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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Huang, Yang Luo, Aimin Zhang, Mengmeng Bai, Liang Song, Yanjie Li, Jiting Science and Technology on Information Systems Engineering Laboratory College of Systems Engineering National University of Defense Technology Changsha China College of Systems Engineering National University of Defense Technology Changsha China Chinese Academy of Military Science Beijing China

ISBN: (纸本)9789819915484

The UAV mobile crowd sensing problem is a new research area due to the flexibility and low-cost advantage of UAVs. Current research rarely considers the task assignment and path planning problem simultaneously. In this paper, we describe the improved UAV mobile crowed sensing model that takes both the task assignment and path planning into consideration, meanwhile the model also considered the limit of UAV's power. In our paper, a task location distribution based genetic algorithm is proposed to solve the problem more efficiently. A series of instances involving different number of tasks and UAV bases is used in the paper. The results of the experiment indicate that our proposed method is efficient and can deal with large-scale problems. This research has resulted in a solution of the UAV mobile crowd sensing problem and can provide ideas to similar problems. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Genetic algorithms

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An AD-SPSO Algorithm for Solving the Measurement Resource Scheduling Problem with Satellite Cataloging Requirements

An AD-SPSO Algorithm for Solving the Measurement Resource Sc...

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2024 IEEE International Conference on Control science and systems engineering, ICCSSE 2024

作者： Niu, Ge Jiao, Yuanyuan Pan, Xiaogang National University of Defense Technology National Key Laboratory of Information Systems Engineering Changsha China

ISBN: (纸本)9798331517199

Under the condition of limited ground measurement resources, the increasing scale of satellites brings more satellite cataloging requirements and aggravates the measured pressure. How to better utilize limited measurement resources is a crucial issue. In this paper, the measurement resource scheduling problem with satellite cataloging requirements is examined, a measurement resource scheduling model is established with the goal of maximizing profits from satellite cataloging task completion, and a switching particle swarm optimization algorithm based on adaptive large neighborhood search and dynamic neighborhood (AD-SPSO) is proposed. The AD-SPSO algorithm uses the time greedy strategy and chaos mapping to obtain an initial population with better quality. Then, the algorithm designs the dynamic neighborhood of the particle, after which the particle's velocity is updated by selecting the optimal position from the dynamic neighborhood of the particle, so as to enhance the inter-particle information interaction and utilize the population information. In addition, the AD-SPSO algorithm joins the adaptive large neighborhood search algorithm, which selects different particles for perturbation according to the population state. This effectively prevents its early convergence. To evaluate the performance of the AD-SPSO algorithm, this paper performs experiments in four scenarios, and in different scenarios, compared with other improved algorithms, the AD-SPSO algorithm can obtain higher and more stable overall profit for scheduling plans, which verifies its effectiveness in solving the measurement resource scheduling problem with satellite cataloging requirements. © 2024 IEEE.

关键词： Profitability

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Parsing Objects at a Finer Granularity: A Survey

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Machine Intelligence Research 2024年第3期21卷 431-451页

作者： Yifan Zhao Jia Li Yonghong Tian School of Computer Science Peking UniversityBeijing100871China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing100191China

Fine-grained visual parsing, including fine-grained part segmentation and fine-grained object recognition, has attracted considerable critical attention due to its importance in many real-world applications, e.g., agriculture, remote sensing, and space technologies. Predominant research efforts tackle these fine-grained sub-tasks following different paradigms, while the inherent relations between these tasks are neglected. Moreover, given most of the research remains fragmented, we conduct an in-depth study of the advanced work from a new perspective of learning the part relationship. In this perspective, we first consolidate recent research and benchmark syntheses with new taxonomies. Based on this consolidation, we revisit the universal challenges in fine-grained part segmentation and recognition tasks and propose new solutions by part relationship learning for these important challenges. Furthermore, we conclude several promising lines of research in fine-grained visual parsing for future research.

