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arXiv 2025年

作者： Sun, Geng Ma, Weilong Li, Jiahui Sun, Zemin Wang, Jiacheng Niyato, Dusit Mao, Shiwen College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore College of Software Jilin University Changchun130012 China Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States

The low-altitude economy (LAE), driven by unmanned aerial vehicles (UAVs) and other aircraft, has revolutionized fields such as transportation, agriculture, and environmental monitoring. In the upcoming six-generation (6G) era, UAV-assisted mobile edge computing (MEC) is particularly crucial in challenging environments such as mountainous or disaster-stricken areas. The computation task offloading problem is one of the key issues in UAV-assisted MEC, primarily addressing the trade-off between minimizing the task delay and the energy consumption of the UAV. In this paper, we consider a UAV-assisted MEC system where the UAV carries the edge servers to facilitate task offloading for ground devices (GDs), and formulate a calculation delay and energy consumption multi-objective optimization problem (CDECMOP) to simultaneously improve the performance and reduce the cost of the system. Then, by modeling the formulated problem as a multi-objective Markov decision process (MOMDP), we propose a multi-objective deep reinforcement learning (DRL) algorithm within an evolutionary framework to dynamically adjust the weights and obtain non-dominated policies. Moreover, to ensure stable convergence and improve performance, we incorporate a target distribution learning (TDL) algorithm. Simulation results demonstrate that the proposed algorithm can better balance multiple optimization objectives and obtain superior non-dominated solutions compared to other methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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Secure personal data sharing for simultaneous, parallel or sequential processing service: Autonomously and controllably

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Future Generation Computer Systems 2025年 173卷

作者： Lyu, Qiuyun Zhou, Yilong Ren, Yizhi Zhou, Lingfei Wu, Zekai Zhao, Chengyao Zhang, Jilin Ma, Duohe School of Cyberspace Hangzhou Dianzi University Zhejiang Hangzhou310018 China Zhejiang Provincial Key Laboratory of Data Storage Transmission and Application Technology Zhejiang Hangzhou310018 China Pinghu Digital Technology Innovation Institute Co. Ltd Hangzhou Dianzi University Zhejiang Jiaxing314299 China Zhejiang Provincial Key Laboratory of Sensitive Data Security Protection and Confidentiality Governance Zhejiang Hangzhou310018 China Zhejiang Big Data Development Center Zhejiang Hangzhou310018 China Zhejiang Data Bureau Zhejiang Hangzhou310018 China Institute of Information Engineering of Chinese Academy of Sciences Beijing100084 China

Personal data, as an important category of data elements of a trusted data circulation, needs to be shared to others in "one-to-one" mode or "one-to-many" mode with simultaneously, parallelly or sequentially to meet all kinds of complex business scenarios. Actually, today's application asks more personalized content and more often than ever before, it increasingly highlights the need for data owners to have privacy rights such as the right to be informed and the right to erasure. However, existing personal data sharing schemes mainly deal with "one-to-one" mode and some of them have made breakthroughs in "one-to-many" mode, they still do not support complex scenarios such as simultaneously operating, parallelly executing or sequentially processing in a data privacy protection way. Therefore, this paper first encapsulates personal data into data capsules and designs three types of access tasks based on the requirements of complex scenarios to achieve secure collaborative sharing, secure multi-copies sharing, and secure ordered sharing. Specifically, the scheme embeds fine-grained authorization mechanisms within the data capsules and combines them with access task tokens that support autonomous control, achieving personal data sharing autonomy, including selective sharing, informed consent authorization, and permission revocation. Finally, the security of the proposed scheme is proven through formal and informal security proofs. The results of performance analysis show that the proposed scheme has better computational and storage efficiency while supporting the data sharing needs of complex scenarios. © 2025 Elsevier B.V.

关键词： data Sharing

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An integrated classification model for massive short texts with few words 19

An integrated classification model for massive short texts w...

