2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)最新文献_第9页

Binary vulnerability mining technology based on neural network feature fusion 基于神经网络特征融合的二进制漏洞挖掘技术

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00058

Wenjie Han, Jianmin Pang, Xin Zhou, Dixia Zhu

{"title":"Binary vulnerability mining technology based on neural network feature fusion","authors":"Wenjie Han, Jianmin Pang, Xin Zhou, Dixia Zhu","doi":"10.1109/AEMCSE55572.2022.00058","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00058","url":null,"abstract":"The high complexity of software and the diversity of security vulnerabilities have brought severe challenges to the research of software security vulnerabilities Traditional vulnerability mining methods are inefficient and have problems such as high false positives and high false negatives, which can not meet the growing needs of software security. To solve the above problems, this paper proposes a binary vulnerability mining technology based on neural network feature fusion. Firstly, this method constructs binary vulnerability data sets containing multiple vulnerability types, then decompile them to the pcode intermediate language level, and then extracts relevant feature vectors from binary vulnerability data sets according to Bert fine tuning model and bilstm model respectively. In order to fully obtain the semantic information of vulnerabilities, this method standardized the two, fused them, and carried out relevant experiments. The experimental results show that the accuracy of vulnerability detection on SARD data set is 96.92%, which is higher than other binary vulnerability detection methods based on neural network.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123080361","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

Tuning the electronic and optical properties of BaNiO3 via Fe substitution: a first-principles study 通过Fe取代调整BaNiO3的电子和光学性质:第一性原理研究

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00026

Jingjing Liu, Sa Zhang, Haiyan Xiao, L. Qiao

引用次数: 0

A Statistical Method for the Number and Size of Luminescent Zooplankton in Deep Sea 深海发光浮游动物数量和大小的统计方法

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00110

Yulong Zhou, Xi Zhang, Yuxing Wang, F. Zhao

引用次数: 0

A Study of Answer Selection Task Based on Deep Learning Methods 基于深度学习方法的答案选择任务研究

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00100

Na Wang, Ruoyan Chen, Kunming Du

引用次数: 0

Comparative study on properties of in situ particles reinforced Al-Si-X (Mg, Ti, Ni) composites by centrifugal casting 离心铸造原位颗粒增强Al-Si-X (Mg, Ti, Ni)复合材料性能的对比研究

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00027

X. Lin, Linxian Che, Jian Sun, Weibo Li

{"title":"Comparative study on properties of in situ particles reinforced Al-Si-X (Mg, Ti, Ni) composites by centrifugal casting","authors":"X. Lin, Linxian Che, Jian Sun, Weibo Li","doi":"10.1109/AEMCSE55572.2022.00027","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00027","url":null,"abstract":"In this study, Al-Si-X (Mg, Ti, Ni) composite tubular castings were prepared by centrifugal casting. The segregation behavior of primary particles formed in different alloys under the action of centrifugal field was analyzed, and the hardness and wear resistance of different composites were tested. The results show that primary Si/Mg2Si particle reinforcement layer is formed in the inner layer of the casting by Al-Si-Mg composite, the primary TiAlSi particle reinforcement layer is formed in the outer layer of the casting by Al-Si-Ti composites, and the primary NiAb3/Si particle reinforcement layer is formed in the inner and outer layers of the casting for Al-Si-Ni composites, respectively. The hardness of particle reinforced layer in Al-18Si-7Mg (Ti, Ni) alloy castings reaches HRB71.5, HRB67 and HRB67.5, respectively. The volume wear of Al-18Si-7Mg alloy is the least. The difference of hardness and wear resistance of particle reinforcement layer is mainly related to the volume fraction, size and particle morphology of primary particles in the alloy.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129648699","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 Improved Density Peak Clustering Algorithm Based on K Nearest Neighbors and Tissue-like P System 基于K近邻和类组织P系统的改进密度峰值聚类算法

