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A robust tensor watermarking algorithm for diffusion-tensor images

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Frontiers of Information Technology & Electronic Engineering 2024年第3期25卷 384-397页

作者： Chengmeng LIU Zhi LI Guomei WANG Long ZHENG State Key Laboratory of public big data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China

Watermarking algorithms that use convolution neural networks have exhibited good robustness in studies of deep learning ***,after embedding watermark signals by convolution,the feature fusion eficiency of convolution is relatively low;this can easily lead to distortion in the embedded *** distortion occurs in medical images,especially in diffusion tensor images(DTIs),the clinical value of the DTI is *** address this issue,a robust watermarking algorithm for DTIs implemented by fusing convolution with a Transformer is proposed to ensure the robustness of the watermark and the consistency of sampling distance,which enhances the quality of the reconstructed image of the watermarked DTIs after embedding the watermark *** the watermark-embedding network,Ti-weighted(Tlw)images are used as prior *** correlation between T1w images and the original DTI is proposed to calculate the most significant features from the T1w images by using the Transformer *** maximum of the correlation is used as the most significant feature weight to improve the quality of the reconstructed *** the watermark extraction network,the most significant watermark features from the watermarked DTI are adequately learned by the Transformer to robustly extract the watermark signals from the watermark *** results show that the average peak signal-to-noise ratio of the watermarked DTI reaches 50.47 dB,the diffusion characteristics such as mean diffusivity and fractional anisotropy remain unchanged,and the main axis deflection angleαAc is close to *** proposed algorithm can effectively protect the copyright of the DTI and barely affects the clinical diagnosis.

关键词： Robust watermarking algorithm Transformer Image reconstruction Diffusion tensor images Soft attention Hard attention Tl-weighted images

Diffusion of nanochannel-confined knot along a tensioned polymer

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Communications in Theoretical Physics 2024年第4期76卷 158-166页

作者： Guobing Cai Yong Li Yuyu Feng Zhouhui Deng Yanhui Liu College of Physics Guizhou UniversityGuiyang 550025China Kechuang Industrial Development Company Limited Guian New AreaGuiyang 550025China State Key Laboratory of public big data Guizhou UniversityGuiyang 550025China

The knots frequently occur in biopolymer and their diffusion plays an active role in the gene *** this work,Langevin dynamics simulations were carried out to detect the diffusion behaviours of a knot along a tensioned polymer in different spatial *** polymer accommodating a knot was tethered to two macrospheres to block the unravelling of the *** a result,the curves for the diffusion coefficients of the knot with different bending stiffness as a function of the tension in different spatial constraints were *** the space without constraints or with weak constraints,the corresponding curves for the knot with relatively large bending stiffness exhibited two turnover *** the contrary,for the knot with relatively small bending stiffness,the diffusion coefficients were monotonically reduced with increasing ***,in a space with strong constraints,all the curves showed one turnover behaviour regardless of the bending *** turnover behaviours divided the curves into different regimes,and the dominant diffusion mechanisms in the regimes,namely,knot-region breathing,self-reptation,and internal friction,were clearly *** effective friction coefficientsξof the knots with 3_(1),4_(1),5_(1) and 5_(2) types as a function of the knot size N at a fixed tension were well fitted by the relationξ∝*** effective friction coefficients of the knots at relatively large tension f>3 sharply increased with the knot complexity,which is not dependent on the spatial *** contrast,the values of these coefficients at relatively small tension f≤3 were remarkably dependent on the spatial *** work not only provides valuable simulation results to assist the understanding of the diffusion of DNA knot,but also highlights the single-molecule design for the manipulation of DNA knots in future.

关键词： knot langevin dynamics simulations diffusion coefficient self-reptation knot-region breathing internal friction

Enhancing Tea Leaf Disease Identification with Lightweight MobileNetV2

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Computers, Materials & Continua 2024年第7期80卷 679-694页

作者： Zhilin Li Yuxin Li Chunyu Yan Peng Yan Xiutong Li Mei Yu Tingchi Wen Benliang Xie College of big data and Information Engineering Guizhou UniversityGuiyang550025China Power Semiconductor Device Reliability Engineering Center of the Ministry of Education Guiyang550025China State Key Laboratory of public big data Guizhou UniversityGuiyang550025China The Mushroom Research Centre Guizhou UniversityGuiyang550025China The Engineering Research Center of Southwest Bio-Pharmaceutical Resources Ministry of EducationGuizhou UniversityGuiyang550025China

