检索结果-内蒙古大学图书馆

IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Xin Shen Weijian Huang Jing Gong Zhixin Sun School of Science Nanjing University of Posts and Telecommunications Nanjing China Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781665421751

Graph neural network, with its powerful learning ability, has become a cutting-edge method of processing ultra-large-scale network data. In order to polished up the representation accuracy of embedding, the key is to find the intrinsic geometric metric of the complex network. Since the real data is mostly scale-free network, the embedding accuracy of traditional models is still limited by the dimensionality of the euclidean space and computational complexity. Therefore, the hyperbolic embedding, whose metric properties conform to the power-law distribution and tree-like hierarchical structure of the complex network, will effectively approximates the latent low-dimensional manifold of the data distribution. This paper proposes an auto-encoder in hyperbolic space (HVGAE), taking full use of hyperbolic graph convolutional (HGCN) and the idea of variational autoencoder. Under the optimal combination of the encoder module, competitive results have been achieved in different real scenarios.

关键词： Measurement Geometry Representation learning Manifolds Computational modeling Complex networks data models

来源：评论

学校读者我要写书评

暂无评论

Prudent Promotion, Steady Development: Capability and Safety Considerations for Applying Large Language Models in Medicine 1

引用

1st International Artificial Intelligence Conference, IAIC 2023

作者： Xu, Sheng Chen, Shuwen Chen, Mike School of Physics and Information Engineering Jiangsu Second Normal University Nanjing211200 China Jiangsu Province Engineering Research Center of Basic Education Big Data Application Nanjing211200 China

ISBN: (数字)9789819712809

ISBN: (纸本)9789819712793

The powerful capabilities of large language models (LLMs) in the medical field have been affirmed by various benchmark tests. However, safety assessments are indispensable for high-risk medical applications. We systematically analyzed LLMs, including their technical principles, applicability in healthcare, medical capability assessment, potential security risks, and countermeasures. The study found that LLMs demonstrate strong capabilities in medical text processing, decision support, and text generation, but also have risks like "hallucination". To ensure safe and effective applications of LLMs, we analyzed the causes of hallucination and proposed using output detection and prompting techniques to mitigate hallucinations generated by LLMs. The results affirm that LLMs can advance AI innovation in healthcare, but need to be introduced prudently without comprehensive safety assessments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Medical applications

来源：评论

学校读者我要写书评

暂无评论

A Survey of Internet of Things in Healthcare 29th

A Survey of Internet of Things in Healthcare

引用

29th International Conference on Computational and Experimental engineering and Sciences, ICCES 2023

作者： Chen, Shuwen Wang, Jiaji Song, Zhijun School of Physics and Information Engineering Jiangsu Second Normal University Nanjing211200 China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom Jiangsu Province Engineering Research Center of Basic Education Big Data Application Nanjing211200 China State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China

ISBN: (纸本)9783031449468

With the rapid development of computers, Internet of Things (IoT) technology is becoming more and more closely integrated with the healthcare sector. This article introduces two major applications of IoT in healthcare: hospital information management and remote healthcare. In digitizing the healthcare industry, it is a great challenge to avoid the leakage of private medical data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

research on Tensor Multi-Clustering Distributed Incremental Updating Method for big data

引用

Computers, Materials & Continua 2024年第10期81卷 1409-1432页

作者： Hongjun Zhang Zeyu Zhang Yilong Ruan Hao Ye Peng Li Desheng Shi School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing210023China Ministry of Science and Technology Innovation China Communications Services Corporation LimitedBeijing100071China School of Artificial Intelligence The University of ManchesterManchesterM139PLUK Ministry of Technology Innovation China Telecom Artificial Intelligence Technology(Beijing)Corporation LimitedBeijing100032China Ministry of Science and Technology Innovation Zhongbo Information Technology Research Institute Corporation LimitedNanjing210012China Jiangsu Postal Big Data Technology and Application Engineering Research Center Nanjing University of Posts and TelecommunicationsNanjing210003China

