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International Joint Conference on Neural Networks (IJCNN)

作者： Mingshan Du Hongxia Wang Rui Zhang Zihan Yan School of Cyber Science and Engineering Sichuan University Chengdu China Key Laboratory of Data Protection and Intelligent Management (Sichuan University) Ministry of Education China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Song voice conversion tools have gained more and more popularity in the recent past. People have been uploading their self-made forgery songs on video websites, and these songs have been converted in timbre. However, singing voice conversion technology may cause copyright infringement of the songs. In order to protect the copyright of songs, the method of singing voice conversion detection needs to be investigated. We propose Rhythm and Pitch Aware Songs Conversion Detection (RPA-SCD), a dual-branch network for song voice conversion detection. RPA-SCD can predict forged song fragments through rhythm and pitch which are the global and local information of music. To evaluate the proposed method, we contribute a multilingual song conversion detection(MSCD) dataset. Our proposed model achieves the EER of 2.30% in the original domain of MSCD, which is lower than other benchmarks for speech forgery detection. The experiments show that our approach achieves state-of-the-art performance on the song conversion detection task. The MSCD dataset can be found at https://***/file/d/1rFsvMYihVtk81uFbL7UpyUEs-qBgsX6H/view?usp=drive_link. The code can be found at https://***/Samantha-Du/RPA-SDD.

关键词： Codes Neural networks Speech enhancement Copyright protection Benchmark testing Rhythm Forgery

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Adaptive Video Watermarking with Perceptual Guarantee and Efficiency Optimization

Adaptive Video Watermarking with Perceptual Guarantee and Ef...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Fei Zhang Hongxia Wang Mingze He Ling Yang Jinhe Li School of Cyber Science and Engineering Sichuan University Chengdu China Key Laboratory of Data Protection and Intelligent Management (Sichuan University) Ministry of Education China

Existing video watermarking embeds robust watermarks in each frame of the video for copyright protection and tracking. However, just as any content written on a blank paper is easily perceived, embedding watermarks in the texture-poor frames impairs imperceptibility. Common geometric attacks such as scaling and rotation pose a significant challenge to the existing video watermarking. Image watermarking based on moments is robust against geometric attacks. However, moment-based watermarking is difficult to migrate to the video due to its lack of perceptual guarantee and high computational cost. In this paper, we propose an adaptive video watermarking scheme by exploring the relationship between moments and video textures, which can adaptively select texture-rich frames to embed watermarks for perceptual guarantee. Furthermore, we utilize the properties of moment calculation in videos to optimize efficiency. Extensive experiments show that the proposed method can achieve better imperceptibility than existing methods while maintaining strong robustness.

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A possible initiation mechanism of Muztag rock avalanche induced by nearby fault creep

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Earth Surface Processes and Landforms 2025年第6期50卷

作者： Yingbin Zhang Qingdong Wang Pengcheng Yu Lei Wang Zhongkun Zhang Jianxian He Yao Xiao Xinyan Peng Wenfang Wang Qiangong Cheng Marco Bohnhoff State Key Laboratory of Intelligent Geotechnics and Tunnelling Southwest Jiaotong University Chengdu China Department of Civil Engineering School of Civil Engineering Lanzhou Jiaotong University Lanzhou China Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences Potsdam Germany State Key Laboratory of Geo-Hazard Prevention and Geo-Environment Protection Chengdu University of Technology Chengdu China MOE Key Laboratory of Deep Earth Science and Engineering Institute for Disaster Management and Reconstruction Sichuan University Chengdu China Lanzhou Petrochemical University of Vocational Technology Lanzhou Gansu China Department of Geological Engineering Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University Chengdu China

