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8th IEEE International Conference on Computer and Communications, ICCC 2022

作者： Li, Xiang Zeng, Zhi Wu, Mingmin Huang, Zhongqiang Sha, Ying Shi, Lei 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)9781665450515

Various forms of social interactions are often char-acterized by toxic or offensive words that can be collectively referred to as offensive languages, which has become a unique linguistic phenomenon in social media platforms. How to detect and identify these offensive languages in social media platforms has become one of the important research in the field of natural language processing. Existing methods utilize machine learning algorithms or text representation models based on deep learning to learn the features of offensive languages and identify them, which have achieved good performances. However, traditional machine learning-based methods mainly rely on keyword identi-fication and blocking, deep learning-based methods do not ade-quately explore the fused deep semantic features of the content by combining word-level embeddings and sentence-level deep semantic feature representations of sentences, which cannot ef-fectively identify offensive languages that do not contain common offensive words but indicate offensive meanings. In this research, we propose a novel offensive language identification model based on deep semantic feature fusion, which uses the pre-trained model Bert to obtain word-level embedding representations of offensive languages, and then integrates the RCNN that combines with the attention mechanism to extract the fused deep semantic feature representations of offensive languages, and label encoder and offensive predictor to improve the identification accuracy and generalization ability of the model so that the performances of the model do not rely on the offensive language lexicon entirely and can identify offensive languages that do not contain common offensive words but indicate offensive meanings. Experimental results on Wikipedia and Twitter comment datasets show that our proposed model can better understand the context and discover potential offensive meanings, and outperforms existing methods. © 2022 IEEE.

关键词： Embeddings

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LLM App Store Analysis: A Vision and Roadmap

arXiv

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arXiv 2024年

作者： Zhao, Yanjie Hou, Xinyi Wang, Shenao Wang, Haoyu Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology China Huazhong University of Science and Technology Wuhan China

The rapid growth and popularity of large language model (LLM) app stores have created new opportunities and challenges for researchers, developers, users, and app store managers. As the LLM app ecosystem continues to evolve, it is crucial to understand the current landscape and identify potential areas for future research and development. This paper presents a forward-looking analysis of LLM app stores, focusing on key aspects such as data mining, security risk identification, development assistance, and market dynamics. Our comprehensive examination extends to the intricate relationships between various stakeholders and the technological advancements driving the ecosystem's growth. We explore the ethical considerations and potential societal impacts of widespread LLM app adoption, highlighting the need for responsible innovation and governance frameworks. By examining these aspects, we aim to provide a vision for future research directions and highlight the importance of collaboration among stakeholders to address the challenges and opportunities within the LLM app ecosystem. The insights and recommendations provided in this paper serve as a foundation for driving innovation, ensuring responsible development, and creating a thriving, user-centric LLM app landscape. Copyright © 2024, The Authors. All rights reserved.

关键词： Ecosystems

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Community Evolution Tracking Based on High-Order Neighbor Consideration and Node Change Identification 19th

Community Evolution Tracking Based on High-Order Neighbor C...

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19th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2024

作者： Zhang, Yunan Wang, Chaohui Wu, Ling Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789819623723

Community evolution tracking is widely used in complex network analysis, which analyzes and identifies how communities evolve over time based on dynamic community detection. However, the current incremental dynamic community detection method has the phenomenon of ’concept drift’, which leads to inaccurate tracking of community evolution. Although some studies on dynamic community detection have proposed to perform global community detection on the network by timing or when the error information accumulates to a certain extent, this method will lead to a sudden change in community division, which will interrupt the evolution sequence of some communities and bring great difficulties to the continuous tracking of community evolution. In addition, the current community evolution tracking methods match the communities of two adjacent snapshots, and it is difficult to capture the fine-grained evolution process within the community. This paper proposes a community evolution tracking algorithm based on high-order neighbor consideration and node change identification. Firstly, based on an incremental update strategy that considers high-order neighbors, we adaptively expand the scope of incremental updates to reduce the accumulation of error information. Secondly, through the node change identification strategy to mine fine-grained community evolution events. Experiments show that our method can effectively track the evolution of communities in dynamic networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Community evolution Complex network Dynamic network Evolution tracking

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DFGET: Displacement-Field Assisted Graph Energy Transmitter for Gland Instance Segmentation

DFGET: Displacement-Field Assisted Graph Energy Transmitter ...

