Pub Date : 2024-05-02DOI: 10.1109/mitp.2024.3371179
Andrei A. Ternikov
This article contributes to the field of matching techniques by introducing a new algorithm based on labor market data enrichment. This approach is able to collect and balance the training and test samples for data integration purposes. By setting thresholds for textual matching and geographic proximity, it simplifies the process of finding suitable company matches. Based on insufficiently studied datasets, the experimental findings show that the performance evaluation of proposed models differs depending on the similarity thresholds used.
{"title":"Company Name Matching Using Job Market Data Enrichment","authors":"Andrei A. Ternikov","doi":"10.1109/mitp.2024.3371179","DOIUrl":"https://doi.org/10.1109/mitp.2024.3371179","url":null,"abstract":"This article contributes to the field of matching techniques by introducing a new algorithm based on labor market data enrichment. This approach is able to collect and balance the training and test samples for data integration purposes. By setting thresholds for textual matching and geographic proximity, it simplifies the process of finding suitable company matches. Based on insufficiently studied datasets, the experimental findings show that the performance evaluation of proposed models differs depending on the similarity thresholds used.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"57 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-02DOI: 10.1109/mitp.2023.3338455
Mohamed Saied, Ahmed Mohammed Elfatatry, Shawkat Kamal Guirguis
Ever since the invention of software, change has been a destabilizing factor. Although many new software changes are being applied, the terminologies used to describe them are often inconsistent. This restricts practitioners to designing and evaluating their changes. This article aims to develop a conceptual framework of software change based on six main dimensions regarding the source, essence, and consequences of software change. To evaluate the proposed framework, benchmarking is applied against selected 11 previous studies.
{"title":"Conceptual Framework for Software Change","authors":"Mohamed Saied, Ahmed Mohammed Elfatatry, Shawkat Kamal Guirguis","doi":"10.1109/mitp.2023.3338455","DOIUrl":"https://doi.org/10.1109/mitp.2023.3338455","url":null,"abstract":"Ever since the invention of software, change has been a destabilizing factor. Although many new software changes are being applied, the terminologies used to describe them are often inconsistent. This restricts practitioners to designing and evaluating their changes. This article aims to develop a conceptual framework of software change based on six main dimensions regarding the source, essence, and consequences of software change. To evaluate the proposed framework, benchmarking is applied against selected 11 previous studies.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-02DOI: 10.1109/mitp.2024.3375571
Caitlin Ferreira, Andrew Park, Jan Kietzmann, Dionysios Demetis, Andrew Flostrand, Ian McCarthy, Leyland Pitt, Amir Dabirian
The meteoric rise in cybercrime in recent years has resulted in renewed efforts to stem the potential negative effects of these nefarious activities. In this context, the role of the chief information security officer (CISO) has become one of strategic importance, safeguarding the integrity of the organization’s digital assets. Given the economic impact of cybercrime, it has become critically important to understand the cybercrime-related issues that organizations face. We sought to identify these issues by conducting a bibliographic analysis of cybercrime research. The results identified the most prolific and impactful authors, journals, and countries of publication, the most influential articles, and trends in the literature on cybercrime. The research suggests that interest in the field is wide-reaching with the growth in publications stemming from diverse academic disciplines and geographies. The identified trends represent critical knowledge areas for the CISO that are likely to continue the expansion of the field.