Rock avalanches are catastrophic events that can be triggered by various geological and climatic factors. Large-scale rock avalanches have been observed near fault zones, indicating a potential relationship between fault creep motions and the initiation of rock avalanches. This study proposes a physical mechanism that explains how fault creep leads to the initiation of near-fault rock avalanches through stress redistribution. The Muztag rock avalanche which occurred near the Muztag fault in Muztag Ata, Kashgar, China is revisited using field measurements and numerical modelling. We consider the Muztag rock avalanche model with its initial slope toe supported by a portion of the fault's hanging wall. Site-specific numerical simulations using discontinuous deformation analysis (DDA) reveal that fault creep initially generates localized stress concentrations at the slope toe. Once the slope toe completely detaches from the hanging wall, the slope toe fails when the accumulated stress exceeds the local strength, resulting in a sharp stress drop. This stress redistribution triggers consecutive failure at the bottom of the rear edge and middle slope, forming a through-going shear sliding surface, which leads to the initiation of the overall rock avalanche. The kinematic processes of the avalanche, including sliding distance and deposit thickness, as modelled by DDA, are consistent with the post-failure characteristics of the Muztag rock avalanche. These findings suggest that tectonic fault creep motions can play a significant role in inducing near-fault rock avalanches.

关键词： discontinuous deformation analysis (DDA) fault creep initiation mechanism rock avalanche stress concentration

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Tri-level combination for image representation 17th

Tri-level combination for image representation

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17th Pacific-Rim Conference on Multimedia, PCM 2016

作者： Li, Ruiying Zhang, Chunjie Huang, Qingming School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783319488899

The context of objects can provide auxiliary discrimination beyond objects. However, this effective information has not been fully explored. In this paper, we propose Tri-level Combination for Image Representation (TriCoIR) to solve the problem at three different levels: object intrinsic, strongly-related context and weakly-related context. Object intrinsic excludes external disturbances and more focuses on the objects themselves. Strongly-related context is cropped from the input image with a more loose bound to contain surrounding context. Weaklyrelated one is recovered from the image other than object for global context. First, strongly and weakly-related context are constructed from input images. Second, we make cascade transformations for more intrinsical object information, which depends on the consistency between generated global context and input images in the regions other than object. Finally, a joint representation is acquired based on these three level features. The experiments on two benchmark datasets prove the effectiveness of TriCoIR. © Springer International Publishing AG 2016.

关键词： Image representation

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Theory-screened Prussian blue analogues-based nanozymes for promoting diabetic wound healing via ferroptosis inhibition

Materials Today Bio

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Materials Today Bio 2025年 32卷

作者： Qingrong Dong Xiaomei Shen Ge Fang Jia Shi Xiafeng Zhu Jiangfeng Du Hui Zhang Cuicui Ge Department of Medical Imaging First Hospital of Shanxi Medical University Taiyuan 030001 China State Key Laboratory of Radiation Medicine and Protection School of Radiation Medicine and Protection Collaborative Innovation Center of Radiological Medicine of Jiangsu Higher Education Institutions Soochow University Suzhou 215123 China Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province Taiyuan 030001 China College of Chemistry and Materials Jiangxi Normal University Nanchang 330022 China College of Pharmacy Academy of Medical Sciences Shanxi Medical University Jinzhong 030619 China

Diabetes mellitus (DM) induced wound healing impairment remains a serious health problem, which can lead to limb amputation and even shorten life span. Inhibiting ferroptosis of endothelial cells has shown promise in promoting tissue repair and regeneration. However, a majority of known ferroptosis inhibitors belong to either antioxidants or iron-chelators but with poor pharmacological adherence and even serious side effects. Herein, we construct a series of Prussian blue analogues-based nanozymes as ferroptosis nano-inhibitors to simultaneously achieve highly efficient intracellular iron capture and antioxidant properties. Through computational and experimental methods, the optimized Prussian blue analogues (MPBs) with highest iron chelating efficiency and efficacy (CuPBs) are screened out and both the CuPBs and the post-chelated products have been demonstrated to exhibit reactive oxygen species (ROS)-scavenging activities. As expected, the CuPBs successfully inhibit ferroptosis in high glucose-cultured skin repair cells, thereby repairing their proliferation, migration and angiogenesis. Mechanistically, the CuPBs regulate ferroptosis by inhibiting iron accumulation and improving the antioxidant capacity of the Xc − -GPX4 system. Moreover, in a murine diabetic wound model, the CuPBs remarkably promote the wound healing by inhibiting ferroptosis and increasing the M2/M1 macrophage ratio, showing a 2-fold higher wound closure rate than deferoxamine (DFO). Collectively, our study presents a general design strategy on developing ferroptosis nano-inhibitors and provides a promising approach for treating ferroptosis-related diseases.

