2021 7th International Conference on Systems and Informatics (ICSAI)最新文献_第8页

The Alzheimer's Disease continuum Supervised Classification Using the Merged Connectome of Metabolic and Structural Imaging 利用代谢和结构成像的合并连接组对阿尔茨海默病的连续监督分类

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/icsai53574.2021.9664123

Ronghua Ling, Yinghui Yang, Chengcheng Fan, Minxiong Zhou

{"title":"The Alzheimer's Disease continuum Supervised Classification Using the Merged Connectome of Metabolic and Structural Imaging","authors":"Ronghua Ling, Yinghui Yang, Chengcheng Fan, Minxiong Zhou","doi":"10.1109/icsai53574.2021.9664123","DOIUrl":"https://doi.org/10.1109/icsai53574.2021.9664123","url":null,"abstract":"Previous connectome research about glucose metabolic network, obtained with 18F-FDG PET data by sparse inverse covariance estimation (SICE), which has been revealed in neurodegenerative diseases. However, this metabolic network construction suffers from the lack of robustness with the metabolic connection estimation. Metabolic connection matrices have been observed to present similar patterns as the structural connection matrices obtained from diffusion MRI. Further, we aim to use the structural connectivity regularize the sparse estimation of metabolic connection. The merged connectome of metabolic and structure imaging based on FDG PET and diffusion MRI imaging is employed to measure the metabolic connection. The proposed method is then applied in a clinical dataset including healthy subjects and Alzheimer's disease continuum patients. The merged results had proved the improvement in the accuracy of the estimated metabolic connection network (Accuracy: 0.94 [HC-AD], 0.89 [HC-MCI], 0.83 [MCI-AD]). Compared to standard SICE, the structural weighting has shown more stable performance in the supervised classification.","PeriodicalId":131284,"journal":{"name":"2021 7th International Conference on Systems and Informatics (ICSAI)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133434471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Strategy of IP Address Hopping Based on Attack Surface Evaluation 基于攻击面评估的IP地址跳转优化策略

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/icsai53574.2021.9664031

Bihai Lin, Jiaqi Li, Yanhua Liu, Kedong Wu

{"title":"Optimal Strategy of IP Address Hopping Based on Attack Surface Evaluation","authors":"Bihai Lin, Jiaqi Li, Yanhua Liu, Kedong Wu","doi":"10.1109/icsai53574.2021.9664031","DOIUrl":"https://doi.org/10.1109/icsai53574.2021.9664031","url":null,"abstract":"To solve the problems of incomplete network attack risk assessment and randomization of IP address hopping in dynamic defense, the optimal dynamic defense strategy selection method based on network attack surface evaluation is proposed. The network attack surface evaluation model based on the analytic hierarchy process (AHP) and cloud model is studied, and the attack surface evaluation index and its quantitative method are designed. A method for evaluating the global importance of host assets based on the K-CORE algorithm is proposed, and different hopping frequencies are set by the importance of host assets. Based on this, the IP address hopping offensive and defensive scenario is modeled, and an optimal hopping strategy selection method based on the dynamic game is proposed. The value of attack surface under different game conditions is used as the offensive and defensive gains parameter, and the solution is solved by refining the Bayesian Nash equilibrium, to achieve the optimal IP address hopping strategy selection. Experiments show that the proposed method can effectively calculate the optimal hopping strategy and provide meaningful support for improving dynamic defense capabilities.","PeriodicalId":131284,"journal":{"name":"2021 7th International Conference on Systems and Informatics (ICSAI)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134431630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Inter-Pulse Non-Coherent Jamming Technology Against SAR Based on Stepped Time-Delay 基于阶跃时延的SAR脉冲间非相干干扰技术

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/ICSAI53574.2021.9664141

Yuhan Shi, Hongxu Huang, Zhenyan Ma

引用次数: 0

A Time Series Prediction Model Based on Long Short-Term Memory Networks 基于长短期记忆网络的时间序列预测模型

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/icsai53574.2021.9664063

Linkai Wang, Jing Chen, Wei Wang, Ruofan Wang, Lina Yang, Mai An

引用次数: 0

A Deblurring Method of Electric Power Inspection Images Based on GAN 基于GAN的电力检测图像去模糊方法

