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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： Wu, Mingmin Su, Guixin Zhang, Yongcheng Huang, Zhongqiang Sha, Ying College of Informatics Huazhong Agricultural University Wuhan China Key Laboratory of Smart Farming for Agricultural Animals Wuhan China Hubei Engineering Technology Research Center of Agricultural Big Data Wuhan China Engineering Research Center of Intelligent Technology for Agriculture Ministry of Education China

ISBN: (纸本)9782493814104

Chinese idioms on social media demand a nuanced understanding for correct usage. The Chinese idiom cloze test poses a unique challenge for machine reading comprehension due to the figurative meanings of idioms deviating from their literal interpretations, resulting in a semantic bias in models' comprehension of idioms. Furthermore, given that the figurative meanings of many idioms are similar, their use as suboptimal options can interfere with optimal selection. Despite achieving some success in the Chinese idiom cloze test, existing methods based on deep learning still struggle to comprehensively grasp idiom semantics due to the aforementioned issues. To tackle these challenges, we introduce a Refining Idioms Semantics Comprehension Framework (RISCF) to capture the comprehensive idioms semantics. Specifically, we propose a semantic sense contrastive learning module to enhance the representation of idiom semantics, diminishing the semantic bias between figurative and literal meanings of idioms. Meanwhile, we propose an interference-resistant cross-attention module to attenuate the interference of suboptimal options, which considers the interaction between the candidate idioms and the blank space in the context. Experimental results on the benchmark datasets demonstrate the effectiveness of our RISCF model, significantly outperforming state-of-the-art methods. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Semantics

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Social inequity of park accessibility in Taiyuan:highlighting the unfair layout of parks in second-tier cities of China and the relative role of contributors

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地球空间信息科学学报（英文版） 2024年第4期27卷 1118-1140页

作者： Jing He Fu Ren Jiaxin Dong Huihui Zhang Wenhao Yan Jiping Liu School of Resource and Environmental Sciences Wuhan UniversityWuhanChina School of Resource and Environmental Sciences Wuhan UniversityWuhanChina Key Laboratory of Geographic Information Systems Ministry of EducationWuhan UniversityWuhanChina School of Remote Sensing and Information Engineering Wuhan UniversityWuhanChina Guangdong Provincial Department of Natural Resources Land and Resources Technology CenterGuangzhouChina Research Center of Geospatial Big Data Application Chinese Academy of Surveying and MappingBeijingChina

The scarcity of public resources and environmental pollution caused by rapid urbanization highlight the practical significance of parks in ensuring the sustainable development of a ***,the social equity of parks warrants further *** paper proposes a fine-grained comprehensive evaluation framework that combines geographic accessibility models,geo-statistical analysis,and machine learning algorithms to explore social inequity in Taiyuan,*** this framework,gini coefficient and lorentz curve express spatial equality,accessibility shows spatial equity,and ridge regression model handles the interdependence of variables with different dimensions to quantify the relative effects of local participants on changes in park *** this basis,the imbalance between vulnerable groups and park supply is analyzed to further understand the core concept of social *** highlight serious spatial inequality in all three types of parks allocation of six urban areas,especially in commu-nity *** actual access level of people to parks is also stratified by their demographic and socioeconomic characteristics,revealing the social inequity in access to *** distribution is indeed not conducive to some social vulnerable groups,whose contradiction between supply and demand is highly prominent in urban-rural junctions and new urban *** paper also confirms the unfair layout of public facilities can be observed in second-tier cities of China by highlighting the social inequity of parks in *** findings of this work have profound implications for urban planning and sustainable development.