关键词： Diabetic wound Ferroptosis inhibition Iron chelation Prussian blue analogue ROS-scavenging activity

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Differential Urban-Rural Inequalities and Driving Mechanisms of Pm2.5 Exposure in Urban Agglomerations - Evidence from the Central Plains Urban Agglomeration, China

SSRN

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SSRN 2025年

作者： Sun, Xiaofan Wang, Chengyuan Ji, Yaqin Dang, Qiuling Fu, Zhicong Mao, Xuegang Wang, Enheng Jiang, Yan State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China College of Forestry Northeast Forestry University Harbin150040 China Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education Northeast Forestry University Harbin150040 China Research and Development Center of Big Data for Ecosystem Northeast Forestry University Harbin150040 China College of Environmental Science and Engineering Nankai University Tianjin300350 China State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control Tianjin300350 China College of Materials and Energy Lanzhou University Lanzhou730137 China

Exposure to PM2.5 poses severe risks to public health and sustainable development, with exposure inequalities exacerbated by variations in atmospheric activity and uneven regional development. However, the urban−rural inequalities and natural−human driving mechanisms underlying PM2.5 exposure inequalities within urban agglomerations are poorly understood. Taking the Central Plains Urban Agglomeration (CPUA) in China as an example, this study investigated the spatio-temporal variations of PM2.5 and considered its future trends. The Theil index was employed to quantify PM2.5 exposure inequalities. An interpretable machine learning model (RF-SHAP) was applied to identify the natural and socioeconomic driving factors. We found that 99.68% of the CPUA exhibited a decreasing trend in ground-level PM2.5. The overall Theil index decreased from 0.168 to 0.142, with a rural decline from 0.115 to 0.084, suggesting an overall reduction in air pollution, particularly in rural areas. Conversely, the urban Theil index increased from 0.096 to 0.208, highlighting an increasing disparity in urban PM2.5 exposure. Resource-based cities, such as Changzhi, Jincheng, and Jiaozuo, exhibited the largest PM2.5 exposure inequality. Elevation was identified as the dominant factor influencing overall and rural PM2.5 exposure inequalities, while population density was the primary driver of urban inequalities. This study highlighted the differences in urban−rural PM2.5 inequalities and their drivers at the city agglomeration scale. The aims were to mitigate PM2.5 exposure inequalities through socio-environmental systems, provide evidence for the integrated management of PM2.5 exposure inequalities in city agglomerations, and support regional sustainable development. © 2025, The Authors. All rights reserved.

关键词： Health risks

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Research on Knowledge Graph Construction for Emergency Resource management 12

Research on Knowledge Graph Construction for Emergency Resou...

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12th International Symposium on Project management, ISPM 2024

作者： Zhang, Kehong Wang, Min Zhou, Chenjie School of Information Engineering and Artificial Intelligence Lanzhou University of Finance and Economics Gansu Lanzhou730030 China Gansu Provincial Key Laboratory of Intelligent Business China "Belt and Road" Intellectual Property Protection and Data Utilization Industrial Research Institute China

ISBN: (纸本)9798331302344

Emergency resource management is a very important part of the public affairs emergency management system, once the emergence of public emergencies requires timely and efficient emergency rescue response, and rapid emergency rescue capabilities must rely on scientific and reasonable emergency resource management scheduling. Therefore, this paper addresses the problem of emergency resource management scheduling, the application of knowledge mapping technology to build an emergency resource decision-making system, combining the government, enterprises and other social forces, collaborative cooperation, to ensure a rapid response in the event of emergencies, and improve the efficiency of emergency rescue. In this paper, we obtain the original text from the emergency management website through web crawlers and label the entity relationship types to complete the construction of the dataset;on this basis, the entity relationships are objectively displayed through the Neo4j graph database to complete the creation of the knowledge graph of emergency resource scheduling. The constructed knowledge graph is reliable and can provide a scientific program for emergency management scheduling. © 2024 ISPM. All Rights Reserved.

