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Cooperative differential games guidance laws for multiple attackers against an active defense target

Chinese Journal of Aeronautics 2022年第5期35卷 374-389页

作者： Fei LIU Xiwang DONG Qingdong LI Zhang REN School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang UniversityBeijing 100083China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100083China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education of ChinaChongqing UniversityChongqing 400044China

This paper is concerned with a scenario of multiple attackers trying to intercept a target with active *** types of agents are considered in the guidance:The multiple attackers,the target and the defender,where the attackers aim to pursuit the target from different directions and evade from the defender *** guidance engagement is formulated in the framework of a zero-sum two-person differential game between the two opposing teams,such that the measurements on the maneuver of the target or estimations on the defending strategy of the defender can be *** of the attackers resides in two aspects:redundant interception under the threat of the defender and the relative intercept geometry with the *** miss distances,the relative intercept angle errors and the costs of the agents are combined into a single performance index of the *** formulation enables a unitary approach to the design of guidance laws for the *** minimize the control efforts and miss distances for the attackers,an optimization method is proposed to find the best anticipated miss distances to the defender under the constraint that the defender is endowed with a capture *** simulations with two cases are conducted to illustrate the effectiveness of the proposed cooperative guidance law.

关键词： Active defense Cooperative guidance Differential games Minimum effort optimization Relative intercept angle

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Adaptive Multi-Updating Strategy Based Particle Swarm Optimization

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intelligent Automation & Soft computing 2023年第9期37卷 2783-2807页

作者： Dongping Tian Bingchun Li Jing Liu Chen Liu Ling Yuan Zhongzhi Shi School of Computer Science and Technology Kashi UniversityKashi844006China Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing100190China

Particle swarm optimization(PSO)is a stochastic computation tech-nique that has become an increasingly important branch of swarm intelligence ***,like other evolutionary algorithms,PSO also suffers from premature convergence and entrapment into local optima in dealing with complex multimodal *** this paper puts forward an adaptive multi-updating strategy based particle swarm optimization(abbreviated as AMS-PSO).To start with,the chaotic sequence is employed to generate high-quality initial particles to accelerate the convergence rate of the ***,according to the current iteration,different update schemes are used to regulate the particle search process at different evolution *** be specific,two different sets of velocity update strategies are utilized to enhance the exploration ability in the early evolution stage while the other two sets of velocity update schemes are applied to improve the exploitation capability in the later evolution *** by the unequal weightage of acceleration coefficients is used to guide the search for the global worst particle to enhance the swarm *** addition,an auxiliary update strategy is exclusively leveraged to the global best particle for the purpose of ensuring the convergence of the PSO ***,extensive experiments on two sets of well-known benchmark functions bear out that AMS-PSO outperforms several state-of-the-art PSOs in terms of solution accuracy and convergence rate.

关键词： Particle swarm optimization local optima acceleration coefficients swarm diversity premature convergence

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A Mutual Information-Based Assessment of Reverse Engineering on Rewards of Reinforcement Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1089-1100页

作者： Chen, Tong Liu, Jiqiang Baker, Thar Wu, Yalun Xiang, Yingxiao Li, Yike Niu, Wenjia Tong, Endong Zomaya, Albert Y. Beijing Jiaotong University Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing100044 China College of Computing and Informatics University of Sharjah Department of Computer Science Sharjah27272 United Arab Emirates The University of Sydney School of Computer Science Sydney2006 Australia