关键词： Parks social inequity spatial equality accessibility social vulnerable groups Taiyuan

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An Efficient Multilevel Threshold Image Segmentation Approach Based on Rafflesia Optimization Algorithm 1

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18th International Conference on intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2022

作者： Zhou, Jin-Liang Chu, Shu-Chuan Weng, Shaowei Zheng, Wei-Min College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China College of Science and Engineering Flinders University Adelaide Australia Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China

ISBN: (数字)9789819901050

ISBN: (纸本)9789819901043

Segmentation is an important step from image processing to analysis. The thresholding technique based on entropy has become one of the most commonly used techniques in this field. Among the many thresholding techniques based on entropy, the minimum cross-entropy threshold (MCET) has been dramatically developed. The key to multilevel MCET technology is quickly finding the optimal threshold point. MCET is a relatively time-consuming technique, so we use optimization techniques to search for optimal multilevel thresholds. Rafflesia optimization algorithm (ROA) is an optimization algorithm inspired by rafflesia growth theory to solve real-world multi-parameter optimization problems. In this paper, Rafflesia optimization algorithm, particle swarm optimization, gray wolf optimization, whale optimization algorithm, and multi-version optimizer are used to segment six images and the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and feature similarity index (FSIM) as evaluation metrics. The experimental results show that the ROA algorithm can achieve higher-quality image segmentation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image segmentation

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The Connections Between the Approximate Three-Way Concept Lattice and the Three-Way Approximate Concept Lattice 11th

The Connections Between the Approximate Three-Way Concept L...

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11th International Joint Conference on Rough Sets, IJCRS 2025

作者： Li, Mei-Zheng Li, Lei-Jun Mi, Ju-Sheng Hebei Normal University Hebei Shijiazhuang 050024 China Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics and Data Security Shijiazhuang 050024 China Hebei Key Laboratory of Computational Mathematics and Applications Shijiazhuang 050024 China

ISBN: (纸本)9783031927430

The approximate three-way concept lattice (ATWL), a novel model for conflict analysis, is an extension of classical concept lattice in formal concept analysis. However, little effort has been devoted on the connections between the ATWL and other existing three-way concept lattice models, which will be of great help to construct the ATWL efficiently. This paper reveals the connections between the ATWL and the three-way approximate concept lattice (TWAL) of an incomplete formal context from the viewpoints of concept fusion. Furthermore, the construct algorithm for ATWL based on TWAL is presented. The obtained results are finally demonstrated and verified by an example. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Approximate concept construction Concept lattice Incomplete formal context Three-way decisions

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T³Planner: Multi-Phase Planning Across Structure-Constrained Optical, IP, and Routing Topologies

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IEEE Journal on Selected Areas in Communications 2025年第5期43卷 1823-1839页

作者： Yijun Hao Shusen Yang Fang Li Yifan Zhang Cong Zhao Xuebin Ren Peng Zhao Chenren Xu Shibo Wang National Engineering Laboratory for Big Data Analytics Xi’an Jiaotong University Xi’an China National Engineering Laboratory for Big Data Analytics and the Ministry of Education Key Laboratory for Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an China School of Computer Science Peking University Beijing China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China National Engineering Laboratory for Big Data Analytics XiÃan Jiaotong University XiÃan China

Network topology planning is an essential multi-phase process to build and jointly optimize the multi-layer network topologies in wide-area networks (WANs). Most existing practices target single-phase/layer planning, and are incapable of satisfying all rigorous topological structure constraints (e.g., dual-homing rings) defined by network standards and operators, especially in large-scale networks. These significantly limit their usability and performance in production networks. We consider a general topology planning problem with typical structure constraints over three essential phases (greenfield, reconfiguration, and site expansion) and topological layers (optical, IP, and routing topologies). We present, T3Planner, a novel practical solver to this problem in production. Specifically, we develop a structure-driven encoder based on graph neural network (GNN) for concise structure encoding, and design a new learning framework with optical-centric layer compression/reconstruction and rule-aided reinforcement learning (RL) for fast convergence and high performance. Extensive experiments on nine real topologies demonstrate that T3Planner scales to large optical networks with hundreds of sites, saves 46.6% cost, and supports $3.12\times $ more demand when compared to related existing approaches.

