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40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Wang, Xi Jin, Ruochun Huang, Wanrong Tang, Yuhua Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China College of Computer Science and Technology Department of Intelligent Data Science National University of Defense Technology Changsha China

ISBN: (纸本)9798350317152

Functional dependencies (FDs) form a valuable ingredient for various data management tasks. However, existing methods can hardly discover practical and interpretable FDs, especially in large noisy real-life datasets. This paper studies the problem of discovering meaningful functional dependencies (FDms) that utilize support and error parameters to capture interesting dependencies in such datasets and proposes an efficient discovery algorithm called FDM?. In order to scale with large datasets, FDM ? employs an efficient sampling method with accuracy guarantees to capture the differences between tuple pairs and to quantify the connection between support/error of dependencies on samples and those on the entire dataset. Moreover, it adopts a clustering-based correlated attributes extraction to divide the exponentially large search space into multiple small sub-spaces and proposes an easy-first traversal strategy with covariance-based guidance that quickly detects candidate dependencies and validates them. Additionally, we prove a covariance lower bound as an additional pruning criterion to reduce the search space. Extensive experiments on real-life and synthetic datasets demonstrate that FDM ? is 14 times faster than existing discovery algorithms on average, up to 31 times, and scales to larger datasets with the least memory cost. © 2024 IEEE.

关键词： Large datasets

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Machine learning design of 400 MPa grade biodegradable Zn-Mn based alloys with appropriate corrosion rates

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International Journal of Minerals,Metallurgy and Materials 2024年第12期31卷 2727-2736页

作者： Wangzhang Chen Wei Gou Yageng Li Xiangmin Li Meng Li Jianxin Hou Xiaotong Zhang Zhangzhi Shi Luning Wang Beijing Advanced Innovation Center for Materials Genome Engineering State Key Laboratory for Advanced Metals and MaterialsSchool of Materials Science and EngineeringUniversity of Science and Technology BeijingBeijing 100083China Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China School of Computer and Communication Engineering Shunde Innovation SchoolUniversity of Science and Technology BeijingShunde 528399China

The commonly used trial-and-error method of biodegradable Zn alloys is costly and *** this study,based on the self-built database of biodegradable Zn alloys,two machine learning models are established by the first time to predict the ultimate tensile strength(UTS)and immersion corrosion rate(CR)of biodegradable Zn alloys.A real-time visualization interface has been established to design Zn-Mn based alloys;a representative alloy is *** tensile mechanical properties and immersion corrosion rate tests,its UTS reaches 420 MPa,and the prediction error is only 0.95%.CR is 73μm/a and the prediction error is 5.5%,which elevates 50 MPa grade of UTS and owns appropriate corrosion ***,influences of the selected features on UTS and CR are discussed in *** combined application of UTS and CR model provides a new strategy for synergistically regulating comprehens-ive properties of biodegradable Zn alloys.

关键词： Zn alloys machine learning alloy design performance prediction

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Remission of iron overload in adipose tissue of obese mice by fatty acid-modified polyoxovanadates

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Rare Metals 2025年第1期44卷 461-471页

作者： Kun Chen Yu-Rong Qin Sheng-Qiu Liu Rou-Ling Chen South China Advanced Institute for Soft Matter Science and Technology School of Emergent Soft MatterSouth China University of TechnologyGuangzhou 510641China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing South China University of TechnologyGuangzhou 510641China Guangdong Provincial Key Laboratory of Functional and Intelligent Hybrid Materials and Devices South China University of TechnologyGuangzhou 510641China Department of Computer Science City University of Hong KongHong Kong 999077China

Iron overload has been evidenced to contribute to obesity-associated metabolic disorders,including insulin *** to reduce iron levels might help manage the metabolic complications associated with ***,it is demonstrated that the specific accumulation of oleic acid-modified polyoxovanadates(OPOVs)in adipose tissue leads to the reduction of iron concentrations in adipocytes in mice fed with a high-fat diet(HFD).Conjugation of oleic acids to polyoxovanadates enables tissue-specific depletion of iron from white adipose tissue(WAT)by OPOVs,protecting mice from HFD-induced obesity and obesity-associated metabolic *** tolerance and insulin sensitivity are improved in OPOV-treated mice,which demonstrates that the OPOV-induced iron depletion can reverse the metabolic degeneration caused by HFD-induced ***,a decrease in expression of the marker genes of iron overload suggests the participation of OPOVs in maintaining iron homeostasis and a potential medical application of vanadium clusters in targeting the iron overload caused by *** findings underscore the potential of vanadate-based clusters tailored to address the complex interplay between iron metabolism and metabolic health.

