Pub Date : 2023-01-01DOI: 10.1504/ijris.2023.10058890
Ziyou Zhou
{"title":"Research on Korean translation error text detection method based on machine vision","authors":"Ziyou Zhou","doi":"10.1504/ijris.2023.10058890","DOIUrl":"https://doi.org/10.1504/ijris.2023.10058890","url":null,"abstract":"","PeriodicalId":38715,"journal":{"name":"International Journal of Reasoning-based Intelligent Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66703101","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/ijris.2023.130193
Nianhui Wang, Qingxue Li
In order to solve the problems of low recall rate of human posture data collection results, low recognition rate and long recognition time in traditional recognition methods, a rapid recognition method of athlete's human posture based on SVM decision tree was proposed. The Kinect sensor is used to collect the athlete's human posture data, and the mixed Gaussian background modelling method is used to segment the collected athlete's human posture image. Scale normalisation is performed on the segmented images, and a star model is used to extract the pose features of athletes' bodies. According to the characteristics of human posture, the SVM decision tree is used to classify and identify the human posture of athletes. The experimental results show that the maximum recall rate of this method is 98%, the minimum value is 93%, the recognition rate is above 97.2%, and the average recognition time is 0.62.
{"title":"A rapid recognition of athlete's human posture based on SVM decision tree","authors":"Nianhui Wang, Qingxue Li","doi":"10.1504/ijris.2023.130193","DOIUrl":"https://doi.org/10.1504/ijris.2023.130193","url":null,"abstract":"In order to solve the problems of low recall rate of human posture data collection results, low recognition rate and long recognition time in traditional recognition methods, a rapid recognition method of athlete's human posture based on SVM decision tree was proposed. The Kinect sensor is used to collect the athlete's human posture data, and the mixed Gaussian background modelling method is used to segment the collected athlete's human posture image. Scale normalisation is performed on the segmented images, and a star model is used to extract the pose features of athletes' bodies. According to the characteristics of human posture, the SVM decision tree is used to classify and identify the human posture of athletes. The experimental results show that the maximum recall rate of this method is 98%, the minimum value is 93%, the recognition rate is above 97.2%, and the average recognition time is 0.62.","PeriodicalId":38715,"journal":{"name":"International Journal of Reasoning-based Intelligent Systems","volume":"24 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":"135585155","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 : 2021-01-01DOI: 10.1504/ijris.2021.10041239
Maja Celeska Krstevska, M. Srbinovska, Tomislav Kartalov, Vesna Andova, A. Mateska
{"title":"Low-cost energy-efficient air quality monitoring system using sensor network","authors":"Maja Celeska Krstevska, M. Srbinovska, Tomislav Kartalov, Vesna Andova, A. Mateska","doi":"10.1504/ijris.2021.10041239","DOIUrl":"https://doi.org/10.1504/ijris.2021.10041239","url":null,"abstract":"","PeriodicalId":38715,"journal":{"name":"International Journal of Reasoning-based Intelligent Systems","volume":"96 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85733210","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 : 2019-11-05DOI: 10.1504/ijris.2019.10025157
Zhang Min, Q. Rui
Decision demand has hierarchies for different users and decision analysis demand in various areas and fields have particularity according to different topics. Since traditional MIS is hard to meet the demand of analysis and processing of growing mass data, a novel decision support system (DSS) is urgent to be proposed for decision makers. Based on data warehouse, data mining and OLAP technology, we propose a DSS with modular design, and explain the structure and key technologies of it in this article. Our study establishes multidimensional dataset for OLAP analysis to perform slicing, dicing, drilling and rotation operation. In data mining, for the problems of large data-set such as long learning time and decreasing generalisation ability, an SVM accelerating algorithm based on boundary sample selection is put forward. The system test results demonstrate that the data mining has better prediction effects on economical forecasting. Therefore, the research has better practicability and higher accuracy, which shows certain value of popularisation and implementation.
{"title":"Data mining and economic forecasting in DW-based economical decision support system","authors":"Zhang Min, Q. Rui","doi":"10.1504/ijris.2019.10025157","DOIUrl":"https://doi.org/10.1504/ijris.2019.10025157","url":null,"abstract":"Decision demand has hierarchies for different users and decision analysis demand in various areas and fields have particularity according to different topics. Since traditional MIS is hard to meet the demand of analysis and processing of growing mass data, a novel decision support system (DSS) is urgent to be proposed for decision makers. Based on data warehouse, data mining and OLAP technology, we propose a DSS with modular design, and explain the structure and key technologies of it in this article. Our study establishes multidimensional dataset for OLAP analysis to perform slicing, dicing, drilling and rotation operation. In data mining, for the problems of large data-set such as long learning time and decreasing generalisation ability, an SVM accelerating algorithm based on boundary sample selection is put forward. The system test results demonstrate that the data mining has better prediction effects on economical forecasting. Therefore, the research has better practicability and higher accuracy, which shows certain value of popularisation and implementation.","PeriodicalId":38715,"journal":{"name":"International Journal of Reasoning-based Intelligent Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66701712","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 : 2019-08-23DOI: 10.1504/IJRIS.2019.10023445
Guo Jing, Han Yaxiong, Ke Yongzhen
Chinese named entity recognition (CNER) is different from English named entity recognition (ENER). There is no specific delimiter in Chinese text to determine the words in a sentence. Besides, the combination of Chinese text has a strong arbitrariness. These special cases usually bring more errors to the Chinese NER (CNER). We propose a re-ranking model based on BILSTM network and without using any other auxiliary methods. Our approach uses N-best generalised label sequences that are produced by baseline model as input and feeds them into our re-ranking model for modelling the context within the generalised sequences. The optimal output sequence is obtained by comprehensively considering the result of baseline model and re-ranking model. Experimental results show that our model achieves better F1-score on Bakeoff-3 MSRA corpus than the best previous experimental results, which yields a 0.97% improvement on F1-score over our neural baseline model and a 0.22% improvement over the state-of-the-art CNER model.
