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13th International Conference on Information technology in Medicine and Education, ITME 2023

作者： Zhenfeng, Wang Quanwang, Lin Huihui, Gao Xiehua, Yu University of Fujian Province Key Laboratory of Big Data and Artificial Intelligence China MinNan Science and Technology University Fujian China School of Computer and Information MinNan Science and Technology University Quanzhou China University of Fujian Key Laboratory of Big Data and Artificial Intelligence Quanzhou China

ISBN: (纸本)9798350319156

The release of OpenAI's ChatGPT chatbot has sparked widespread concern around the world about the threats and legal issues of generative AI. Although this technological innovation has opened a new chapter in the field of artificial intelligence, it has also caused the public to worry about its possible negative effects. In order to solve the above problems and reasonably regulate the legal risks of generative artificial intelligence, this paper mainly adopts the literature, quantitative and qualitative analysis methods, etc. The first part mainly introduces the development process and current situation of generative artificial intelligence, the second part mainly discusses the impact of generative artificial intelligence on tort law, the third part mainly discusses the legal risks of generative artificial intelligence, and the fourth part mainly discusses the governance path of generative artificial intelligence legal risks. The last part is the conclusion of the research. Among them, the fourth part is the focus of this paper. By taking these issues into account, we can provide legal guarantees for the sustainable development of the generative AI industry and ensure that the widespread application of AI benefits human society[1]. © 2023 IEEE.

关键词： Artificial intelligence

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Facile synthesis of W-Mo bimetallic oxides with high adsorption properties from secondary resources

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Tungsten 2024年第4期6卷 806-820页

作者： Jia-Li Cheng Yang-Si Liu Xiao-Li Xi Zuo-Ren Nie Collaborative Innovation Center of Capital Resource-Recycling Material Technology College of Materials Science and EngineeringBeijing University of TechnologyBeijing100124China National Engineering Laboratory for Industrial Big-Data Application Technology Beijing University of TechnologyBeijing100124China Key Laboratory of Advanced Functional Materials Ministry of EducationBeijing University of TechnologyBeijing100124China

A simple solvothermal method was used to obtain W-Mo bimetallic oxides from W-Mo alloy scrap,and pure metal powders were also used as the raw materials to simulate *** products had a sea urchin-like structure with abundant oxygen vacancies and the products prepared at low temperatures forms a sosoloid resembling orthorhombic W_(0.4)Mo_(0.6)O_(3).The WMo bimetallic oxide prepared at the reaction temperature of 120℃exhibited excellent selective adsorption performance for methylene blue(MB),which the adsorption rate of MB reached 99%in 12 min and the adsorption rate reached 90%after6 adsorption *** the W-Mo molar ratio is 1:3,the maximum adsorption capacity of sample for MB can reach1148 mg·g^(-1).The adsorption process followed the Langmuir and pseudo-second-order models,which is surface-controlled monolayer *** experimental results show the feasibility of preparing W-Mo bimetal oxide products from pure materials and *** process is simple and effective,which offered a potential approach for secondary resource recycling and reusing.

关键词： W-Mo bimetallic oxide Oxygen vacancy Selective adsorption W-Mo alloy scrap Solvothermal

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Hydrogen Energy Demand Management in China:A Department Scenario Analysis Method

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Energy Engineering 2025年第3期122卷 971-983页

作者： Zhongxun Li Bing Wang Xiaolin Liu Center for Sustainable Development and Energy Policy Research School of Energy and Mining EngineeringChina University of Mining and Technology-BeijingBeijing100083China Research Institute of Decision-Making Science and Big Data School of ManagementChina University of Mining and Technology-BeijingBeijing100083China

The proposal of carbon neutrality target makes decarbonization and hydrogenation typical features of future energy development in *** a wide range of application scenarios,hydrogen energy will experience rapid growth in production and *** formulate an effective hydrogen energy development strategy for the future of China,this study employs the departmental scenario analysis method to calculate and evaluate the future consumption of hydrogen energy in China’s heavy industry,transportation,electricity,and other related *** technical parameters are selected and predicted accurately and reliably in combination with different development *** findings indicate that the period from 2030 to 2050 will enjoy rapid development of hydrogen energy,having an average annual growth rate of 2%to 4%.The technological progress and breakthroughs scenario has the greatest potential for hydrogen demand scale among the four development *** this scenario,the total demand for hydrogen energy is expected to reach 446.37Mt in *** sector will be the sector with the greatest potential for hydrogen deployment growth from 2023 to 2060,which is expected to rise from 0.038Mt to about 163.18Mt,with the ambitious growth in the ***,hydrogen energy has a considerable development potential in the steel sector,and the trend of de-refueling coke by hydrogenation in this sector will be imperative for this energy-intensive industries.