关键词： Polyoxovanadates Lipophilic conjugation Obesity Iron overload Insulin resistance

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Robust-MSA: Understanding the Impact of Modality Noise on Multimodal Sentiment Analysis 37

Robust-MSA: Understanding the Impact of Modality Noise on Mu...

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37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Mao, Huisheng Zhang, Baozheng Xu, Hua Yuan, Ziqi Liu, Yihe State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing100084 China Beijing100084 China School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang050018 China

ISBN: (纸本)9781577358800

Improving model robustness against potential modality noise, as an essential step for adapting multimodal models to real-world applications, has received increasing attention among researchers. For Multimodal Sentiment Analysis (MSA), there is also a debate on whether multimodal models are more effective against noisy features than unimodal ones. Stressing on intuitive illustration and in-depth analysis of these concerns, we present Robust-MSA, an interactive platform that visualizes the impact of modality noise as well as simple defence methods to help researchers know better about how their models perform with imperfect real-world data. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Sentiment analysis

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Error-Robust Retrieval for Chinese Spelling Check 30

Error-Robust Retrieval for Chinese Spelling Check

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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： Yin, Xunjian Hu, Xinyu Jiang, Jin Wan, Xiaojun Wangxuan Institute of Computer Technology Peking University Center for Data Science State Key Laboratory of Media Convergence Production Technology and Systems China

ISBN: (纸本)9782493814104

Chinese Spelling Check (CSC) aims to detect and correct error tokens in Chinese contexts, which has a wide range of applications. However, it is confronted with the challenges of insufficient annotated data and the issue that previous methods may actually not fully leverage the existing datasets. In this paper, we introduce our plug-and-play retrieval method with error-robust information for Chinese Spelling Check (RERIC), which can be directly applied to existing CSC models. The datastore for retrieval is built completely based on the training data, with elaborate designs according to the characteristics of CSC. Specifically, we employ multimodal representations that fuse phonetic, morphologic, and contextual information in the calculation of query and key during retrieval to enhance robustness against potential errors. Furthermore, in order to better judge the retrieved candidates, the n-gram surrounding the token to be checked is regarded as the value and utilized for specific reranking. The experiment results on the SIGHAN benchmarks demonstrate that our proposed method achieves substantial improvements over existing work. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Errors

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Radiative cooling for passive thermal management towards sustainable carbon neutrality

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National science Review 2023年第1期10卷 87-97页

作者： Jun Liang Jiawei Wu Jun Guo Huagen Li Xianjun Zhou Sheng Liang Cheng-Wei Qiu Guangming Tao Wuhan National Laboratory for Optoelectronics and Optics Valley Laboratory Huazhong University of Science and Technology Department of Electrical and Computer Engineering National University of Singapore MOE Key Laboratory of Thermo-Fluid Science and Engineering School of Energy and Power Engineering Xi'an Jiaotong University Key Laboratory of Education Ministry on Luminescence and Optical Information Technology National Physical Experiment Teaching Demonstration CenterDepartment of PhysicsSchool of Physical Science and Engineering Beijing Jiaotong University State Key Laboratory of Material Processing and Die &Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology

Photonic structures at the wavelength scale offer innovative energy solutions for a wide range of applications,from high-efficiency photovoltaics to passive cooling,thus reshaping the global energy *** cooling based on structural and material design presents new opportunities for sustainable carbon neutrality as a zero-energy,ecologically friendly cooling *** this review,in addition to introducing the fundamentals of the basic theory of radiative cooling technology,typical radiative cooling materials alongside their cooling effects over recent years are summarized and the current research status of radiative cooling materials is outlined and ***,technical challenges and potential advancements for radiative cooling are forecast with an outline of future application scenarios and development *** the future,radiative cooling is expected to make a significant contribution to global energy saving and emission reduction.

关键词： photonic structures radiative cooling energy saving and emission reduction carbon neutrality

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Improving the Interpretability through Maximizing Mutual Information for EEG Emotion Recognition

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IEEE Transactions on Affective Computing 2024年第2期16卷 744-757页

作者： Yang, Hua Philip Chen, C.L. Chen, Bianna Zhang, Tong North Carolina State University Department of Computer Science United States South China University of Technology Guangdong Provincial Key Laboratory of AI Large Model and Intelligent Cognition The School of Computer Science and Engineering Guangzhou510006 China Pazhou Lab Guangzhou510335 China Engineering Research Center The Ministry of Education on Health Intelligent Perception and Paralleled Digital-Human Guangzhou China

