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41st International Conference on Machine Learning, ICML 2024

作者： Liu, Hongyu Cong, Runmin Li, Hua Xu, Qianqian Huang, Qingming Zhang, Wei Institute of Information Science Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing China School of Control Science and Engineering Shandong University Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Computer Science and Technology Hainan University Hainan China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspective of evolution and succession, including an evolution stage with Low-resolution Location Model (LrLM) and a succession stage with High-resolution Refinement Model (HrRM). The evolution stage achieves detail-preserving salient objects localization on the low-resolution image through the evolution mechanisms on supervision and feature;the succession stage utilizes the shallow high-resolution features to complement and enhance the features inherited from the first stage in a lightweight manner and generate the final high-resolution saliency prediction. Besides, a new metric named Boundary-Detail-aware Mean Absolute Error (MAEBD) is designed to evaluate the ability to detect details in high-resolution scenes. Extensive experiments on five datasets demonstrate that our network achieves superior performance at real-time speed (49 FPS) compared to state-of-the-art methods. Our code is publicly available at: https://***/rmcong/ESNet_ICML24. Copyright 2024 by the author(s)

关键词： Miocene

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A Behavioral Authentication Method for Mobile Based on Browsing Behaviors

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IEEE/CAA Journal of Automatica Sinica 2020年第6期7卷 1528-1541页

作者： Dongxiang Chen Zhijun Ding Chungang Yan Mimi Wang Department of Computer Science and Technology Tongji UniversityShanghai 201804China Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji UniversityShanghai 201804China IEEE

The passwords for unlocking the mobile devices are relatively simple,easier to be stolen,which causes serious potential security *** important research direction of identity authentication is to establish user behavior models to authenticate *** this paper,a mobile terminal APP browsing behavioral authentication system architecture which synthesizes multiple factors is *** architecture is suitable for users using the mobile terminal APP in the daily *** architecture includes data acquisition,data processing,feature extraction,and sub model *** can use this architecture for continuous authentication when the user uses APP at the mobile terminal.

关键词： Behavioral authentication browsing behaviors mobile device multiple factors

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A Chinese Font Generation Method based on Dynamic Convolution Improved Generative Adversarial Network

A Chinese Font Generation Method based on Dynamic Convolutio...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Xuefei Guo Li Zhao Xiaojun Wu Honghong Yang Yufang Man School of Computer Science Shaanxi Normal University Xi’an China Key Laboratory of Intelligent Computing and Service Technology for Folk Song Ministry of Culture and Tourism Xi’an China Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Font generation is a challenging research topic in the field of computer vision, aiming to apply the style from a reference image to a source character image. The core task of font generation is to generate images, especially complex character images, that closely resemble the style of the reference font while maintaining the original glyph structure. This paper proposes a novel font generation method based on the generation adversarial network (GAN). Firstly, a new unsupervised end-to-end Chinese font generation network is designed. Then, a Convolution-Transformer (CNNTrans) module is devised to extract style features from global and local with attention constraint. Finally, a dynamic convolutional skip connection module (DCSC) is proposed to dynamically fuse font content and style according the importance of content and style features in different positions. Experimental results demonstrate that the proposed font generation method can generate higher quality styled fonts compared to other methods.

关键词： Computer vision Costs Convolution Fuses Layout Feature extraction Generative adversarial networks

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Predictive Resilience Assessment Featuring Diffusion Reconstruction for Road Networks Under Rainfall Disturbances

SSRN

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SSRN 2024年

作者： Zang, Di Wei, Chenguang Zhao, Jiayi Zhang, Junqi Tang, Keshuang Zhu, Hong Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Computer Science and Technology Tongji University No. 4800 Cao’an Road Shanghai200092 China Key Laboratory of Road and Traffic Engineering Ministry of Education College of Transportation Engineering Tongji University No. 4800 Cao’an Road Shanghai200092 China

The ability of road networks to withstand external disturbances is a crucial measure of transportation system performance, where resilience distinctly emerges as an effective perspective for its unique insights into the system's resistance and recovery capabilities. In the face of unforeseen resilience disturbance events, predictive and accurate assessment of road network resilience is essential for better traffic regulation and emergency response management. However, existing resilience assessment methods of road networks are insufficient: they lack reliable real-time big-data analysis, do not possess predictive capabilities for guiding decision-making, and have a narrow view with single-dimensional resilience indicators. To address these issues, focusing on rainfall disturbance scenarios, this work introduces a novel resilience assessment method, which is predictive and real-time, consisting of two components: a traffic indicator prediction model and a comprehensive resilience assessment model. Firstly, we propose a two-stage traffic indicator prediction model, namely the Conditional Diffusion-Reconstruction-based Graph Neural Network (CDRGNN), which particularly enhances disturbance-scenario prediction accuracy, thereby providing reliable foresight in aid of the following assessments. Subsequently, we develop a resilience assessment model featuring structural-functional comprehensive resilience indicators established on the shortest-path aggregation, and the overall resilience assessment is performed through comparative analysis using indicators obtained in real time with historical non-disruptive resilience benchmarks. In a case study focusing on heavy rainfall disturbances on a road network in California, USA, abundant experiments and visualizations are conducted to demonstrate the rationality of our proposed comprehensive resilience indicators as well as the precision and reliability of these predictive resilience assessment outcomes. © 2024, The Authors. All