关键词： Hydrogen demand management department scenario analysis carbon neutrality

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From Global to Hybrid: A Review of Supervised Deep Learning for 2D Image Feature Representation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第6期6卷 1540-1560页

作者： Dong, Xinyu Wang, Qi Deng, Hongyu Yang, Zhenguo Ruan, Weijian Liu, Wu Lei, Liang Wu, Xue Tian, Youliang Guizhou University State Key Laboratory of Public Big Data College of computer science Guiyang550025 China Guangdong University of Technology Guangzhou510006 China Chinese Academy of Sciences Shenzhen Institute of Advanced Technology Shenzhen518000 China AI Research of *** Beijing100101 China

Computer vision is the science that aims to enable computers to emulate human visual perception, and it encompasses various techniques and methods for extracting and interpreting information from two-dimensional images. Supervised deep 2D image feature representation is a fundamental problem in computer vision that applies deep learning techniques to extract and process information from a given 2D image under supervised settings. The goal is to obtain a feature vector that can be utilized for various downstream computer vision applications. The quality of supervised deep 2D image feature representation algorithms directly affects the performance of downstream applications. However, most of the existing vision research only explores supervised deep 2D image feature representation for specific subtasks. Therefore, a comprehensive discussion on this topic is needed. In this paper, we propose a taxonomy of supervised deep 2D image feature representation methods based on four categories: global representation, region representation, hash representation, and hybrid representation, and we introduce their typical approaches. Furthermore, we perform a comparative analysis of the representative methods on three fundamental tasks: image classification, object detection, and semantic segmentation, as well as other common tasks. We also discuss the limitations of supervised deep 2D image feature representation and investigate future directions in image representation to facilitate the advancement of computer vision through image representation. © 2020 IEEE.

关键词： Self-supervised learning

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Side-Channel Analysis of Curve-25519 Based on Deep Learning: Side-channel analysis of Curve-25519 implementation using analysis models built on deep learning techniques

Side-Channel Analysis of Curve-25519 Based on Deep Learning:...

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2024 International Conference on Generative Artificial Intelligence and Information Security, GAIIS 2024

作者： Zhang, Zongnan Li, Meng An, Xiaoxin Li, Zhen Ma, Zhe College of Big Data and Internet Shenzhen Technology University Shenzhen518118 China School of Cyber Science and Technology Shandong University Jinan250100 China Beijing100000 China

ISBN: (纸本)9798400709562

This paper explores the integration of deep learning technology with Side-Channel Analysis (SCA) methods to effectively analyze the Curve-25519 algorithm implemented on an MCU chip. The Curve-25519 algorithm, protected by the security features of elliptical curve algorithms and constant-time operations, presents a challenge for low-cost, non-invasive SCA methods due to its robustness. This work focuses on the leakage of conditional judgment operations that occur before each point addition and point doubling operation. By identifying these information leakage points through SCA, electromagnetic radiation and power consumption information are collected and labeled. We conduct a dataset and transformed 1-dimensional signals into a 2D image for training. The trained model is subsequently used for testing. Experiments demonstrate that this method can effectively analyze leakage points in the Curve-25519 algorithm and help to improve the robustness of the algorithm. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Electromagnetic waves

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The impact and prospects of computer-aided technology for promoting universal breast cancer screening 2

The impact and prospects of computer-aided technology for pr...

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2nd International Conference on Health big data and Intelligent Healthcare, ICHIH 2023

作者： Zhu, Tianyuan Fu, Xiaoyang Huang, Yucheng Zhuhai College of Science and Technology Alibaba Cloud Big Data Application School Zhuhai China Zhuhai College of Science and Technology School of Computer Science Zhuhai China

ISBN: (纸本)9798350309324

Since breast cancer is difficult to prevent, detecting and treating it early may improve patient outcomes. Universal breast cancer screening is an important method for early detection and treatment. Our work surveyed different populations about their awareness of breast cancer and their willingness to be screened. Then, we summarized the potential barriers to universal breast cancer screening through a comparison of current breast cancer screening methods and models. We propose using computer-aided technology for promoting universal breast cancer screening, including predicting disease risk, improving diagnostic efficiency, and achieving individualized screening goals. Finally, we analyze the problems that need to be solved, outline the basic steps to implement improvements in the integration of computer-aided technology into the health care field represented by breast cancer screening and describe the prospects for future development. © 2023 IEEE.

关键词： Diseases

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Metamorphic Testing for Traffic Sign Detection and Recognition 23

Metamorphic Testing for Traffic Sign Detection and Recogniti...

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23rd IEEE International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2023

作者： Long, Yuanyuan Fan, Yong Pan, Ya School of Computer Science and Technology of Southwest University of Science and Technology Mianyang China Sichuan Big Data and Intelligent System Engineering Technology Research Center Mianyang China

ISBN: (纸本)9798350359398

Traffic sign detection and recognition (TSDR) is a crucial technology to realize vehicle autonomous driving and maintain road safety. Misdetection or misclassification of traffic signs can lead to serious traffic accidents. Therefore, it is essential to ensure the correctness of traffic sign detection and recognition systems. However, most existing methods use labeled data, but it isn't easy to obtain labeled data. The metamorphic testing can reduce the dependence on the labeled data, but the current metamorphic relations do not consider the domain characteristics of traffic signs, so it is difficult to effectively detect traffic sign detection and recognition systems faults. To solve the above problems, this paper introduces metamorphic testing to verify traffic sign detection and recognition systems and designs and implements a tool, MTSDR, which provides a series of metamorphic relations in the traffic domain. It can generate many follow-up test images based on these metamorphic relations and automatically performs tests for evaluation, focusing on practical failure situations. The experimental evaluation was carried out on four advanced traffic sign detection and recognition models on open datasets. The results show that MTSDR can generate natural images and find thousands of traffic sign detection and recognition faults. Compared with the previous methods, our method has a higher fault detection capability, and the highest fault detection rate reaches more than 40%. In addition, it finds that retraining the traffic sign detection and recognition models using the images that found the fault can improve the model's performance, reduce its fault, and reduce the fault rate by 11.77% on average. © 2023 IEEE.

