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2024 International Conference Optoelectronic Information and Optical Engineering, OIOE 2024

作者： Zhang, Xinyue Lv, Weimin Wei, Dingjiang Yang, Dongsheng Yang, Lin Naval Aviation University Yantai China No. 91593 of PLA Sanya China The Laboratory for Military-Civilian Integration Emergency Command and Control Jinan University Guangzhou China School of Public Management/Emergency Management Jinan University Guangzhou China Key Laboratory of Information System Engineering National University of Defense Technology Changsha China School of Information and Intelligent Engineering University of Sanya Academician Guoliang Chen Team Innovation Center University of Sanya Sanya China

ISBN: (数字)9781510688209

ISBN: (纸本)9781510688193

This paper examines the potential for leveraging the order dispatch algorithm in the commercial domain to enhance the intelligent allocation of military combat tasks, thereby improving the speed and accuracy of command decision-making in the context of intelligent warfare. The study proposes an "order-based" command and control model, which aims to overcome the efficiency bottleneck and information lag problem in traditional combat task allocation. The algorithmic design incorporates multi-dimensional association rules and similarity matching algorithms to guarantee the optimal matching of combat tasks and resources, thereby achieving the objectives of rapid response, efficient resource utilization, and enhanced combat effectiveness. This paper focuses on the challenges and advantages of this model in the context of naval warfare. It highlights the strategic value of order-based command and control in non-direct confrontation missions, such as reconnaissance, patrol, and intelligence gathering. The utilization of the "combat cloud," artificial intelligence, and a highly integrated command network enables the precise allocation of resources and the rapid execution of tasks. This, in turn, enhances the ISR capability, network-centered warfare effectiveness, and cross-domain synergistic warfare capability in naval warfare. The study also delineates the specific implementation process of the algorithm, which includes multi-dimensional association rule mining and similarity matching based on historical cases, with the objective of generating optimal combat scenarios and ensuring the effective execution of task orders. © 2025 SPIE.

关键词： Naval warfare

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Learning the continuous-time optimal decision law from discrete-time rewards

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national science Open 2024年第5期3卷 130-147页

作者： Ci Chen Lihua Xie Kan Xie Frank Leroy Lewis Yilu Liu Shengli Xie School of Automation Guangdong University of TechnologyGuangdong Key Laboratory of IoT Information TechnologyGuangzhou 510006China Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of EducationGuangzhou 510006China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou 510006China UTA Research Institute the University of Texas at ArlingtonFort Worth 76118USA Department of Electrical Engineering and Computer Science University of TennesseeKnoxville 37996USA Oak Ridge National Laboratory Oak Ridge 37830USA Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou 510006China

The concept of reward is fundamental in reinforcement learning with a wide range of applications in natural and social *** an interpretable reward for decision-making that largely shapes the system's behavior has always been a challenge in reinforcement *** this work,we explore a discrete-time reward for reinforcement learning in continuous time and action spaces that represent many phenomena captured by applying physical *** find that the discrete-time reward leads to the extraction of the unique continuous-time decision law and improved computational efficiency by dropping the integrator operator that appears in classical results with integral *** apply this finding to solve output-feedback design problems in power *** results reveal that our approach removes an intermediate stage of identifying dynamical *** work suggests that the discrete-time reward is efficient in search of the desired decision law,which provides a computational tool to understand and modify the behavior of large-scale engineering systems using the optimal learned decision.

