Uncertain trajectory privacy-preserving method of moving object by Shuang WANG, Fu-cai ZHOU, Li-na WU

“…With the development of location based service(LBS) and location-aware devices，the amount of trajectories of moving objects collected by service providers was continuously increasing,meanwhile,it can cause great threaten for personal privacy.Most researches of trajectory privacy preserving were on deterministic data,however,trajectory’s uncertainty was inherent due to the inaccuracy of data acquisition equipment,delayed update,and so on.A new method was prosed to protect the privacy of trajectory data in publishing.It is the first time to present the idea that transforming the trajectory to an uncertain area to cluster.First,a probability statistics method to model the trajectory to an uncertain area was proposed.Second,the similar uncertain area into a cluster was put and sanitized in an equivalence class.Finally,the performance of the proposal was compared with (K δ)-anonymity model in real datasets.…”
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Impact of integration time steps of rain drop size distribution on their double-moment normalization: a case study in northern Benin by Moumouni, Sounmaïla, Akponi, Fulgence Payot, Zahiri, Eric-Pascal, Lawin, Agnidé Emmanuel, Gosset, Marielle

“…This study analyzed the sensitivity of the double-moment normalization of rain drop size distributions (DSDs) to their integration time steps. Six DSD datasets measured at different integration time steps were modeled by the double-moment normalization method. …”
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A case of gangrenous cystitis with bilateral hydronephrosis 10 years after radiotherapy by Mariko Oniwa, Yuki Kataoka, Midori Yamada, Takuya Miyagawa, Takuro Sunada, Hideyuki Konishi, Gen Suzuki, Yoko Fujita

“…She became anuric despite having an indwelling bladder catheter. Imaging studies revealed bladder wall thickening, bilateral hydroureter formation, and hydronephrosis. …”
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Bacteremia with an Unusual Pathogen: Mycobacterium neoaurum by Hesham Awadh, Munthir Mansour, Mahmoud Shorman

“…We report a case of M. neoaurum bacteremia in an immune competent host, with a chronically placed peripherally inserted central catheter (PICC line).…”
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Mediastinal Hematoma and Tracheal Compression following Transradial Percutaneous Coronary Intervention by Nathaniel R. Smilowitz, Muhamed Saric, Michael J. Attubato, James N. Slater

“…This case highlights the importance of careful guide catheter placement from the right radial approach. …”
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The Flow Separation of Peristaltic Transport for Maxwell Fluid between Two Coaxial Tubes by S. Z. A. Husseny, Y. Abd elmaboud, Kh. S. Mekheimer

“…The results show that the presence of the endoscope (catheter) tube in the artery increases the pressure gradient and shear stress. …”
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CLB-Defense: based on contrastive learning defense for graph neural network against backdoor attack by Jinyin CHEN, Haiyang XIONG, Haonan MA, Yayu ZHENG

“…For the problem that the existing backdoor attack defense methods are difficult to deal with irregular and unstructured discrete graph data to alleviate the threat of backdoor attacks, a backdoor attack defense method for GNN based on contrastive learning was proposed, namely CLB-Defense.Specifically, a contrastive model was built by using contrastive learning in an unsupervised way, which searches suspicious backdoored samples.Then the suspicious backdoored samples were reshaped by using the graph importance indexes and the label smoothing strategy, and the defense against graph backdoor attack was realized.Finally, extensive experimental results show that CLB-Defense realizes the effect of defense performance on four public datasets and five popular graph backdoor attacks, e.g., CLB-Defense can reduce the attack success rate by an average of 75.66% (compared with the baselines, an improvement of 54.01%).…”
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Research on Management Model Based on Deep Learning by Yuting Zhao

“…The training system is used with three available datasets from big company, health issue, and industry. …”
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Link prediction method based on matching degree of resource transmission for complex network by Shuxin LIU, Xing LI, Hongchang CHEN, Kai WANG

“…In order to solve the problem that many existing resource-transmission-based methods ignore the important influence of the matching degree of two endpoints on resource transmission,a link prediction method was proposed based on matching degree of resource transmission for complex networks.Firstly,by analyzing the two endpoints on the resource transmission path in detail,the method of quantifying the matching degree between two nodes was proposed.Then,in order to describe the influence of matching degree on resource transmission process between nodes,the matching degree of resource transmission was defined.Finally,based on the matching degree of resource transmission,a resource transmission matching index was proposed considering the resource amount of bidirectional transmission between nodes.The experimental results of nine datasets show that compared with other similarity indices,the proposed index can achieve higher prediction accuracy under the AUC and Precision metrics.…”
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Research on Image Recognition and Classification Algorithms in Cloud Computing Environment Based on Deep Neural Networks by Zheshu Jia

“…The integration of CNNs with cloud computing has significantly enhanced the speed, scalability, and usability, enabling the real-time analysis of extremely extensive picture datasets. This article discusses significant algorithms, including CNN architectures such as AlexNet, VGG, and ResNet-based models. …”
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Dependable identity recognition and authorization based on visual information by Chunlei PENG, Xinbo GAO, Nannan WANG, Jie LI