关键词： Traffic signs

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Study on Classification Models Utilizing the Multilayer Perceptron Feature Selection and Ensemble Voting Classifier 24

Study on Classification Models Utilizing the Multilayer Perc...

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5th International Conference on Computer science and Management technology, ICCSMT 2024

作者： Zhu, Xiaohang Fang, Huan Zhao, Xinli School of Mathematics and Big Data Anhui University of Science and Technology Anhui Huainan China School of Petroleum and Natural Gas Engineering Changzhou University Jiangsu Changzhou China

ISBN: (纸本)9798400709999

The existing classification prediction models increase in training time and cost with the increase in the number of features, significantly increase in computational complexity, and irrelevant or redundant features interfere with the model's learning process and affect the accuracy of classification prediction *** this study, a model combining the multilayer perceptron (MLP) feature selection with an ensemble voting classifier (MRS) is *** MLP feature selection method demonstrates superiority in screening important features, which can effectively extract key information from the original ***, the classification prediction performance of the model is further improved by feeding the filtered features into an ensemble voting classifier that incorporates Random Forest (RF) and Support Vector Machine (SVM).The model enhances the processing efficiency of classification problems in the field of data mining, especially in the context of confronting multi-featured and high-dimensional data, and more accurately performs classification ***, the accuracy of the model exceeds that of many other models is proved by the experiments, demonstrating its great potential in solving the classification and prediction problems in the field of data mining. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Random forests

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Numerical Simulation of Deterioration Process in Reinforced Concrete Based on COMSOL Multiphysics

Numerical Simulation of Deterioration Process in Reinforced ...

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2023 International Conference on Applied Mechanics and Physics

作者： Li, Gen Wang, Chenggong Jiang, Minghui Li, Lin Wang, Ruiqi College of Artificial Intelligence and Big Data Guangdong Vocational and Technical University of Business and Technology Guangdong China College of Materials Science & Engineering Beijing University of Technology Beijing China

Reinforced concrete is deteriorated by chloride attack and dry-wet cycles to suffer serious durability problems. Reinforced concrete degradation typically occurs in two distinct stages: initially through chloride erosion, followed by the electrochemical corrosion of rebars. In this research, COMSOL Multiphysics was employed to model how various crack widths impact the degradation of reinforced concrete. Findings indicated that the deterioration process of reinforced concrete could be better simulated by COMSOL Multiphysics, and the degradation of reinforced concrete was significantly influenced by crack widths. As crack widths widen, chloride diffusion accelerated, leading to a rise in the corrosion current density of rebars. Notably, a crack width increased from 0.1 mm to 0.4 mm resulted in a 227.53% higher corrosion current density in rebars after 150 days of exposure. This study provides a theoretical basis for predicting reinforced concrete deterioration in the future. © Published under licence by IOP Publishing Ltd.

关键词： Reinforced concrete

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Intersecting-Boundary-Sensitive Fingerprinting for Tampering Detection of DNN Models 41

Intersecting-Boundary-Sensitive Fingerprinting for Tampering...

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41st International Conference on Machine Learning, ICML 2024

作者： Bai, Xiaofan He, Chaoxiang Ma, Xiaojing Zhu, Bin Benjamin Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China Microsoft United States School of Computer Science and Technology Huazhong University of Science and Technology China Cluster and Grid Computing Lab China

Cloud-based AI services offer numerous benefits but also introduce vulnerabilities, allowing for tampering with deployed DNN models, ranging from injecting malicious behaviors to reducing computing resources. Fingerprint samples are generated to query models to detect such tampering. In this paper, we present Intersecting-Boundary-Sensitive Fingerprinting (IBSF), a novel method for black-box integrity verification of DNN models using only top-1 labels. Recognizing that tampering with a model alters its decision boundary, IBSF crafts fingerprint samples from normal samples by maximizing the partial Shannon entropy of a selected subset of categories to position the fingerprint samples near decision boundaries where the categories in the subset intersect. These fingerprint samples are almost indistinguishable from their source samples. We theoretically establish and confirm experimentally that these fingerprint samples' expected sensitivity to tampering increases with the cardinality of the subset. Extensive evaluation demonstrates that IBSF surpasses existing state-of-the-art fingerprinting methods, particularly with larger subset cardinality, establishing its state-of-the-art performance in black-box tampering detection using only top-1 labels. The IBSF code is available at: https://***/CGCL-codes/IBSF. Copyright 2024 by the author(s)

关键词： HTTP

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