关键词： Topology Network topology Planning IP networks Optical fiber networks Routing Optical fibers Optical feedback Production Graph neural networks

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Blockchain-Based Multi-Cloud data Storage System Disaster Recovery

Blockchain-Based Multi-Cloud Data Storage System Disaster Re...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Wang, Feiyu Zhou, Jian-Tao College of Computer Science Inner Mongolia University Inner Mongolia Hohhot China Engineering Research Center of Ecological Big Data Ministry of Education Natl. Loc. Jt. Eng. Research Center of Intelligent Information Processing Technology for Mongolian Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Inner Mongolia Key Laboratory of Social Computing and Data Processing Inner Mongolia Engineering Laboratory for Big Data Analysis Technology China

ISBN: (纸本)9798350337020

Cloud storage services have been used by most businesses and individual users. However, data loss, service interruptions and cyber attacks often lead to cloud storage services not being provided properly, and these incidents have caused financial losses to users. Second, traditional and single-cloud model disaster recovery services are no longer suitable for the current complex cloud storage systems. Therefore, a scheme to provide disaster recovery for cloud storage services in a multi-cloud storage environment is needed in real production. In this paper, we propose a disaster recovery scheme based on blockchain technology. The proposed scheme outlined in this study aims to address the issue of data availability within the cloud storage landscape. The proposed scheme achieves this goal by dividing data into hot and cold categories, verifying the integrity of copy data via blockchain technology, and utilizing blockchain networks to manage multi-cloud storage systems. Experimental findings demonstrate that the proposed scheme yields superior results in terms of computation and time overheads. © 2023 IEEE.

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STMAD:A Simple Multimodal Anomaly Detection for Thyroid Medical Information 17

STMAD:A Simple Multimodal Anomaly Detection for Thyroid Medi...

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17th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2024

作者： Xu, Wentong Fu, Chao Yu, Jing Si, Caifeng Li, Zuoyong Li, Chaochao Fan, Haoyi School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China First Affiliated Hospital of Zhengzhou University Department of Ultrasound Henan Zhengzhou450052 China School of Computer and Big Data Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou350121 China

ISBN: (纸本)9798331507398

Anomaly detection has been widely explored by training an out-of-distribution detector with only normal data. Medical image analysis, as a common tool, faces the challenge of how to further enhance the detection performance for thyroid cancer, especially with the application of various deep learning methods in the thyroid-related field. In this paper, we validate the effectiveness of sonographic feature descriptions (textual information) for thyroid cancer diagnosis. Building on this, we propose a simple multimodal self-supervised framework that leverages both textual and image modalities for thyroid cancer anomaly detection. Results on a private dataset demonstrate the effectiveness and superiority of our proposed method compared to advanced methods. © 2024 IEEE.

关键词： Self-supervised learning

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Temporal Transformation Network Based On Scale Sequences for Cloth-Changing Person Re-Identification in Video datasets 9

Temporal Transformation Network Based On Scale Sequences for...

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9th International Conference on Computer and Communications, ICCC 2023

作者： Zhu, Xiaoke Zhao, Bo Dong, Zhiwei Dong, Lingyun Li, Danyang School of Computer and Information Engineering Henan University Kaifeng China Henan University Henan Engineering Research Center of Intelligent Technology and Application China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China

ISBN: (纸本)9798350317251

This paper introduces the Temporal Transform Network based on Scale Sequences (TTS) for cloth-changing person re-identification in video datasets. The TTS network is designed to capture multi-scale temporal cues within video sequences. It accomplishes this by initially modeling short-term temporal cues between adjacent frames, followed by capturing long-term relationships between non-consecutive frames. In more detail, short-term temporal cues are modeled through parallel inflated convolutions with different time dilation rates, enabling the representation of pedestrian movement and appearance dynamics. Long-term relationships are effectively captured using a temporal self-attention model, mitigating challenges such as occlusion and noise within the video sequence. The TTS network outperforms existing methods across cloth-changing video ReID datasets such as CCVID. For instance, under general settings, our approach exhibits a 1.1% improvement in top-1 accuracy and a corresponding 1.1% increase in mAP compared to the baseline. In cloth-changing settings, we observe a 0.2% enhancement in top-1 accuracy and a notable 1.3% increase in mAP relative to the baseline. © 2023 IEEE.

