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13th International Conference on computer engineering and Networks, CENet 2023

作者： Li, Yicheng Liang, Guangjun Tang, Keyan Teng, Yijia Ruan, Haoran Mo, Zixi Department of Computer Information and Cyber Security Jiangsu Police Institute Nanjing China Engineering Research Center of Electronic Data Forensics Analysis Nanjing China Key Laboratory of Digital Forensics Department of Public Security of Jiangsu Province Nanjing China

ISBN: (纸本)9789819992386

In order to cope with the widespread emergence of malicious APK in the application market and the increasingly rampant situation of mobile malware, as well as to meet the needs of the actual forensics work, this paper, based on the analysis of Android security mechanisms and their security problems, analyses and summarises the methodological principles, main technologies and functional flaws of existing APK automated analysis tools, and proposes an APK automated analysis system for actual forensics. Compared with traditional systems, the system is easy to operate and has a higher recognition accuracy rate. Besides, it will perform machine learning on the analysis results and calculate the similarity through the model to effectively assist the forensic work and fill the demand for APK analysis in the field of combat. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Malware

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Topology-optimized thermal metamaterials traversing full-parameter anisotropic space

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npj Computational Materials 2022年第1期8卷 1717-1726页

作者： Wei Sha Run Hu Mi Xiao Sheng Chu Zhan Zhu Cheng-Wei Qiu Liang Gao State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Coal Combustion School of Energy and Power EngineeringHuazhong University of Science and TechnologyWuhan430074China School of Engineering Cardiff UniversityCardiffCF243AAUnited Kingdom Department of Electrical and Computer Engineering National University of SingaporeKent Ridge117583Republic of Singapore

It is widely adopted in thermal metamaterials that mixing different materials could conveniently result in effective thermal conductivities(ETCs)beyond naturally-occurring *** multiple materials are isotropically mixed,the ETC is a direct average governed by their filling fractions and given bulk *** could lead to an inhomogeneous and anisotropic value within the maximal and minimal thermal conductivities of constituent *** thermal metadevices rely on anisotropic thermal conductivity tensor,whose tensorial elements are frequently inter-dependent and confined within a limited parametric *** is thus nontrivial to establish a design recipe for advanced thermal metamaterials whose ETCs could cover full-parameter anisotropic *** demonstrate topological functional cells(TFCs)with copper and polydimethylsiloxane,and show that the anisotropic ETCs traverse their full-parameter *** robust scheme based on topology-optimized TFCs unlocks unexplored opportunities for functional thermal metadevices whose parameters may not be reached in previous mixing *** study also sheds light on the developments in emerging acoustic,mechanical and electromagnetic composite materials.

关键词： parameter mixing thermal

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Reinforcement-Learning-Based Scheduling for Age of Information Optimization in MEC Multi-User Network 9

Reinforcement-Learning-Based Scheduling for Age of Informati...

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9th International Conference on computer and Communications, ICCC 2023

作者： Gao, Ke Chen, Yuchao Chen, Guozhi Wang, Jintao Beijing China Tsinghua University Department of Electronic Engineering Beijing China Research Institute of Tsinghua University in Shenzhen Key Laboratory of Digital Tv System of Guangdong Province and Shenzhen City Shenzhen China

ISBN: (纸本)9798350317251

In this paper, we consider an optimization problem in a mobile edge computing (MEC) multi-user network for collecting fresh information under bandwidth and energy constraints. We use the popular metric Age of Information (AoI) to measure the data freshness. To solve the age optimization problem, we first relax the bandwidth constraints, and then decouple the problem, where each sub-problem is formulated into a constrained Markov decision process (CMDP) problem. Due to the fast mobility of the users, the distribution of channel state information and size of raw data is difficult to obtain for the base station. To overcome the unknown channel statistics challenge, we introduce a Reinforcement-Learning-based Q-learning algorithm to learn the channel information, which helps to guide the optimal scheduling decision. Simulation results demonstrate that the proposed algorithm can achieve the better AoI performance compared with other traditional algorithm while satisfying bandwidth and energy constraints. © 2023 IEEE.

关键词： Reinforcement learning

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Single Block Encoder-Decoder Transformer Model for Multi-Step Traffic Flow Forecasting 6

Single Block Encoder-Decoder Transformer Model for Multi-Ste...