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2019 International Conference on Robotics Systems and Vehicle Technology, RSVT 2019

作者： Tang, Xuetao Zhu, Yi Hu, Xuegang Li, Peipei Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology China

ISBN: (纸本)9781450362429

The excellent performance of short texts classification has emerged in the past few years. However, massive short texts with few words like invoice data are different with traditional short texts like tweets in its no contextual and less semantic information, which hinders the application of conventional classification algorithms. To address these problems, we propose an integrated classification model for massive short texts with few words. More specifically, the word embedding model is introduced to train the word vectors of massive short texts with few words to form the feature space, and then the vector representation of each instance in texts is trained based on sentence embedding. With this integrated model, higher level representations are learned from massive short texts with few words. It can boost the performance of the base subsequent classifiers such as K-Nearest Neighbor. Extensive experiments conducted on dataset including 16 million real data demonstrate the superior classification performance of our proposed model compared with all competing state-of-the-art models. © 2019 Association for Computing Machinery.

关键词： Embeddings

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Eu 3+ /Mn 4+ co-doped GdGeSbO 6 dual-emitting phosphor for multifunctional applications

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Journal of Rare Earths 2025年

作者： Chong Yang Bin Li Rongbo Ma Bin Cao Chaoyong Deng Weichao Huang Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information Engineering Guizhou University Guiyang 550025 China

Multifunctional phosphors have gained significant attention for their extensive application potential. In this work, novel Eu 3+ /Mn 4+ co-doped GdGeSbO 6 dual-emission phosphors were synthesized by high temperature solid-phase method. The crystal structure, optical properties, and temperature-sensing performance of these phosphors were systematically investigated. Under 463 nm excitation, GdGeSbO 6 :Eu 3+ ,Mn 4+ phosphors have multiple emission peaks in the range of 500–800 nm, corresponding to the 5 D 0 → 7 F J transition for Eu 3+ and the 2 E→ 4 A 2 transition for Mn 4+ , respectively. The optical temperature properties of GdGeSbO 6 :Eu 3+ ,Mn 4+ were analyzed using fluorescence intensity ratio (FIR) analysis, and the maximum relative sensitivity at 423 K is found to be 2.73%/K. By integrating GdGeSbO 6 :Eu 3+ ,Mn 4+ phosphors with near-UV light-emitting diode (LED) chips, a prototype LED device was successfully fabricated with a spectrum that significantly overlaps with the absorption curve of phytochrome. In addition, the anti-counterfeiting ink was prepared using GdGeSbO 6 :Eu 3+ ,Mn 4+ phosphors, and they show tunable emission under different light stimulation. These results indicate that GdGeSbO 6 :Eu 3+ ,Mn 4+ multifunctional phosphors have promising applications in optical thermometry, promoting plant growth and anti-counterfeiting.

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An improved secure designated server certificateless authenticated searchable encryption scheme for IIoT

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High-Confidence Computing 2025年

作者： Le Zhang Feng Zhou Qijia Zhang Wei Xiong Youliang Tian State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang 550025 Guizhou China College of Big Data and Information Engineering Guizhou University Guiyang 550025 Guizhou China

The Industrial Internet of Things (IIoT) achieves the automation, monitoring, and optimization of industrial processes by interconnecting various sensors, smart devices, and the Internet, which dramatically increases productivity and product quality. Nevertheless, the IIoT comprises a substantial amount of sensitive data, which requires encryption to ensure data privacy and security. Recently, Sun et al. proposed a certificateless searchable encryption scheme for IIoT to enable the retrieval of ciphertext data while protecting data privacy. However, we found that their scheme not only fails to satisfy trapdoor indistinguishability but also lacks defense against keyword guessing attacks. In addition, some schemes use deterministic algorithms in the encryption process, resulting in the same ciphertexts after encryption for the same keyword, thereby leaking the potential frequency distribution of the keyword in the ciphertext space, thereby leaking the potential frequency distribution of the keyword in the ciphertext space, allowing attackers to infer the plaintext information corresponding to the ciphertext through statistical analysis. To better protect data privacy, we propose an improved certificateless searchable encryption scheme with a designated server. With security analysis, we prove that our scheme provides multi-ciphertext indistinguishability and multi-trapdoor indistinguishability security under the random oracle. Experimental results show that the proposed scheme has good overall performance in terms of computational overhead, communication overhead, and security features.