Rewards are critical hyperparameters in reinforcement learning (RL), since in most cases different reward values will lead to greatly different performance. Due to their commercial value, RL rewards become the target of reverse engineering by the inverse reinforcement learning (IRL) algorithm family. Existing efforts typically utilize two metrics to measure the IRL performance: the expected value difference (EVD) and the mean reward loss (MRL). Unfortunately, in some cases, EVD and MRL can give completely opposite results, due to MRL focusing on whole state-space rewards, while EVD only considering partly sampled rewards. Such situation naturally rises to one fundamental question: whether current metrics and assessment are sufficient and accurate for more general use. Thus, in this article, based on the metric called normalized mutual information of reward clusters (C-NMI), we propose a novel IRL assessment;we aim to fill this research gap by considering a middle-granularity state space between the entire state space and the specific sampling space. We utilize the agglomerative nesting algorithm (AGNES) to control dynamical C-NMI computing via a fourth-order tensor model with injected manipulated trajectories. With such a model, we can uniformly capture different-dimension values of MRL, EVD, and C-NMI, and perform more comprehensive and accurate assessment and analyses. Extensive experiments on several mainstream IRLs are experimented in object world, hence revealing that the assessing accuracy of our method increases 110.13% and 116.59%, respectively, when compared with the EVD and MRL. Meanwhile, C-NMI is more robust than EVD and MRL under different demonstrations. © 2020 IEEE.

关键词： Reverse engineering

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Multiscale Temporal-Convolution and Attention Improved Neural Network for Biased Mental State Recognition 17th

Multiscale Temporal-Convolution and Attention Improved Neur...

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17th International Conference on Brain Informatics, BI 2024

作者： Zuo, Guoyu Xiao, Erjun Zhang, Tielin Beijing Key Laboratory of Computing Intelligence and Intelligent Systems Beijing University of Technology Beijing100124 China Center for Excellence in Brain Science and Intelligence Technology University of Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9789819632930

Accurate detection of mental state is vital for sleep assessment and anesthesia monitoring. However, challenges exist, including 1) limited data sources caused by few modalities, few channels, biased sample distribution, or large individual differences;2) multiscale dynamic feature of mental state signals, containing complex and dynamic fluctuations. In this paper, we proposed a multiscale temporal convolution and attention improved neural network (MTA-NN) to handle these two challenges, including: a preprocessing method using a clustering-first and label-generation approach for data augmentation involves filtering the production samples to mitigate the impact of noise on model performance;multiscale temporal-convolution module for detecting different scales of temporal and frequency features;an attention module for decoding key features in different spatial and temporal channels, and for setting the importance of historical dependencies;a full-connection layer is designed to recognize different sleep stage. The proposed MTA-NN is then verified in three typical sleep-state recognition tasks, including SleepEDF-20, SleepEDF-78, and ISRUC3. Compared to some state-of-the-art algorithms, the proposed MTA-NN achieves higher performance. Further ablation experiments show the necessary and importance of these designed sub modules in MTA-NN. We consider the same algorithm can also be extended to further similar mental state recognition tasks such as anesthesia monitoring. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Anesthesiology

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Thermal engineering in ALD-grown ZGO thin films for high-performance photodetectors

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材料科学技术（英文版） 2025年第6期209卷 19-26页

作者： Si-Tong Ding Yu-Chang Chen Cai-Yu Shi Lei Shen Qiu-Jun Yu Lang-Xi Ou Ze-Yu Gu Na Chen Ting-Yun Wang David Wei Zhang Hong-Liang Lu State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & SystemsSchool of MicroelectronicsFudan UniversityShanghai 200433China Zhangjiang Fudan International Innovation Center Shanghai 201203China National Integrated Circuit Innovation Center Shanghai 201203China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai Institute Communication and Data ScienceShanghai UniversityShanghai 200444China State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & SystemsSchool of MicroelectronicsFudan UniversityShanghai 200433China Zhangjiang Fudan International Innovation Center Shanghai 201203China National Integrated Circuit Innovation Center Shanghai 201203China Jiashan Fudan Institute Jiaxing 314100China

