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20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023

作者： Liu, Minghao Han, Rui Jia, Fuqi Huang, Pei Ma, Feifei Zhang, Hantao Zhang, Jian State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Laboratory of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences Beijing China Stanford University StanfordCA United States Computer Science Department The University of Iowa Iowa CityIA52242 United States University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789819970216

Holey Latin square (HLS) is a special combinatorial design of interest to mathematicians and is helpful in the construction of many important structures in design theory. In this paper, we investigate the existence of HLSs satisfying the seven kinds of identities with automated reasoning techniques. We formulate this problem as propositional logic formulae. Since state-of-the-art SAT solvers have difficulty solving many HLS problems, we further propose a symmetry breaking method, called partially ordered HLS (POHLS), to eliminate isomorphic solutions. We have achieved the following goals through experimental evaluation. First, we have solved a dozen of open problems interested by mathematicians. Second, we identify the impact of different encodings. Third, we demonstrate the advantages of SAT solver over other FOL-based solvers. Fourth, we show that the proposed POHLS reduction can improve the efficiency of solving and find the complementarity between two types of symmetry breaking techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Model checking

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Grey-box Adversarial Attack on Communication in Multi-agent Reinforcement Learning 22

Grey-box Adversarial Attack on Communication in Multi-agent ...

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22nd International Conference on Autonomous Agents and Multiagent systems, AAMAS 2023

作者： Ma, Xiao Li, Wu-Jun National Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China

Although research on communication in multi-agent reinforcement learning (MARL) has achieved some progress, the vulnerability of the communication mechanism in MARL caused by adversarial communication messages generated by malicious agents has not been well investigated. Existing works about adversarial communication messages in MARL focus on the black-box scenario where the attacker cannot access any model information about the multi-agent system (MAS). But a more practical setting is the grey-box scenario where the attacker can access the model information about its controlled agent. To the best of our knowledge, there has not been any work investigating grey-box attacks on communication in MARL. In this paper, we propose the first grey-box attack method on communication in MARL, which is called victim-simulation based adversarial attack (VSA). At each timestep, the attacker simulates a victim attacked by other regular agents' communication messages and generates adversarial perturbations on its received communication messages. The aggregation of these perturbations is sent by the attacker to the regular agents through communication messages, which will induce non-optimal actions of the regular agents. Experimental results show that VSA can effectively degrade the performance of the MAS on Predator-Prey. The findings in this paper will make researchers aware of the grey-box attack in MARL. © 2023 International Foundation for Autonomous Agents and Multiagent systems (***). All rights reserved.

关键词： Reinforcement learning

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Automated object recognition in high-resolution optical remote sensing imagery

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National science Review 2023年第6期10卷 38-41页

作者： Yazhou Yao Tao Chen Hanbo Bi Xinhao Cai Gensheng Pei Guoye Yang Zhiyuan Yan Xian Sun Xing Xu Hai Zhang School of Computer Science and Engineering Nanjing University of Science and Technology Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology (NIST) Aerospace Information Research Institute Chinese Academy of Sciences Department of Computer Science and Technology Tsinghua University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely *** automated object detection and recognition of these images,which aims to automatically locate objects of interest in remote sensing images and distinguish their specific categories,is an important fundamental task in the *** provides an effective means for geospatial object monitoring in many social applications,such as intelligent transportation,urban planning,environmental monitoring and homeland security.

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Deep learning based water leakage detection for shield tunnel lining

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 887-898页

作者： Shichang LIU Xu XU Gwanggil JEON Junxin CHEN Ben-Guo HE College of Computer Science Sichuan UniversityChengdu 610065China School of Computer Science and Engineering Northeastern UniversityShenyang 110004China Department of Embedded Systems Engineering Incheon National UniversityIncheon 22012Korea School of Software Dalian University of TechnologyDalian 116621China Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines Northeastern UniversityShenyang 110819China

Shield tunnel lining is prone to water leakage,which may further bring about corrosion and structural damage to the walls,potentially leading to dangerous *** avoid tedious and inefficient manual inspection,many projects use artificial intelligence(Al)to detect cracks and water leakage.A novel method for water leakage inspection in shield tunnel lining that utilizes deep learning is introduced in this *** proposal includes a ConvNeXt-S backbone,deconvolutional-feature pyramid network(D-FPN),spatial attention module(SPAM).and a detection *** can extract representative features of leaking areas to aid inspection *** further improve the model's robustness,we innovatively use an inversed low-light enhancement method to convert normally illuminated images to low light ones and introduce them into the training *** experiments are performed,achieving the average precision(AP)score of 56.8%,which outperforms previous work by a margin of 5.7%.Visualization illustrations also support our method's practical effectiveness.