关键词： continuous-time state and action decision law learning discrete-time reward dynamical systems reinforcement learning

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An approach to measuring business-IT alignment maturity via DoDAF2.0

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Journal of systems Engineering and Electronics 2020年第1期31卷 95-108页

作者： ZHANG Mengmeng CHEN Honghui MAO Yi LUO Aimin Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410072China State Key Laboratory of Air Traffic Management System and Technology Nanjing 210014China

Measuring the business-IT alignment(BITA)of an organization determines its alignment level,provides directions for further improvements,and consequently promotes the organizational *** to the capabilities of enterprise architecture(EA)in interrelating different business/IT viewpoints and elements,the development of EA is superior to support BITA *** BITA measurement literature is sparse when it concerns *** literature tends to explain how EA viewpoints or models correlate with BITA,without discussing where to collect and integrate EA *** address this gap,this paper attempts to propose a specific BITA measurement process through associating a BITA maturity model with a famous EA framework:DoD Architectural Framework 2.0(DoDAF2.0).The BITA metrics in the maturity model are connected to the meta-models and models of *** illustrative ArchiSurance case is conducted to explain the measurement ***,this paper explores the process of BITA measurement from the viewpoint of EA,which helps to collect the measurement data in an organized way and analyzes the BITA level in the phase of architecture development.

关键词： business-IT alignment(BITA) measurement enterprise architecture(EA) DoD Architectural Framework 2.0(DoDAF2.0) meta-model

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Improving Code Search with Multi-Modal Momentum Contrastive Learning

Improving Code Search with Multi-Modal Momentum Contrastive ...

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IEEE/ACM International Conference on Program Comprehension (ICPC)

作者： Zejian Shi Yun Xiong Yao Zhang Zhijie Jiang Jinjing Zhao Lei Wang Shanshan Li Shanghai Key Laboratory of Data Science School of Computer Science Fudan University China Peng Cheng Laboratory Shenzhen China School of Computer National University of Defense Technology China National Key Laboratory of Science and Technology on Information System Security China

Contrastive learning has recently been applied to enhancing the BERT-based pre-trained models for code search. However, the existing end-to-end training mechanism cannot sufficiently utilize the pre-trained models due to the limitations on the number and variety of negative samples. In this paper, we propose MoCoCS, a multi-modal momentum contrastive learning method for code search, to improve the representations of query and code by constructing large-scale multi-modal negative samples. MoCoCS increases the number and the variety of negative samples through two optimizations: integrating multi-batch negative samples and constructing multi-modal negative samples. We first build momentum contrasts for query and code, which enables the construction of large-scale negative samples out of a mini-batch. Then, to incorporate multi-modal code information, we build multi-modal momentum contrasts by encoding the abstract syntax tree and the data flow graph with a momentum encoder. Experiments on CodeSearchNet with six programming languages demonstrate that our method can further improve the effectiveness of pre-trained models for code search.

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integration of Vehicle Target Detection and Recognition in Large-Scene SAR Images Based on YOLOv5

Integration of Vehicle Target Detection and Recognition in L...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiangdong Tan Xiangguang Leng Siqian Zhang Kefeng Ji State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology National University of Defense Technology Changsha China

In response to the problems existing in traditional SAR image target detection methods, such as complicated processes, long detection times, and poor detection effects in complex backgrounds, this paper proposes an integration of detection and recognition method based on deep learning for large-scene SAR images with vehicle targets. The paper introduces the issues of target identification through three stages of target detection, identification, and classification in traditional methods. To address these problems, this paper introduces a one-stage detection network based on YOLOv5 to construct a SAR image vehicle target detection and recognition algorithm. To verify the performance of the algorithm, this paper generated a dataset containing 10 different vehicle targets in large-scene SAR images and applied it to experiments. The results demonstrate that the algorithm has good performance and fast detection speed. The research results of this paper can provide important references for large-scale SAR image target detection.

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Research on Image Captioning Based on Vision-language Pre-trained Models

Research on Image Captioning Based on Vision-language Pre-tr...

