Pub Date : 2023-01-01DOI: 10.1504/ijcse.2023.10058966
Mukta Kambhampati, Sandhya Harikumar
{"title":"Time series models for web service activity prediction","authors":"Mukta Kambhampati, Sandhya Harikumar","doi":"10.1504/ijcse.2023.10058966","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10058966","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"28 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78879668","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: 10.1504/ijcse.2023.133674
Sean Savitz, Charith Perera, Omer Rana
Camera sensors can measure our environment at high precision, providing the basis for detecting more complex phenomena in comparison to other sensors, e.g., temperature or humidity. Using benchmarks, this work evaluates object classification on resource constrained devices, focusing on video feeds from IoT cameras. The models that have been used in this research include MobileNetV1, MobileNetV2 and faster R-CNN that can be combined with regression models for precise object localisation. We compare the models by using their accuracy for classifying objects and the demand they impose on the computational resources of a Raspberry Pi. We conclude that the faster R-CNN model that is configured with the InceptionV2 regression model has the highest accuracy. However, this is at the cost of additional computational resources. We found that the best model to use for object detection functionality on the Raspberry Pi is the MobileNetV2 model paired with the SSDLite regression model.
{"title":"Edge analytics on resource constrained devices","authors":"Sean Savitz, Charith Perera, Omer Rana","doi":"10.1504/ijcse.2023.133674","DOIUrl":"https://doi.org/10.1504/ijcse.2023.133674","url":null,"abstract":"Camera sensors can measure our environment at high precision, providing the basis for detecting more complex phenomena in comparison to other sensors, e.g., temperature or humidity. Using benchmarks, this work evaluates object classification on resource constrained devices, focusing on video feeds from IoT cameras. The models that have been used in this research include MobileNetV1, MobileNetV2 and faster R-CNN that can be combined with regression models for precise object localisation. We compare the models by using their accuracy for classifying objects and the demand they impose on the computational resources of a Raspberry Pi. We conclude that the faster R-CNN model that is configured with the InceptionV2 regression model has the highest accuracy. However, this is at the cost of additional computational resources. We found that the best model to use for object detection functionality on the Raspberry Pi is the MobileNetV2 model paired with the SSDLite regression model.","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844473","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: 10.1504/ijcse.2023.133671
Ilaria Henke, Luigi Di Francesco, Assunta Errico
{"title":"Design and cost benefit analysis of an e-mobility service: an electric bus service in Naples, Italy","authors":"Ilaria Henke, Luigi Di Francesco, Assunta Errico","doi":"10.1504/ijcse.2023.133671","DOIUrl":"https://doi.org/10.1504/ijcse.2023.133671","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844946","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: 10.1504/ijcse.2023.10058276
Peixian Chen, Binjie Liao, Weipeng Liang, Yipeng Wang, Shanshan Ai, Yu Wang, Teng Huang, Jianwei He
{"title":"Attack and defence simulation platform for satellite networks based on Mininet","authors":"Peixian Chen, Binjie Liao, Weipeng Liang, Yipeng Wang, Shanshan Ai, Yu Wang, Teng Huang, Jianwei He","doi":"10.1504/ijcse.2023.10058276","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10058276","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"22 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83491341","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: 10.1504/ijcse.2023.10058179
José Miqueias, Antônio Carvalho, Francisco Airton Silva, Jorge Macedo, J. Carvalho, G. Callou
{"title":"Availability assessment and sensitivity analysis of an MBaaS platform","authors":"José Miqueias, Antônio Carvalho, Francisco Airton Silva, Jorge Macedo, J. Carvalho, G. Callou","doi":"10.1504/ijcse.2023.10058179","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10058179","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"11965 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76418545","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: 10.1504/ijcse.2023.10059380
Maria Ida Di Bartolomeo, Assunta Errico, Ilaria Henke, Armando Cartenì
{"title":"A big data and cloud computing model architecture for a multi-class travel demand estimation through traffic measures: a real case application in Italy","authors":"Maria Ida Di Bartolomeo, Assunta Errico, Ilaria Henke, Armando Cartenì","doi":"10.1504/ijcse.2023.10059380","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10059380","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135749593","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}
After the separation of rail infrastructure managers from rail service operators that occurred within the European Union in 1991, the necessity of defining an access charge framework for ensuring non-discriminatory access to the rail market arose. Basically, it has to guarantee an economic balance for infrastructure manager accounts. Currently, in the Italian context, access charge schemes neglect the actual energy-consumption of rail operators and related costs of energy traction for infrastructure managers. Therefore, we propose a methodology, integrating cloud-based tasks and simulation tools, for including such an aspect within the infrastructure toll, thus making the system more sustainable. Finally, to show the feasibility of the proposed approach, it has been applied to an Italian real rail context, i.e., the Rome-Naples high-speed railway line. Results have shown that customising the tool access charges, by considering the power supply required, may generate a virtuous loop with an increase in energy-efficiency of rail systems.