关键词： water leakage detection deep learning deconvolutional-feature pyramid spatial attention

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USee: Ultrasound-based Device-free Eye Movement Sensing 21

USee: Ultrasound-based Device-free Eye Movement Sensing

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21st Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2024

作者： Cheng, Wen Pang, Mingzhi Wan, Haoran Dong, Shichen Liu, Dongxu Wang, Wei State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Science Princeton University Princeton United States

ISBN: (纸本)9798331519186

Eye movements play a significant role in human-computer interaction and are widely recognized as an essential health indicator, making their detection both appealing and technically challenging. In this paper, we present a system named USEE that achieves high-precision capture of weak and aperiodic eye movements by utilizing fine-grained and ubiquitous ultrasound signals, capturing both blinking and more subtle saccades. We first identify signal changes associated with eye movements by capturing the unique impact of blinking. Further, we establish a pioneering relationship between the residuals from signal decomposition and subtle eye movements. Utilizing innovative signal processing architectures, we mitigate interference and effectively extract eye movement features. Subsequently, we employ one-dimensional convolutional operations in place of signal cross-correlation, designing filters for motion category identification and a lightweight convolutional neural network for saccade direction classification. This enables our system to serve as a foundational sensing layer for eye movement tracking, applicable across diverse applications. We implement USEE on both a research-purpose platform and a commodity Raspberry Pi. Extensive experimental results demonstrate the effectiveness of our system, achieving 91% accuracy in saccade recognition and 94% in blink detection. The system proves robust, even in challenging scenarios with strong interference, such as the presence of moving pedestrians. © 2024 IEEE.

关键词： Motion sensors

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LAMB: Label-Induced Mixed-Level Blending for Multimodal Multi-label Emotion Detection 19th

LAMB: Label-Induced Mixed-Level Blending for Multimodal Mul...

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19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Qian, Shuwei Guo, Ming Fan, Zhicheng Chen, Mingcai Wang, Chongjun State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Science and Technology Nanjing University Nanjing China

ISBN: (纸本)9783031545276

To better understand complex human emotions, there is growing interest in utilizing heterogeneous sensory data to detect multiple co-occurring emotions. However, existing studies have focused on extracting static information from each modality, while overlooking various interactions within and between modalities. Additionally, the label-to-modality and label-to-label dependencies still lack exploration. In this paper, we propose LAbel-induced Mixed-level Blending (LAMB) to address these challenges. Mixed-level blending leverages shallow but manifold self-attention and cross-attention encoders in parallel to model unimodal context dependency and cross-modal interaction simultaneously. This is in contrast to previous works either use one of them or cascade them successively, which ignores the diversity of interaction in multimodal data. LAMB also employs label-induced aggregation to allow different labels to attend to the most relevant blended tokens adaptively using a transformer-based decoder, which facilitates the exploration of label-to-modality dependency. Unlike common low-order strategies in multi-label learning, correlations among multiple labels can be learned by self-attention in label embedding space before being treated as queries. Comprehensive experiments demonstrate the effectiveness of our methods for multimodal multi-label emotion detection. © ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Emotion Recognition

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Testing Constraint Checking Implementations via Principled Metamorphic Transformations 31

Testing Constraint Checking Implementations via Principled M...

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31st IEEE International Conference on software Analysis, Evolution and Reengineering, SANER 2024

作者： Gao, Mingchen Wang, Huiyan Xu, Chang Nanjing University State Key Laboratory for Novel Software Technology Nanjing China Nanjing University Department of Computer Science and Technology Nanjing China

ISBN: (纸本)9798350330663

Constraint checking techniques are being widely used for ensuring the consistency of software artifacts during their development and evolution (e.g., detecting inconsistency in an application's running contexts or identifying rule violation in the code being developed). Typically, consistency constraints are formulated and checked upon the changes of software artifacts under checking. When any constraint is violated, an inconsistency is said to occur and then follow-up actions can be taken to remedy the problem. Currently, various constraint checking techniques have been proposed and implemented with sophisticated mechanisms for higher efficiency and scalability. However, these implementations could be far from being well tested due to their oracle problems, i.e., hardly able to tell what the checking result should be, given any software artifacts and their consistency constraints to check. In this paper, we leverage metamorphic testing and propose a family of metamorphic relations catered for testing constraint checking implementations. We dedicatedly design these relations by following the sensitivity principle via a fine-granularity control and the diversity principle via input-oriented transformations. Our experiments reported promising results (disclosing 80 % mutation bugs and five real bugs) without the need of any manual labeling. © 2024 IEEE.