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00125

Fuhua Ge, Xiyu Liu

{"title":"An Improved Density Peak Clustering Algorithm Based on K Nearest Neighbors and Tissue-like P System","authors":"Fuhua Ge, Xiyu Liu","doi":"10.1109/AEMCSE55572.2022.00125","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00125","url":null,"abstract":"Recently, the density peak clustering algorithm (DPC) has attracted wide attention of researchers. DPC can quickly find the clustering centers and complete the clustering task. However, DPC still has some defects, such as the need to manually set the cutoff distance, the cascade reaction of points distribution, and the vulnerability to noise interference. In order to address these problems, we propose an improved density peak clustering algorithm based on K nearest neighbors and tissue-like P system. Firstly, the local density of each data point is calculated on the basis of K nearest neighbors and the clustering centers are selected via the Score value. Afterward, the remaining points are assigned according to the new similarity matrix calculated by KNN. Moreover, we embed the improved algorithm into the framework of the tissue-like P system, so that the maximum parallelism of the P system will improve the computational efficiency of the algorithm. The experimental results on multiple synthetic datasets and real datasets illustrate that the improved algorithm has a better clustering effect than other algorithms.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129073721","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

Meta-Learning based Heterogeneous Graph Attention Network for Top-N Review Recommendation 基于元学习的异构图注意网络Top-N评论推荐

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00091

Shuwei Wang, Wei Liu, Jian Yin

{"title":"Meta-Learning based Heterogeneous Graph Attention Network for Top-N Review Recommendation","authors":"Shuwei Wang, Wei Liu, Jian Yin","doi":"10.1109/AEMCSE55572.2022.00091","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00091","url":null,"abstract":"User-generated content (UGC) has become more and more popular on the web and the published review is an essential type of UGC. Nevertheless, the explosion of reviews brings a problem of severe information overload. Therefore, most web services supply review recommendations for users. Traditionally, reviews of an item could be exhibited in chronological or popularity order without personalization. However, some researchers are aware of the significant role of the personalized review recommendation, which focuses on discovering users’ personalized preferences so that recommended reviews could match users’ preferences better. Unfortunately, it is hard to obtain users’ feedback on reviews due to the privacy protection and trade secrets. Furthermore, the difficulty in capturing varying patterns of users’ preferences and the sparsity of interactions between users and reviews are also challenging. To address these problems, we first formally define the top-N review recommendation problem and construct two categories of datasets based on a public dataset. Secondly, we propose a meta-learning based heterogeneous graph attention network incorporating multiple relationships among the users, items and reviews to model personalized users’ preferences and cope with the sparse situation. Moreover, to accelerate the message propagation computation, a method of the substructure-oriented local graph construction is proposed and is fused into the meta-learning framework based on a pair-wise ranking. For the top-N review recommendation, experiments are conducted on the two categories of a real-world dataset. Compared with the state-of-the-arts, the results validate the effectiveness of our model for review recommendation.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129085050","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

3D Communication System Integrating 3D Reconstruction and Rendering Display 集三维重建与渲染显示于一体的三维通信系统

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00041

Chaoying Zhang, Minglan Su, Qiaoqiao Liu, Mingchuan Yang

{"title":"3D Communication System Integrating 3D Reconstruction and Rendering Display","authors":"Chaoying Zhang, Minglan Su, Qiaoqiao Liu, Mingchuan Yang","doi":"10.1109/aemcse55572.2022.00041","DOIUrl":"https://doi.org/10.1109/aemcse55572.2022.00041","url":null,"abstract":"In order to solve the problem that the existing 2D video communication has a high bandwidth occupancy rate, the inability to present three-dimensional portraits of characters and the high dependence of three-dimensional projection technology on hardware, we propose a 3D communication framework that integrates 3D reconstruction and rendering display. The framework transmits the video stream to the video encoding module. The video coding module mainly completes the work of face detection, key point feature extraction and depth map feature coding. It is transmitted to the terminal device through the transmission protocol for video decoding and reconstruction. Then combined with the 3D rendering algorithm, virtual viewpoint synthesis and stereo image encoding are performed to realize the 3D reconstruction of the real face. The frame structure opens up the technical path from ordinary 2D video acquisition to 3D communication system implementation. Experiments show that the use of this communication framework for real face 3D reconstruction has higher accuracy and better information fusion. The reconstruction rate can reach 15fps.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129922811","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

SVD based Image Actual Resolution Estimation 基于SVD的图像实际分辨率估计

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00115

Shiqiang Zheng, Lizhe Duan, Wenguang Hou, D. Kurlovich

引用次数: 0

Different machine learning methods for tic-tac-toe prediction 不同的机器学习方法来预测井字棋

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00082

Supeng Wu

引用次数: 0