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2023 International Conference on Networks, Communications and Intelligent Computing, NCIC 2023

作者： Lu, Jie Zhang, Yuexia Li, Junjie Ministry of Information Industry Beijing Information Science and Technology University Key Laboratory of Information and Communication Systems Beijing China Control Technology Ministry of Education Beijing Information Science and Technology University Key Laboratory of Modern Measurement Beijing China

ISBN: (纸本)9798350371949

Since the advancement of mobile communication technology, traditional industries are gradually transforming and upgrading, which leads to problems such as insufficient computing resources and excessive energy consumption of Internet of Things (IoT) devices. To address this issue, a resource allocation algorithm for the mobile edge computing-assisted industrial IoT (IIoT) is proposed. First, a mobile edge computing-assisted IIoT network model was constructed. Using the collaboration between IoT devices, mobile edge computing (MEC) servers, and cloud servers, the issue of minimizing all IIoT devices energy cost was proposed. Subsequently, in order to address the optimization issue, obtain its optimal solution, the alternating direction method of multipliers (ADMM) algorithm is introduced. Finally, the ADMM algorithm's convergence was verified through an experimental simulation. In contrast to baseline algorithm 1 and algorithm 2, the ADMM algorithm can significantly diminish energy cost, proving the effectiveness of the proposed scheme. © 2023 IEEE.

关键词： Resource allocation

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The global regulation of c-di-GMP and cAMP in bacteria

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mLife 2024年第1期3卷 42-56页

作者： Cong Liu Rui Shi Marcus S.Jensen Jingrong Zhu Jiawen Liu Xiaobo Liu Di Sun Weijie Liu Jiangsu Key Laboratory of Phylogenomics&Comparative Genomics School of Life SciencesJiangsu Normal UniversityXuzhouChina Key Laboratory of Metabolic Engineering and Biosynthesis Technology Ministry of Industry and Information TechnologyNanjing University of Science and TechnologyNanjingChina

Nucleotide second messengers are highly versatile signaling molecules that regulate a variety of key biological processes in *** best-studied examples are cyclic AMP(cAMP)and bis-(3'-5')-cyclic dimeric guanosine monophosphate(c-di-GMP),which both act as global *** regulatory frameworks of c-di-GMP and cAMP in bacteria show several parallels but also significant *** this review,we llustrate the global regulatory models of the two nucleotide second messengers,compare the different regulatory frameworks between c-di-GMP and cAMP,and discuss the mechanisms and physiological significance of cross-regulation between c-di-GMP and cAMP.c-di-GMP responds to numerous signals de-pendent on a great number of metabolic enzymes,and it regulates various signal transduction pathways through its huge number of effectors with varying *** contrast,due to the limited quantity,the cAMP metabolic enzymes and its major effector are regulated at different levels by diverse *** performs its global regulatory function primarily by controlling the transcription of a large number of genes via cAMP receptor protein(CRP)in most *** review can help us understand how bacteria use the two typical nucleotide second messengers to effectively coordinate and integrate various physiological processes,providing theoretical guidelines for future research.

关键词： bacteria cAMP c-di-GMP cross-regulation CRP

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Highly Reliable Multilayer Encryption Scheme With Constellation Shaping Based on Joint Index Modulation

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Journal of Lightwave technology 2025年第12期43卷 5689-5698页

作者： Zhu, Dongxu Liu, Bo Ren, Jianxin Mao, Yaya Song, Xiumin Chen, Shuaidong Zhao, Lilong Yin, Mengtong Dai, Wei Chen, Guoqing Cai, Junjie Institute of Optics and Electronics Nanjing University of Information Science & Technology Nanjing210044 China State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu International Joint Laboratory for Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu Engineering Research Center for Intelligent Optoelectronic Sensing Technology of Atmosphere Nanjing University of Information Science & Technology Nanjing210044 China Beijing University of Posts and Telecommunications Beijing100876 China Department of Electronic Engineering Tsinghua University Beijing100084 China

This paper proposes a highly reliable multilayer encryption scheme with constellation shaping based on joint index modulation. Multilayer encryption is used to ensure the security of the scheme. We utilize the 3D-Zhang chaotic system to realize the multidimensional perturbation of bits, subcarriers, and symbols of the original signal. The key information is masked with the signal using joint index modulation (JIM). The cooperative transmission of the initial value of the chaotic system is realized through the position information of the silent subcarriers and the constellation modes of the corresponding subcarriers. The scheme interleaves the initial values of the two chaotic systems to encode them as index bits, realizing the first layer of masked keys. Additional constellation shaping is achieved by optimizing the index mapping rules and changing the distribution of constellation points in the center and in the dual mode. The rotational encryption of the constellation is realized using a one-dimensional sinusoidal chaotic system after the completion of JIM, and the second layer of spherical shell masking of the key information is completed. The experimental implementation demonstrates the successful transmission of a 14 Gb/s 3D-JIM -8QAM signal over a 2 km weakly coupled seven-core fiber. Results confirm that the multi-layer encryption approach ensures secure signal transmission even under partial key leakage, without introducing degradation to the system's transmission performance. Compared to a random constellation distribution, the optimized index mapping scheme provides a coding gain of 0.75 dB at an FEC (Forward Error Correction) threshold of 3.8×10-3. The proposed scheme achieves error-free key transmission, with a bit error rate (BER) consistently maintained at 0. Notably, even minor key misalignments result in a BER of 0.5, facilitating timely key updates. The scheme boasts a vast key space of 10150, effectively resisting brute-force attacks. Due to its hi

