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arXiv 2024年

作者： Lin, Zheng Zhang, Neng Liu, Chao Zheng, Zibin School of Software Engineering Sun Yat-Sen University Zhuhai China School of Big Data & Software Engineering Chongqing University Chongqing China

Due to its powerful capabilities in natural language understanding and content generation, ChatGPT has received widespread attention since its launch in 2022. An increasing number of ChatGPT-related projects (that enhance the capabilities of ChatGPT, develop applications by calling ChatGPT APIs, improve the usage of ChatGPT, etc.) are being released on GitHub and have sparked widespread discussions. However, GitHub does not provide a detailed classification of these projects to help users effectively explore interested projects. Additionally, the issues raised by users for these projects cover various aspects, e.g., installation, usage, and updates. It would be valuable to help developers prioritize more urgent issues and improve development efficiency. Unfortunately, there is currently no research focused on understanding the categories and issues of ChatGPT-related projects. To fill this gap, we retrieved 71,244 projects from GitHub using the keyword ‘ChatGPT’ and selected the top 200 representative projects with the highest numbers of stars as our dataset. By analyzing the project descriptions, we identified three primary categories of ChatGPT-related projects, namely ChatGPT Implementation & Training, ChatGPT Application, ChatGPT Improvement & Extension. Next, we applied a topic modeling technique to 23,609 issues of those projects and identified ten issue topics, e.g., model reply and interaction interface. We further analyzed the popularity, difficulty, and evolution of each issue topic within the three project categories. Our main findings are: 1) The increase in the number of projects within the three categories is closely related to the development of ChatGPT;and 2) There are significant differences in the popularity, difficulty, and evolutionary trends of the issue topics across the three project categories. Based on these findings, we finally provided implications for project developers and platform managers on how to better develop and manage ChatGPT-rel

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A Lightening Fine-grained Access Control Scheme Supporting Full Policy Hiding in Cloud Storage 29

A Lightening Fine-grained Access Control Scheme Supporting F...

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

作者： Shi, Jiaoli Hu, Chao Yao, Shimao Mei, Zhuolin Wu, Bin Li, Hui Jiujiang Univ. School of Computer and Big Data Jiujiang China Jiangxi Univ. of Finance and Economics School of Software IoT Engineering Nanchang China Jiujiang Key Lab. of Network and Information Security Jiujiang China Jiujiang University School of Computer and Big Data Jiujiang China Peking University School of Elec. and Comp. Engineering Shenzhen China

ISBN: (纸本)9798350330717

Efficiency, security, and flexibility are difficult to balance in a full policy hiding CP-ABE scheme. This paper creatively converts the privacy matching problem of access policy and a user's private key to the privacy three-party set computation problem. Then the new privacy set computation problem is resolved by a message driven key generation method. Additionally, the ROBDD (Reduced Ordered Binary Decision Diagrams) is utilized to rich access structure expression and convert access policies into feasible path sets. Each feasible path is composed of attributes and these attributes are bound to the ciphertext using CP-ABE. Based on the innovative ideas mentioned above, we present a Lighten Fine-grained Access Control scheme supporting Full Policy Hidden (LFAC-FPH) that integrates data confidentiality protection, access policy rich expression but complete hiding, fine-grained access control, and lightweight terminal computing. Our scheme has three advantages: 1) High Efficiency. The proposed scheme can achieve fast privacy matching of access policies during user decryption. 2) Full Policy Hiding. The access policy bound by an owner on the ciphertext does not leak any information. Moreover, a user cannot know attributes they do not own. 3) High Flexibility. The decryption process does not require online from owners or KGC, and system attributes can be added at any time. © 2023 IEEE.

关键词： CP-ABE full policy hiding lighten computation Private-Preserving

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A Feature Distribution Smoothing Network Based on Gaussian Distribution for QoS Prediction

A Feature Distribution Smoothing Network Based on Gaussian D...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Lu, Tongxin Zhang, Xiaohong Wang, Ziliang Yan, Meng Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing University Ministry of Education China Chongqing University School of Big Data and Software Engineering Chongqing China

ISBN: (纸本)9798350304855

With the increasing number of services and their homogenization, the use of Quality of Service (QoS) for recommendations has become necessary. However, existing QoS prediction solutions have limitations in solving the noise and label imbalance problems of dataset, which greatly limit the improvement of QoS prediction accuracy. In this paper, we propose FSNet that contains a feature distribution smoothing module and an improved W-Huber loss function. The feature distribution smoothing module mitigates the effect of noise problem by fitting potential Gaussian distribution of known features with a supervised feedforward neural network. W-Huber loss function mitigates the impact of label imbalance problem on QoS prediction by reweighting the two components of Huber loss function. We conduct extensive experiments on real large-scale QoS dataset, and the results demonstrate that the proposed FSNet method outperforms existing QoS prediction methods. © 2023 IEEE.