“…Recently,deep learning has been widely applied to video and image based identity recognition and authorization tasks,including face recognition and person identification.However,machine learning models,especially deep learning models,can be easily fooled by adversarial attacks,which may cause the identity recognition systems to make a wrong decision.Therefore,dependable identity recognition and authorization has become one of the hot topics currently.Recent advances on dependable identity recognition and authorization from both information space and physical space were presented,where the development of the attack models on face detection,face recognition,person re-identification,and face anti-spoofing as well as printable adversarial patches were introduced.The algorithms of visual identity anonymization and privacy protection were further discussed.Finally,the datasets,experimental protocols and performance of dependable identity recognition methods were summarized,and the possible directions in the future research were presented.…”
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Model split-based data privacy protection method for federated learning by CHEN Ka

“…To evaluate the proposed BLDP algorithm, experiments were conducted on four commonly benchmarked datasets and the leakage loss and model accuracy were analyzed. …”
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Generation and Evaluation of Multiple-choice Reading Comprehension Questions for Swedish by Dmytro Kalpakchi, Johan Boye

“…An extensive evaluation of the MCQ-generating capabilities of 12 different models, using this two-stage scheme, reveals that GPT-based models surpass smaller models that have been fine-tuned using small-scale datasets on this specific problem. …”
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Image cluster algorithm of hybrid encoding method by Chun-hui ZHAO, Xue-yuan LI, Ying CUI

“…In the clustering analysis based on swarm intelligence optimization algorithm,the most of encoding method only used single form,and this method might be limit range of search space,the algorithm was easy to fall into local op-timum.In order to solve this problem,image clustering algorithm of hybrid encoding (HEICA) was proposed.Firstly,a hybrid encoding model based on image clustering was established,this method could expand the scope of the search space.Meanwhile,it was combined with two optimization algorithms which improved rain forest algorithm (IRFA) and quantum particle swarm optimization (QPSO),this method could improve the global search capability.In the simulation experiment,it was carried out to illustrate the performance of the proposed method based on four datasets.Compared with results form four measured cluster algorithm.The experimental results show that the algorithm has strong global search capability,high stability and clustering effect.…”
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Time-variant interest community based query message routing algorithm in opportunity social network by Junlei BI, Zhiyuan LI

“…To solve the problem that the successful rate of resource query is low in opportunity social network,a query message routing algorithm based on time-variant interest community was proposed.Two well-known mobile social datasets were firstly analyzed,and then the temporal and spatial correlations of users were found.The time-variant interest communities based on temporal and spatial correlations of users were constructed.Next,a dynamic query routing on the constructed time-variant interest communities was proposed.Theoretical analysis shows that the proposed routing can run in O (nlog n) time.The comparisons between the proposed routing and state-of-the-art message delivery algorithms show that the proposed routing can keep high query success rate,reduce the average query latency and the hop count of a query and maintain low system overhead.…”
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New Lindley Generator Based on T-X Family of Distributions: Properties and Reliability Applications by Fatehi Yahya Eissa, Chhaya Dhanraj Sonar

“…Furthermore, we illustrate the practical applicability of this new family of distributions through the analysis of real-life datasets.…”
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Multi-channel based edge-learning graph convolutional network by Shuai YANG, Ruiqin WANG, Hui MA

“…Usually the edges of the graph contain important information of the graph.However, most of deep learning models for graph learning, such as graph convolutional network (GCN) and graph attention network (GAT), do not fully utilize the characteristics of multi-dimensional edge features.Another problem is that there may be noise in the graph that affects the performance of graph learning.Multilayer perceptron (MLP) was used to denoise and optimize the graph data, and a multi-channel learning edge feature method was introduced on the basis of GCN.The multi-dimensional edge attributes of the graph were encoded, and the attributes contained in the original graph were modeled as multi-channel.Each channel corresponds to an edge feature attribute to constrain the training of graph nodes, which allows the algorithm to learn multi-dimensional edge features in the graph more reasonably.Experiments based on Cora, Tox21, Freesolv and other datasets had proved the effectiveness of denoising methods and multi-channel methods.…”
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An end-to-end implicit neural representation architecture for medical volume data. by Armin Sheibanifard, Hongchuan Yu, Zongcai Ruan, Jian J Zhang

“…This approach significantly reduces GPU memory requirements and processing time, making it a practical solution for handling large medical datasets.…”
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Co-pairwise ranking model for item recommendation by Bin WU, Yun CHEN, Zhongchuan SUN, Yangdong YE

“…Most of existing recommendation models constructed pairwise samples only from a user’s perspective.Nevertheless,they overlooked the functional relationships among items--A key factor that could significantly influence user purchase decision-making process.To this end,a co-pairwise ranking model was proposed,which modeled a user’s preference for a given item as the combination of user-item interactions and item-item complementarity relationships.Considering that the rank position of positive sample and the negative sampler had a direct impact on the rate of convergence,a rank-aware learning algorithm was devised for optimizing the proposed model.Extensive experiments on four real-word datasets are conducted to evaluate of the proposed model.The experimental results demonstrate that the devised algorithm significantly outperforms a series of state-of-the-art recommendation algorithms in terms of multiple evaluation metrics.…”
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Shrinkage Methods for Estimating the Shape Parameter of the Generalized Pareto Distribution by Wilhemina Adoma Pels, Atinuke O. Adebanji, Sampson Twumasi-Ankrah, Richard Minkah

“…The proposed estimators are illustrated with practical datasets from climate and insurance studies.…”
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