关键词： Forward error correction

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Trial Selection Tensor Canonical Correlation Analysis (TSTCCA) for Depression Recognition with Facial Expression and Pupil Diameter

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IEEE Journal of Biomedical and Health Informatics 2023年第6期29卷 1-12页

作者： Yang, Minqiang Wu, Yushan Tao, Yongfeng Hu, Xiping Hu, Bin School of Information Science and Engineering Lanzhou University Lanzhou China Beijing Institute of Technology Beijing China Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University Gansu China

Facial expressions have been widely used for depression recognition because it is intuitive and convenient to access. Pupil diameter contains rich emotional information that is already reflected in facial video streams. However, the spatiotemporal correlation between pupillary changes and facial behavior changes induced by emotional stimuli has not been explored in existing studies. This paper presents a novel multimodal fusion algorithm - Trial Selection Tensor Canonical Correlation Analysis (TSTCCA) to optimize the feature space and build a more robust depression recognition model, which innovatively combines the spatiotemporal relevance and complementarity between facial expression and pupil diameter features. TSTCCA explores the interaction between trials and obtains an effective fusion representation of two modalities from a trial subset related to depression. The experimental results show that TSTCCA achieves the highest accuracy of 78.81% with the subset of 25 trials. IEEE

关键词： Face recognition

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Metallic Sb-stabilized porous silicon with stable SEI and high electron/ion conductivity boosting lithium-ion storage performance

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Rare Metals 2024年第9期43卷 4234-4242页

作者： Jia-Guo Deng Hao-Qin Feng Yu-Long Xu Si-Guang Guo Jian-Ping Li Kai-Fu Huo Ji-Jiang Fu Biao Gao Pual-K.Chu The State Key Laboratory of Refractories and Metallurgy and Institute of Advanced Materials and Nanotechnology Wuhan University of Science and TechnologyWuhan 430081China Wuhan National Laboratory for Optoelectronics(WNLO) School of Optical and Electronic InformationHuazhong University of Science and TechnologyWuhan 430074China Department of Physics Department of Materials Science&Engineeringand Department of Biomedical EngineeringCity University of Hong KongHong Kong 999077China

Silicon(Si)has mild discharge potential and high theoretical capacity,making it a highly desirable material for lithium-ion batteries(LIBs).Nevertheless,the excessive volume expansion,poor ion/electron conductiv ity and unstable solid electrolyte interface(SEI)hinde practical application to ***,the metallic antimony(Sb)stabilized porous Si(SiDSb)composite was prepared by magnesiothermic reduction of Sb_(2)O_(3)and Mg_(2)Si and chemical etching to remove the by-product of *** highly conductive Sb nanodots embedded in the Si liga ments promote not only the formation of conductive and stable LiF-rich SEI,but also the electron/ion transpor ability of *** to the outstanding bulk/interface stability,excellent conductivity,as well as ideal porous structure,the SiDSb electrode demonstrates a capacity of820 mAh·g^(-1)after undergoing 320 turns at 1000 mA·g^(-1).Additionally,it exhibits a stable capacity of 675 m Ah·g^(-1)when tested at a higher current density of 5000 m A·g^(-1).The results reveal a viable solution to solve three problems at the same time,namely the poor conductivity,inferior SEI and excessive volume expansion of Si,boding well for the design of Si-based materials for high-energy LIBs.

关键词： Silicon Anodes Lithium-ion batteries Antimony Solid electrolyte interphase

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Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 157-169页

作者： Rui Wang Zhiming Zhou Kaiwen Li Tao Zhang Ling Wang Xin Xu Xiangke Liao IEEE the Xiangjiang Laboratory and the College of Systems Engineering National University of Defense TechnologyChangsha 410073China the Institute of Automation Chinese Academy of SciencesBeijing 100190China the College of Systems Engineering National University of Defense TechnologyChangsha 410073 the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha 410073China the Department of Automation Tsinghua UniversityBeijing 100084China the College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China the College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex *** the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

关键词： Branch-and-bound(B&B) combinatorial optimization deep learning graph neural network imitation learning

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Distributed Deep Reinforcement Learning-based Approach for Fast Preventive Control Considering Transient Stability Constraints

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CSEE Journal of Power and Energy systems 2023年第1期9卷 197-208页