关键词： Finer granularity visual parsing part segmentation fine-grained object recognition part relationship

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Effectiveness of Precursor Emission Reductions for the Control of Summertime Ozone and PM2.5 in the Beijing–Tianjin–Hebei Region under Different Meteorological Conditions

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Advances in Atmospheric sciences 2025年第4期42卷 653-669页

作者： Jing QIAN Hong LIAO Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science&TechnologyNanjing 210044JiangsuChina

We used observed concentrations of air pollutants,reanalyzed meteorological parameters,and results from the Goddard Earth Observing System Chemical Transport Model to examine the relationships between concentrations of maximum daily 8-h average ozone(MDA8 O_(3)),PM_(2.5)(particulate matter with diameter of 2.5μm or less),and PM_(2.5)components and 2-m temperature(T2)or relative humidity(RH),as well as the effectiveness of precursor emission reductions on the control of O_(3) and PM_(2.5) in Beijing–Tianjin–Hebei(BTH)under different summertime temperature and humidity *** observed(simulated)MDA8 O_(3) and PM_(2.5) concentrations increased as T2 went up,with linear trends of 4.8(3.2)ppb℃^(−1) and 1.9(1.5)μg m^(−3)℃^(−1),*** results showed that the decreases in MDA8 O_(3) from precursor emission reductions were more sensitive to T2 than to *** a larger proportion of volatile organic compound(VOC)emissions at higher T2 was more effective for the control of summertime O_(3) in *** the control of summertime PM_(2.5) in BTH,reducing nitrogen oxides(NOx)combined with a small proportion of VOCs was the best *** magnitude of reduction in PM_(2.5) from reducing precursor emissions was more sensitive to RH than to T2,with the best efficiency at high *** from this study are helpful for formulating effective policies to tackle O_(3) and PM_(2.5) pollution in BTH.

关键词： ozone PM_(2.5) emission reductions meteorological conditions

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Programmable array antenna based on nematic liquid crystals for the Ka-band

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Journal of Southeast University(English Edition) 2025年第1期41卷 78-83页

作者： WANG Qiang KE Junchen BAI Lin Guangxi Key Laboratory of Optoelectronic Information Processing Guilin University of Electronic TechnologyGuilin 541004China School of Optoelectronic Engineering Guilin University of Electronic TechnologyGuilin 541004China School of Information Science and Engineering Southeast UniversityNanjing 211189China

A programmable low-profile array antenna based on nematic liquid crystals(NLCs)is *** antenna unit comprises a square patch radiating structure and a tunable NLC-based phase shifter capable of achieving a phase shift exceeding 360°with high ***,the above 64 antenna units are periodically arranged into an 8×8 NLC-based antenna array,and the bias voltage of the NLC-based phase shifter loaded on the antenna unit is adjusted through the control of the field-programmable gate array(FPGA)programming *** configuration enables precise phase changes for all 64 *** simulation,sample processing,and experimental measurements of the antenna array are conducted to validate the performance of the *** numerical and experimental results demonstrate that the proposed antenna performs well within the frequency range of 19.5-20.5 GHz,with a 3 dB relative bandwidth of 10%and a maximum main lobe gain of 14.1 dBi.A maximum scanning angle of±34°is achieved through the adjustment of the FPGA programming *** NLC-based programmable array antenna shows promising potential for applications in satellite communication.