Diseases in tea trees can result in significant losses in both the quality and quantity of tea *** monitoring can help to prevent the occurrence of large-scale diseases in tea ***,existingmethods face challenges such as a high number of parameters and low recognition accuracy,which hinders their application in tea plantation monitoring *** paper presents a lightweight I-MobileNetV2 model for identifying diseases in tea leaves,to address these *** proposed method first embeds a Coordinate Attention(CA)module into the originalMobileNetV2 network,enabling the model to locate disease regions ***,a Multi-branch Parallel Convolution(MPC)module is employed to extract disease features across multiple scales,improving themodel’s adaptability to different disease ***,the AutoML for Model Compression(AMC)is used to compress themodel and reduce computational *** results indicate that our proposed algorithm attains an average accuracy of 96.12%on our self-built tea leaf disease dataset,surpassing the original MobileNetV2 by 1.91%.Furthermore,the number of model parameters have been reduced by 40%,making itmore suitable for practical application in tea plantation environments.

关键词： Disease identification coordinate attention mechanism multi-scale feature extraction model pruning

Image Recognition Model of Fraudulent Websites Based on Image Leader Decision and Inception-V3 Transfer Learning

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China Communications 2024年第1期21卷 215-227页

作者： Shengli Zhou Cheng Xu Rui Xu Weijie Ding Chao Chen Xiaoyang Xu Information Department of Zhejiang Police College Hangzhou 310053China Hangzhou Dianzi University Hangzhou 310018China big data Laboratory of Zhejiang Police College Hangzhou 310053China Hangzhou public Security Bureau Hangzhou 310002China

The fraudulent website image is a vital information carrier for telecom *** efficient and precise recognition of fraudulent website images is critical to combating and dealing with fraudulent *** research on image recognition of fraudulent websites is mainly carried out at the level of image feature extraction and similarity study,which have such disadvantages as difficulty in obtaining image data,insufficient image analysis,and single identification *** study develops a model based on the entropy method for image leader decision and Inception-v3 transfer learning to address these *** data processing part of the model uses a breadth search crawler to capture the image ***,the information in the images is evaluated with the entropy method,image weights are assigned,and the image leader is *** model training and prediction,the transfer learning of the Inception-v3 model is introduced into image recognition of fraudulent *** selected image leaders to train the model,multiple types of fraudulent websites are identified with high *** experiment proves that this model has a superior accuracy in recognizing images on fraudulent websites compared to other current models.

关键词： fraudulent website image leaders telecom fraud transfer learning

Source Camera Identification Algorithm Based on Multi-Scale Feature Fusion

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Computers, Materials & Continua 2024年第8期80卷 3047-3065页

作者： Jianfeng Lu Caijin Li Xiangye Huang Chen Cui Mahmoud Emam School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Shangyu institute of Science and Engineering Hangzhou Dianzi UniversityShaoxing312300China Key Laboratory of public Security Information Application Based on big-data Architecture Ministry of Public SecurityZhejiang Police CollegeHangzhou310000China Faculty of Artificial Intelligence Menoufia UniversityShebin El-Koom32511Egypt

The widespread availability of digital multimedia data has led to a new challenge in digital *** source camera identification algorithms usually rely on various traces in the capturing ***,these traces have become increasingly difficult to extract due to wide availability of various image processing *** Neural Networks(CNN)-based algorithms have demonstrated good discriminative capabilities for different brands and even different models of camera ***,their performances is not ideal in case of distinguishing between individual devices of the same model,because cameras of the same model typically use the same optical lens,image sensor,and image processing algorithms,that result in minimal overall *** this paper,we propose a camera forensics algorithm based on multi-scale feature fusion to address these *** proposed algorithm extracts different local features from feature maps of different scales and then fuses them to obtain a comprehensive feature *** representation is then fed into a subsequent camera fingerprint classification *** upon the Swin-T network,we utilize Transformer Blocks and Graph Convolutional Network(GCN)modules to fuse multi-scale features from different stages of the backbone ***,we conduct experiments on established datasets to demonstrate the feasibility and effectiveness of the proposed approach.

关键词： Source camera identification camera forensics convolutional neural network feature fusion transformer block graph convolutional network

An Innovative K-Anonymity Privacy-Preserving Algorithm to Improve data Availability in the Context of big data

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Computers, Materials & Continua 2024年第4期79卷 1561-1579页

作者： Linlin Yuan Tiantian Zhang Yuling Chen Yuxiang Yang Huang Li State Key Laboratory of public big data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China College of Information Engineering Guizhou Open UniversityGuiyang550025China Guizhou Academy of Tobacco Science Guiyang550025China

The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more *** K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big ***,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data *** addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be *** on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data ***,we construct a new information loss function based on the information quantity *** that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss *** addition,to reduce information loss,we improve K-anonymity in two ***,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering *** addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of ***,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information ***,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.