关键词： Diffusion

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Behavioral Unicity: On the Limits of Anonymized Social Behavior Metadata 1st

Behavioral Unicity: On the Limits of Anonymized Social Beh...

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1st Conference on Blockchain and Web3.0 technology Innovation and Application, BWTAC 2024

作者： Tang, Hao Wang, Cheng Tongji University Shanghai201804 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China Shanghai Artificial Intelligence Laboratory Shanghai200030 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

ISBN: (纸本)9789819794119

Social behavior metadata has altered business models and human lifestyles. However, the inclusion of personal information in social behavior metadata poses risks of identity exposure for users. Under the requirements of modern data management laws, service providers now employ anonymization techniques when collecting user behavior metadata, which aims to break the link between personal identifiers and behavioral attributes for privacy protection. This paper conducts experiments on an open-source dataset of anonymized social behavior metadata and finds that even with privacy protection techniques such as data generalization, there remains a high risk of reidentification. Specifically, four social behavior metadata records are sufficient to reidentify users from the anonymized social behavior metadata, achieving a unicity of 90.10%. This indicates that the current widespread collection of social behavior metadata brings a high risk of privacy breaches. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Anonymity

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Predictive Resilience Assessment Featuring Diffusion Reconstruction for Road Networks Under Rainfall Disturbances

SSRN

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SSRN 2024年

The ability of road networks to withstand external disturbances is a crucial measure of transportation system performance, where resilience distinctly emerges as an effective perspective for its unique insights into the system's resistance and recovery capabilities. In the face of unforeseen resilience disturbance events, predictive and accurate assessment of road network resilience is essential for better traffic regulation and emergency response management. However, existing resilience assessment methods of road networks are insufficient: they lack reliable real-time big-data analysis, do not possess predictive capabilities for guiding decision-making, and have a narrow view with single-dimensional resilience indicators. To address these issues, focusing on rainfall disturbance scenarios, this work introduces a novel resilience assessment method, which is predictive and real-time, consisting of two components: a deep learning traffic indicator prediction model and a comprehensive resilience assessment model. Firstly, we propose a two-stage traffic indicator prediction model, namely the Conditional Diffusion-Reconstruction-based Graph Neural Network (CDRGNN), which particularly enhances disturbance-scenario prediction accuracy, thereby providing reliable foresight in aid of the following assessments. Subsequently, we develop a resilience assessment model featuring structural-functional comprehensive resilience indicators established through shortest-path aggregation, and the overall resilience assessment is performed through comparative analysis using indicators obtained in real-time with historical non-disruptive resilience benchmarks. In a case study focusing on heavy rainfall disturbances on a road network in California, the United States, abundant experiments and visualizations are conducted to demonstrate the rationality of our proposed comprehensive resilience indicators as well as the precision and reliability of these predictive resilience assessment outcom

关键词： Diffusion

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Upper Bounds on Lifetime of Three Dimensional Extended UWB Sensor Networks*

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Chinese Journal of Electronics 2023年第2期19卷 307-312页

作者： Juan Xu Changjun Jiang Aihuang Guo Yongfa Hong Shu Li Cheng Wang School of Electronics and Information Engineering Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing of the Ministry of Education Tongji University Shanghai China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China

The upper bounds on lifetime of three dimensional extended Time hopping impulse radio Ultrawide band (TH-IR UWB) sensor networks are derived using percolation theory arguments. The TH-IR UWB sensor network consists of $n$ sensor nodes distributed in a cube of edge length $n^{1/3}$ according to a Poisson point process of unit intensity. It is shown that for such a static three dimensional extended TH-IR UWB sensor network, the upper bound on the lifetime is of order $O(n^{-1})$ , while in the ideal case, the upper bound on the lifetime is longer than that of a static network by a factor of $n^{2/3}$ . Therefore sensor nodes moving randomly in the deployment area can improve the upper bound on network lifetime. The results also reveal that the upper bounds on network lifetime decrease with the number of nodes $n$ , thus extended TH-IR UWB sensor networks aren't prone to be employed in large-scale network.