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International Conference on Big Data and Information Analytics (BigDIA)

作者： Shiwei Zou Yuxiang Xie Jie Yan Yingmei Wei Xidao Luan Department of System Engineering National University of Defense Technology Hunan China Key Laboratory of Big Data Department of System Engineering National University of Defense Technology Hunan Changsha China Department of Computer Science Changsha University Hunan China

Image captioning is a vision-language task that targets at describing an image by generating a coherent sentence automatically. This technology allows computers to understand and describe images like humans, enabling further processing of images. It combines computer vision and natural language processing, which has broad applications. This paper investigates the use of vision-language pre-trained models for image captioning. In this article, an encoder-decoder hybrid model based on PVT and BERT is pre-trained on a large number of image-text pairs, possessing both understanding and generation capabilities. It consists of three components: 1) an image encoder and a text encoder to extract image and text features respectively; 2) a multi-modal encoder to align the two modalities; and 3) a text decoder to generate text descriptions. This paper focuses on enhancing the image encoder of the model, which is crucial for image captioning models as it extracts high-resolution image features. Reducing training time and computational costs can also improve the applicability of pre-trained models. Improvements are made to the original model by modifying the ViT model architecture of the image encoding module. A feature pyramid structure and a spatial reduction attention mechanism is introduced to extract high-resolution image features while reducing computational complexity and memory usage, thereby enhancing the universality of the model. The model adopts a pure Transformer architecture, discarding the convolutional structure, and achieves excellent performance.

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Dynamic Event-Triggered Consensus on Matrix-Weighted Networks: Leadless Case 42

Dynamic Event-Triggered Consensus on Matrix-Weighted Network...

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42nd Chinese Control Conference, CCC 2023

作者： Dou, Lintao Wei, Haoyu Huang, Jian Pan, Lulu Shao, Haibin Li, Dewei College of Intelligent Science National University of Defense Technology Changsha410003 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581543

This paper examines the event-triggered consensus of the multi-agent system on matrix-weighted networks, where the interdependencies among higher-dimensional states of neighboring agents are characterized by matrix-weighted edges in the network. Specifically, a novel distributed dynamic event-triggered coordination strategy is proposed for this category of generalized networks, in which an auxiliary system is employed for each agent to dynamically adjust the triggering threshold, which plays an essential role in guaranteeing that the triggering time sequence does not exhibit Zeno behavior. Distributed event-triggered control protocols are proposed to guarantee leaderless consensus for multi-agent systems on matrix-weighted networks, respectively. Remarkably, the spectrum of matrix-valued weights is crucial in event-triggered mechanism design for matrix-weighted networks, generalizing those results only applicable for scalar-weighted networks. The proposed approach allows each agent to broadcast and receive information only at its triggering instants. Finally, simulation examples are provided to demonstrate the theoretical results. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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Research on the Scattering Characteristics of Motion Modulated Ultra-long Chaff 4

Research on the Scattering Characteristics of Motion Modulat...

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4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021

作者： Lin, Gan Jianbing, Li Xin, Liu Xuesong, Wang College of Electronic Science and Technology National University of Defense Technology State Key Laboratory of Complex Electromagnetic Effects on Electronics and Information System Changsha China

ISBN: (纸本)9781733509619

In order to develop a new kind low-dimensional and efficient chaff interference mode, a discontinuous super-long chaff made of S-type glass fiber is proposed. In this paper, its kinematics and scattering characteristics in the thin atmosphere are emphatically studied. Simulation results show that long chaffs have stronger shape-maintaining ability and better interference effect than the traditional dipole chaffs under different polarization conditions. © 2021 Applied Computational Electromagnetics Society (ACES).