Doped gallium oxide-based thin films are a class of wide-band semiconductor materials with the ad-vantages of chemically stable,tunable bandgap,and offer the benefit of ultraviolet *** order to obtain photodetectors(PDs)with superior response,higher demands are placed on the quality of growth and processing of doped *** this work,Zn-doped ternary metal oxide ZnGaO(ZGO)thin films were grown using the atomic layer deposition technique and annealed at different temperatures under an oxy-gen *** results showed that the high-quality ZGO films with good uniformity,high visible light transmittance,low roughness,and significant reduction of oxygen vacancies were obtained after ***,metal-semiconductor-metal PDs were prepared based on the studied ZGO *** responsivity(R),detectivity(D*),and external quantum efficiency(EQE)of the optimized device are 61.8 A W-1,1.2 x 1012 Jones,and 255.9％,*** to the unannealed device,the an-nealed ZGO PD achieves a maximum 309-fold increase in *** thermal engineering work may provide a strong reference for the development of low-cost,large-area,high-performance ultraviolet *** it also broadens the application of ternary metal oxides in optoelectronics.

关键词： Atomic layer deposition Oxygen annealing ZGO thin films Photodetector Ultraviolet detection

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Are LLMs Aware that Some Questions are not Open-ended?

Are LLMs Aware that Some Questions are not Open-ended?

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Yang, Dongjie Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China

ISBN: (纸本)9798891761681

Large Language Models (LLMs) have shown the impressive capability of answering questions in a wide range of scenarios. However, when LLMs face different types of questions, it is worth exploring whether LLMs are aware that some questions have limited answers and need to respond more deterministically but some do not. We refer to this as question awareness of LLMs. The lack of question awareness in LLMs leads to two phenomena that LLMs are: (1) too casual to answer non-open-ended questions or (2) too boring to answer open-ended questions. In this paper, we first evaluate the question awareness in LLMs. The experimental results show that LLMs have the issues of lacking awareness of questions in certain domains, e.g. factual knowledge, resulting in hallucinations during the generation. To mitigate these, we propose a method called Question Awareness Temperature Sampling (QuATS). This method enhances the question awareness of LLMs by adaptively adjusting the output distributions based on question features. The automatic adjustment in QuATS eliminates the need for manual temperature tuning in text generation and consistently improves model performance in various benchmarks. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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A Survey of SDN data Plane Attacks and Defense Strategies 23

A Survey of SDN Data Plane Attacks and Defense Strategies

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2nd International Conference on Networks, Communications and Information Technology, CNCIT 2023

作者： Zhang, Wenxiu Jing, Shan Zhao, Chuan School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network-based Intelligent Computing Jinan China Quan Cheng Laboratory Jinan China

ISBN: (纸本)9798400700620

The Software-Defined Networking (SDN) paradigm proposes the decoupling of control and data planes and a centralized software-oriented management approach based on a central controller, easing the development of new applications and services, and fundamentally changed the network architecture. This paper introduces the present situation of SDN and its data plane research, but as with traditional networks, there are multiple vulnerabilities in the security aspects of the SDN architecture, which can be used to perform malicious operations with these vulnerabilities to affect the network and its services. In this paper, the SDN data plane security issues are mainly discussed, the attacks on the SDN data plane are summarized, and the existing attack defense policies are summarized and compared. Finally, the research direction of SDN data plane security is proposed and the whole paper is summarized. CCS CONCEPTS •Security and privacy •Network security •Security protocols © 2023 ACM.

关键词： Information management

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DiMSOD: A Diffusion-Based Framework for Multi-Modal Salient Object Detection 39

DiMSOD: A Diffusion-Based Framework for Multi-Modal Salient ...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhang, Shuo Huang, Jiaming Tang, Wenbing Wu, Yan Hu, Terrence Xu, Xiaogang Liu, Jing Shanghai Key Laboratory of Trustworthy Computing East China Normal University China Technology Center Huolala China College of Computing and Data Science Nanyang Technological University Singapore The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)157735897X

