{"title":"Retracted: Analysis of Chinese Image Discourse Based on Crawler Algorithms","authors":"Mobile Information Systems","doi":"10.1155/2023/9783894","DOIUrl":"https://doi.org/10.1155/2023/9783894","url":null,"abstract":"<jats:p />","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135824667","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}
In the modern and complex realm of networking, the pursuit of ideal QoS metrics is a fundamental objective aimed at maximizing network efficiency and user experiences. Nonetheless, the accomplishment of this task is hindered by the diversity of networks, the unpredictability of network conditions, and the rapid growth of multimedia traffic. This manuscript presents an innovative method for enhancing the QoS in SDN by combining the load-balancing capabilities of FL and genetic algorithms. The proposed solution aims to improve the dispersed aggregation of multimedia traffic by prioritizing data privacy and ensuring secure network load distribution. By using federated learning, multiple clients can collectively participate in the training process of a global model without compromising the privacy of their sensitive information. This method safeguards user privacy while facilitating the aggregation of distributed multimedia traffic. In addition, genetic algorithms are used to optimize network load balancing, thereby ensuring the efficient use of network resources and mitigating the risk of individual node overload. As a result of extensive testing, this research has demonstrated significant improvements in QoS measurements compared to traditional methods. Our proposed technique outperforms existing techniques such as RR, weighted RR, server load, LBBSRT, and dynamic server approaches in terms of CPU and memory utilization, as well as server requests across three testing servers. This novel methodology has applications in multiple industries, including telecommunications, multimedia streaming, and cloud computing. The proposed method presents an innovative strategy for addressing the optimization of QoS metrics in SDN environments, while preserving data privacy and optimizing network resource usage.
{"title":"Optimizing QoS Metrics for Software-Defined Networking in Federated Learning","authors":"Mahdi Fallah, Parya Mohammadi, Mohammadreza NasiriFard, Pedram Salehpour","doi":"10.1155/2023/3896267","DOIUrl":"https://doi.org/10.1155/2023/3896267","url":null,"abstract":"In the modern and complex realm of networking, the pursuit of ideal QoS metrics is a fundamental objective aimed at maximizing network efficiency and user experiences. Nonetheless, the accomplishment of this task is hindered by the diversity of networks, the unpredictability of network conditions, and the rapid growth of multimedia traffic. This manuscript presents an innovative method for enhancing the QoS in SDN by combining the load-balancing capabilities of FL and genetic algorithms. The proposed solution aims to improve the dispersed aggregation of multimedia traffic by prioritizing data privacy and ensuring secure network load distribution. By using federated learning, multiple clients can collectively participate in the training process of a global model without compromising the privacy of their sensitive information. This method safeguards user privacy while facilitating the aggregation of distributed multimedia traffic. In addition, genetic algorithms are used to optimize network load balancing, thereby ensuring the efficient use of network resources and mitigating the risk of individual node overload. As a result of extensive testing, this research has demonstrated significant improvements in QoS measurements compared to traditional methods. Our proposed technique outperforms existing techniques such as RR, weighted RR, server load, LBBSRT, and dynamic server approaches in terms of CPU and memory utilization, as well as server requests across three testing servers. This novel methodology has applications in multiple industries, including telecommunications, multimedia streaming, and cloud computing. The proposed method presents an innovative strategy for addressing the optimization of QoS metrics in SDN environments, while preserving data privacy and optimizing network resource usage.","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135092770","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}
Fully autonomous vehicles are a new technology that is expected to be widely accepted by consumers because of their various advantages. This study examined consumers’ intention to accept fully autonomous vehicles based on trust and resistance. To this end, consumer data were analyzed by integrating the innovation resistance model and the technology trust model. The subjects of the survey were 400 drivers between the ages of twenty and sixty-nine. As a result of the study, variables related to the “technical characteristics” of fully autonomous vehicles affected the resistance. On the other hand, “experiential characteristics” were confirmed to affect trust. Second, consumers with a high innovation propensity are more likely to accept fully autonomous vehicles when they are commercialized in the future. Third, it was found that resistance had a negative effect and trust had a positive effect on consumers’ intention to accept fully autonomous vehicles. Therefore, for consumers to accept these, technology should be developed in the direction of removing factors affecting resistance and providing factors increasing trust. As such, consumers have anxiety and concerns as well as expectations, even though they have not yet experienced a fully autonomous vehicle. In particular, since fully autonomous vehicles completely change the existing driving paradigm, more careful consideration is required in the diffusion of this technology.