关键词： Finite element method

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A Game-Theoretic Approach for Satellites Beam Scheduling and Power Control in a Mega Hybrid Constellation Spectrum Sharing Scenario

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IEEE Internet of Things Journal 2025年

作者： Li, Wei Jia, Luliang Chen, Yingwu Chen, Quan Yan, Jungang Qi, Nan National University of Defense Technology College of Systems Engineering Changsha China Space Engineering University College of Space Information Beijing China National University of Defense Technology College of Aerospace Science and Engineering Changsha China Nanjing University of Aeronautics and Astronautics Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing210016 China

A mega hybrid constellation of Low Earth Orbit (LEO) and Geosynchronous Orbit (GEO) satellites represents a typical architecture for future space networks. However, the emergence of such large constellations exacerbates the shortage of spectrum resources. To address this issue, this paper investigates a hierarchical optimization method for beam scheduling and power control of LEO satellites, aiming to extend the available spectrum by sharing the downlink spectrum of GEO satellites. In the upper-layer optimization, a many-to-one matching game model is constructed to achieve optimal matching of LEO satellite beams and LEO Users (LU). A distributed beam matching learning algorithm (DBMLA) is designed to find a stable matching solution for the model, with the convergence of the algorithm theoretically proven. In the lower-layer optimization, an LEO beam power level optimization game model is developed for discrete LEO beam power levels. This model is demonstrated to be an exact potential game with at least one Nash Equilibrium (NE). To solve this NE, a dynamic power allocation logarithmic learning algorithm (DPALLA) is proposed. Simulation results verify that the proposed DBMLA-DPALLA hierarchical optimization scheme effectively balances convergence time and accuracy compared to traditional independent optimization strategies. By leveraging the combined effects of the two optimization strategies, it better mitigates the co-channel interference experienced by GEO satellites and improves the average network satisfaction of the LUs. © 2025 IEEE.

关键词： Cochannel interference

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Designed fabrication of active tumor targeting covalent organic framework nanotherapeutics via a simple post-synthetic strategy

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Nano Research 2023年第5期16卷 7085-7094页

作者： Yue Yu Guoxin Zhang Zhongping Li Jia Wang Yang Liu Rahul Bhardwaj Renu Wadhwa Yuki Nagao Mototada Shichiri Ran Gao Biomedical Research Institute National Institute of Advanced Industrial Science and Technology(AIST)Osaka 563-8577Japan AIST-INDIA DAILAB DBT-AIST International Center for Translational&Environmental Research(DAICENTER)AISTTsukubaIbaraki 305-8565Japan Beijing Engineering Research Center for Experimental Animal Models of Human Critical Diseases NHC Key Laboratory of Human Disease Comparative MedicineNational Human Diseases Animal Model Resource CenterInstitute of Laboratory Animal ScienceChinese Academy of Medical Sciences(CAMS)&Peking Union Medical CollageBeijing 100021China School of Materials Science Japan Advanced Institute of Science and TechnologyIshikawa 923-1211Japan Department of Chemical and Biomolecular Engineering Yonsei University50 Yonsei-roSeodaemun-guSeoul 120-749Republic of Korea Flexible 3D System Integration Laboratory SANKENOsaka UniversityOsaka 567-0047Japan

Developing agents that can accurately differentiate tumors from normal healthy tissues is of utmost importance for safe cancer *** targeting has been considered as an effective technique for tumor *** this work,we demonstrate a folate-functionalized nanoscale covalent organic framework(FATD nCOF)highly specific to cancer cells through active targeting of their enriched folate receptors(FRs).The FATD nCOF prepared by simple post-synthetic modification of the COF surface defeats disperses well in water and exhibits a high loading capacity for various anticancer *** biocompatible FATD nCOF is selectively internalized by FR-harboring cancer cells and consequently augments the efficacy of the loaded drug,Withaferin A(Wi-A),for targeted cancer cell *** biomolecular mechanism studies,Wi-A-loaded FATD(FATD@Wi-A)nanocomposites show remarkably a higher rate of apoptosis in FR-enriched cancer *** analyses of FR-positive and FR-negative tumor xenografts reveal enhanced selective antitumor activity of FATD@Wi-A *** together,the study findings suggest that FATD nCOF holds great promise for active targeting of tumors in *** simple yet effective technology might be valuable for creating new state-of-the-art COFs for chemical and biomedical applications.

关键词： covalent organic framework active targeting folate receptor drug delivery cancer therapy

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