Proceedings of the 5th International Conference on Computer Science and Software Engineering最新文献_第3页

Power load forecasting based on SSA non-noise reduction processing 基于SSA非降噪处理的电力负荷预测

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3569999

Yindong Jin, He Xiao, Chengui Fu

引用次数: 0

Pattern Synthesis of Antenna Array Based on Improved Flower Pollination Algorithm 基于改进花授粉算法的天线阵方向图综合

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570080

Cuicui Cai, Yao Nie, Huan Wu, Maosheng Fu, Xianmeng Meng

引用次数: 0

Heterogeneous Computing and Applications in Deep Learning: A Survey 异构计算及其在深度学习中的应用综述

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570075

Qiong Wu, Yuefeng Shen, Mingqing Zhang

引用次数: 1

Design and Implementation of VSTO-based Online Compilation Teaching System for C Language 基于vsto的C语言在线编译教学系统的设计与实现

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570094

Xiya Yu, Xuetao Zhang, Yuanyuan Shi, Chang-Chung Wu, Xianhe Li

{"title":"Design and Implementation of VSTO-based Online Compilation Teaching System for C Language","authors":"Xiya Yu, Xuetao Zhang, Yuanyuan Shi, Chang-Chung Wu, Xianhe Li","doi":"10.1145/3569966.3570094","DOIUrl":"https://doi.org/10.1145/3569966.3570094","url":null,"abstract":"C programming is a compulsory general education course for science and technology majors in colleges and universities, and its importance is self-evident. At present, the teaching mode of C language in colleges and universities generally has the code lecture according to the text, teachers usually use PowerPoint to explain classroom knowledge, code demonstration needs to operate several software at the same time, the operation process is tedious, the performance of teaching computer is a great challenge, the classroom efficiency is affected. In order to solve the above teaching problems, it is necessary to develop a system based on VSTO's PowerPoint technology development and Spring Boot framework for C online compilation and running. The system enables PowerPoint to compile and run online in C language, which can effectively solve the problem of complicated operation of C language compiler in classroom. The system design uses Spring Boot framework to write the interaction logic, MySQL database for the data layer, Docker container for system resource virtualization and program isolation, and Nginx for front-end load balancing to improve the concurrent processing capability. The design and operation of the C online compilation system embedded in PowerPoint is studied and analyzed to achieve the goal of security and high concurrency, which will positively contribute to the progress of teaching programming courses.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"78 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":"121775854","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

An Effective Data Recovery Approach for Distributed Storage based on Interference Alignment 基于干扰对齐的分布式存储数据恢复方法

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3569971

Jingyao Zhang

引用次数: 0

Electric Bicycle Detection Based on Deep Learning 基于深度学习的电动自行车检测

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570001

Jiakang Sun, Yuhan Zhang

引用次数: 0

Research on Data Governance and Data Migration based on Oracle Database Appliance in campus 基于Oracle数据库应用的校园数据治理与数据迁移研究

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3571273

Mingxiu. Tong, Ying Xia

引用次数: 0

A light and efficient attention model for 3D shape part-segmentation 一种轻巧高效的三维形状零件分割注意模型

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570055

W. Shi, Zhongyi Li

{"title":"A light and efficient attention model for 3D shape part-segmentation","authors":"W. Shi, Zhongyi Li","doi":"10.1145/3569966.3570055","DOIUrl":"https://doi.org/10.1145/3569966.3570055","url":null,"abstract":"Part segmentation is one of the important tasks in 3D shape analysis. Prior works mostly rely on complex local modeling to learn features directly from raw mesh or point cloud. We proposed a simple, fast and robust approach for 3D shape part segmentation without sophisticated local geometric modeling and ingenious networks. Our main idea is to learn more discriminative features from different geometric descriptors by sparse convolution and attention mechanism. Specifically, an effective shape representation block, consists of a features embedding module, two attention module. The coordinates are fed into the features embedding module to produce embedding vectors. The attention head to learn the intrinsic relations between different descriptors and produce more informative feature maps. In the lower branch, We use some geometric descriptors as local features. And a classification head predicts the corresponding label. Conditional Random Field (CRF) is applied to optimize the segmentation of the network. The experiment results on Princeton Shape Benchmark(PSB) demonstrate that our architecture outperforms different methods, with higher accuracy, lower complexity and faster speed.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"25 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":"121642852","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

Study on the Evaluation Model of Airborne Software Supplier Development Capability 航空软件供应商开发能力评价模型研究

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3569976

Tiequan Liu, J. Sun, Lei Chen, Hanxiao Zhang, Fujian Pi

引用次数: 0

Hybrid Sampling Light Graph Collaborative Filtering for Social Recommendation 社会推荐的混合采样光图协同过滤

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570002

Yefan Zhu, Li Zhang, Siqi Yang

{"title":"Hybrid Sampling Light Graph Collaborative Filtering for Social Recommendation","authors":"Yefan Zhu, Li Zhang, Siqi Yang","doi":"10.1145/3569966.3570002","DOIUrl":"https://doi.org/10.1145/3569966.3570002","url":null,"abstract":"• The use of graph neural networks has been widely adopted in recommender systems as a state-of-the-art collaborative filtering mechanism. In graph neural collaborative filtering, extracting negative signals from implicit feedback aris-ing from the interaction between users and items is a ma-jor challenge. The negative sampling aspect has not been fully explored in the use of graph neural collaborative filtering for the social recommendation. This study explores negative sampling by combining a graph neural network aggregation procedure with social recommendation graph structures. A system called Hybrid Sampling Light Graph Convolution Collaborative Filtering for Social Recommendations (HLCS) is proposed in this paper. Through the propagation and fusion of embedded representations of users and items in the item domain and social domain, hard negative samples are generated by the hybrid sampling technique to optimize the recommendation model’s performance. Using two real-world datasets, we conducted comprehensive experiments and showed that the HLCS approach was superior to the SOTA approach, particularly in cold-start situations. ;","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"1 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":"130829200","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