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International Conference on Signal Processing Proceedings (ICSP)

作者： Caiqing Jian Yongbin Qin Lihui Wang Chen Ye Xinyu Cheng GState Key Laboratory of Public Big Data College of Computer Science and Technology Engineering Research Center of Text Computing & Cognitive Intelligence Ministry of Education Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province Guizhou University Guiyang China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

Gland instance segmentation is an essential but challenging task in the diagnosis of adenocarcinoma. The existing models usually achieve gland instance segmentation through multi-task learning and boundary loss constraint. However, how to deal with the problems of gland adhesion and inaccurate boundary in segmenting the complex samples remains a challenge. In this work, we propose a novel geometric feature named displacement field (DF), which can represent the geometric information such as shape, size, and orientation of the glands. Based on the explicit constraint of DF, a displacement-field assisted graph energy transmitter (DFGET) framework is proposed for solving the above problems. Using such graph framework, the gland semantic segmentation map and the displacement field of the graph nodes are estimated with two graph network branches. With the constraint of DF, a graph cluster module is presented to improve the intra-class feature consistency and inter-class feature discrepancy, as well as to separate the adherent glands. Extensive comparison and ablation experiments on the GlaS dataset demonstrate the effectiveness of the displacement field and the superiority of DFGET. Compared to the best comparative model, DFGET increases the object-Dice and object-F1 score by 2.27% and 3.11% respectively, while decreases the object-HD by 15.58, achieving state-of-the-art performance, which indicates that DFGET can serve as an auxiliary tool for the diagnosis of adenocarcinoma.

关键词： Instance segmentation Measurement Visualization Adhesives Shape Semantic segmentation Glands Signal processing algorithms Signal processing Market research

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Traceable Ring Signature Scheme in Internet of Vehicles Based on Lattice Cryptography

Traceable Ring Signature Scheme in Internet of Vehicles Base...

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IEEE International Conference on big data and Cloud Computing (BdCloud)

作者： Wei Liao Lansheng Han Peng Chen Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China

Lattice cryptography, as a recognized Cryptosystem that can resist quantum computation, has great potential for development. Lattice based signature scheme is currently a research focus. In this paper, the traceable ring signature scheme based on lattice cryptography in the Internet of Vehicles (IoV) environment is studied. Firstly, users’ public and private keys are generated on the lattice, which effectively reduces the key size and time cost. Secondly, the scheme also achieves traceability by adding additional information. The scheme satisfies strong unforgeability, traceability, and anonymity. In addition, the traceable ring signature scheme based on lattice cryptography is applied in the IoV environment to effectively protect user privacy. Model communication can not only protect user privacy, but also trace the signer when necessary, achieving a balance between security and privacy. The simulation results show that the average delay of IoV of our scheme is better than that of similar schemes. The research in this paper improves the security of data transmission in the IoV environment, enables it to adapt to the complex and changeable new network environment, and effectively guarantees the information security of vehicles and owners.

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System Reliability Analysis of Planar Rock Slope Based on the Modified Pseudo-Dynamic Method and the Nonlinear Barton-Bandis Criterion

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Iranian Journal of Science and Technology, Transactions of Civil engineering 2025年 1-16页

作者： Zuo, Shi Liu, Wensheng Zhao, Lianheng Yu, Chenghao Liu, Le Xin, Yue Zhu, Jincheng School of Civil Engineering Changsha University Changsha China Hunan Provincial Key Laboratory for Big Data Smart Application of Natural Disaster Risks Survey of Highway Engineering Changsha University Changsha China The Second Engineering Co LTD. Of CTCE Group Suzhou China College of Civil Engineering Central South University Changsha China Key Laboratory of Heavy-Haul Railway Engineering Structure Ministry of Education Central South University Changsha China Hunan Provincial Key Laboratory for Disaster Prevention and Mitigation of Rail Transit Engineering Structure Central South University Changsha China

The stability analysis of jointed rock slopes under seismic activity is a crucial and challenging task. To assess the various potential damage modes of rock slopes featuring tension fracture planes, it is necessary to take into consideration the nonlinear properties of shear strength and the dynamic features of seismic activity. A modified pseudo-dynamic technique has been used to represent the slope safety coefficient under seismic action by utilizing the nonlinear Barton-Bandis failure criterion. Furthermore, a system reliability analysis of slope stability is carried out using a Monte Carlo simulation method. The findings indicate that the slope safety coefficient exhibits periodic variations over time when considering seismic action in dynamic conditions. Additionally, the interaction force between the blocks significantly influences the factor of safety. The slope system stability is notably affected by the horizontal seismic coefficient, while the vertical seismic coefficient has a less effect. Among the various potential failure modes, failure modes 2 and 4 are identified as the primary failure modes. The likelihood of failure mode 1 occurrence gradually increases with an increase in the nodal strength parameter.