The scale and complexity of big data are growing continuously,posing severe challenges to traditional data processing methods,especially in the field of clustering *** address this issue,this paper introduces a new method named big data Tensor Multi-Cluster Distributed Incremental Update(BDTMCDIncreUpdate),which combines distributed computing,storage technology,and incremental update techniques to provide an efficient and effective means for clustering ***,the original dataset is divided into multiple subblocks,and distributed computing resources are utilized to process the sub-blocks in parallel,enhancing ***,initial clustering is performed on each sub-block using tensor-based multi-clustering techniques to obtain preliminary *** new data arrives,incremental update technology is employed to update the core tensor and factor matrix,ensuring that the clustering model can adapt to changes in ***,by combining the updated core tensor and factor matrix with historical computational results,refined clustering results are obtained,achieving real-time adaptation to dynamic *** experimental simulation on the Aminer dataset,the BDTMCDIncreUpdate method has demonstrated outstanding performance in terms of accuracy(ACC)and normalized mutual information(NMI)metrics,achieving an accuracy rate of 90%and an NMI score of 0.85,which outperforms existing methods such as TClusInitUpdate and TKLClusUpdate in most ***,the BDTMCDIncreUpdate method offers an innovative solution to the field of big data analysis,integrating distributed computing,incremental updates,and tensor-based multi-clustering *** not only improves the efficiency and scalability in processing large-scale high-dimensional datasets but also has been validated for its effectiveness and accuracy through *** method shows great potential in real-world applications where dynamic data growth is common,and it is of significant imp

关键词： Tensor incremental update distributed clustering processing big data

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Dynamic Testing technology source code XSS vulnerability detection method

A Hybrid Dynamic Testing technology source code XSS vulnerab...

引用

Smart World Congress (SWC), IEEE

作者： Xubin Wang Yuhua Xu Zhixin Sun Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Research and Development Center of Post Industry Technology of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing China Engineering Research Center of Broadband Wireless Communication Technology of the Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

Presently power network security attacks occur frequently, data security and privacy communication are facing a major threat, and secure data communication is imminent. Aiming at the injection attack type of Cross-site scripting attack(XSS), we analyze it and design a hybrid dynamic testing technology method. SVM is combined to build a discriminator to distinguish malignant scripts. Browser tools are used to simulate attacks and built-in script execution functions are used to continuously monitor the target attribute values and page status, dynamically discover malicious content, and improve source code security. Experiments show that this method is effective for vulnerability detection. It has low overhead in the process of implementing dynamic testing and effectively improves the accuracy of vulnerability analysis combined with static content analysis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

IoT Intrusion Detection Using SDN Cloud-Edge Collaboration and Ensemble Deep Learning

IoT Intrusion Detection Using SDN Cloud-Edge Collaboration a...

引用

Cyber Science and technology Congress (CyberSciTech), IEEE

作者： Yuhua Xu Yan Li Zhixin Sun Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing China Broadband Wireless Communication Technology Engineering Research Center of the Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9798331532093

ISBN: (纸本)9798331532109

5G technology promotes the development of Internet of Things (IoT), but IoT faces various attacks, which lead to cybersecurity threats and property damage. Software Defined Networking (SDN) is one of the key technologies of 5G, and it is a new network paradigm that facilitates monitoring network flows, enabling programmable networks. Leveraging SDN to implement intrusion detection can improve the security of local IoT. In order to ensure the reliable communication of IoT and realize the precise network protection, this paper proposes an IoT intrusion detection scheme based on SDN cloud-edge collaboration and Ensemble Deep Learning (EDL). First, the edge controller realizes the accurate classification of normal traffic and suspicious traffic through the joint model of Naive Bayesian and Back Propagation neural networks (NB - BP), and then transmits the suspicious traffic to the cloud for detection. The attack type of suspicious traffic is identified by the EDL model deployed in the cloud detector, and the result is returned to the edge controller. The controller can adopt corresponding protective measures to protect network security according to the type of attack. It is verified by experiments that NB-BP can betray normal and abnormal traffic more accurately than NB and BP models, while EDL model has higher attack category recognition accuracy than a single deep learning model.

关键词： Deep learning Cloud computing Accuracy 5G mobile communication Image edge detection Computational modeling Collaboration Detectors Internet of Things Software defined networking

来源：评论

学校读者我要写书评

暂无评论

application of Diffusion Artificial Hummingbird Algorithm for Multimodal Transportation Logistics Distribution Routing Problem

Application of Diffusion Artificial Hummingbird Algorithm fo...