Multi-modal salient object detection (SOD) through the integration of additional data such as depth or thermal information has become a significant task in computer vision during recent years. Traditionally, the challenges of identifying salient objects in RGB, RGB-D (Depth), and RGBT (Thermal) images are tackled separately. However, without intricate cross-modal fusion strategies, such approaches struggle to effectively integrate multi-modal information, often resulting in poorly defined object edges or overconfident inaccurate predictions. Recent studies have shown that designing a unified end-to-end framework to handle all three types of SOD tasks simultaneously is both necessary and difficult. To address this need, we propose a novel approach that treats multi-modal SOD as a conditional mask generation task utilizing diffusion models. We introduce DiMSOD, which enables the concurrent use of local (depth maps, thermal maps) and global controls (original images) within a unified model for progressive denoising and refined prediction. DiMSOD only requires fine-tuning newly introduced modules on a pretrained stable diffusion trained on RGB images, which not only reduces fine-tuning costs for practical applications but also enhances the integration of multi-modal conditional controls. Specifically, we have developed modules including SOD-ControlNet, Feature Adaptive Network (FAN), and Feature Injection Attention Network (FIAN) to enhance the model's performance. Extensive experiments demonstrate that DiMSOD efficiently detects salient objects across RGB, RGB-D, and RGB-T datasets, achieving superior performance compared to previous well-established methods. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Object detection

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Knowledge-Guided Cross-Topic Visual Question Generation 30

Knowledge-Guided Cross-Topic Visual Question Generation

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Liu, Hongfei Wang, Guohua Xie, Jiayuan Chen, Jiali Fang, Wenhao Cai, Yi School of Software Engineering South China University of Technology China Key Laboratory of Big Data and Intelligent Robot South China University of Technology Ministry of Education China Department of Computing The Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9782493814104

Visual question generation (VQG) task aims to generate high-quality questions based on the input image. Current methods primarily focus on generating questions containing specified content utilizing answers or question types as constraints. However, these constraints make it challenging to control the topic of generated questions (e.g., conversation or test subject topics) for various applications. Thus, it is necessary to utilize topics as constraints to guide question generation. Considering that there are many topics and it is almost impossible for human annotations to cover them, we propose the cross-topic learning VQG (CTL-VQG) task, which aims to generate questions related to unseen topics in cross-topic scenarios. In this paper, we propose a knowledge-guided cross-topic visual question generation (KC-VQG) model to extract unseen topic-related information for question generation. Specifically, an image-topic feature extractor is introduced in our model to extract topic-related intuitive visual features;an image-topic knowledge extractor is used to extract and select the most appropriate topic-related implicit knowledge from large language models for generating questions. Extensive experiments show that our model outperforms baselines and can effectively generate unseen topic-related questions in cross-topic scenarios. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： data mining

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BFP-Net: Boundary Feature Pyramid for Medical Image Segmentation

BFP-Net: Boundary Feature Pyramid for Medical Image Segmenta...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Min, Shiquan Zhang, Xiang Wang, Shunfang Yunnan University School of Information Science and Engineering Kunming650504 China Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Kunming650504 China

ISBN: (纸本)9798350337488

In this paper, we propose a novel method, namely boundary feature pyramid network (BFP-Net), which can effectively segment targets with blurred boundaries. Specifically, we first propose a global feature fusion module (GFFM) at the top of BFP-Net to fuse feature maps within different scales. It can learn more global region localization of the target and help the learning of boundaries more effectively. Then, we propose a series of boundary enhancement modules (BEMs) at the decoder to effectively extract and integrate boundary information during the upsampling process, thereby enhancing the ability to capture fine details (such as the boundaries). Furthermore, we introduce a boundary-enhanced composite loss function to effectively segment both the regions and their boundaries within different scales. Finally, extensive experiments on two widely-used datasets demonstrate that BFP-Net is more effective in fusing contextual information and guiding feature map boundaries compared to previous competitive methods. © 2023 IEEE.

关键词： Boundary enhancement Feature pyramid Global feature fusion Medical images Segmentation

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