关键词： Industrial Internet of Things Searchable encryption Indistinguishability keyword guessing attacks Random oracle

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Theoretical Insights on transition metals confined in black phosphorus for engineering stable single-atom catalysts

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Surfaces and Interfaces 2025年

作者： Guangxu Yang Dingming Ma Li Zhang Yujia Zhang Xu Tang Chunyan Li Can Cui Xin Tong Yadian Xie Yingchun Luo Lingyun Zhou School of Chemical Engineering Key Laboratory of Low-Dimensional Materials and Big Data Guizhou Minzu University Guizhou Guiyang 550025 China

Black phosphorus (BP) is a promising support for single-atom catalysts (SACs), yet detailed insights into metal-support interactions remains lacking. Using density functional theory (DFT) and ab initio molecular dynamics (AIMD), we investigate the coordination, electronic properties, and stability of 12 catalytic metals (Fe, Co, Ni, Cu, Ru, Rh, Pd, Ag, Os, Ir, Pt, Au) on BP. Most metals prefer the Hollow site, while Rh and Ir favor substitutional doping. Fe, Co, Ru, and Os exhibit unique embedding within the BP lattice. Covalent bonding is observed between metals and phosphorus atoms, with charge transfer trends aligning with electronegativity: 3d metals are positively charged, 4d metals neutral, and 5d metals negatively charged. Four metals (Ni, Rh, Pd, and Ir) are identified as promising candidates for single-atom dispersion on BP, with stability analysis and AIMD simulations revealing that Ir and Rh exhibit the highest stability, followed by Pd and Ni. Small molecule adsorption studies highlight Rh 1 /BP as a promising candidate for CO oxidation. These insights provide valuable theoretical guidance for the rational design of BP-supported SACs and understanding their catalytic behavior.

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In-situ synthesized SiC/TiC/SiTiOC hybrid nanofiber mats for broad-range temperature microwave absorption

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Science China Technological Sciences 2025年第6期 183-196页

作者： Yashan HUO Yuetong QIAN Minshan ZHAO Lei ZHANG Yujia TAN Zhihui HE Peng MIAO Fuchun ZHANG Wei CUI Renchao CHE School of Physics and Electronic Information Yan'an University Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data Laboratory of Advanced Materials Shanghai Key Lab of Molecular Catalysis and Innovative Materials Academy for Engineering &Technology Advanced Coatings Research Center of Ministry of Education of China Fudan University School of Materials and Chemical Engineering Xi'an Technological University School of Materials Science & Engineering Tongji University College of Physics Donghua University

Efficient, temperature-insensitive electromagnetic attenuation materials are critical for high microwave absorption at high temperatures. This study presents SiC/TiC/SiTiOC hybrid nanofiber mats constructed using an in-situ synthesis method;these mats incorporate SiC/TiC as the microwave loss unit and SiTiOC as the antioxidant unit, offering an innovative approach to high-temperature microwave absorption. The introduction of high-conductivity TiC not only optimizes the dielectric constant and impedance matching of the material but also enhances its thermal cycling stability. This design ensures steady electromagnetic attenuation, enabling the hybrid nanofiber mats to maintain robust absorption performance in the X-band, even at high temperatures. At 873 K, the material demonstrates an effective absorption bandwidth of 3.6 GHz and a minimum reflection loss of-45.55 dB. Compared to single-system absorbers, such as SiC/C nanofiber materials, with a single system, the multicomponent SiC/TiC/SiTiOC hybrid nanofiber mats deliver reliable absorption performance in the temperature range of 293–873 K. This study confirms that highly conductive titanium-based ceramic materials used for dielectric property regulation effectively address the challenges of poor temperature stability and limited reusability in high-temperature carbon-ceramic absorbing materials, providing valuable insights and guidance for designing efficient microwave absorbers that can operate across a wide temperature range.