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6th IEEE Symposium on computers and Informatics, ISCI 2024

作者： Omar, Mas Yakub, Fitri Talip, Mohamad Sofian Abu Maslan, Mohd Nazmin Sinha, Vijay Kumar Muljono, Muljono Universiti Teknologi Malaysia Wee Laboratory Malaysia-Japan International Institute of Technology Kuala Lumpur Malaysia Universiti Teknologi Malaysia Malaysia-Japan International Institute of Technology Department of Electronic System Engineering Kuala Lumpur Malaysia University of Malaya Faculty of Engineering Department of Electrical Engineering Kuala Lumpur Malaysia Universiti Teknikal Malaysia Faculty of Industrial and Manufacturing Technology and Engineering Melaka Malaysia Chitkara University School of Engineering & Technology Department of Computer Science & Engineering Himachal Pradesh India Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350353853

Accurate traffic flow forecasting is crucial for managing and planning urban transportation systems. Despite the widespread use of sequence modelling models like Long Short-Term Memory (LSTM) for this purpose, the potential of Transformer models remains underexplored. This is particularly true for the simplest form of a single block encoder-decoder Transformer model, which can be finely tuned through optimised hyperparameters. This paper examines the performance of a singular horizon-step forecasting method for multi-step traffic flow forecasting using a proposed Single Block Encoder-Decoder Transformer model optimised with a Grid Search algorithm. Results demonstrate that this model can enhance forecasting accuracy compared to the state-of-the-art LSTM model typically used for multi-step forecasting. The model effectively captures long-range temporal dependencies within a single road traffic flow dataset. It was tested on hourly traffic flow data to forecast the next 24 hours for the I5-North freeway in California, sourced from the Caltrans Performance Measurement system. The optimal configuration included an embedding dimension of 32, a feed-forward dimension of 128, and 8 attention heads. Results show a significant improvement, with a 4.7% reduction in Root Mean Squared Error compared to an LSTM model with two hidden layers of 100 neurons each, showcasing the potential of Single Block Encoder-Decoder Transformer models for real-world traffic prediction applications. © 2024 IEEE.

关键词： Mean square error

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A Police UAV system Based on Target Recognition 13th

A Police UAV System Based on Target Recognition

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13th International Conference on computer engineering and Networks, CENet 2023

作者： Qiu, Zhenyu Liang, Guangjun Du, Hongtian Yan, Bohan Peng, Jiahao Ju, Zexin Department of Computer Information and Cyber Security Jiangsu Police Institute Nanjing China Engineering Research Center of Electronic Data Forensics Analysis Nanjing China Key Laboratory of Digital Forensics Department of Public Security of Jiangsu Province Nanjing China

ISBN: (纸本)9789819992386

The As a kind of aircraft without carrying operators, unmanned aerial vehicle (UAV) has been rapidly developed in the civil field. It is widely used in police, urban management, agriculture, geology, meteorology, electric power, disaster relief and other industries. However, the current police UAV still has shortcomings in specific target recognition and tracking. Therefore, the police UAV equipped with target recognition technology is designed in this project to enhance its performance. The project also investigates the materials and structure of police UAV, and focuses on target recognition systems which use sensors and algorithms to identify, classify and track targets, providing support for autonomous navigation and surveillance of UAV. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Python

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A 1 km Line-of-Sight Ultraviolet Communication system with a Data Rate of 26.6kbps

A 1 km Line-of-Sight Ultraviolet Communication System with a...

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2023 International Conference on Electrical engineering and Photonics, EExPolytech 2023

作者： Wang, Mingyang Cao, Tian Chen, Shihan Pan, Changyong Song, Jian School of Telecommunications Engineering Xidian University State Key Laboratory of Integrated Service Networks Xian China Tsinghua University Department of Electronic Engineering Beijing China Research Institute of Tsinghua University in Shenzhen Key Laboratory of Digital Tv System of Guangdong Province and Shenzhen City Shenzhen China

ISBN: (纸本)9798350310481

Ultraviolet communication (UVC) has emerged as a promising solution for close-range communication within the intricate electromagnetic setting. The atmosphere's attenuation, however, restricts the scope and rate of communication. We demonstrated a line-of-sight (LOS) UV communication system. In our system, we employed ultraviolet light-emitting diodes (LEDs) in our system to transmit the signal light with a broad radiation angle and use lenses to enhance the communication range. We propose a combined approach of theory and practice to analyze the feasibility of a LOS UVC system. © 2023 IEEE.

关键词： Optical communication

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Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms 13

Last-X-Generation Archiving Strategy for Multi-Objective Evo...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Shu, Tianye Nan, Yang Shang, Ke Ishibuchi, Hisao Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China Southern University of Science and Technology Shenzhen518055 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

ISBN: (纸本)9798350308365

For evolutionary multi-objective optimization algorithms (EMOAs), an external archive can be utilized for saving good solutions found throughout the evolutionary process. Recent studies showed that a solution set selected from an external archive is usually superior to the final population. That is, the incorporation of an external archive improves the performance of EMOAs. However, the computation time for maintaining an external archive is long, especially when the archive size is large. To solve this issue, a simple archiving strategy is to save all solutions generated in the last several generations. In this paper, we examine this archiving strategy for three representative EMOAs on artificial test problems (Minus-DTLZ and WFG) and real-world problems (RE). Our results show that archiving the last several generations clearly improves the performance of EMOAs without severely increasing the computation time. © 2024 IEEE.

