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2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)最新文献

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A Feature Selection Method Based on Adaptive Differential Evolution 基于自适应差分进化的特征选择方法
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940171
Hongbin Dong, Xue Wang, Xingmei Wang, Jing Sun, Tao Li
{"title":"A Feature Selection Method Based on Adaptive Differential Evolution","authors":"Hongbin Dong, Xue Wang, Xingmei Wang, Jing Sun, Tao Li","doi":"10.1109/icis46139.2019.8940171","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940171","url":null,"abstract":"This paper proposes a feature selection method based on adaptive differential evolution-ISHADEFS. By using mutual information and Pearson correlation coefficient to construct a new fitness function, the enhancement effect of correlation and similarity is used to improve the efficiency and accuracy of filtering. A triangular mutation operator is improved, and the operator diversity is enhanced by the operator adaptive structure to improve the performance of the algorithm. The experimental results show that compared to conventional filtering methods and original evolution methods, ISHADEFS can achieve better classification performance.","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117231087","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
Face Detection and Extraction from Low Resolution Surveillance Video Using Motion Segmentation 基于运动分割的低分辨率监控视频人脸检测与提取
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940319
Chen Xu-hui, Ejaz Ui Haq, Zhou Chengyu
{"title":"Face Detection and Extraction from Low Resolution Surveillance Video Using Motion Segmentation","authors":"Chen Xu-hui, Ejaz Ui Haq, Zhou Chengyu","doi":"10.1109/icis46139.2019.8940319","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940319","url":null,"abstract":"Face detection is a prominent research domain in the field of digital image processing particularly in the field of video surveillance systems. Today is the world of video technology starting from low resolution videos to the high definition videos. The videos obtained from surveillance systems are often of low resolution due to the reasons such as distance between the camera and place of footage, environment factors, wide coverage area, installation problems, out of focus, bandwidth issue, hardware constraints, storage space limitations etc. because of which the frames need to be compressed or converted to lower resolution before storage. In this paper, we have worked on motion segmentation based face detection from low resolution surveillance videos. The motion segmentation is used to extract the region of interest from the current frame. Thereafter only the pixels obtained after the motion segmentation are subjected to the face detection process. The haar features based face detection has been used in this work, employing the image scaling to facilitate multi-scale face detection. Considerable search space reduction and efficiency boost has been achieved by proposed motion segmentation technique.","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120950066","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: 3
Using lda2vec Topic Modeling to Identify Latent Topics in Aviation Safety Reports 利用lda2vec主题建模识别航空安全报告中的潜在主题
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940271
Yonghui Luo, Hongwei Shi
{"title":"Using lda2vec Topic Modeling to Identify Latent Topics in Aviation Safety Reports","authors":"Yonghui Luo, Hongwei Shi","doi":"10.1109/icis46139.2019.8940271","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940271","url":null,"abstract":"The study of aviation safety report in the aviation industry usually relies on manually labeled data sets, and then classifies and models related problems, which have become insufficient in the face of increasingly rapid report data. Therefore, in this paper, we propose an unsupervised machine learning algorithm architecture to explore topics (rather than categories) for optimizing aviation safety report text mining research, and further conducts preliminary experiments with real data from the Aviation Safety Report System (ASRS). The experimental results show that compared with traditional classification modeling, this scheme can identify latent topics with higher interpretability, and the training data does not rely on manual labeling, which can greatly improve the efficiency and pertinence of aviation safety report research.","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127506408","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: 4
Complex Networks of Characters in Fictional Novels 虚构小说中人物的复杂网络
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940174
Jiarong Li, Chi Zhang, Huan Tan, Chunfang Li
{"title":"Complex Networks of Characters in Fictional Novels","authors":"Jiarong Li, Chi Zhang, Huan Tan, Chunfang Li","doi":"10.1109/icis46139.2019.8940174","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940174","url":null,"abstract":"Using the complex network theory to analyze the character social network in literatures provides a perspective in literary analysis. This paper proves that the character social networks of Harry Potter and The Lord of the Rings are small-world and scale-free and not only preferential attachment but also some specific plots affect the development of The Lord of the Rings trilogy. That means the social networks from two literatures obey the complex network theories that the social networks in real word follow. Hence, these above properties make the two fictional novels’ networks more like networks in the real world and make people accept them well.","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126964120","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: 7
ICIS 2019 Message from Program Chairs ICIS 2019项目主席致辞
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940221
{"title":"ICIS 2019 Message from Program Chairs","authors":"","doi":"10.1109/icis46139.2019.8940221","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940221","url":null,"abstract":"","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116131427","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
Entity Relationship Extraction Based on BLSTM Model 基于BLSTM模型的实体关系提取