关键词： Blockchain big data K-anonymity 2-means clustering greedy algorithm mean-center method

An extended social force model on unidirectional flow considering psychological and behavioral impacts of hazard source

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Chinese Physics B 2024年第2期33卷 567-576页

作者：邓凯丰李梦胡祥敏陈涛 institute of public safety Research Department of Engineering PhysicsTsinghua UniversityBeijing 100084China Anhui Province Key Laboratory of Human safety Hefei 230601China Beijing Key Laboratory of Comprehensive Emergency Response Science Beijing 100084China

An accurate assessment of the evacuation efficiency in case of disasters is of vital importance to the safety design of buildings and street *** sources not only physically but psychologically affect the pedestrians,which may further alter their behavioral *** effect is especially significant in narrow spaces,such as corridors and *** study aims to integrate a non-spreading hazard source into the social force model following the results from a previous experiment and simulation,and to simulate unidirectional pedestrian flows over various crowd densities and clarity–intensity properties of the hazard *** integration include a virtual repulsion force from the hazard source and a decay on the social force *** simulations reveal(i)that the hazard source creates virtual bottlenecks that suppress the flow,(ii)that the inter-pedestrian push forms a stabilisation phase on the flow-density curve within medium-to-high densities,and(iii)that the pedestrians are prone to a less orderly and stable pattern of movement in low clarity–intensity scenarios,possibly with lateral collisions passing the hazard source.

关键词： evacuation social force model hazard source unidirectional pedestrian flow

Economic Development and Social Integration of Migrants in China

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China & World Economy 2024年第1期32卷 1-20页

作者： Guangjun Shen Chuanchuan Zhang Lingnan College Sun Yat-sen UniversityChina School of Economics and institute for Fiscal big data and Policy Zhejiang UniversityChina

Migrants often face challenges in social *** a nationally representative sample of migrant workers and employing the epidemiological approach,this paper examines the determinants of social *** finds that,conditional on a set of individual features,the migrants from less-developed provinces have greater difficulty in integrating into local *** results still demonstrate robustness across alternative variables,samples,and various *** analysis shows that educational and employment factors account for over 40 percent of the variance in social integration levels,suggesting their significant ***,the analysis suggests that native bias against migrants,along with misunderstandings between them,may account for part of the remaining variation in social integration ***,the ability to speak local dialects has been identified as a crucial factor that can significantly improve migrants'subjective experience of integrating into a new *** identifying one specific cause of social integration,this paper provides information to individuals and governments and assists them to improve social integration.

关键词： economic development epidemiologic approach migrant social integration

A Survey of LLM datasets:From Autoregressive Model to AI Chatbot

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Journal of Computer Science & Technology 2024年第3期39卷 542-566页

作者：杜非马新建杨婧如柳熠罗超然王学斌姜海鸥景翔 National Key Laboratory of data Space Technology and System Beijing 100195China Advanced institute of big data Beijing 100195China Fu Foundation School of Engineering and Applied Science Columbia UniversityNY 10027U.S.A. School of Software and Microelectronics Peking UniversityBeijing 100091China CCF IEEE

Since OpenAI opened access to ChatGPT,large language models(LLMs)become an increasingly popular topic attracting researchers’attention from abundant ***,public researchers meet some problems when developing LLMs given that most of the LLMs are produced by industries and the training details are typically *** datasets are an important setup of LLMs,this paper does a holistic survey on the training datasets used in both the pre-train and fine-tune *** paper first summarizes 16 pre-train datasets and 16 fine-tune datasets used in the state-of-the-art ***,based on the properties of the pre-train and fine-tune processes,it comments on pre-train datasets from quality,quantity,and relation with models,and comments on fine-tune datasets from quality,quantity,and *** study then critically figures out the problems and research trends that exist in current LLM *** study helps public researchers train and investigate LLMs by visual cases and provides useful comments to the research community regarding data *** the best of our knowledge,this paper is the first to summarize and discuss datasets used in both autoregressive and chat *** survey offers insights and suggestions to researchers and LLM developers as they build their models,and contributes to the LLM study by pointing out the existing problems of LLM studies from the perspective of data.

关键词： large language model(LLM) autoregressive model AI chatbot natural language processing(NLP)corpora OpenAI