关键词： Barton-Bandis failure criterion Earthquake Modified pseudo-dynamic method Rock slope System reliability

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QGEval: Benchmarking Multi-dimensional Evaluation for Question Generation

arXiv

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arXiv 2024年

作者： Fu, Weiping Wei, Bifan Hu, Jianxiang Cai, Zhongmin Liu, Jun School of Computer Science and Technology Xi’an Jiaotong University Xi’an China School of Continuing Education Xi’an Jiaotong University Xi’an China MOE KLINNS Lab School of Automation Science and Engineering Xi’an Jiaotong University Xi’an China Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi’an Jiaotong University Xi’an China

Automatically generated questions often suffer from problems such as unclear expression or factual inaccuracies, requiring a reliable and comprehensive evaluation of their quality. Human evaluation is widely used in the field of question generation (QG) and serves as the gold standard for automatic metrics. However, there is a lack of unified human evaluation criteria, which hampers consistent and reliable evaluations of both QG models and automatic metrics. To address this, we propose QGEval, a multi-dimensional Evaluation benchmark for Question Generation, which evaluates both generated questions and existing automatic metrics across 7 dimensions: fluency, clarity, conciseness, relevance, consistency, answerability, and answer consistency. We demonstrate the appropriateness of these dimensions by examining their correlations and distinctions. Through consistent evaluations of QG models and automatic metrics with QGEval, we find that 1) most QG models perform unsatisfactorily in terms of answerability and answer consistency, and 2) existing metrics fail to align well with human judgments when evaluating generated questions across the 7 dimensions. We expect this work to foster the development of both QG technologies and their evaluation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Vision BEV-MAE: Masked Bird's Eye View Autoencoders for Camera-based 3D Object Detection

Vision BEV-MAE: Masked Bird's Eye View Autoencoders for Came...

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Chinese Automation Congress (CAC)

作者： Zhenguo Zhang Yuanzhouhan Cao Hui Zhang Naiyue Chen Chao Ren Yidong Li School of Computer Science and Technology Beijing Jiaotong University Key Laboratory of Big Data & Artificial Intelligence in Transportation Beijing Jiaotong University Ministry of Education College of Electronics and Information Engineering Sichuan University

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

3D object detection is one of the fundamental per-ception tasks in autonomous driving. In recent years, perception in the Bird's Eye View (BEV) has attracted tremendous attention due to its outstanding ability in preserving geometric cues. How-ever, like other supervised learning tasks, BEV-based perception suffers from inadequate labeled training data. In this work, we propose the Vision BEV-MAE, a self-supervised learning approach for BEV perception from camera images. Specifically, we design a feature-level masking strategy to mask the mid-level representations, i.e., the encoded BEV features instead of directly masking input multi-view images, and reconstruct BEV features with a light-weight decoder. Our Vision BEV-MAE is independent of any geometric data such as point clouds, or any additional supervision, and can be easily implemented within any state-of-the-art BEV perception frameworks to improve the performance. We conduct experiments on benchmark dataset to validate our approach.

关键词： Point cloud compression Three-dimensional displays Autoencoders Supervised learning Training data Object detection Self-supervised learning Cameras Decoding Image reconstruction

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A Parallelizable Counterfactual Generation Method Based on Gradient Optimization 29

A Parallelizable Counterfactual Generation Method Based on G...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Ding, Haorun Jiang, Xuesong Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Quan Cheng Laboratory Jinan China State Key Laboratory of High-end Server and Storage Technology Jinan China

ISBN: (纸本)9798350330717

Post-hoc explanations are important for people to understand the predictions of explanation models. One class of methods in post-hoc explanation is the generation of counterfactuals, where a hypothetical example is obtained by perturbing the inputs to show how one could obtain a different prediction from the decision model. Counter-factual explanations should satisfy several properties: One is that counterfactuals generated under specific scenarios and constraints should be feasible for users, i.e., they should accommodate different causal constraints. The other is that it is more desirable for users to have a wider variety of viable examples, i.e., counterfactual diversity. To this end, we propose a parallelizable method based on gradient optimization. We partition the input feasible domains, perform counterfactual generation independently for each feasible domain, and then parallelize the counterfactual generation process for each feasible domain. Experimental results show that our approach effectively improves the diversity, sparsity, and proximity of the generated counterfactual instances on the public datasets Adult-Income, Lending-Club, German-Credit, and COMPAS compared to other models. © 2023 IEEE.

关键词： counterfactual explanation machine learning parallel computing

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Design and Implementation of Control System for Four-axis Picking Manipulator 33

Design and Implementation of Control System for Four-axis Pi...

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第33届中国控制与决策会议

作者： Chunyang Mu Wenxiao Gao Haiping An Xing Ma The Key Laboratory of Intelligent Information and Big Data Processing of Ningxia Province North Minzu University College of Mechatronic Engineering North Minzu University School of Electrical and Information Engineering North Minzu University

ISBN: (纸本)9781665431293

Manual fruit picking has the disadvantages of high labor intensity,low efficiency and high *** order to solve these problems,a fruit picking robot based on machine vision was *** using the steering gear as the actuator of each axis rotation and the Arduino as the control module to realize the motion control of four axis *** binocular vision positioning,the spatial point coordinate data of fruits were *** the data with the motion control algorithm of four axis manipulator,we can get the angle that each axis needs to *** system transmits data through Bluetooth module,and then controls the rotation of the mechanical arm to realize the fruit *** experiments,accuracy is compensated by software programming,and the smooth rotation of the manipulator has been solved.

关键词： Binocular potioning Accuracy compensation Four-axis manipulator Arduino

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