Pub Date : 2023-01-01DOI: 10.1504/ijcat.2023.10057079
A. Shahade, K. Walse, V. Thakare
{"title":"Deep learning approach based hybrid fine-tuned Smith algorithm with Adam optimiser for multilingual opinion mining","authors":"A. Shahade, K. Walse, V. Thakare","doi":"10.1504/ijcat.2023.10057079","DOIUrl":"https://doi.org/10.1504/ijcat.2023.10057079","url":null,"abstract":"","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75238638","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/ijcat.2023.134774
Henderson Acosta Bragança, Paulo Caetano Da Silva, Nacles Bernardino Pirajá Gomes
{"title":"Web service and internet of things: a systematic literature review","authors":"Henderson Acosta Bragança, Paulo Caetano Da Silva, Nacles Bernardino Pirajá Gomes","doi":"10.1504/ijcat.2023.134774","DOIUrl":"https://doi.org/10.1504/ijcat.2023.134774","url":null,"abstract":"","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135605221","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/ijcat.2023.132553
Ali Kadhum Idrees, Marwa Saieed Khlief
{"title":"Lossless EEG data compression using clustering and encoding for fog computing based IoMT networks","authors":"Ali Kadhum Idrees, Marwa Saieed Khlief","doi":"10.1504/ijcat.2023.132553","DOIUrl":"https://doi.org/10.1504/ijcat.2023.132553","url":null,"abstract":"","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135734792","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/ijcat.2023.133294
Bráulio Alturas
{"title":"Connection between UML use case diagrams and UML class diagrams: a matrix proposal","authors":"Bráulio Alturas","doi":"10.1504/ijcat.2023.133294","DOIUrl":"https://doi.org/10.1504/ijcat.2023.133294","url":null,"abstract":"","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135400597","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/ijcat.2023.134091
Salam Jayachitra Devi, Buddha Singh
The paper focuses on analysing link prediction using the Node2Vec embedding technique, which is based on the Random Walk algorithm. In addition to this, several machine learning models have been employed to assess the effectiveness of the embedding technique. Node2Vec employs various embedding operators, including Hadamard, Concatenation, Average, Weighted L1, and Weighted L2. The comparative analysis of this embedding technique is done on real world network data sets using various machine learning models with state of the art link prediction algorithms. Performance assessment of Node2Vec's embedding technique is based on the AUC metric. According to the simulation results, it has been determined that the concatenation operator with the bagging classifier yields mean AUC value of 0.939, outperforming the other operators, which produce AUC values below 0.91. Furthermore, the study has also revealed that the embedding technique provides superior results when applied to networks with a low ratio of nodes to edges.
{"title":"Link prediction analysis based on Node2Vec embedding technique","authors":"Salam Jayachitra Devi, Buddha Singh","doi":"10.1504/ijcat.2023.134091","DOIUrl":"https://doi.org/10.1504/ijcat.2023.134091","url":null,"abstract":"The paper focuses on analysing link prediction using the Node2Vec embedding technique, which is based on the Random Walk algorithm. In addition to this, several machine learning models have been employed to assess the effectiveness of the embedding technique. Node2Vec employs various embedding operators, including Hadamard, Concatenation, Average, Weighted L1, and Weighted L2. The comparative analysis of this embedding technique is done on real world network data sets using various machine learning models with state of the art link prediction algorithms. Performance assessment of Node2Vec's embedding technique is based on the AUC metric. According to the simulation results, it has been determined that the concatenation operator with the bagging classifier yields mean AUC value of 0.939, outperforming the other operators, which produce AUC values below 0.91. Furthermore, the study has also revealed that the embedding technique provides superior results when applied to networks with a low ratio of nodes to edges.","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136209415","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/ijcat.2023.133292
Rachana Yogesh Patil, Yogesh H. Patil, Sheetal U. Bhandari
Automatic detection of fatigue from the face provides non-intrusive passive identification of fatigue. The traditional approach of fatigue detection has focused on detecting yawning and eyelid closure. However, fatigue is manifested in the face through various minute facial features. In this paper, we propose a fatigue detection model, which can learn facial expression features through a deep learning-based facial expression recognition model and provide the same to the fatigue recognition model. Experiments indicate that the proposed approach achieves a qualitative improvement of facial features used for fatigue detection and improves the accuracy quantitatively on the custom Indian fatigue data set. The approach also allows mitigation of limitations of fatigue data sets of significantly fewer subjects and allows for training fatigue models suitable for unconstrained real-world settings.