关键词： Forecasting

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Image denoising based on residual network 3

Image denoising based on residual network

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3rd International Conference on Electronic Information engineering, big data, and Computer Technology, EIBDCT 2024

作者： Ma, Lihe Wang, Yan Sha, Ning Ma, Lin School of Information Engineering Harbin University Harbin China Heilongjiang Government Affairs Big Data Center3 Harbin China Heilongjiang Provincial Key Laboratory of the Intelligent Perception and Intelligent Software Harbin China

ISBN: (纸本)9781510680449

Image denoising has always been a hot research topic in the field of computer vision, playing an important role in improving image quality and accuracy. In this paper, a method for image denoising based on residual network is proposed, which uses deep learning technology to improve the effect of image processing. This method can automatically learn useful features in the image and effectively remove noise in the image, achieving automatic removal of image noise. Finally, experiments were conducted on standard image datasets for evaluation. The experimental results show that the image denoising method based on residual network has better performance compared to traditional methods. It can effectively remove various types of noise, improve image quality and clarity, and has broad application prospects in image processing. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image denoising

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Dynamic Hand Gesture Classification Based on Attention Mechanism and Transformer 3

Dynamic Hand Gesture Classification Based on Attention Mecha...

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3rd International Conference on Computer Vision and Pattern Analysis, ICCPA 2023

作者： Ren, Zhen He, Haonan Huang, Zhengyi School of Big Data & Software Engineering Chongqing University Chongqing401331 China School of Mechanical & Automotive Engineering South China University of Technology Guangdong Guangzhou510641 China School of Electromechanical Engineering Guangdong University of Technology Guangdong Guangzhou510006 China

ISBN: (纸本)9781510667563

In the era of rapid development of deep learning, the popular transformer in recent years has played an outstanding role in many fields, but most of it focuses on the development of language models, and is still in the development stage in computer vision. Gesture recognition is a relatively popular module in computer vision, but the mainstream method still uses CNN for gesture recognition, and there are few articles combining gesture recognition with attention mechanism and transformer. In this paper, we propose a dynamic gesture recognition model based on attention mechanism and Transformer. In order to extract the valid information in each frame, we add the attention mechanism to the feature extraction network, followed by passing it into the transformer to predict the hand gesture through the self-attention mechanism. The model has been tested on the IsoGD dataset, achiving good experimental results. Not only do we confirm that the attention mechanism can improve the recognition accuracy through ablation study, but also prove that transformer is feasible to process and identify the temporal information among frames in dynamic gestures and perform recognition. © 2023 SPIE.

关键词： Gesture recognition

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The value of the FTO gene in breast cancer treatment and prevention: a systematic review with Meta-analysis 24

The value of the FTO gene in breast cancer treatment and pre...

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3rd International Conference on Public Health and data Science, ICPHDS 2024

作者： Li, Zheng Gu, Fengming Zhang, Chengan School of Public Health Chengdu University of Traditional Chinese Medicine Sichuan Chengdu China College of Light Industry Science and Engineering Sichuan University Sichuan Chengdu China Chongqing University College of Big Data and Software Chongqing China

ISBN: (纸本)9798400711671

Background: The FTO gene has been shown to be significantly associated with obesity and body fat content, and Recent studies have suggested that it may be strongly associated with a variety of cancers, including breast cancer, by affecting obesity. The aim of this study was to systematically evaluate the role of the FTO gene in the prevention and treatment of breast cancer and to determine the association between the two by meta-analysis. Method: Relevant literature published between 2019 and January 20, 2024 in five online databases including pubmed and others were systematically searched in this study. Estimates of the association between FTO rs9939609 and breast cancer were determined by Meta-analysis and expressed using Odds ratio (OR) and its 95% confidence interval (95% CI). Results: A total of 16 STUDIES, INCLUDING 6, 039 subjects, were included in this study. Seven FTO-related SNPs were involved in the association between FTO and BC. The overall study quality was moderately low. Meta-analysis showed that FTO rs9939609 all comparison groups (including heterozygous, pure, dominant and recessive) were in significantly associated with BC. Conclusion: The FTO gene can be used as a screening indicator for breast cancer risk, and its use as a target for breast cancer treatment is feasible. More research is needed to support its application to the treatment of breast cancer as well as its prevention in practice. © 2024 Copyright held by the owner/author(s).

关键词： breast cancer

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Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need 38

Unlearnable 3D Point Clouds: Class-wise Transformation Is Al...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Wang, Xianlong Li, Minghui Liu, Wei Zhang, Hangtao Hu, Shengshan Zhang, Yechao Zhou, Ziqi Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China

Traditional unlearnable strategies have been proposed to prevent unauthorized users from training on the 2D image data. With more 3D point cloud data containing sensitivity information, unauthorized usage of this new type data has also become a serious concern. To address this, we propose the first integral unlearnable framework for 3D point clouds including two processes: (i) we propose an unlearnable data protection scheme, involving a class-wise setting established by a category-adaptive allocation strategy and multi-transformations assigned to samples;(ii) we propose a data restoration scheme that utilizes class-wise inverse matrix transformation, thus enabling authorized-only training for unlearnable data. This restoration process is a practical issue overlooked in most existing unlearnable literature, i.e., even authorized users struggle to gain knowledge from 3D unlearnable data. Both theoretical and empirical results (including 6 datasets, 16 models, and 2 tasks) demonstrate the effectiveness of our proposed unlearnable framework. Our code is available at https://***/CGCL-codes/UnlearnablePC. © 2024 Neural information processing systems foundation. All rights reserved.