关键词： array antenna nematic liquid crystals electronically beam scanning field programmable gate array(FPGA)

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Weapon Target Assignment Based on Deep Q-learning 9

Weapon Target Assignment Based on Deep Q-learning

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9th IEEE International Conference on Data science in Cyberspace, DSC 2024

作者： Qin, Jianbo Wang, Yi Ding, Zhaoyun National University of Defense Technology National Key Laboratory of Information Systems Engineering ChangSha China

ISBN: (纸本)9798350391367

This paper introduces an innovative approach to addressing the Weapon Target Assignment (WTA) problem, utilizing the Deep Q-Learning (DQN) algorithm. The goal is to optimize the allocation between weapons and targets to achieve the most effective combat outcome. Initially proposed by Manne, the WTA problem is a multi-objective, multi-constraint NP-complete problem, the complexity of which increases with the number and variety of weapons and targets. The DQN model presented in this paper transforms the WTA problem into a reinforcement learning issue, effectively addressing the issues of low efficiency and the propensity to fall into local optima associated with traditional heuristic algorithms in large-scale scenarios. © 2024 IEEE.

关键词： Deep reinforcement learning

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Support vector regression-based operational effectiveness evaluation approach to reconnaissance satellite system

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Journal of systems engineering and Electronics 2023年第6期34卷 1626-1644页

作者： HAN Chi XIONG Wei XIONG Minghui LIU Zhen College of Aerospace Information Space Engineering UniversityBeijing 101400China Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering UniversityBeijing 101400China

As one of the most important part of weapon system of systems(WSoS),quantitative evaluation of reconnaissance satellite system(RSS)is indispensable during its construction and *** at the problem of nonlinear effectiveness evaluation under small sample conditions,we propose an evaluation method based on support vector regression(SVR)to effectively address the defects of traditional *** the performance of SVR is influenced by the penalty factor,kernel type,and other parameters deeply,the improved grey wolf optimizer(IGWO)is employed for parameter *** the proposed IGWO algorithm,the opposition-based learning strategy is adopted to increase the probability of avoiding the local optima,the mutation operator is used to escape from premature convergence and differential convergence factors are applied to increase the rate of *** experiments of 14 test functions validate the applicability of IGWO algorithm dealing with global *** index system and evaluation method are constructed based on the characteristics of *** validate the proposed IGWO-SVR evaluation method,eight benchmark data sets and combat simulation are employed to estimate the evaluation accuracy,convergence performance and computational *** to the experimental results,the proposed method outperforms several prediction based evaluation methods,verifies the superiority and effectiveness in RSS operational effectiveness evaluation.

关键词： reconnaissance satellite system(RSS) support vector regression(SVR) gray wolf optimizer opposition-based learning parameter optimization effectiveness evaluation

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Multispectral radiation thermometry approach based on feasible region constraints-divide and conquer optimization

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Optics Express 2025年第10期33卷 20736-20753页

作者： Huang, Hairui Zhang, Wei Yu, Peifeng Xu, Jiawen Liu, Xin Gao, Shan Wang, Chao Zhang, Zezhan Niu, Yi Jiang, Jing Clean Energy Materials and Engineering Center School of Electronic Science and Engineering State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China Chengdu611731 China The State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision Instrument Tsinghua University Beijing100084 China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology School of Information and Communication Engineering Harbin Engineering University Harbin150001 China

Multispectral radiation thermometry is a widely used non-contact temperature measurement method, particularly in extreme environments. However, accurately retrieving the true temperature remains challenging due to the unknown emissivity of the object. This paper proposes a collaborative optimization approach (feasible region constraints-divide and conquer optimization), which combines a feasible domain constraints method (PCR-PSO) with a divide and conquer optimization algorithm (multi-BFGS). Simulation results show that the proposed approach reduces the temperature inversion error from 0.59% to 0.19% compared to the traditional BFGS algorithm. Experimental results obtained with stainless steel samples indicate an average error of less than 0.2% and an average processing time of 0.2 seconds, highlighting the potential for real-time temperature measurement in engineering applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Temperature measurement

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Deep Learning Based Side-Channel Attack Detection for Mobile Devices Security in 5G Networks

