Proceedings of the 2020 9th International Conference on Software and Computer Applications最新文献_第7页

A Method of Collecting the IP Addresses of Hidden Server in Tor Networks 一种Tor网络中隐藏服务器IP地址的采集方法

Proceedings of the 2020 9th International Conference on Software and Computer Applications Pub Date : 2020-02-18 DOI: 10.1145/3384544.3384589

N. Yoshiura, Kento Koizumi

引用次数: 0

Masked Face Detection Based on Locally Nonlinear Feature Fusion 基于局部非线性特征融合的被遮挡人脸检测

Proceedings of the 2020 9th International Conference on Software and Computer Applications Pub Date : 2020-02-18 DOI: 10.1145/3384544.3384568

Xin-Yi Peng, Jun Cao, Fuyuan Zhang

引用次数: 3

Estimation of Heat of Formation for Chemical Systems using the Lasso Regression-Based Approach 用Lasso回归方法估计化学系统的生成热

Proceedings of the 2020 9th International Conference on Software and Computer Applications Pub Date : 2020-02-18 DOI: 10.1145/3384544.3384600

T. Nguyen, Nam T.H. Nguyen, T. Le, Sang T. T. Nguyen, Lam Huynh

引用次数: 0

Recommendations for Improving Data Management Process in Government of Bandung Regency using COBIT 4.1 Framework 关于使用COBIT 4.1框架改进万隆县政府数据管理过程的建议

Proceedings of the 2020 9th International Conference on Software and Computer Applications Pub Date : 2020-02-18 DOI: 10.1145/3384544.3384588

Heru Nugroho, S. F. Gumilang

引用次数: 1

A Review of Artificial Intelligence Techniques used for Urban Automatic Incident Detection Systems 人工智能技术在城市事件自动检测系统中的应用综述

Proceedings of the 2020 9th International Conference on Software and Computer Applications Pub Date : 2020-02-18 DOI: 10.1145/3384544.3384557

H. Samia, Dennai Abdeslem

{"title":"A Review of Artificial Intelligence Techniques used for Urban Automatic Incident Detection Systems","authors":"H. Samia, Dennai Abdeslem","doi":"10.1145/3384544.3384557","DOIUrl":"https://doi.org/10.1145/3384544.3384557","url":null,"abstract":"Over the past decades, tremendous research efforts have been proposed to deploy Automatic Incident Detection Systems (AIDSs) onto urban roads. As a result, new challenges to the research community have been introduced to enhance the AIDS performances. To overcome these challenges, and to improve the efficiency and safety of road traffic, attention has been drawn to use Artificial Intelligence (AI) techniques as a solution. However, choosing appropriate AI technologies to process real-time traffic data is an area that needs spotlighting. The aim of this paper is to discuss recent advancements in urban AIDSs based on AI techniques. We carried out a review for twelve previous AIDS study proposed since 2009. We compared these AIDSs in term of traffic data sources, input variables, and type of incident. Also, a comparison of simulators, techniques and the evaluation metrics has been used. The results indicated that hybrid AI techniques reported the best detection performances. In this context, fixed or fusion data sources were also given good results compared to others. This review shows reliable results of AI classification techniques applied in AIDS approaches. This finding urges to continue improve the performances of the proposed AI techniques. In future research, testing others AI techniques with smart technologies may increase the incident detection efficiency.","PeriodicalId":200246,"journal":{"name":"Proceedings of the 2020 9th International Conference on Software and Computer Applications","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126401916","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

Improving Classification Accuracy of Random Forest Algorithm Using Unsupervised Discretization with Fuzzy Partition and Fuzzy Set Intervals 利用模糊划分和模糊集区间的无监督离散提高随机森林算法的分类精度

Proceedings of the 2020 9th International Conference on Software and Computer Applications Pub Date : 2020-02-18 DOI: 10.1145/3384544.3384590

Muhammad Nur Fikri Hishamuddin, M. Hassan, A. Mokhtar

{"title":"Improving Classification Accuracy of Random Forest Algorithm Using Unsupervised Discretization with Fuzzy Partition and Fuzzy Set Intervals","authors":"Muhammad Nur Fikri Hishamuddin, M. Hassan, A. Mokhtar","doi":"10.1145/3384544.3384590","DOIUrl":"https://doi.org/10.1145/3384544.3384590","url":null,"abstract":"It is known that certain classification algorithm requires continuous data to be discretized for it to produce better classification accuracy. Hence, many works have explored the pairing of classification algorithm and discretization techniques, yet tree-based classifier especially Classification and Regression Trees (CART) still have an issue with classification accuracy regardless of different pairing with existing discretization techniques. The role of fuzzy partition and fuzzy sets interval are not something new in data discretization but none yet to explore the pairing of fuzzy discretization with tree-based algorithm. This paper will be discussing on an approach of using fuzzy based discretization and a member of tree-based algorithm known as Random Forest, a better version of CART. In this study, continuous data are identified from a dataset and discretized through the fuzzy discretization. Then, 10-fold cross validation is done on the transformed dataset and seven well-known classifiers are used including the proposed approach. Based on the results, better classification accuracy is achieved when fuzzy discretization is paired with Random Forest algorithm compared to CART. On top of that, with the present of fuzzy discretization technique, an increased in the classification accuracy has been obtained compared to other classification algorithms.","PeriodicalId":200246,"journal":{"name":"Proceedings of the 2020 9th International Conference on Software and Computer Applications","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124664797","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

EQ101 EQ101

Proceedings of the 2020 9th International Conference on Software and Computer Applications Pub Date : 2020-02-18 DOI: 10.1145/3384544.3384605

N. Hiransakolwong

{"title":"EQ101","authors":"N. Hiransakolwong","doi":"10.1145/3384544.3384605","DOIUrl":"https://doi.org/10.1145/3384544.3384605","url":null,"abstract":"Emotional Quotient or EQ means being able to realize feelings of oneself and others to create self-motivation and can handle various emotions become good, smart, and happy. There are only web applications for EQ assessment, but it cannot record any EQ history of the tests for seeing personal development of EQ and cannot report the test results to teachers or parents. Nowadays, most students use smartphones. This research presents an application in EQ assessment for students aging 12-17 years with processing on smartphones using Android OS. There were randomly selected 31 students from a local school to test with this application. The experiment results show that the application can help these students to know their EQ assessment results that were reported to their parents and counselor teachers. The application can record the previous results also to see the development of EQ in personal. At the same time, the executive board of school can use the histogram of EQ assessment results to plan for school activities that are suitable for developing EQ to their students. This can help students avoid with depression. All users gave an excellent level of satisfaction with this application on an average of 4.88 from 5.","PeriodicalId":200246,"journal":{"name":"Proceedings of the 2020 9th International Conference on Software and Computer Applications","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116778286","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

Proceedings of the 2020 9th International Conference on Software and Computer Applications 2020年第九届软件与计算机应用国际会议论文集

Proceedings of the 2020 9th International Conference on Software and Computer Applications Pub Date : 1900-01-01 DOI: 10.1145/3384544

引用次数: 0