Pub Date : 2023-01-01DOI: 10.1504/ijict.2023.134834
Yan Xiang, Junjun Guo, Yuxin Huang, Zhengtao Yu
{"title":"Content and opinion-enhanced neural model for opinion sentence classification of Chinese microblog comments","authors":"Yan Xiang, Junjun Guo, Yuxin Huang, Zhengtao Yu","doi":"10.1504/ijict.2023.134834","DOIUrl":"https://doi.org/10.1504/ijict.2023.134834","url":null,"abstract":"","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"135709250","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/ijict.2023.10056387
E. Saudabekova, Anastasiya Skripnikova, Saken Mukan, M. Negizbayeva, Azel Zhanibek
{"title":"The communication trends referring to Kazakhstans international image (the case of The Washington Post)","authors":"E. Saudabekova, Anastasiya Skripnikova, Saken Mukan, M. Negizbayeva, Azel Zhanibek","doi":"10.1504/ijict.2023.10056387","DOIUrl":"https://doi.org/10.1504/ijict.2023.10056387","url":null,"abstract":"","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"67043402","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/ijict.2023.134252
Yongliang Feng
{"title":"An intelligent detection method of local feature points in computer vision image","authors":"Yongliang Feng","doi":"10.1504/ijict.2023.134252","DOIUrl":"https://doi.org/10.1504/ijict.2023.134252","url":null,"abstract":"","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"136366994","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/ijict.2023.134831
Kan Pan, Hailong Chen, Qian Liu, Jian Wang, Yingming Pu, Chunlin Yin, Zheng Yang, Na Zhao
{"title":"Multi-feature fusion friend recommendation algorithm based on complex network","authors":"Kan Pan, Hailong Chen, Qian Liu, Jian Wang, Yingming Pu, Chunlin Yin, Zheng Yang, Na Zhao","doi":"10.1504/ijict.2023.134831","DOIUrl":"https://doi.org/10.1504/ijict.2023.134831","url":null,"abstract":"","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"135709266","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/ijict.2023.134853
Rachid Fateh, Anouar Darif, Said Safi
{"title":"The influence of Gaussian kernel width on indoor and outdoor radio channels identification from binary output measurements","authors":"Rachid Fateh, Anouar Darif, Said Safi","doi":"10.1504/ijict.2023.134853","DOIUrl":"https://doi.org/10.1504/ijict.2023.134853","url":null,"abstract":"","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"135709240","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/ijict.2023.131223
Limin Zhou, Cong Zhang, Miao Wang
Aiming at the problems of traditional methods of emotion recognition accuracy, long recognition time and low recognition rate, a basketball player emotion recognition algorithm based on deep learning is proposed. Based on the Emotic dataset, a basketball remote mobilisation emotion recognition dataset is constructed to realise emotion classification. The LBP method is used to extract the facial expression features in the dataset, and the KDIsomap algorithm is used to perform nonlinear dimensionality reduction on the features according to the feature extraction results. According to the deep learning algorithm, the SVM classifier is combined with the KNN classification to form an SVM-KNN classifier to recognise the emotions of basketball players. Experimental results show that the shortest recognition time of the proposed algorithm is only 4.38 s, the highest recognition accuracy rate reaches 94.2%, and the recognition rate is high, indicating that the algorithm has a certain effectiveness.