作者： Hongtai Zeng Yanzhen Zhou Qinglai Guo Zhongmin Cai Hongbin Sun State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Automation Science and Technology Xi’an Jiaotong UniversityXi’an 710000China

Preventive transient stability control is an effective measure for the power system to withstand high-probability severe *** is mathematically an optimal power flow problem with transient stability *** to the constraints involved for differential algebraic equations of transient stability,it is difficult and time-consuming to solve this *** address these issues,this paper presents a novel deep reinforcement learning(DRL)framework for preventive transient stability control of power systems.A distributed deep deterministic policy gradient is utilized to train a DRL agent that can learn its control policy through massive interactions with a grid *** properly trained,the DRL agent can instantaneously provide effective strategies to adjust the system to a safe operating position with a near-optimal operational *** effectiveness of the proposed method is verified through numerical experiments conducted on a New England 39-bus system and NPCC 140-bus system.

关键词： Deep reinforcement learning preventive Control transient stability

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Co-electrolysis of ethylene glycol and carbon dioxide for formate synthesis

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science China Chemistry 2024年第5期67卷 1539-1544页

作者： Dongfeng Du Fusong Kang Shiru Yang Bin Shao Jingshan Luo Institute of Photoelectronic Thin Film Devices and Technology State Key Laboratory of Photovoltaic Materials and CellsKey Laboratory of Photoelectronic Thin Film Devices and Technology of TianjinMinistry of Education Engineering Research Center of Thin Film Photoelectronic TechnologyNankai UniversityTianjin 300350China Haihe Laboratory of Sustainable Chemical Transformations Tianjin 300192China Frontiers Science Center for New Organic Matter Nankai UniversityTianjin 300071China College of Electronic Information and Optical Engineering Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network TechnologyNankai UniversityTianjin 300350China

Co-electrolysis of waste plastics and carbon dioxide(CO_(2)) into value-added chemicals or fuels is a promising pathway for a sustainable society, but efficient and selective conversion remains a challenge. Herein, a gold-mediated nickel hydroxide(Au/Ni(OH)_(2)) is developed to oxidize waste plastic-derived ethylene glycol(EG) into formate. In-situ electrochemical experiments and theoretical results reveal that the introduction of Au favors the redox properties and EG adsorption behavior of Ni(OH)_(2). The Au/Ni(OH)_(2) catalyst shows an excellent formate selectivity of >90% at high current densities of above 100 m A cm^(-2). When coupled with sputtered bismuth(Bi) cathode for CO_(2) reduction, a high formate Faradic efficiency(FE) of 188.2% at 200 m A cm^(-2)and a good formate productivity of 7.33 mmol m^(-2)s^(-1)at 10 A are obtained in a flow cell and a zero-gap membrane electrode assembly(MEA) cell, respectively. This work demonstrates a promising strategy to convert waste plastics and CO_(2) into valuable products.

关键词： waste plastic upcycling ethylene glycol oxidation carbon dioxide reduction electrocatalysis formate synthesis

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MMH-FE:AMulti-Precision and Multi-Sourced Heterogeneous Privacy-Preserving Neural Network Training Based on Functional Encryption

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Computers, Materials & Continua 2025年第3期82卷 5387-5405页

作者： Hao Li Kuan Shao Xin Wang Mufeng Wang Zhenyong Zhang The State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science CenterQilu University of Technology(Shandong Academy of Sciences)Jinan250014China China Industrial Control Systems Cyber Emergency Response Team Beijing100040China

Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model ***,dishonest clouds may infer user data,resulting in user data *** schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing *** address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training ***,we design a multi-precision functional encryption computation based on Euclidean ***,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced ***,we conduct experiments on three *** results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.

关键词： Functional encryption multi-sourced heterogeneous data privacy preservation neural networks

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Integrated design and performance optimization of three-electrode sliding discharge plasma power supply

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Plasma science and technology 2024年第11期26卷 152-161页

作者： Borui ZHENG Linwu WANG Jianbo ZHANG Shaojie QI Yuhong CHEN Haodong LIU Dongliang BIAN School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048People’s Republic of China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038People’s Republic of China

The three-electrode sliding dielectric barrier discharge(TES-DBD) plasma actuator significantly enhances the ionization rate and momentum exchange between charged particles and neutral particles by incorporating a parallel DC electrode into the standard DBD design. This design improves the body force and induced jet velocity while allowing flexible control of the induced jet angle, overcoming the limitations of discharge extension and uncontrollable direction in traditional DBD plasma actuators. An integrated plasma power supply has been designed specifically for TES-DBD plasma actuators, streamlining the power supply management. The methodology involves designing the circuit topology for the TES-DBD power supply, followed by simulating and validating its operating principles using Multisim software. The operational performance of the power supply is evaluated through a comprehensive analysis of its electrical,thermal, and aerodynamic properties specific to TES-DBD plasma actuation.

关键词： plasma flow control dielectric barrier discharge three-electrode sliding discharge plasma power supply

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