关键词： Optimization algorithms

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Generative AI-Enhanced Cooperative MEC of UAVs and Ground Stations for Unmanned Surface Vehicles 59

Generative AI-Enhanced Cooperative MEC of UAVs and Ground St...

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59th Annual Conference on Information Sciences and systems, CISS 2025

作者： You, Jiahao Jia, Ziye Dong, Chao Wu, Qihui Han, Zhu Nanjing University of Aeronautics and Astronautics The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Nanjing211111 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

ISBN: (纸本)9798331513269

The increasing deployment of unmanned surface vehicles (USVs) require computational support and coverage in applications such as maritime search and rescue. Unmanned aerial vehicles (UAVs) can offer low-cost, flexible aerial services, and ground stations (GSs) can provide powerful supports, which can cooperate to help the USVs in complex scenarios. However, the collaboration between UAVs and GSs for USVs faces challenges of task uncertainties, USVs trajectory uncertainties, heterogeneities, and limited computational resources. To address these issues, we propose a cooperative UAV and GS based robust multi-access edge computing framework to assist USVs in completing computational tasks. Specifically, we formulate the optimization problem of joint task offloading and UAV trajectory to minimize the total execution time, which is in the form of mixed integer nonlinear programming and NP-hard to tackle. Therefore, we propose the algorithm of generative artificial intelligence-enhanced heterogeneous agent proximal policy optimization (GAI-HAPPO). The proposed algorithm integrates GAI models to enhance the actor network ability to model complex environments and extract high-level features, thereby allowing the algorithm to predict uncertainties and adapt to dynamic conditions. Additionally, GAI stabilizes the critic network, addressing the instability of multi-agent reinforcement learning approaches. Finally, extensive simulations demonstrate that the proposed algorithm outperforms the existing benchmark methods, thus highlighting the potentials in tackling intricate, cross-domain issues in the considered scenarios. © 2025 IEEE.

关键词： Unmanned surface vehicles

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GPU accelerated blockchain over key-value database transactions

IET Blockchain

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IET Blockchain 2022年第1期2卷 1-12页

作者： Iliakis, Konstantinos Koliogeorgi, Konstantina Litke, Antonios Varvarigou, Theodora Soudris, Dimitrios Microprocessors and Digital Systems Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Zografou Campous 9 Iroon Polytechniou str Athens Greece Distributed Knowledge and Media Systems group Department of Electrical and Computer Engineering National Technical University of Athens Zografou Campous 9 Iroon Polytechniou str Athens Greece

Blockchain is a distributed ledger based on peer-to-peer networks, originally used for crypto-currency systems. Blockchains are being used as an enabling technology for decentralised applications in the areas of Internet-of-Things, finance, supply-chain and others. Consistency, data privacy, performance, and energy efficiency are of paramount importance in such applications. The full nodes of public, permissionless blockchains undertake the task of verifying the transactions generated by the network. Full nodes perform operations such as confirming balances, transactions, and history, i.e. mostly database search queries. Consequently, their throughput is crucial for the performance of blockchain systems. In this work, the benefits of accelerating the blockchain search and insert queries by leveraging GPU platforms are studied. An extensive comparison between the most dominant utilized database is provided, i.e. LevelDB, and MegaKV, a high-performance GPU-accelerated database. Realistic operations that take place in blockchain systems are emulated and evaluated over representative scenarios, showing three orders of magnitude gains in throughput and energy efficiency without compromising the security aspect. The extensive comparison between LevelDB and MegaKV indicates that GPU acceleration is an effective solution for runtime and energy efficiency enhancement of blockchain systems, and the integration of the two technologies is a promising field of research. © 2022 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Blockchain

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Improved High-Speed Thermal Analysis Based on Two-Step Simulation for High-Frequency Transformers 14

Improved High-Speed Thermal Analysis Based on Two-Step Simul...

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14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Yi, Zheyuan Sun, Kai Li, Qiang Liu, Zengyang Tsinghua University State Key Laboratory of Power System Department of Electrical Engineering Beijing China Delta Electronics Shanghai Co. Ltd. Shanghai China University Blacksburg Center for Power Electronics Systems The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State BlacksburgVA United States

ISBN: (纸本)9798331516116

Thermal analysis is a crucial and time-consuming step in the optimization design process of high-frequency transformers (HFTs). This paper proposes an improved thermal analysis method based on heat dissipation-conduction two-step simulation, significantly reducing the computation time while ensuring the accuracy of thermal analysis. Simulation results validate the accuracy and of the proposed method and demonstrate that the proposed method saves 82% of computation time for a single thermal analysis case compared to direct CFD. Experimental results further verify the accuracy of the proposed method. An exemplary application of the proposed method in the optimization design of the HFT illustrates a 98% reduction in computation time for thermal analysis during the optimization process. © 2025 IEEE.

关键词： Thermal modeling

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