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/icsai53574.2021.9664028

Chong Liang, Yu Yin, Yu Qin, Xiangjun He

引用次数: 0

Vehicle Trajectory Prediction Based on Attention Mechanism and GAN 基于注意机制和GAN的车辆轨迹预测

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/icsai53574.2021.9664094

Yi Wang, Wangqiao Chen, Chao Wang, Shuang Wang

引用次数: 2

User Alignment across Dynamic Social Networks based on Heuristic Algorithm 基于启发式算法的动态社交网络用户对齐

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/ICSAI53574.2021.9664205

Jiawei He, Li Liu, Zihan Yan, Zhiqian Wang, Min Xiao, Youmin Zhang

{"title":"User Alignment across Dynamic Social Networks based on Heuristic Algorithm","authors":"Jiawei He, Li Liu, Zihan Yan, Zhiqian Wang, Min Xiao, Youmin Zhang","doi":"10.1109/ICSAI53574.2021.9664205","DOIUrl":"https://doi.org/10.1109/ICSAI53574.2021.9664205","url":null,"abstract":"User alignment across social networks, whose main goal is to fuse user information in different network platforms, is a fundamental task in social network analysis. It can benefit social network applications such as user recommendation and information diffusion. Attributed to the inherent dynamic characteristic of the social networks, aligning users in dynamic networks is a key issue in practice. However, most of the alignment models encounter model retraining when the network is updated, thus result in the consumption of time and resources. To address this problem, a heuristic algorithm is proposed to align users in a dynamic environment. Firstly, the attention mechanism is leveraged to obtain the local importance weight of the new node in a single network. Secondly, the anchor nodes are adopted as supervised information for heuristically learning the alignment task-driven local influence of new nodes. Finally, by preserving the second-order similarity of the network, the model aligns users across networks. Experimental results conducted on realworld datasets prove that the proposed model has a comparable performance but lower time complexity compared with several state-of-the-art algorithms.","PeriodicalId":131284,"journal":{"name":"2021 7th International Conference on Systems and Informatics (ICSAI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122715279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Credit Approval Prediction Based on Boruta-GBM Model 基于Boruta-GBM模型的信贷审批预测

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/icsai53574.2021.9664026

Ze Chen, Geng-Mei Lin, Xiuling Jin

引用次数: 0

Design of Multi-Scroll Chaotic Attractors Based on Tempered Fractional Differential Systems 基于回火分数阶微分系统的多涡旋混沌吸引子设计

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/ICSAI53574.2021.9664115

Jing-wei Deng, Kai-ying Deng

引用次数: 1

Clothing retrieval based by image and text combination 基于图像和文本组合的服装检索

2021 7th International Conference on Systems and Informatics (ICSAI) Pub Date : 2021-11-13 DOI: 10.1109/ICSAI53574.2021.9664041

Zongbao Liang, Liu Yang, YunFei Yuan, Bo Chen, Feifei Tang

{"title":"Clothing retrieval based by image and text combination","authors":"Zongbao Liang, Liu Yang, YunFei Yuan, Bo Chen, Feifei Tang","doi":"10.1109/ICSAI53574.2021.9664041","DOIUrl":"https://doi.org/10.1109/ICSAI53574.2021.9664041","url":null,"abstract":"Image text combination retrieval is a new direction in multimodal retrieval, in which query is composed of image and modified text. The retrieved target image should not only be similar to the query image, but also have the change specified by the modified text. The traditional clothing retrieval adopts the single-mode retrieval method of image search or text search, which is lack of retrieval flexibility. To solve the problem of feature fusion caused by semantic differences between clothing image and text, this paper proposes a multi-dimensional feature fusion model, which constructs a high-dimensional visual feature and semantic feature fusion model based on the scaling point product attention mechanism to extract high-dimensional fusion features, then the low dimension visual semantic fusion features are used as the residual of high dimension fusion features for target image retrieval. Compared with the previous feature fusion methods, the recall rate of Top1 on Fashion200k data set is increased by 15.4%, which is obviously superior to most of the existing graph and text feature fusion models, which shows that the model is advanced and effective.","PeriodicalId":131284,"journal":{"name":"2021 7th International Conference on Systems and Informatics (ICSAI)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123247631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0