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1012-1026页

作者： Amjed A.Ahmed Mohammad Kamrul Hasan Ali Alqahtani Shayla Islam Bishwajeet Pandey Leila Rzayeva Huda Saleh Abbas Azana Hafizah Mohd Aman Nayef Alqahtani Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Imam Alkadhim University College Department of Computer Techniques EngineeringBaghdad 10066Iraq Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Department of Networks and Communications Engineering College of Computer Science and Information SystemsNajran UniversityNajran 61441Saudi Arabia Institute of Computer Science and Digital Innovation UCSI UniversityKuala Lumpur 56000Malaysia Department of Intelligent Systems and Cyber Security Astana IT UniversityAstana 20000Kazakstan Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMadinah 42353Saudi Arabia Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Hofuf 31982Saudi Arabia

Mobile devices within Fifth Generation(5G)networks,typically equipped with Android systems,serve as a bridge to connect digital gadgets such as global positioning system,mobile devices,and wireless routers,which are vital in facilitating end-user communication ***,the security of Android systems has been challenged by the sensitive data involved,leading to vulnerabilities in mobile devices used in 5G *** vulnerabilities expose mobile devices to cyber-attacks,primarily resulting from security ***-permission apps in Android can exploit these channels to access sensitive information,including user identities,login credentials,and geolocation *** such attack leverages"zero-permission"sensors like accelerometers and gyroscopes,enabling attackers to gather information about the smartphone's *** underscores the importance of fortifying mobile devices against potential future *** research focuses on a new recurrent neural network prediction model,which has proved highly effective for detecting side-channel attacks in mobile devices in 5G *** conducted state-of-the-art comparative studies to validate our experimental *** results demonstrate that even a small amount of training data can accurately recognize 37.5％of previously unseen user-typed ***,our tap detection mechanism achieves a 92％accuracy rate,a crucial factor for text *** findings have significant practical implications,as they reinforce mobile device security in 5G networks,enhancing user privacy,and data protection.

关键词： Fifth Generation(5G)networks smartphone information leakage Side-Channel Attack(SCA) deep learning

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An Approach Based on Grey Wolf Optimizer for Path Planning in Searching Missing Submersibles 14

An Approach Based on Grey Wolf Optimizer for Path Planning i...

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14th International Conference on Logistics and systems engineering

作者： Zhang, Zhongyuan Yang, Zhenyu Ji, Xiaofeng Ren, Bangbang College of Systems Engineering National University of Defense Technology Hunan Changsha410073 China National Key Laboratory of Information Systems Engineering National University of Defense Technology China

ISBN: (纸本)9798331314347

In ocean search and rescue missions, how to efficiently locate missing submersibles is a challenging problem. The distribution of submersibles may remain relatively stable in some periods of time, but it may also show dynamic changes due to changes in environmental conditions such as terrain, density of seawater and ocean currents. Affected by factors such as minerals, the density of seawater generally increases linearly with the increase of depth. The partial derivative and gradient differential methods are used to simulate and analyze different terrain when it has great influence on submersible. The speed of ocean currents decreases with depth, and submarine currents are usually slow and steady. Ocean current data set is collected for data preprocessing. A large amount of real data is helpful to determine the direction and speed of ocean currents in each region quantitatively, and then analyze the motion trajectory of submersible, which proves the reliability of theory applied in practice. Considering the uncertainty of submersible position over time, this paper proposes a path planning method combining greedy algorithm and grey wolf optimization (GWO) algorithm together, and discusses the cooperative working mechanism of multiple searchers. The greedy algorithm is used to plan the path of a single search submersible, and the grey wolf optimization algorithm is introduced when considering the joint search of multiple search submersibles. Each step of greedy algorithm is to select the current optimal solution and build the overall path to the local optimal. Through programming, a route with a success rate of about 91% was obtained, and the shortest path was calculated to be about 50,155.69 meters. The GWO is solved by simulating the hunting behavior of wolves, combining the obstacle avoidance strategy of the submersible and the multi-agent cooperative method. When the search success rate remains above 90%, by applying GWO, the search efficiency is improved as the s

关键词： Seawater

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