{"title":"The Effect of Consumer Resistance and Trust on the Intention to Accept Fully Autonomous Vehicles","authors":"Dawoon Wang, Hyekyong Choi","doi":"10.1155/2023/3620148","DOIUrl":"https://doi.org/10.1155/2023/3620148","url":null,"abstract":"Fully autonomous vehicles are a new technology that is expected to be widely accepted by consumers because of their various advantages. This study examined consumers’ intention to accept fully autonomous vehicles based on trust and resistance. To this end, consumer data were analyzed by integrating the innovation resistance model and the technology trust model. The subjects of the survey were 400 drivers between the ages of twenty and sixty-nine. As a result of the study, variables related to the “technical characteristics” of fully autonomous vehicles affected the resistance. On the other hand, “experiential characteristics” were confirmed to affect trust. Second, consumers with a high innovation propensity are more likely to accept fully autonomous vehicles when they are commercialized in the future. Third, it was found that resistance had a negative effect and trust had a positive effect on consumers’ intention to accept fully autonomous vehicles. Therefore, for consumers to accept these, technology should be developed in the direction of removing factors affecting resistance and providing factors increasing trust. As such, consumers have anxiety and concerns as well as expectations, even though they have not yet experienced a fully autonomous vehicle. In particular, since fully autonomous vehicles completely change the existing driving paradigm, more careful consideration is required in the diffusion of this technology.","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135346291","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}
{"title":"Retracted: Construction of Online Shopping Legal Protection Mechanism Based on Artificial Intelligence Technology","authors":"Mobile Information Systems","doi":"10.1155/2023/9891645","DOIUrl":"https://doi.org/10.1155/2023/9891645","url":null,"abstract":"<jats:p />","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135551892","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}
{"title":"Retracted: Construction and Coping Strategies of Ideological and Political Education Evaluation System under the Background of Intelligent Internet of Things","authors":"Mobile Information Systems","doi":"10.1155/2023/9816940","DOIUrl":"https://doi.org/10.1155/2023/9816940","url":null,"abstract":"<jats:p />","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135552071","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}
{"title":"Retracted: Analysis of the Role of Decision Tree Algorithm in Art Education Based on the Background of the Internet of Things","authors":"Mobile Information Systems","doi":"10.1155/2023/9832072","DOIUrl":"https://doi.org/10.1155/2023/9832072","url":null,"abstract":"<jats:p />","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135590752","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}
{"title":"Retracted: Cultivating the Humanistic Quality of Nursing Undergraduates in the Internet Age","authors":"Mobile Information Systems","doi":"10.1155/2023/9784679","DOIUrl":"https://doi.org/10.1155/2023/9784679","url":null,"abstract":"<jats:p />","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135590891","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}
{"title":"Retracted: Application of Deep Learning for Discourse Expression Recognition in Ideological and Political Education","authors":"Mobile Information Systems","doi":"10.1155/2023/9763930","DOIUrl":"https://doi.org/10.1155/2023/9763930","url":null,"abstract":"<jats:p />","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135552271","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}
{"title":"Retracted: Application of Mathematical Model in Orthodontics","authors":"Mobile Information Systems","doi":"10.1155/2023/9792856","DOIUrl":"https://doi.org/10.1155/2023/9792856","url":null,"abstract":"<jats:p />","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135552267","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}
{"title":"Retracted: Intervention Algorithm of Horse Racing for Students’ Psychological Disorders Based on Big Data","authors":"Mobile Information Systems","doi":"10.1155/2023/9894267","DOIUrl":"https://doi.org/10.1155/2023/9894267","url":null,"abstract":"<jats:p />","PeriodicalId":49802,"journal":{"name":"Mobile Information Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135552288","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}
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