关键词： Wireless communication Wireless sensor networks Upper bound Protocols

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LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU

arXiv

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arXiv 2024年

作者： Zhu, Peng Li, Yuante Hu, Yifan Liu, Qinyuan Cheng, Dawei Liang, Yuqi Department of Computer Science and Technology Tongji University Shanghai China Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Artificial Intelligence Laboratory Shanghai China Seek Data Group Emoney Inc Shanghai China

Stock price prediction is a challenging problem in the field of finance and receives widespread attention. In recent years, with the rapid development of technologies such as deep learning and graph neural networks, more research methods have begun to focus on exploring the interrelationships between stocks. However, existing methods mostly focus on the short-term dynamic relationships of stocks and directly integrating relationship information with temporal information. They often overlook the complex nonlinear dynamic characteristics and potential higher-order interaction relationships among stocks in the stock market. Therefore, we propose a stock price trend prediction model named LSR-IGRU in this paper, which is based on long short-term stock relationships and an improved GRU input. Firstly, we construct a long short-term relationship matrix between stocks, where secondary industry information is employed for the first time to capture long-term relationships of stocks, and overnight price information is utilized to establish short-term relationships. Next, we improve the inputs of the GRU model at each step, enabling the model to more effectively integrate temporal information and long short-term relationship information, thereby significantly improving the accuracy of predicting stock trend changes. Finally, through extensive experiments on multiple datasets from stock markets in China and the United States, we validate the superiority of the proposed LSR-IGRU model over the current state-of-the-art baseline models. We also apply the proposed model to the algorithmic trading system of a financial company, achieving significantly higher cumulative portfolio returns compared to other baseline methods. Our sources are released at https://***/ZP1481616577/Baselines_LSR-IGRU. Copyright © 2024, The Authors. All rights reserved.

关键词： Graph neural networks

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A Novel ICD Coding Method Based on Associated and Hierarchical Code Description Distillation

arXiv

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arXiv 2024年

作者： Zhang, Bin Wang, Junli Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai201804 China Collaborative Innovation Center for Financial Network Security Tongji University Shanghai201804 China

ICD(International Classification of Diseases) coding involves assigning ICD codes to patients visit based on their medical notes. ICD coding is a challenging multilabel text classification problem due to noisy medical document inputs. Recent advancements in automated ICD coding have enhanced performance by integrating additional data and knowledge bases with the encoding of medical notes and codes. However, most of them ignore the code hierarchy, leading to improper code assignments. To address these problems, we propose a novel method based on associated and hierarchical code description distillation (AHDD) for better code representation learning and avoidance of improper code *** utilize the code description and the hierarchical structure inherent to the ICD codes. Therefore, in this paper, we leverage the code description and the hierarchical structure inherent to the ICD codes. The code description is also applied to aware the attention layer and output layer. Experimental results on the benchmark dataset show the superiority of the proposed method over several state-of-the-art baselines. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Mechanistic investigations of corrosion and localized corrosion of X80 steel in seawater comprising sulfate-reducing bacteria under continuous carbon starvation

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Corrosion Communications 2022年第4期8卷 70-80页

作者： Hongwei Liu Cuiying Chen Muhammad Asif Tong Zhao Bing Lei Guozhe Meng Hongfang Liu School of Chemical Engineering and Technology Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Sun Yat-sen University School of Materials Science and Engineering Wuhan Institute of Technology Beijing Key Laboratory of Pipeline Critical Technology and Equipment for Deepwater Oil & Gas Development Beijing Institute of Petrochemical Technology Key Laboratory for Large-Format Battery Materials and System Ministry of Education Hubei Key Laboratory of Materials Chemistry and Service Failure School of Chemistry and Chemical Engineering Huazhong University of Science and Technology

Sulfate-reducing bacteria（SRB） corrosion is one of the main reasons leading to the service failure of engineering materials in the marine environment. An understanding of SRB corrosion especially under continuous organic carbon starvation is required. In this work, SRB corrosion of X80 pipeline steel under continuous organic carbon starvation was studied using mass loss, electrochemical measurements, and surface analysis. The effects of initial SRB concentrations on steel corrosion were also studied and discussed. The results indicated that more than 99% population of SRB die after 21 d of testing in various conditions, but there are still amounts of SRB survivors. SRB survivors with continued organic carbon starvation have a better adaptive ability and accelerated steel corrosion. Both the uniform and localized corrosion rates are also proportional to the initial SRB concentration as well as SRB survivors. The localized corrosion rate and density of corrosion pits of specimen corresponding to an initial SRB count of 10～8 cells/m L reach bigger values of（0.693 ± 0.114） mm/y and（1.94 ± 0.39） ×10～4 pits/cm2, respectively, which are induced by the combination of the sessile and planktonic SRB.

关键词： Microbial corrosion Sulfate-reducing bacteria X80 steel Continued carbon starvation

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