Trustworthy Graph Neural Networks (GNNs) for EEG emotion recognition should identify emotions accurately and elucidate corresponding rationales. Current GNNs have achieved notable performance by dynamically modeling emotional connections between EEG channels. However, these GNNs lack interpretability due to the absence of explicit rationale behind their predictions. This paper conducts a comprehensive identification of important EEG channels to enhance the interpretability of EEG emotion recognition from the perspective of mutual information. Specifically, an Adjacency-Explainable Graph Neural Network (AEG) for ante-hoc interpretability is proposed to capture genuine EEG emotional connections, which gives a theoretical guarantee to remove spurious connections. Moreover, a Channel-wise Adaptive Class Activation Mapping Explainer (CACA) for post-hoc interpretability is developed to locate the EEG channels that contribute most to predictions. Experimental results on three datasets, i.e., SEED, SEED-IV, and DREAMER, prove that imbuing training processes with enhanced interpretability ensures significant performance improvements in emotion recognition. Quantitative comparisons of post-hoc interpretability also demonstrate the superiority of CACA. Furthermore, this paper illustrates two potential applications of the proposed methodologies, showing their broader utility and significance. © 2010-2012 IEEE.

关键词： Graph neural networks

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A practical PID variable stiffness control and its enhancement for compliant force-tracking interactions with unknown environments

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science China(Technological sciences) 2023年第10期66卷 2882-2896页

作者： ZHANG Xin ZHOU Hao LIU JinGuo JU ZhaoJie LENG YuQuan YANG ChenGuang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China School of Computing University of PortsmouthPortsmouth PO13HEUK Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhen 518055China Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510640China

Compliant interaction control is a key technology for robots performing contact-rich manipulation *** design of the compliant controller needs to consider the robot hardware because complex control algorithms may not be compatible with the hardware performance,especially for some industrial robots with low bandwidth *** paper focuses on effective and easy-to-use compliant control algorithms for position/velocity-controlled *** by human arm stiffness adaptation behavior,a novel variable target stiffness(NVTS)admittance control strategy is proposed for adaptive force tracking,in which a proportional integral derivative(PID)variable stiffness law is designed to update the stiffness coefficient of the admittance function by the force and position ***,its stability and force-tracking capability are theoretically *** addition,an impact compensator(Impc)is integrated into the NVTS controller to enhance its disturbance-suppression capability when the robot is subjected to strong vibration disturbances in complicated surface polishing *** proposed controllers are validated through four groups of experimental tests using different robots and the corresponding results demonstrate that they have high-accuracy tracking capability and strong adaptability in unknown environments.

关键词： compliant interaction control force tracking PID variable stiffness impact compensator unknown environments

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Network synchronizability enhancement viaadding antagonistic interactions

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Autonomous intelligent systems 2024年第1期4卷 1-7页

作者： Yue Song Xiaoqin Liu Dingmei Wang Pengfei Gao Mengqi Xue Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai201210China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai201210China Department of Control Science and Engineering Tongji UniversityShanghai201210China National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji UniversityShanghai201210China Lanzhou Longneng Electric Power Technology Company Lanzhou730070China

We discover a“less-is-more”effect that adding local antagonistic interactions(negative edge weights)can enhance the overall synchronizability of a dynamical network *** explain this seemingly counterintuitive phenomenon,a condition is established to identify those edges the weight reduction of which improves the synchronizability index of the underlying *** further reveal that this condition can be interpreted from the perspective of resistance distance and network community *** obtained result is also verified via numerical experiments on a 14-node network and a 118-node *** brings new thoughts and inspirations to the future directions of optimal network design problems.

关键词： Synchronizability Complex network Laplacian matrix Antagonistic interaction

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Distance-Based Subset Selection With a Knee Point for Multi-Objective Optimization 13

Distance-Based Subset Selection With a Knee Point for Multi-...

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Joint 13th International Conference on Soft Computing and intelligent systems and 25th International Symposium on Advanced intelligent systems, SCIS and ISIS 2024

作者： Pang, Lie Meng 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

ISBN: (纸本)9798350373332

Recently, the use of an unbounded external archive in the design of evolutionary multi-objective optimization (EMO) algorithms has received increasing attention. An important component in the use of an unbounded external archive is its subset selection method used to select a pre-specified number of solutions from the archive. One of the most commonly used subset selection method is distance-based subset selection (DSS) since it is very easy to calculate and can easily scale to many-objective optimization. However, the DSS's selection mechanism usually lead to a small hypervolume value for the selected subset even when the optimal subset with respect to the minimum distance among the selected solutions is obtained. In this paper, we propose a modification to the DSS algorithm by selecting a knee point as the first solution. The knee point is often a solution of interest to decision makers in the absence of preference information. Experimental results show that the inclusion of a knee point generally has a positive effect on improving the hypervolume value of the selected subset. © 2024 IEEE.

关键词： Optimization algorithms

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