{"title":"FER to FFR: a deep-learning-based approach for robust fatigue detection","authors":"Rachana Yogesh Patil, Yogesh H. Patil, Sheetal U. Bhandari","doi":"10.1504/ijcat.2023.133292","DOIUrl":"https://doi.org/10.1504/ijcat.2023.133292","url":null,"abstract":"Automatic detection of fatigue from the face provides non-intrusive passive identification of fatigue. The traditional approach of fatigue detection has focused on detecting yawning and eyelid closure. However, fatigue is manifested in the face through various minute facial features. In this paper, we propose a fatigue detection model, which can learn facial expression features through a deep learning-based facial expression recognition model and provide the same to the fatigue recognition model. Experiments indicate that the proposed approach achieves a qualitative improvement of facial features used for fatigue detection and improves the accuracy quantitatively on the custom Indian fatigue data set. The approach also allows mitigation of limitations of fatigue data sets of significantly fewer subjects and allows for training fatigue models suitable for unconstrained real-world settings.","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135400327","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/ijcat.2023.134773
Mangesh Phate, Shraddha Toney, Vikas Phate
{"title":"Modelling and simulation of portable solar Scheffler reflector water heater using soft computing techniques","authors":"Mangesh Phate, Shraddha Toney, Vikas Phate","doi":"10.1504/ijcat.2023.134773","DOIUrl":"https://doi.org/10.1504/ijcat.2023.134773","url":null,"abstract":"","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135610006","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/ijcat.2023.134775
Vinh T. Nguyen
{"title":"A systematic review of factors in augmented reality studies: a visualisation approach","authors":"Vinh T. Nguyen","doi":"10.1504/ijcat.2023.134775","DOIUrl":"https://doi.org/10.1504/ijcat.2023.134775","url":null,"abstract":"","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135610009","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/ijcat.2023.10059367
Mangesh Phate, Shraddha Toney, Vikas Phate
{"title":"Modelling and simulation of portable solar Scheffler reflector water heater using soft computing techniques","authors":"Mangesh Phate, Shraddha Toney, Vikas Phate","doi":"10.1504/ijcat.2023.10059367","DOIUrl":"https://doi.org/10.1504/ijcat.2023.10059367","url":null,"abstract":"","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135653444","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/ijcat.2023.133881
Fei Xu, Jing Chen, Xia Yin
This article proposes a Coyote Optimisation Compound Iterative Algorithm (CO-CIA) for rational models. Particularly, the parameters in the numerator and denominator of rational models make the derivative equation hard to solve. To deal with this problem, the Coyote Optimisation Algorithm (COA) is applied to estimate the parameters in the denominator. Compared with the Bias Compensation-based Least Squares (BCLS) algorithm and the Particle Swarm Optimisation Compound Iterative Algorithm (PSO-CIA), the proposed method has higher accuracy and faster convergence rates. Finally, a simulation example is utilised to verify the effectiveness of the proposed algorithm.
{"title":"The compound iterative algorithm for rational models based on the Coyote optimisation algorithm","authors":"Fei Xu, Jing Chen, Xia Yin","doi":"10.1504/ijcat.2023.133881","DOIUrl":"https://doi.org/10.1504/ijcat.2023.133881","url":null,"abstract":"This article proposes a Coyote Optimisation Compound Iterative Algorithm (CO-CIA) for rational models. Particularly, the parameters in the numerator and denominator of rational models make the derivative equation hard to solve. To deal with this problem, the Coyote Optimisation Algorithm (COA) is applied to estimate the parameters in the denominator. Compared with the Bias Compensation-based Least Squares (BCLS) algorithm and the Particle Swarm Optimisation Compound Iterative Algorithm (PSO-CIA), the proposed method has higher accuracy and faster convergence rates. Finally, a simulation example is utilised to verify the effectiveness of the proposed algorithm.","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136004388","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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