关键词： software testing

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ENHANCING ROBUST FAIRNESS VIA CONFUSIONAL SPECTRAL REGULARIZATION

arXiv

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arXiv 2025年

作者： Jin, Gaojie Wu, Sihao Liu, Jiaxu Huang, Tianjin Mu, Ronghui The Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Beijing China Department of Computer Science University of Exeter Exeter United Kingdom Department of Computer Science University of Liverpool Liverpool United Kingdom

Recent research has highlighted a critical issue known as "robust fairness", where robust accuracy varies significantly across different classes, undermining the reliability of deep neural networks (DNNs). A common approach to address this has been to dynamically reweight classes during training, giving more weight to those with lower empirical robust performance. However, we find there is a divergence of class-wise robust performance between training set and testing set, which limits the effectiveness of these explicit reweighting methods, indicating the need for a principled alternative. In this work, we derive a robust generalization bound for the worst-class robust error within the PAC-Bayesian framework, accounting for unknown data distributions. Our analysis shows that the worst-class robust error is influenced by two main factors: the spectral norm of the empirical robust confusion matrix and the information embedded in the model and training set. While the latter has been extensively studied, we propose a novel regularization technique targeting the spectral norm of the robust confusion matrix to improve worst-class robust accuracy and enhance robust fairness. We validate our approach through comprehensive experiments on various datasets and models, demonstrating its effectiveness in enhancing robust fairness. Copyright © 2025, The Authors. All rights reserved.

关键词： Deep neural networks

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First-principles study of the dilute magnetic compounds Mg6MnO8 and Bi12MnO20

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Physical Review B 2024年第15期110卷 155204页

作者： Jianyong Sheng Aming Lin Yi-Yang Sun Mathematics and Science College State Key Laboratory of High Performance Ceramics and Superfine Microstructure Key Laboratory of System Software (Chinese Academy of Sciences) and State Key Laboratory of Computer Science

Dilute magnetic materials may find applications in spin-dependent applications such as spintronics and spin thermoelectrics. The conventional approach to realizing such materials is by doping a host material with transition-metal and rare-earth elements, which has been widely pursued in developing dilute magnetic semiconductors. However, such an approach could face issues such as solubility and inhomogeneity. Here, we study the dilute magnetic compounds (DMCs), which contain magnetic elements in a relatively small percentage and have the magnetic atoms occupying well-defined (ordered) lattice sites. The diluteness is thus guaranteed by enthalpy, instead of entropy as in the doping approach. By screening the inorganic crystal structure database, we identify two DMCs, Mg6MnO8 and Bi12MnO20. Mg6MnO8 has a fcc Mn lattice and octahedral coordination. Bi12MnO20 has a bcc Mn lattice and tetrahedral coordination. By using first-principles calculations, we calculated magnetic exchange interaction, magnon spectra, and electronic band structures of these materials. The Mn-Mn distance in Mg6MnO8 and Bi12MnO20 is 5.926 and 8.839 Å, respectively. The exchange interaction in Mg6MnO8 is 4–5 meV, while for Bi12MnO20 the largest distance renders the exchange interaction less than 1 meV. Mg6MnO8 holds promise for realizing the antiferromagnetic spin Seebeck effect. Bi12MnO20 has a band gap of 3.5 eV (ignoring the Mn 3d states in the band gap) and may be further doped for spintronic applications.

关键词： Exchange interaction Spintronics Magnetic insulators Magnetic semiconductors First-principles calculations Holstein-Primakoff method Spin wave theory

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User story clustering in agile development:a framework and an empirical study

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Frontiers of computer science 2023年第6期17卷 43-59页

作者： Bo YANG Xiuyin MA Chunhui WANG Haoran GUO Huai LIU Zhi JIN School of Information Science and Technology Beijing Forestry UniversityBeijing 100083China Engineering Research Center for Forestry Oriented Intelligent Information Processing National Forestry and Grassland AdministrationBeijing 100083China School of Information Science and Technology North China University of TechnologyBeijing 100144China College of Computer Science and Technology Inner Mongolia Normal UniversityHohhot 010020China Department of Computer Science and Software Engineering Swinburne University of TechnologyHawthorn VIC 3122Australia Key Laboratory of High Confidence Software Technologies(Peking University) Ministry of EducationBeijing 100871China Institute of Software School of Computer SciencePeking UniversityBeijing 100871China

Agile development aims at rapidly developing software while embracing the continuous evolution of user requirements along the whole development *** stories are the primary means of requirements collection and elicitation in the agile development.A project can involve a large amount of user stories,which should be clustered into different groups based on their functionality’s similarity for systematic requirements analysis,effective mapping to developed features,and efficient ***,the current user story clustering is mainly conducted in a manual manner,which is time-consuming and subjective to human *** this paper,we propose a novel approach for clustering the user stories automatically on the basis of natural language ***,the sentence patterns of each component in a user story are first analysed and determined such that the critical structure in the representative tasks can be automatically extracted based on the user story *** similarity of user stories is calculated,which can be used to generate the connected graph as the basis of automatic user story *** evaluate the approach based on thirteen datasets,compared against ten baseline *** results show that our clustering approach has higher accuracy,recall rate and F1-score than these *** is demonstrated that the proposed approach can significantly improve the efficacy of user story clustering and thus enhance the overall performance of agile *** study also highlights promising research directions for more accurate requirements elicitation.

关键词： user story agile development user story mapping clustering

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