Pub Date : 2023-07-03DOI: 10.1007/s12530-023-09512-1
Debajit Sarma, H. Dutta, K. Yadav, M. Bhuyan, R. Laskar
{"title":"Attention-based hand semantic segmentation and gesture recognition using deep networks","authors":"Debajit Sarma, H. Dutta, K. Yadav, M. Bhuyan, R. Laskar","doi":"10.1007/s12530-023-09512-1","DOIUrl":"https://doi.org/10.1007/s12530-023-09512-1","url":null,"abstract":"","PeriodicalId":12174,"journal":{"name":"Evolving Systems","volume":"35 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90956566","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 : 2023-07-01DOI: 10.1007/s12530-023-09515-y
Delano Mendes de Santana, Sérgio Ricardo Lourenço, D. A. Cassiano
{"title":"Data mining approach for energy efficiency improvements in a utilities supply on a petrochemical plant","authors":"Delano Mendes de Santana, Sérgio Ricardo Lourenço, D. A. Cassiano","doi":"10.1007/s12530-023-09515-y","DOIUrl":"https://doi.org/10.1007/s12530-023-09515-y","url":null,"abstract":"","PeriodicalId":12174,"journal":{"name":"Evolving Systems","volume":"42 1","pages":"1071 - 1081"},"PeriodicalIF":3.2,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85026127","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 : 2023-06-27DOI: 10.1007/s12530-023-09511-2
E. Soares, P. Angelov, Sarah Biaso, M. Cury, D. Abe
{"title":"A large multiclass dataset of CT scans for COVID-19 identification","authors":"E. Soares, P. Angelov, Sarah Biaso, M. Cury, D. Abe","doi":"10.1007/s12530-023-09511-2","DOIUrl":"https://doi.org/10.1007/s12530-023-09511-2","url":null,"abstract":"","PeriodicalId":12174,"journal":{"name":"Evolving Systems","volume":"60 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91166953","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 : 2023-06-12DOI: 10.1007/s12530-023-09510-3
Saman Khamesian, Hamed Malek
{"title":"Hybrid self-attention NEAT: a novel evolutionary self-attention approach to improve the NEAT algorithm in high dimensional inputs","authors":"Saman Khamesian, Hamed Malek","doi":"10.1007/s12530-023-09510-3","DOIUrl":"https://doi.org/10.1007/s12530-023-09510-3","url":null,"abstract":"","PeriodicalId":12174,"journal":{"name":"Evolving Systems","volume":"9 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78756920","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}
Coronavirus emerged as a highly contagious, pathogenic virus that severely affects the respiratory system of humans. The epidemic-related data is collected regularly, which machine learning algorithms can employ to comprehend and estimate valuable information. The analysis of the gathered data through time series approaches may assist in developing more accurate forecasting models and strategies to combat the disease. This paper focuses on short-term forecasting of cumulative reported incidences and mortality. Forecasting is conducted utilizing state-of-the-art mathematical and deep learning models for multivariate time series forecasting, including extended susceptible-exposed-infected-recovered (SEIR), long-short-term memory (LSTM), and vector autoregression (VAR). The SEIR model has been extended by integrating additional information such as hospitalization, mortality, vaccination, and quarantine incidences. Extensive experiments have been conducted to compare deep learning and mathematical models that enable us to estimate fatalities and incidences more precisely based on mortality in the eight most affected nations during the time of this research. The metrics like mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) are employed to gauge the model's effectiveness. The deep learning model LSTM outperformed all others in terms of forecasting accuracy. Additionally, the study explores the impact of vaccination on reported epidemics and deaths worldwide. Furthermore, the detrimental effects of ambient temperature and relative humidity on pathogenic virus dissemination have been analyzed.
{"title":"Multivariate time series short term forecasting using cumulative data of coronavirus.","authors":"Suryanshi Mishra, Tinku Singh, Manish Kumar, Satakshi","doi":"10.1007/s12530-023-09509-w","DOIUrl":"10.1007/s12530-023-09509-w","url":null,"abstract":"<p><p>Coronavirus emerged as a highly contagious, pathogenic virus that severely affects the respiratory system of humans. The epidemic-related data is collected regularly, which machine learning algorithms can employ to comprehend and estimate valuable information. The analysis of the gathered data through time series approaches may assist in developing more accurate forecasting models and strategies to combat the disease. This paper focuses on short-term forecasting of cumulative reported incidences and mortality. Forecasting is conducted utilizing state-of-the-art mathematical and deep learning models for multivariate time series forecasting, including extended susceptible-exposed-infected-recovered (SEIR), long-short-term memory (LSTM), and vector autoregression (VAR). The SEIR model has been extended by integrating additional information such as hospitalization, mortality, vaccination, and quarantine incidences. Extensive experiments have been conducted to compare deep learning and mathematical models that enable us to estimate fatalities and incidences more precisely based on mortality in the eight most affected nations during the time of this research. The metrics like mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) are employed to gauge the model's effectiveness. The deep learning model LSTM outperformed all others in terms of forecasting accuracy. Additionally, the study explores the impact of vaccination on reported epidemics and deaths worldwide. Furthermore, the detrimental effects of ambient temperature and relative humidity on pathogenic virus dissemination have been analyzed.</p>","PeriodicalId":12174,"journal":{"name":"Evolving Systems","volume":" ","pages":"1-18"},"PeriodicalIF":2.7,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9705198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-26DOI: 10.1007/s12530-023-09508-x
Pranjal Kumar, S. Chauhan
{"title":"Towards improvement of baseline performance for regression based human pose estimation","authors":"Pranjal Kumar, S. Chauhan","doi":"10.1007/s12530-023-09508-x","DOIUrl":"https://doi.org/10.1007/s12530-023-09508-x","url":null,"abstract":"","PeriodicalId":12174,"journal":{"name":"Evolving Systems","volume":"46 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73819976","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 : 2023-05-16DOI: 10.1007/s12530-023-09506-z
Brijesh Bakariya, Arshdeep Singh, Harmanpreet Singh, P. Raju, Rohit Rajpoot, K. Mohbey
{"title":"Facial emotion recognition and music recommendation system using CNN-based deep learning techniques","authors":"Brijesh Bakariya, Arshdeep Singh, Harmanpreet Singh, P. Raju, Rohit Rajpoot, K. Mohbey","doi":"10.1007/s12530-023-09506-z","DOIUrl":"https://doi.org/10.1007/s12530-023-09506-z","url":null,"abstract":"","PeriodicalId":12174,"journal":{"name":"Evolving Systems","volume":"16 1","pages":"1-18"},"PeriodicalIF":3.2,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83512825","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 : 2023-05-05DOI: 10.1007/s12530-023-09503-2
Elif Selen Babüroğlu, A. Durmuşoğlu, Türkay Dereli
{"title":"Concept drift from 1980 to 2020: a comprehensive bibliometric analysis with future research insight","authors":"Elif Selen Babüroğlu, A. Durmuşoğlu, Türkay Dereli","doi":"10.1007/s12530-023-09503-2","DOIUrl":"https://doi.org/10.1007/s12530-023-09503-2","url":null,"abstract":"","PeriodicalId":12174,"journal":{"name":"Evolving Systems","volume":"1 1","pages":"1-21"},"PeriodicalIF":3.2,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75959547","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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