引用

Chinese Automation Congress (CAC)

作者： Fan Yang Lei Yue Xu Zhang YTO Express Co. Ltd. Shanghai China Post Industry Technology Research and Development Center of State Posts Bureau Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Anhui Yougu Express Intelligent Technology Co. Ltd Wuhu China

With the rapid development of e-commerce and the logistics industry, logistics transportation networks based on different modes of transport have gradually become increasingly complex. Currently, the multimodal transportation logistics distribution routing problem, which is considered a complex vehicle routing problem, has gained significant attention. Therefore, the selection of appropriate routes plays a crucial role in enhancing the economic efficiency and rationality of logistics planning. In order to obtain optimal routes, this paper proposes an improved diffusion artificial hummingbird algorithm based on the hummingbird swarm diffusion flight strategy. This algorithm improves the population initialization method to cover the solution space as comprehensively as possible. In addition, a migration diffusion strategy is proposed, by spreading the worst solution to the outer area of the population to find the optimal solution, thereby improving the global search capability of the algorithm. In order to verify the convergence performance of the algorithm, this paper conducts comparative tests with multiple algorithms, effectively verifying the high accuracy and fast convergence performance of the DAHA algorithm. Applying it to the multimodal logistics distribution path problem can effectively avoid excessively slow convergence speed and The disadvantage of low convergence accuracy. Finally, the feasibility and effectiveness of the algorithm are verified through experiments.

关键词：

来源：评论

学校读者我要写书评

暂无评论

research on Improved U-net Based Remote Sensing Image Segmentation Algorithm

Research on Improved U-net Based Remote Sensing Image Segmen...

引用

Internet of Things, Automation and Artificial Intelligence (IoTAAI), International Conference on

作者： Qiming Yang Zixin Wang Shinan Liu Zizheng Li Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Nanjing University of Posts and Telecommunications Jiangsu China Digital Media University of Washington Seattle US College of Engineering Northeastern University Boston USA National Higher School of Advanced Techniques (ENSTA) Paris France

ISBN: (数字)9798350386974

ISBN: (纸本)9798350386981

In recent years, although U-Net network has made significant progress in the field of image segmentation, it still faces performance bottlenecks in remote sensing image segmentation. In this paper, we innovatively propose to introduce SimAM and CBAM attention mechanism in U-Net, and the experimental results show that after adding SimAM and CBAM modules alone, the model improves 17.41% and 12.23% in MIoU, and the Mpa and Accuracy are also significantly improved. And after fusing the two, the model performance jumps up to 19.11% in MIoU, and the Mpa and Accuracy are also improved by 16.38% and 14.8% respectively, showing excellent segmentation accuracy and visual effect with strong generalization ability and robustness. This study opens up a new path for remote sensing image segmentation technology and has important reference value for algorithm selection and improvement.

关键词： Measurement Image segmentation Accuracy Attention mechanisms Network architecture Visual effects Robustness Internet of Things Remote sensing Optimization

来源：评论

学校读者我要写书评

暂无评论

research on the Loading Method of Logistics Vehicle and Cargo Based on IPSO Algorithm

Research on the Loading Method of Logistics Vehicle and Carg...

引用

第42届中国控制会议

作者： Zewei Zhao Huqing Wang Zhe Sun Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationNanjing University of Posts and Telecommunications

Logistics vehicle and cargo matching problem is a typical combination optimization problem,which has important theoretical and application value in the field of logistics *** proved particle swarm optimization(PSO) algorithm is one of the most extensive optimization methods studied in recent years,with excellent global search ability and convergence *** on the IPSO algorithm,this paper proposes an effective IPSO algorithm model for the matching problem of logistics vehicles and goods,and conducts the corresponding comparative *** final experimental results show that the algorithm has good results in practical application and can provide a feasible optimization method for solving the problem of logistics vehicles and goods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Commodity Personalized Recommendation Algorithm Based on the Knowledge Graph

Commodity Personalized Recommendation Algorithm Based on the...

引用

IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Kai Yuan Yang Jun Yang Zhi Xin Sun Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing China Changzhou Anyi SoftwareCc. Ltd Changzhou China Broadband Wireless Communication Technology Engineering Research Center of the Ministry of Education Nanjing University of Posts and Telecommunication Nanjing China

Personalized recommendation systems have become an important part of e-commerce, social media, and other applications. However, the traditional collaborative filtering algorithm is only based on the user's scoring history of the product, ignoring the attributes and characteristics of the product itself. To solve this problem, this paper proposes a personalized recommendation algorithm based on knowledge graph, which can combine the similarity between goods and user preferences to make recommendations and add the scoring mechanism, thus improving the accuracy and practicability of the recommendation system. Experimental results show that our algorithm outperforms the traditional user-based and item-based co-filtering algorithms in evaluation indexes such as accuracy, recall and F1 value, demonstrating the effectiveness and feasibility of this algorithm in the field of personalized recommendation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：