Pub Date : 2023-01-01DOI: 10.4236/jsea.2023.168020
A. Sampaio, A. Gomes, Paulo Sequeira, Gonçalo Ferreira Azevedo
{"title":"BIM Supporting the Development of Multitasks Related with the Structural Project","authors":"A. Sampaio, A. Gomes, Paulo Sequeira, Gonçalo Ferreira Azevedo","doi":"10.4236/jsea.2023.168020","DOIUrl":"https://doi.org/10.4236/jsea.2023.168020","url":null,"abstract":"","PeriodicalId":62222,"journal":{"name":"软件工程与应用(英文)","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70450167","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}
Pub Date : 2023-01-01DOI: 10.4236/jsea.2023.164006
David Jungwirth, D. Haluza
{"title":"Artificial Intelligence and the Sustainable Development Goals: An Exploratory Study in the Context of the Society Domain","authors":"David Jungwirth, D. Haluza","doi":"10.4236/jsea.2023.164006","DOIUrl":"https://doi.org/10.4236/jsea.2023.164006","url":null,"abstract":"","PeriodicalId":62222,"journal":{"name":"软件工程与应用(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70449692","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}
Pub Date : 2023-01-01DOI: 10.4236/jsea.2023.166010
E. O. Aliyu
{"title":"Review of Software Model-Checking Techniques for Dealing with Error Detection in Program Codes","authors":"E. O. Aliyu","doi":"10.4236/jsea.2023.166010","DOIUrl":"https://doi.org/10.4236/jsea.2023.166010","url":null,"abstract":"","PeriodicalId":62222,"journal":{"name":"软件工程与应用(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70449814","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}
Pub Date : 2023-01-01DOI: 10.4236/jsea.2023.162002
Man Liu
{"title":"Research and Practice of Online Service Hall in Colleges and Universities","authors":"Man Liu","doi":"10.4236/jsea.2023.162002","DOIUrl":"https://doi.org/10.4236/jsea.2023.162002","url":null,"abstract":"","PeriodicalId":62222,"journal":{"name":"软件工程与应用(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70450045","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}
Pub Date : 2023-01-01DOI: 10.4236/jsea.2023.162003
Mohammad Mustafa Taye, S. Ghoul
{"title":"An Approach towards Goal-Oriented Requirements Ontology: Consistency and Completeness Based Requirements Analysis","authors":"Mohammad Mustafa Taye, S. Ghoul","doi":"10.4236/jsea.2023.162003","DOIUrl":"https://doi.org/10.4236/jsea.2023.162003","url":null,"abstract":"","PeriodicalId":62222,"journal":{"name":"软件工程与应用(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70450065","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}
Pub Date : 2023-01-01DOI: 10.4236/jsea.2023.168018
Yuan-Gu Wei, Dan Zhang, Meiyan Gao, Yuan Tian, Ya He, Bolin Huang, Changyang Zheng
Breast cancer is a significant health concern, necessitating accurate prediction models for early detection and improved patient outcomes. This study presents a comparative analysis of three machine learning models, namely, Logistic Regression, Decision Tree, and Random Forest, for breast cancer prediction using the Wisconsin breast cancer diagnostic dataset. The dataset comprises features computed from fine needle aspirate images of breast masses, with 357 benign and 212 malignant cases. The research findings high-light that the Random Forest model, leveraging the top 5 predictors—“concave points_mean”, “area_mean”, “radius_mean”, “perimeter_mean”, and “con-cavity_mean”, achieves the highest predictive accuracy of approximately 95% and a cross-validation score of approximately 93% for the test dataset. These results demonstrate the potential of machine learning approaches in breast cancer prediction, underscoring their importance in aiding early detection and diagnosis.
{"title":"Breast Cancer Prediction Based on Machine Learning","authors":"Yuan-Gu Wei, Dan Zhang, Meiyan Gao, Yuan Tian, Ya He, Bolin Huang, Changyang Zheng","doi":"10.4236/jsea.2023.168018","DOIUrl":"https://doi.org/10.4236/jsea.2023.168018","url":null,"abstract":"Breast cancer is a significant health concern, necessitating accurate prediction models for early detection and improved patient outcomes. This study presents a comparative analysis of three machine learning models, namely, Logistic Regression, Decision Tree, and Random Forest, for breast cancer prediction using the Wisconsin breast cancer diagnostic dataset. The dataset comprises features computed from fine needle aspirate images of breast masses, with 357 benign and 212 malignant cases. The research findings high-light that the Random Forest model, leveraging the top 5 predictors—“concave points_mean”, “area_mean”, “radius_mean”, “perimeter_mean”, and “con-cavity_mean”, achieves the highest predictive accuracy of approximately 95% and a cross-validation score of approximately 93% for the test dataset. These results demonstrate the potential of machine learning approaches in breast cancer prediction, underscoring their importance in aiding early detection and diagnosis.","PeriodicalId":62222,"journal":{"name":"软件工程与应用(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70450084","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}
Pub Date : 2023-01-01DOI: 10.4236/jsea.2023.166011
Yuan-Gu Wei, Meiyan Gao, Jun Xiao, Chi-Hung Liu, Yuan Tian, Ya He
{"title":"Research and Implementation of Traffic Sign Recognition Algorithm Model Based on Machine Learning","authors":"Yuan-Gu Wei, Meiyan Gao, Jun Xiao, Chi-Hung Liu, Yuan Tian, Ya He","doi":"10.4236/jsea.2023.166011","DOIUrl":"https://doi.org/10.4236/jsea.2023.166011","url":null,"abstract":"","PeriodicalId":62222,"journal":{"name":"软件工程与应用(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70449854","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}
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