Pub Date : 2023-01-01DOI: 10.1504/ijcse.2023.10055525
{"title":"Examining the role of likes in follower network evolution based on a dynamic panel data model","authors":"","doi":"10.1504/ijcse.2023.10055525","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10055525","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"1 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91197434","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.2023.133690
Longxin Zhang, Yang Hu, Tianyu Chen, Hong Wen, Peng Zhou, Wenliang Zeng
{"title":"Novel freight train image fault detection and classification models based on CNN","authors":"Longxin Zhang, Yang Hu, Tianyu Chen, Hong Wen, Peng Zhou, Wenliang Zeng","doi":"10.1504/ijcse.2023.133690","DOIUrl":"https://doi.org/10.1504/ijcse.2023.133690","url":null,"abstract":"","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":"135844980","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}
The Hurst exponent is used to identify the autocorrelation structure of a stochastic time series, which allows for detecting persistence in time series data. Traditional signal processing techniques work reasonably well in determining the Hurst exponent of a stochastic time series. However, a notable drawback of these methods is their speed of computation. Neural networks have repeatedly proven their ability to learn very complex input-output mappings, even in high dimensional vector spaces. Therefore, an endeavour has been undertaken to employ neural networks to determine the Hurst exponent of a stochastic time series. Unlike previous attempts to solve such problems using neural networks, the proposed architecture can be recognised as the universal estimator of Hurst exponent for short-range and long-range dependent stochastic time series. Experiments demonstrate that if sufficiently trained, neural network can predict the Hurst exponent of any stochastic data at least fifteen times faster than standard signal processing approaches.
{"title":"Hurst exponent estimation using neural network","authors":"Somenath Mukherjee, Bikash Sadhukhan, Arghya Kusum Das, Abhra Chaudhuri","doi":"10.1504/ijcse.2023.129734","DOIUrl":"https://doi.org/10.1504/ijcse.2023.129734","url":null,"abstract":"The Hurst exponent is used to identify the autocorrelation structure of a stochastic time series, which allows for detecting persistence in time series data. Traditional signal processing techniques work reasonably well in determining the Hurst exponent of a stochastic time series. However, a notable drawback of these methods is their speed of computation. Neural networks have repeatedly proven their ability to learn very complex input-output mappings, even in high dimensional vector spaces. Therefore, an endeavour has been undertaken to employ neural networks to determine the Hurst exponent of a stochastic time series. Unlike previous attempts to solve such problems using neural networks, the proposed architecture can be recognised as the universal estimator of Hurst exponent for short-range and long-range dependent stochastic time series. Experiments demonstrate that if sufficiently trained, neural network can predict the Hurst exponent of any stochastic data at least fifteen times faster than standard signal processing approaches.","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"15 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":"135126754","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.2023.129743
Rachana Y. Patil, Yogesh H. Patil
{"title":"A proxy signcryption scheme for secure sharing of industrial IoT data in fog environment","authors":"Rachana Y. Patil, Yogesh H. Patil","doi":"10.1504/ijcse.2023.129743","DOIUrl":"https://doi.org/10.1504/ijcse.2023.129743","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"18 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":"135585755","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}
{"title":"Fake content detection on benchmark dataset using various deep learning models","authors":"Chetana Thaokar, Jitendra Kumar Rout, Himansu Das, Minakhi Rout","doi":"10.1504/ijcse.2023.10060449","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10060449","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"10 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":"135705531","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.2023.10059724
Paresh Kumar Panigrahi, Sukanta Nayak
{"title":"Conjugate gradient with Armijo line search approach to investigate imprecisely defined unconstrained optimisation problem","authors":"Paresh Kumar Panigrahi, Sukanta Nayak","doi":"10.1504/ijcse.2023.10059724","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10059724","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"18 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":"136209893","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.2023.10059782
A.S. Syed Shahul Hameed, Narendran Rajagopalan, J. Jyothsna, B. Surendiran, J. Dhakshayani
{"title":"A deep learning based automated phenotyping for identification of overuse of synthetic fertilisers in Amaranthus crop","authors":"A.S. Syed Shahul Hameed, Narendran Rajagopalan, J. Jyothsna, B. Surendiran, J. Dhakshayani","doi":"10.1504/ijcse.2023.10059782","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10059782","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"20 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":"136304585","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.2023.10059379
Luigi Di Francesco, Assunta Errico, Ilaria Henke
{"title":"Design and cost benefit analysis of an e-mobility service: an electric bus service in Naples, Italy","authors":"Luigi Di Francesco, Assunta Errico, Ilaria Henke","doi":"10.1504/ijcse.2023.10059379","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10059379","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"12 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":"135749896","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}
{"title":"FCAODNet: a fast freight train image detection model based on embedded FCA","authors":"Xiaojun Deng, Chengkang Weng, Longxin Zhang, Miao Wang, Peng Zhou","doi":"10.1504/ijcse.2023.10059395","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10059395","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"87 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":"135750346","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.2023.10058164
Dakota Messer, Hoe-Gil Lee
{"title":"Study on the capacity of a hybrid solar PV/wind turbine system using small-scale prototype application for dairy farm power demand in North Texas","authors":"Dakota Messer, Hoe-Gil Lee","doi":"10.1504/ijcse.2023.10058164","DOIUrl":"https://doi.org/10.1504/ijcse.2023.10058164","url":null,"abstract":"","PeriodicalId":47380,"journal":{"name":"International Journal of Computational Science and Engineering","volume":"377 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80594650","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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