{"title":"Cybercrime: Understanding the Current State of Literature and Issues Facing CISOs","authors":"Caitlin Ferreira, Andrew Park, Jan Kietzmann, Dionysios Demetis, Andrew Flostrand, Ian McCarthy, Leyland Pitt, Amir Dabirian","doi":"10.1109/mitp.2024.3375571","DOIUrl":"https://doi.org/10.1109/mitp.2024.3375571","url":null,"abstract":"The meteoric rise in cybercrime in recent years has resulted in renewed efforts to stem the potential negative effects of these nefarious activities. In this context, the role of the chief information security officer (CISO) has become one of strategic importance, safeguarding the integrity of the organization’s digital assets. Given the economic impact of cybercrime, it has become critically important to understand the cybercrime-related issues that organizations face. We sought to identify these issues by conducting a bibliographic analysis of cybercrime research. The results identified the most prolific and impactful authors, journals, and countries of publication, the most influential articles, and trends in the literature on cybercrime. The research suggests that interest in the field is wide-reaching with the growth in publications stemming from diverse academic disciplines and geographies. The identified trends represent critical knowledge areas for the CISO that are likely to continue the expansion of the field.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"9 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01DOI: 10.1109/mitp.2023.3338026
Byungseok Kang, Youngjae Jo
StyleGAN is a widely used model in various AI domains that generates high-quality images. It has many advantages but has the disadvantage of per-pixel noise inputs. These noise inputs used from StyleGAN are independent of location information and have a negative impact on natural location information learning because random noise is inserted in pixel units at intervals. This problem was even more problematic in the area of creating human faces. StyleGAN3 was announced to overcome this, but it did not completely solve the existing problems. If the angle of a human face is more than 30° from the front, the restoration rate further decreases. In this article, we propose an advanced semantic segment encoder that accurately generates eyes, nose, and mouth even when the angle of a human face is rotated more than 60°. We developed a face-angle analyzer to accurately measure the angle of a person’s face. The proposed idea improved restoration performance by approximately 30% compared to existing encoders when the face is not straight ahead.
{"title":"StyleGAN-Based Advanced Semantic Segment Encoder for Generative AI","authors":"Byungseok Kang, Youngjae Jo","doi":"10.1109/mitp.2023.3338026","DOIUrl":"https://doi.org/10.1109/mitp.2023.3338026","url":null,"abstract":"StyleGAN is a widely used model in various AI domains that generates high-quality images. It has many advantages but has the disadvantage of per-pixel noise inputs. These noise inputs used from StyleGAN are independent of location information and have a negative impact on natural location information learning because random noise is inserted in pixel units at intervals. This problem was even more problematic in the area of creating human faces. StyleGAN3 was announced to overcome this, but it did not completely solve the existing problems. If the angle of a human face is more than 30° from the front, the restoration rate further decreases. In this article, we propose an advanced semantic segment encoder that accurately generates eyes, nose, and mouth even when the angle of a human face is rotated more than 60°. We developed a face-angle analyzer to accurately measure the angle of a person’s face. The proposed idea improved restoration performance by approximately 30% compared to existing encoders when the face is not straight ahead.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"53 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01DOI: 10.1109/mitp.2023.3298520
Yunwu Xu, Yan Li
The investigation develops a method for improving the quality of security bug report (SBR) prediction during the software development and application processes. The research includes three stages. The first stage is preparing the source data. The second stage is constructing an original SBR prediction method using a machine learning algorithm [random forest (RF)]. The third stage is evaluating our method with well-established methods like filtering and ranking for security bug report prediction (FARSEC) and Keywords Matrix. It was shown that the values of such indicators as accuracy, precision, recall, and F-score when using the RF algorithm are, on average, 0.2–1% higher than when using the FARSEC and Keywords Matrix methods. The more initial number of reports the database contains, the higher the value of accuracy, precision, recall, and F-score that can be obtained. A new method can be used to predict SBRs during the software development and application processes.
