Proceedings of the 6th International Conference on Computer Science and Application Engineering最新文献_第4页

CVPCG: Centrosymmetric Virtual Point Cloud Generation For 3D Object Detection 中心对称虚拟点云生成用于3D对象检测

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565449

Lingmei Ai, Zhuoyu Xie, Xiaoying Zhang

引用次数: 0

Data Forwarding at Intersections in Vehicular Social Networks 车辆社交网络交叉口的数据转发

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565435

Jing Zeng, Zifeng Hao, Xiaolan Tang, Chengan Zhao

{"title":"Data Forwarding at Intersections in Vehicular Social Networks","authors":"Jing Zeng, Zifeng Hao, Xiaolan Tang, Chengan Zhao","doi":"10.1145/3565387.3565435","DOIUrl":"https://doi.org/10.1145/3565387.3565435","url":null,"abstract":"In vehicular social networks, the vehicles in different communities have different data requirements and different mobility models. Traditional researches focus on the forwarder selection in vehicle-to-vehicle communication, and hence the frequent forwarder change affects the overall performance. In vehicular scenarios with roadside units deployed at intersections, how to select an appropriate forwarding direction based on the social features is a key issue. In this paper, the roadside unit gathers the social attributes of vehicles on the roads by a well-designed information collection method, in which the odd-hop nodes and the even-hop nodes take different tasks to reduce resource cost. Furthermore, the direct forwarding contribution ratio is computed according to the social attributes, and together with the connectivity and the empirical direction selection of similar data, the forwarding priority of each candidate direction is calculated. Finally, the forwarding directions are selected and the replicas of data packets are distributed in these directions. Experiments with real road map and three communities show that, compared with traditional schemes, the proposed scheme has a high delivery ratio and a small transmission overhead (the number of V2V and V2I data transmissions) while maintaining an acceptable delay.","PeriodicalId":182491,"journal":{"name":"Proceedings of the 6th International Conference on Computer Science and Application Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127983871","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

Design of Embedded Trust Root Based on Dual-Kernel Architecture 基于双核架构的嵌入式信任根设计

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565413

Xiangying Kong, Xinran Kong

引用次数: 0

MPSKT: Multi-head ProbSparse Self-Attention for Knowledge Tracing MPSKT:多头ProbSparse Self-Attention for Knowledge Tracing

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565420

Lingmei Ai, Xiaoying Zhang, Ximing Hu

引用次数: 0

A Separating Embedding Space Based Relation Network with RGB Modality Only for Cloth-Changing Person Re-Identification 基于RGB模态分离嵌入空间的换布人再识别关系网络

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565397

Jian Xu, Bo Liu, Yanshan Xiao

{"title":"A Separating Embedding Space Based Relation Network with RGB Modality Only for Cloth-Changing Person Re-Identification","authors":"Jian Xu, Bo Liu, Yanshan Xiao","doi":"10.1145/3565387.3565397","DOIUrl":"https://doi.org/10.1145/3565387.3565397","url":null,"abstract":"The Cloth-changing person re-identification (CC-ReID) is more challenging than person re-identification (Re-ID) since the cloth-relevant features are unreliable. The current CC-ReID methods usually utilize some human parsing techniques such as semantic segmentation to guide the model to learn more cloth-irrelevant feature cues. However, the human parsing models are not necessarily reliable. For this, we propose a Separating Embedding Space based Relation Network (SESRN) for CC-ReID. Firstly, we use pairs of images as input of the model and consider the relation between them in SESRN instead of a single image that the existing CC-ReID models use. Secondly, we propose to separate the common feature embedding space outputted from the common backbone into two embedding subspaces including the cloth-irrelevant feature embedding subspace and cloth-related feature embedding subspace without using any human parsing techniques since we think that they are unreliable and introduce noise into model. Thirdly, we generate the different feature map weights on different subspaces or different comparison pairs on the same subspace, which is a simple and effective feature map visualization and analysis framework in CC-ReID. Finally, the extensive experiments show the effectiveness and robustness of our method.","PeriodicalId":182491,"journal":{"name":"Proceedings of the 6th International Conference on Computer Science and Application Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126848818","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