{"title":"A methodology for introducing an energy-efficient component within the rail infrastructure access charges in Italy","authors":"Marilisa Botte, Ilaria Tufano, Luca D', N.A. Acierno","doi":"10.1504/ijcse.2023.133673","DOIUrl":"https://doi.org/10.1504/ijcse.2023.133673","url":null,"abstract":"After the separation of rail infrastructure managers from rail service operators that occurred within the European Union in 1991, the necessity of defining an access charge framework for ensuring non-discriminatory access to the rail market arose. Basically, it has to guarantee an economic balance for infrastructure manager accounts. Currently, in the Italian context, access charge schemes neglect the actual energy-consumption of rail operators and related costs of energy traction for infrastructure managers. Therefore, we propose a methodology, integrating cloud-based tasks and simulation tools, for including such an aspect within the infrastructure toll, thus making the system more sustainable. Finally, to show the feasibility of the proposed approach, it has been applied to an Italian real rail context, i.e., the Rome-Naples high-speed railway line. Results have shown that customising the tool access charges, by considering the power supply required, may generate a virtuous loop with an increase in energy-efficiency of rail systems.","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844450","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: 10.1504/ijcse.2023.129149
Ashish Singh Parihar, Swarnendu Kumar Chakraborty
One of the highly researched areas in distributed system is mutual exclusion. To avoid any inconsistent state of system, more than one processes executing on different processors are not allowed to invoke their critical sections simultaneously for the purpose of resource sharing. As a solution to such resource allocation issues, token-based strategy for distributed mutual exclusion algorithms as a prime classification of solutions is one of the most popular and significant ways to handle mutual exclusion in this field. Through this research article, we propose a novel token-based distributed mutual exclusion algorithm. The proposed solution is scalable and has better results in terms of message complexity compared to existing solutions. In this proposed art of work, the numbers of messages exchange per critical section invocation are 3(⌈log N⌉ - 1), 3⌈(⌈log (N + 1) ⌉ - 1)/2⌉ and 6[⌈log (N + 1)⌉ + 2(2(-⌈log (N+1)⌉) - 1)] in case of light load, medium load and high load situations respectively.
{"title":"A new resource sharing protocol in the light of token-based strategy for distributed system","authors":"Ashish Singh Parihar, Swarnendu Kumar Chakraborty","doi":"10.1504/ijcse.2023.129149","DOIUrl":"https://doi.org/10.1504/ijcse.2023.129149","url":null,"abstract":"One of the highly researched areas in distributed system is mutual exclusion. To avoid any inconsistent state of system, more than one processes executing on different processors are not allowed to invoke their critical sections simultaneously for the purpose of resource sharing. As a solution to such resource allocation issues, token-based strategy for distributed mutual exclusion algorithms as a prime classification of solutions is one of the most popular and significant ways to handle mutual exclusion in this field. Through this research article, we propose a novel token-based distributed mutual exclusion algorithm. The proposed solution is scalable and has better results in terms of message complexity compared to existing solutions. In this proposed art of work, the numbers of messages exchange per critical section invocation are 3(⌈log N⌉ - 1), 3⌈(⌈log (N + 1) ⌉ - 1)/2⌉ and 6[⌈log (N + 1)⌉ + 2(2(-⌈log (N+1)⌉) - 1)] in case of light load, medium load and high load situations respectively.","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136298142","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: 10.1504/ijcse.2023.10059160
Jinghui Xiu, Yingnan Ye
{"title":"Research on assessment of hybrid teaching mode in colleges stems from deep learning algorithm","authors":"Jinghui Xiu, Yingnan Ye","doi":"10.1504/ijcse.2023.10059160","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10059160","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135496702","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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