关键词： Knowledge graph

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Semi-Supervised Image Manipulation Localization with Residual Enhancement

SSRN

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SSRN 2024年

作者： Zeng, Qiang Wang, Hongxia Zhou, Yang Zhang, Rui Meng, Sijiang School of Cyber Science and Engineering Sichuan University Chengdu610065 China Key Laboratory of Data Protection and Intelligent Management Sichuan University Ministry of Education China

Images have become a significant medium for information transmission, while image forensics has garnered widespread attention from researchers. Due to the scarcity of finely annotated images in the field of image manipulation detection and localization, existing methods for locating manipulated images can only utilize a limited amount of data for model training. However, deep learning models typically require a large number of finely annotated images to fully leverage their powerful fitting capabilities. In this paper, we propose a semi-supervised image manipulation localization framework, employing semi-supervised learning to use unannotated images for deep learning model training. To achieve this goal, we first design a residual enhancement module that contains an encoding-decoding structure. The regression target of this branch is the pristine regions in the images to generate the reconstructed images. Next, we perform a residual operation between the reconstructed and original images to roughly locate the anomalous regions and refine the features extracted by the encoder. Secondly, we employ weakly-supervised learning by adding an image-level classification head to the final layer of the encoder. The classification head generates a class active map based on image-level classification results, which further guides the model's feature augmentation. Finally, we formulate a specialized semi-supervised framework tailored for image manipulation detection, enabling the utilization of a large volume of unannotated data for model training. Extensive experimental results highlight the notable efficacy of the proposed approach, and outperforms state-of-the-art approaches by a significant margin of 22.5 on the mean of F1 metrics across various benchmark datasets. © 2024, The Authors. All rights reserved.

关键词： Image enhancement

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A mutual authentication lightweight rfid protocol for iot devices 2nd

A mutual authentication lightweight rfid protocol for iot de...

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2nd International Cognitive Cities Conference, IC3 2019

作者： Lu, Yong Wang, Anxi Liu, Shuai School of Management Science and Engineering Nanjing University of Information Science and Technology Nanjing210044 China Guizhou Provincial Key Laboratory of Public Big Data GuiZhou University GuiyangGuizhou550025 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou510632 China

ISBN: (纸本)9789811561122

The IoT data security is a hot topic at a data time. Personal privacy data may be easily leaked to data collectors in an open network environment. If the collectors get enough data, they can analyze the habit and interest of every IoT user, which may give helpful advice or cause endless harass. RFID authentication protocol in IoT is a powerful way to avoid the essential data leaked to data collectors. The previous protocols protect the security of RFID system. But they cannot guard the privacy of RFID system. The protocol we proposed achieves both the privacy and security. © Springer Nature Singapore Pte Ltd 2020.

关键词： Internet of things

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Accumulative Time Based Ranking Method to Reputation Evaluation in Information Networks

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Journal of Computer Science & Technology 2022年第4期37卷 960-974页

作者： Hao Liao Qi-Xin Liu Ze-Cheng Huang Ke-Zhong Lu Chi Ho Yeung Yi-Cheng Zhang National Engineering Laboratory on Big Data System Computing Technology College of Computer Science and SoftwareEngineeringShenzhen UniversityShenzhen 518060China Guangdong Province Key Laboratory of Popular High Performance Computers Shenzhen UniversityShenzhen 518060China Guangdong Province Engineering Center of China-Made High Performance Data Computing System College of ComputerScience and Software EngineeringShenzhen UniversityShenzhen 518060China Institute of Big Data Intelligent Management and Decision Shenzhen UniversityShenzhen 518060China Department of Science and Environmental Studies The Education University of Hong KongHong Kong 999077China Department of Physics University of FribourgFribourg 1700Switzerland

Due to over-abundant information on the Web, information filtering becomes a key task for online users to obtain relevant suggestions and how to extract the most related item is always a key topic for researchers in various fields. In this paper, we adopt tools used to analyze complex networks to evaluate user reputation and item quality. In our proposed Accumulative Time Based Ranking (ATR) algorithm, we take into account the growth record of the network to identify the evolution of the reputation of users and the quality of items, by incorporating two behavior weighting factors which can capture the hidden facts on reputation and quality dynamics for each user and item respectively. Our proposed ATR algorithm mainly combines the iterative approach to rank user reputation and item quality with temporal dependence compared with other reputation evaluation methods. We show that our algorithm outperforms other benchmark ranking algorithms in terms of precision and robustness on empirical datasets from various online retailers and the citation datasets among research publications. Therefore, our proposed method has the capability to effectively evaluate user reputation and item quality.

关键词： temporal network behavior dynamics reputation evaluation ranking algorithm

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