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940185
Minyong Shi, Jingyi Huang, Chunfang Li
{"title":"Entity Relationship Extraction Based on BLSTM Model","authors":"Minyong Shi, Jingyi Huang, Chunfang Li","doi":"10.1109/icis46139.2019.8940185","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940185","url":null,"abstract":"Entity relationship extraction is an important research topic in the field of NLP, which is to extract the relationship between two entities from natural language texts. Research shows that deep neural networks are feasible in the task of entity relation extraction and are superior to traditional relation extraction methods. In this paper, we compare the performance of the BLSTM model and the Bidirectional LSTM model with Attention under the entity relationship extraction task. The comparison includes the different performance of the model after adding additional NLP features and modifying embedding size. Compared with the BLSTM model, the Bidirectional LSTM model with Attention can achieve similar accuracy under the condition of simpler and less preprocessing. In addition, the larger size of dimension of word embedding and additional features acquired by NLP tools can improve the accuracy of relationship extraction. This article provides a reference standard for engineers to select the optimal model under different conditions.","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116454114","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
DNS Network Security Analysis Based on Campus Environment 基于校园环境的DNS网络安全分析
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940338
Ruizhe Ye, Ying Wei, Wenzhi Wu, Feng Sha
{"title":"DNS Network Security Analysis Based on Campus Environment","authors":"Ruizhe Ye, Ying Wei, Wenzhi Wu, Feng Sha","doi":"10.1109/icis46139.2019.8940338","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940338","url":null,"abstract":"In this paper, we analyze the log data of the campus network DNS64, and build a new big data analysis platform to process the DNS64 streaming data in real time. Focus on mining information related to network security threats in DNS64 data. Through our analysis, we can organically correlate domain name traffic, IP address access, server load and other information. Real-time detection of DDOS network security attacks. Also the experimental verification, we found the abnormal behavior of individual IP, and the experimental results were good.","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122769674","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: 4
A C-LSTM with Word Embedding Model for News Text Classification 基于词嵌入的C-LSTM新闻文本分类模型
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940289
Minyong Shi, Kaixiang Wang, Chunfang Li
{"title":"A C-LSTM with Word Embedding Model for News Text Classification","authors":"Minyong Shi, Kaixiang Wang, Chunfang Li","doi":"10.1109/icis46139.2019.8940289","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940289","url":null,"abstract":"Traditional text classification methods are based on statistics and feature selection. It does not perform well in processing large - scale corpus. In recent years, with the rapid development of deep learning and artificial neural networks, many scholars use them to solve text classification problems and achieve good results. Common text classification neural network models include textCNN, LSTM, and C-LSTM. Using a specific model can obtain more accurate features but ignore the context information. This paper proposes a C-LSTM with word embedding model to deal with this problem. Experiments show that the model proposed in this paper has great advantages in Chinese news text classification.","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"261 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122808076","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: 15
Oracle RAC performance analysis on VMware Virtual SAN VMware Virtual SAN环境下Oracle RAC性能分析
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940347
Ying Wei, Ruizhe Ye, Xuhui Chen
{"title":"Oracle RAC performance analysis on VMware Virtual SAN","authors":"Ying Wei, Ruizhe Ye, Xuhui Chen","doi":"10.1109/icis46139.2019.8940347","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940347","url":null,"abstract":"A brand-new Oracle RAC system on VMware Virtual SAN was built with serval rack server. We use this new hardware platform to run the one of the busiest campus information database system on campus. This system takes full advantage of the features of VMware Virtual SAN such as high reliability, flexible expansion, simple backup and recovery, and low maintenance costs. We also tested the performance of the whole system including IO, TPM, query speed, throughput, latency and more. After testing the overall performance of the test achieved the expected results, which can fully meet the actual use.","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128376323","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: 2
Research on the Fine-tuning Technology Based on Faster R-CNN 基于更快R-CNN的微调技术研究
2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) Pub Date : 2019-06-01 DOI: 10.1109/icis46139.2019.8940232
Rigao Yin, Ligu Zhu, Wen Lu
{"title":"Research on the Fine-tuning Technology Based on Faster R-CNN","authors":"Rigao Yin, Ligu Zhu, Wen Lu","doi":"10.1109/icis46139.2019.8940232","DOIUrl":"https://doi.org/10.1109/icis46139.2019.8940232","url":null,"abstract":"In recent years, Deep Learning is widely used in various fields, such as object detection, speech recognition, etc. This paper focuses on the application of convolutional neural networks in transfer leaning. Convolutional Neural Networks (CNN) is a branch of Deep Learning. The calculation speed of matrix and CNN’s training speed have been improved greatly for GPU’s excellent computing capability. In the process of practice, the CNN model shows strong generalization ability. The CNN model can achieve higher classification accuracy with fine-tuning adjustment under the premise of sacrificing certain performance.","PeriodicalId":165136,"journal":{"name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121291251","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
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