{"title":"Emotion recognition algorithm of basketball players based on deep learning","authors":"Limin Zhou, Cong Zhang, Miao Wang","doi":"10.1504/ijict.2023.131223","DOIUrl":"https://doi.org/10.1504/ijict.2023.131223","url":null,"abstract":"Aiming at the problems of traditional methods of emotion recognition accuracy, long recognition time and low recognition rate, a basketball player emotion recognition algorithm based on deep learning is proposed. Based on the Emotic dataset, a basketball remote mobilisation emotion recognition dataset is constructed to realise emotion classification. The LBP method is used to extract the facial expression features in the dataset, and the KDIsomap algorithm is used to perform nonlinear dimensionality reduction on the features according to the feature extraction results. According to the deep learning algorithm, the SVM classifier is combined with the KNN classification to form an SVM-KNN classifier to recognise the emotions of basketball players. Experimental results show that the shortest recognition time of the proposed algorithm is only 4.38 s, the highest recognition accuracy rate reaches 94.2%, and the recognition rate is high, indicating that the algorithm has a certain effectiveness.","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"135685954","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/ijict.2023.10056637
Ruiwei Chen, C. Sivaparthipan
{"title":"Interactive decision support system with machine intelligence for augmentative communication","authors":"Ruiwei Chen, C. Sivaparthipan","doi":"10.1504/ijict.2023.10056637","DOIUrl":"https://doi.org/10.1504/ijict.2023.10056637","url":null,"abstract":"","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"67043456","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/ijict.2023.128709
Jayesh Munjani, Maulin Joshi
The prediction algorithms have been studied as a part of target tracking applications for many years. The prediction algorithm helps to select appropriate nodes to achieve precise target locations while tracking. The only group of sensor nodes nearer the predicted location is activated to save network energy. The inaccurate prediction algorithm may hamper energy consumption by activating inappropriate nodes resulting in a target loss. We propose a nonlinear autoregressive neural network with exogenous input (NARX)-based target-tracking algorithm that improves tracking accuracy and energy efficiency. The proposed algorithm uses vehicle location time series and exogenous vehicle velocity time series as inputs and exerts accurate prediction location for given non-cooperative manoeuvring targets. The proposed algorithm is evaluated in terms of average prediction error, total network energy used, and the count of a target loss with state of art. The experiment outcome proves that the proposed novel NARX-based tracking algorithm outperforms and saves up to 26% of network energy with up to 83% reduction in tracking error compared to existing target tracking algorithms.
{"title":"Nonlinear autoregressive neural network with exogenous input for an energy efficient non-cooperative target tracking in wireless sensor network","authors":"Jayesh Munjani, Maulin Joshi","doi":"10.1504/ijict.2023.128709","DOIUrl":"https://doi.org/10.1504/ijict.2023.128709","url":null,"abstract":"The prediction algorithms have been studied as a part of target tracking applications for many years. The prediction algorithm helps to select appropriate nodes to achieve precise target locations while tracking. The only group of sensor nodes nearer the predicted location is activated to save network energy. The inaccurate prediction algorithm may hamper energy consumption by activating inappropriate nodes resulting in a target loss. We propose a nonlinear autoregressive neural network with exogenous input (NARX)-based target-tracking algorithm that improves tracking accuracy and energy efficiency. The proposed algorithm uses vehicle location time series and exogenous vehicle velocity time series as inputs and exerts accurate prediction location for given non-cooperative manoeuvring targets. The proposed algorithm is evaluated in terms of average prediction error, total network energy used, and the count of a target loss with state of art. The experiment outcome proves that the proposed novel NARX-based tracking algorithm outperforms and saves up to 26% of network energy with up to 83% reduction in tracking error compared to existing target tracking algorithms.","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"135470401","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/ijict.2023.10060378
Said Safi, Anouar Darif, Rachid Fateh
{"title":"The influence of Gaussian kernel width on indoor and outdoor radio channels identification from binary output measurements","authors":"Said Safi, Anouar Darif, Rachid Fateh","doi":"10.1504/ijict.2023.10060378","DOIUrl":"https://doi.org/10.1504/ijict.2023.10060378","url":null,"abstract":"","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"135613877","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/ijict.2023.134828
Mominul Islam, Md. Ashraful Islam, Ahsan Habib
{"title":"Potato late blight disease detection using convolutional neural network","authors":"Mominul Islam, Md. Ashraful Islam, Ahsan Habib","doi":"10.1504/ijict.2023.134828","DOIUrl":"https://doi.org/10.1504/ijict.2023.134828","url":null,"abstract":"","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication 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":"135709259","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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