.H. Tang, X.D. Zhao, H.W. Sun, L.T. Wu, Q. Li, J.Q. Cui, B.Q. Chen, L.H. Ma, R.G. Guo, B. Xu, S.W. Li, J.Y. Qi, N.C. Sun, W.L. Guo, X.Y. Zhang, P. Chen, Y.H. Zhou, Y. Zhou, J.F. He, J.R. Shang, C.S. Li, M.C. Zhou, X.H. Zhang, Y.H. Zhang, F.S. Hu, Z.G. Xu, H.S. Cheng, J.P. Liu, W.P. Key Laboratory of Beam Technology and Material Modification of Ministry of Education College of Nuclear Science and Technology Beijing Normal University Beijing100875 China The Joint Institute for Nuclear Astrophysics Department of Physics University of Notre Dame Notre DameIN46556 United States Bucharest-Magurele077125 Romania Institute of Modern Physics Chinese Academy of Sciences Lanzhou730000 China China Institute of Atomic Energy Beijing102413 China College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Shandong Provincial Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment Institute of Space Sciences Shandong University Weihai264209 China Yalong River Hydropower Development Company Chengdu610051 China Beijing Radiation Center Beijing100875 China

The 19F(p, αγ)16O reaction is of crucial importance for Galactic 19F abundances and CNO cycle loss in first generation Population III stars. Due to its extremely small cross sections, the 19F(p, αγ)16O reaction has not been measured in the low energy part of the Gamow window(70-200 keV). As a day-one campaign, the experiment was performed under the extremely low cosmic-ray-induced background environment of the China JinPing Underground Laboratory(CJPL), one of the deepest underground laboratories in the world. The γ-ray yields were measured over Ec.m.=72.4-344 keV, covering the full Gamow window for the first time. The direct experimental data will help people to expound the fluorine over-abundances, energy generation, as well as heavy-element nuclosynthesis scenario in asymptotic giant branch (AGB) stars, with the astrophysical model on the firm ground. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://***/licenses/by/4.0/).

关键词： Cosmology

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