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The Application of big data and AI Analytics in Rating Industrial and Smart Manufacturing Districts: Challenges and Opportunities 3

The Application of Big Data and AI Analytics in Rating Indus...

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3rd International Conference on big data, Information and Computer Network, BDICN 2024

作者： Zhou, Chenchen Wang, Wei Tian, Maohong Liang, Jian Zhang, Dequan Li, Hualin School of Software and Artificial Intelligence Chongqing Institute of Engineering Chongqing China Intelligent Application of Financial Big Data Chongqing Colleges Universities Engineering Research Center Chongqing China Shu Yi Xin Credit Management Co LTD Chongqing China

ISBN: (纸本)9798350363821

As an important carrier and component of industrial clusters, industrial districts are an important way for regional economic growth, and the economic effects of industrial districts have attracted more and more attention. Therefore, how to identify high-quality districts with good development trends and obvious competitive advantages from a large amount of district information has become an increasingly important topic. This article takes industrial and intelligent manufacturing districts as an example and proposes an innovative industrial and intelligent manufacturing zone rating method that combines rule-based modeling, Analytic Hierarchy Process (AHP), and Artificial Intelligence (AI) models. Collect structured and unstructured data, including real-Time operational data, historical records, market trends, and expert opinions, from multiple sources through big data technology. Apply rule-based models and Analytic Hierarchy Process (AHP) to prioritize and weight various factors that affect regional performance, and obtain district ratings;And use the Kmeans method for clustering to obtain district level classification. Finally, the paper combines the outputs of the rule-based models, AHP, and AI models to create an overall rating system. This system continuously monitors district performance, providing accurate and comprehensive ratings to support decision-making in industry and government. © 2024 IEEE.

关键词： Smart manufacturing

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One-Handed Gesture Recognition Based on Improved ST-GCN and CA Attention Mechanism 3

One-Handed Gesture Recognition Based on Improved ST-GCN and ...

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3rd International Conference on Automation, Robotics and Computer engineering, ICARCE 2024

作者： Wang, Guixin School of Big Data and Computer GuangDong BaiYun University Department of Software Engineering Guangzhou China

ISBN: (纸本)9798331529505

The article takes one-handed gesture video as the research object, and mainly focuses on the recognition process and method of 'isolated words' and static gesture mixtures. Firstly, the algorithm of extracting the key point positions of frame pictures is proposed by grouping rules of frame sequences of different gestures. This algorithm solves the problem of invalid gesture images affecting the recognition due to the redundancy of gesture images when extracting gestures from traditional gesture videos. Finally, a new network (ST-GCN-CA) is proposed, which improves the traditional spatio-temporal graph convolutional network (ST-GCN) and adds the CA attention mechanism. The method and network in this paper are applied to the Chinese isolated word sign language dataset (CSL-500) single-handed video, and the experimental results show that the recognition accuracies in the isolated word gesture video and the hybrid video reach 94.3% and 94.1%, respectively, which improves the recognition accuracies in comparison with other methods in the public domain. © 2024 IEEE.

关键词： Gesture recognition

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Modal-Adaptive Spatial-Aware-Fusion and Propagation Network for Multimodal Vision Crowd Counting

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IEEE Transactions on Consumer Electronics 2025年

作者： Liu, Kai Zou, Xuetao Zhu, Peng Sang, Jun Chongqing University School of Big Data and Software Engineering Chongqing 401331 China

With the rapid development of AI and deep learning technologies, smart consumer electronic devices integrate a variety of sensors, especially thermal imaging or depth imaging technology. Some researchers became keen to explore multimodal vision crowd counting techniques based on RGB-thermal or RGB-depth images. However, existing multimodal counting methods ignore the unique contribution of each modality and the effective propagation of features while achieving multimodal fusion. To address these issues, we propose a Modal-adaptive Spatial-aware-fusion and Propagation Network (MSPNet) for multimodal crowd counting. First, we design a coarse-fine cross-modal dynamic fusion (CCDF) module, which fully captures modality-specific and modality-shared information in different semantic spaces using a spatial activation function-guided fine-grained adaptive weighted fusion mechanism. Then, we adopt adapted different convolutions to channel concatenate the features output by multi-stage CCDF. Finally, considering the visual differences of the same object under different imaging angles, we design a dual-dilation adaptive feed-forward propagation module constructed by the dual dilation transposed attention and the feed-forward neural network improved by the gating mechanism to effectively propagate the enhanced multi-modal fusion features to the counting regression module. Experimental results show that MSPNet outperforms the existing state-of-the-art methods on two multimodal crowd counting datasets ShanghaiTechRGBD and RGBT-CC. © 1975-2011 IEEE.

关键词： crowd counting dynamic fusion feed-forward propagation multimodal vision techniques

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