Research on Group Behavior Modeling of Virtual Tibetan Horse Racing 虚拟藏族赛马群体行为建模研究

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565451

Rui Huang, Xiaobo Yang, Haili Zhao, Yimeng Xiao, Yifan Liu

{"title":"Research on Group Behavior Modeling of Virtual Tibetan Horse Racing","authors":"Rui Huang, Xiaobo Yang, Haili Zhao, Yimeng Xiao, Yifan Liu","doi":"10.1145/3565387.3565451","DOIUrl":"https://doi.org/10.1145/3565387.3565451","url":null,"abstract":"Due to the changeable behavior characteristics of biological groups, this paper aims at the problem that traditional animation technology cannot accurately simulate the movement and avoidance behavior of biological groups. Taking Tibetan horse racing in the biogroup as an example, it is essential to propose a virtual simulation method of Tibetan horse racing group based on the improved Boids model. On the basis of the SAC rules, obstacle avoidance rules are introduced, and the characteristic simulation of horse racing can be realized only by following the four movement rules of separation, alignment, cohesion, and obstacle avoidance, and each individual has ability to adjust its position and speed within the group according to its environment. In order to improve the fluency of system operation and optimize the scene model, a WebGL-based virtual roaming interactive system for Tibetan Horse Racing Festival was developed with Unity3D as a platform. Experimental results show that: Compared with traditional animation techniques and social force models, the algorithm can extremely improve the virtual simulation effect of horse racing group behavior, realize the real simulation of horse racing as well as improve the accuracy of biological group virtual simulation, which enhances user's real sense of reality and has practical significance for the spread and protection of Tibetan culture. In addition, it can be used for virtual racecourse, horse racing teaching demonstration, horse racing scene simulation, etc. In general, it has superior application value.","PeriodicalId":182491,"journal":{"name":"Proceedings of the 6th International Conference on Computer Science and Application Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116967449","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

Quadratic Model of Air Quality Prediction 空气质量预测的二次模型

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565388

L. Yang, Shasha Liu, Xiaoran Li, Wenwen Xu

{"title":"Quadratic Model of Air Quality Prediction","authors":"L. Yang, Shasha Liu, Xiaoran Li, Wenwen Xu","doi":"10.1145/3565387.3565388","DOIUrl":"https://doi.org/10.1145/3565387.3565388","url":null,"abstract":"It is necessary to predict the air pollutants under the condition of increasing air pollution. In this paper, the quadratic mathematical modeling of air quality prediction is mainly based on the primary forecast data and the measured data, and the daily concentration values of six conventional pollutants in the next three days are predicted. Firstly, based on the KNN regression principle, the optimal k-value quadratic prediction model suitable for A1, A2 and A3 monitoring points is established; Secondly, considering the influence of pollutant concentration between adjacent areas, a collaborative prediction model based on random forest algorithm and BP neural network is established to predict the pollutant concentration of four monitoring points A, A1, A2 and A3. At the same time, considering the different variables in the characteristic set of time and space input, a prediction data is introduced to adjust the parameters of the results of the model, spatiotemporal hybrid prediction model based on regression prediction is established. The final results show that the accuracy of prediction is improved based on the first prediction data and combined with the measured data.","PeriodicalId":182491,"journal":{"name":"Proceedings of the 6th International Conference on Computer Science and Application Engineering","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125328651","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

Research on On-orbit Reconfigurable Technology for Space Station Payload System Based on SmartFusion2 基于SmartFusion2的空间站有效载荷系统在轨可重构技术研究

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565446

Ting Wang, Yu'e Gao, Ce Li, Jinzhun Wang, Chong Wang

引用次数: 0

The Relative Extrema of Vertex Degree Distances of Dumbbell Graphs 哑铃图顶点度距离的相对极值

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565394

Hai-li Guo

引用次数: 0

Production Scheduling Optimization of Prefabricated Components Based on Improved Artificial Fish Swarm Algorithm 基于改进人工鱼群算法的预制构件生产调度优化

Proceedings of the 6th International Conference on Computer Science and Application Engineering Pub Date : 2022-10-21 DOI: 10.1145/3565387.3565427

Chunguang Chang, Manqing Wang, Shen Wang

引用次数: 0