这项研究开发了一种在软件开发和应用过程中提高安全漏洞报告（SBR）预测质量的方法。研究包括三个阶段。第一阶段是准备源数据。第二阶段是使用机器学习算法[随机森林 (RF)]构建原始 SBR 预测方法。第三阶段是将我们的方法与安全漏洞报告预测的过滤和排序（FARSEC）和关键词矩阵等成熟方法进行评估。结果表明，使用 RF 算法时，准确率、精确度、召回率和 F 分数等指标值平均比使用 FARSEC 和关键词矩阵方法时高 0.2-1%。数据库包含的初始报告数量越多，准确率、精确率、召回率和 F 分数就越高。新方法可用于在软件开发和应用过程中预测 SBR。
{"title":"A New Method of Security Bug Reports Analysis","authors":"Yunwu Xu, Yan Li","doi":"10.1109/mitp.2023.3298520","DOIUrl":"https://doi.org/10.1109/mitp.2023.3298520","url":null,"abstract":"The investigation develops a method for improving the quality of security bug report (SBR) prediction during the software development and application processes. The research includes three stages. The first stage is preparing the source data. The second stage is constructing an original SBR prediction method using a machine learning algorithm [random forest (RF)]. The third stage is evaluating our method with well-established methods like filtering and ranking for security bug report prediction (FARSEC) and Keywords Matrix. It was shown that the values of such indicators as accuracy, precision, recall, and F-score when using the RF algorithm are, on average, 0.2–1% higher than when using the FARSEC and Keywords Matrix methods. The more initial number of reports the database contains, the higher the value of accuracy, precision, recall, and F-score that can be obtained. A new method can be used to predict SBRs during the software development and application processes.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01DOI: 10.1109/mitp.2024.3390189
{"title":"IEEE Open Journal of the Computer Society","authors":"","doi":"10.1109/mitp.2024.3390189","DOIUrl":"https://doi.org/10.1109/mitp.2024.3390189","url":null,"abstract":"","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"28 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01DOI: 10.1109/mitp.2023.3286213
{"title":"IEEE Computer Society Has You Covered!","authors":"","doi":"10.1109/mitp.2023.3286213","DOIUrl":"https://doi.org/10.1109/mitp.2023.3286213","url":null,"abstract":"","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"64 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01DOI: 10.1109/mitp.2024.3386238
{"title":"IEEE Transactions on Big Data","authors":"","doi":"10.1109/mitp.2024.3386238","DOIUrl":"https://doi.org/10.1109/mitp.2024.3386238","url":null,"abstract":"","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"54 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01DOI: 10.1109/mitp.2024.3388189
{"title":"IEEE Computer Society - Call for Papers","authors":"","doi":"10.1109/mitp.2024.3388189","DOIUrl":"https://doi.org/10.1109/mitp.2024.3388189","url":null,"abstract":"","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"9 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01DOI: 10.1109/mitp.2024.3374129
Mercedes Ruiz, Elena Orta, Javier Gutiérrez
In software engineering, the onboarding process of new software engineers is crucial. The primary goal of this process is to ensure that professionals gain the necessary knowledge and skills to comprehend the company’s culture, integrate into the organization, and perform their activities effectively. Enhancing corporate learning processes and addressing human aspects, such as motivation, engagement, and commitment, are among the key factors influencing the success of the onboarding process. Gamification—the use of game elements in nongame contexts—has been widely employed in different contexts to promote positive changes in people’s behavior and increase their engagement and performance. We consider the integration of gamification into the onboarding process an interesting field of study and research. In this work, we propose a novel method for gamifying the onboarding process and introduce an application case within an organizational context.
{"title":"A Gamification Method for Improving the Onboarding Process of Software Engineers","authors":"Mercedes Ruiz, Elena Orta, Javier Gutiérrez","doi":"10.1109/mitp.2024.3374129","DOIUrl":"https://doi.org/10.1109/mitp.2024.3374129","url":null,"abstract":"In software engineering, the onboarding process of new software engineers is crucial. The primary goal of this process is to ensure that professionals gain the necessary knowledge and skills to comprehend the company’s culture, integrate into the organization, and perform their activities effectively. Enhancing corporate learning processes and addressing human aspects, such as motivation, engagement, and commitment, are among the key factors influencing the success of the onboarding process. Gamification—the use of game elements in nongame contexts—has been widely employed in different contexts to promote positive changes in people’s behavior and increase their engagement and performance. We consider the integration of gamification into the onboarding process an interesting field of study and research. In this work, we propose a novel method for gamifying the onboarding process and introduce an application case within an organizational context.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"89 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：