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knowledge expression,numerical modeling and optimization application of ethylene thermal cracking:From the perspective of intelligent manufacturing

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Chinese Journal of Chemical engineering 2021年第10期34卷 1-17页

作者： Kexin Bi Shuyuan Zhang Chen Zhang Haoran Li Xinye Huang Haoyu Liu Tong Qiu Beijing Key Laboratory of Industrial Big Data System and Application Department of Chemical EngineeringTsinghua UniversityBeijing 100084China

Applications of process systems engineering(PSE)in plants and enterprises are boosting industrial reform from automation to digitization and *** ethylene thermal cracking,knowledge expression,numerical modeling and intelligent optimization are key steps for intelligent *** paper provides an overview of progress and contributions to the PSE-aided production of thermal cracking;introduces the frameworks,methods and algorithms that have been proposed over the past10 years and discusses the advantages,limitations and applications in industrial *** entire set of molecular-level modeling approaches from feedstocks to products,including feedstock molecular reconstruction,reaction-network auto-generation and cracking unit simulation are *** control and optimization methods are exhibited,including at the operational,cycle,plant and enterprise *** software packages are ***,an outlook in terms of future directions is presented.

关键词： Ethylene thermal cracking PSE Intelligent manufacturing Molecularization and digitization Modeling and optimization

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Movable Antenna-Aided Hybrid Beamforming for Multi-User Communications

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IEEE Transactions on Vehicular Technology 2025年

作者： Zhang, Yichi Zhang, Yuchen Zhu, Lipeng Xiao, Sa Tang, Wanbin Eldar, Yonina C. Zhang, Rui University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China University of Electronic Science and Technology of China National Key Laboratory of Science and Technology on Communications Chengdu611731 China Kash Institute of Electronics and Information Industry Kash844000 China Weizmann Institute of Science Faculty of Mathematics and Computer Science Rehovot7610001 Israel National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore Chinese University of Hon g Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen518172 China

In this correspondence, we propose a movable antenna (MA)-aided multi-user hybrid beamforming scheme with a sub-connected structure, where multiple movable sub-arrays can independently change their positions within different local regions. To maximize the system sum rate, we jointly optimize the digital beamformer, analog beamformer, and positions of sub-arrays, under the constraints of unit modulus, finite movable regions, and power budget. Due to the non-concave/non-convex objective function/constraints, as well as the highly coupled variables, the formulated problem is challenging to solve. By employing fractional programming, we develop an alternating optimization framework to solve the problem via a combination of Lagrange multipliers, penalty method, and gradient descent. Numerical results reveal that the proposed MA-aided hybrid beamforming scheme significantly improves the sum rate compared to its fixed-position antenna (FPA) counterpart. Moreover, with sufficiently large movable regions, the proposed scheme with sub-connected MA arrays even outperforms the fully-connected FPA array. © 1967-2012 IEEE.

关键词： Budget control

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Research on Soft Man Component Dynamic Evolution System and Its Distributed Multi-tasks Collaboration Mechanism Based on Game Theory

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Chinese Journal of Electronics 2018年第4期27卷 783-791页

作者： ZHANG Qingchuan ZUO Min CAO Qian CAO Caifeng BI Mingwen ZHANG Ruifang Beijing Key Laboratory of Big Data Technology for Food Safety School of Computer and Information EngineeringBeijing Technology and Business University

Taking the technical requirements for the dynamicity and flexibility of software system in open network environment as cut-in points, this paper put forward a novel dynamic component model named Soft Man component(SMC) which was well-formed and *** then a distributed multi-task collaboration mechanism based on game theory in Soft Man component dynamic evolution system is put forward in order to maximize the utilization of computing resources and resolve multi-tasks collaboration problem. Three kinds of experiments are designed to test the feasibility, robustness and performance of distributed multi-tasks collaboration mechanism. Results show that distributed multi-tasks collaboration mechanism based on game theory has a higher success rate and accuracy with good algorithm stability and reliability.

关键词： Component model Open software system Distributed collaboration Multi-tasks Game theory

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