关键词： Video recording

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Rockburst prediction using artificial intelligence techniques:A review

Rock Mechanics Bulletin

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Rock Mechanics Bulletin 2024年第3期3卷 1-13页

作者： Yu Zhang Kongyi Fang Manchao He Dongqiao Liu Junchao Wang Zhengjia Guo School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and ArchitectureBeijing100044China State Key Laboratory for Geomechanics and Deep Underground Engineering China University of Mining and TechnologyBeijing100083China Thomas Lord Department of Computer Science University of Southern CaliforniaLos Angeles90007CAUSA

Rockburst is a phenomenon where sudden,catastrophic failure of the rock mass occurs in underground deep regions or areas with high tectonic stress during the excavation *** disasters endanger the safety of people's lives and property,national energy security,and social interests,so it is very important to accurately predict *** rockburst prediction has not been able to find an effective prediction method,and the study of the rockburst mechanism is facing a *** the development of artificial intelligence(AI)techniques in recent years,more and more experts and scholars have begun to introduce AI techniques into the study of the rockburst *** previous research,several scholars have attempted to summarize the application of AI techniques in rockburst ***,these studies either are not specifically focused on reviews of the application of AI techniques in rockburst prediction,or they do not provide a comprehensive *** on the advantages of extensive interdisciplinary research and a deep understanding of AI techniques,this paper conducts a comprehensive review of rockburst prediction methods leveraging AI ***,pertinent definitions of rockburst and its associated hazards are ***,the applications of both traditional prediction methods and those rooted in AI techniques for rockburst prediction are summarized,with emphasis placed on the respective advantages and disadvantages of each ***,the strengths and weaknesses of prediction methods leveraging AI are summarized,alongside forecasting future research trends to address existing challenges,while simultaneously proposing directions for improvement to advance the field and meet emerging demands effectively.

关键词： Rockburst Rockburst prediction Artificial intelligence techniques

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Analysis and modeling for illuminance and signal-to-noise of smart traffic information system

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Journal of engineering and Applied Science 2022年第1期69卷 1-17页

作者： Chen, Yaoting Chen, Huanting School of Business Minnan Normal University Zhangzhou363000 China Analysis and Application for Business Big Data of Fujian Provincial Key Laboratory Zhangzhou363000 China College of Physics and Information Engineering Minnan Normal University Zhangzhou363000 China

The traffic lights using by light emitting diode (LED) are able to indicate and provide the information about the ambient. The signal transimission performance of traffic system is related to a variety of factors such as the signal-to-noise ratio (SNR), illuminance. Several factors are influence on illumiance and SNR, such as eatsink temperature and driver parameters. It has not been any substantial investigate on the operated effects of traffic light with sinusoidal waveform driver on illuminance and SNR. With the use of heatsink temperature and driver parameters of the LED source with sinusoidal waveform driver, prediction modeling for the illuminance and SNR of the mixed white LED sources with heatsink temperature, frequency, amplitude voltage, bias voltage and amplification factors are proposed in this paper to enhance the illuminance and SNR model of LED source inside smart traffic information system. The proposed model should carry out a series of calibration step for illuminance, heatsink temperature and driver parameters, which are easy for traffic designer and source system designers to follow in the traffic information system. The proposed model has been measured for the mixed white LED sources, with reasonably good agreements between theoretical and practical results. © 2022, The Author(s).

关键词： Signal to noise ratio

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