{"title":"A neural-based re-ranking model for Chinese named entity recognition","authors":"Guo Jing, Han Yaxiong, Ke Yongzhen","doi":"10.1504/IJRIS.2019.10023445","DOIUrl":"https://doi.org/10.1504/IJRIS.2019.10023445","url":null,"abstract":"Chinese named entity recognition (CNER) is different from English named entity recognition (ENER). There is no specific delimiter in Chinese text to determine the words in a sentence. Besides, the combination of Chinese text has a strong arbitrariness. These special cases usually bring more errors to the Chinese NER (CNER). We propose a re-ranking model based on BILSTM network and without using any other auxiliary methods. Our approach uses N-best generalised label sequences that are produced by baseline model as input and feeds them into our re-ranking model for modelling the context within the generalised sequences. The optimal output sequence is obtained by comprehensively considering the result of baseline model and re-ranking model. Experimental results show that our model achieves better F1-score on Bakeoff-3 MSRA corpus than the best previous experimental results, which yields a 0.97% improvement on F1-score over our neural baseline model and a 0.22% improvement over the state-of-the-art CNER model.","PeriodicalId":38715,"journal":{"name":"International Journal of Reasoning-based Intelligent Systems","volume":"11 1","pages":"265-272"},"PeriodicalIF":0.0,"publicationDate":"2019-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42003703","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 : 2018-06-12DOI: 10.1504/IJRIS.2018.10013288
Niu Chunzhou, Zhu Yukai
Many actual application images in the real world are formed by high dimensional data in most cases, while the manifold learning algorithm can explore the nonlinear information hidden in these high dimensional data. As most of manifold learning algorithms can only be defined in training cluster, it is impossible to project the sample on the lower dimensional space. In the thesis, we introduce a kind of double manifold algorithm based on LLE and Isomap. Different from the traditional LLE algorithm, our algorithm learns two kinds of manifold information in which one group of data relates to many types and it compares two kinds of single LLE algorithm and Isomap algorithm through the setting of the appropriate nearest neighbour number K. No matter for the recognition rate or running time, it is obviously superior to the other two kinds of algorithms and it can effectively achieve the estimation of facial expression and significantly reduce the computation complexity.
{"title":"Design of unsupervised facial expression animation based on geometric grid measurement","authors":"Niu Chunzhou, Zhu Yukai","doi":"10.1504/IJRIS.2018.10013288","DOIUrl":"https://doi.org/10.1504/IJRIS.2018.10013288","url":null,"abstract":"Many actual application images in the real world are formed by high dimensional data in most cases, while the manifold learning algorithm can explore the nonlinear information hidden in these high dimensional data. As most of manifold learning algorithms can only be defined in training cluster, it is impossible to project the sample on the lower dimensional space. In the thesis, we introduce a kind of double manifold algorithm based on LLE and Isomap. Different from the traditional LLE algorithm, our algorithm learns two kinds of manifold information in which one group of data relates to many types and it compares two kinds of single LLE algorithm and Isomap algorithm through the setting of the appropriate nearest neighbour number K. No matter for the recognition rate or running time, it is obviously superior to the other two kinds of algorithms and it can effectively achieve the estimation of facial expression and significantly reduce the computation complexity.","PeriodicalId":38715,"journal":{"name":"International Journal of Reasoning-based Intelligent Systems","volume":"79 1","pages":"96-101"},"PeriodicalIF":0.0,"publicationDate":"2018-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89662597","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 : 2018-06-12DOI: 10.1504/IJRIS.2018.10013289
Sun Shanhui, Li Hong, L. Zhuangzhuang, Zhang Bingqiu
To study the diagnosis of hospitalised patients with neurosis and its influencing factors, this article, on the basis of the data of treating hospitalised patients with neurosis hospitalisation, empirically analyses the relationship between the treating effect and personal basic situation, personal social relations, personal original condition, and makes the corresponding regression analysis and factor analysis. The results show that the patient's social relationship and personal character are obviously related to the diagnosis of neurosis. There are obvious correlations between the original condition in the early diagnosis and patients with neurosis, so it is important to strengthen the understanding and analysis of the original condition. We should strengthen publicity and education of mental health knowledge, encourage people from all walks of life to actively participate in it and improve their awareness of neurosis, and thus to effectively reduce the bias in patients with neurosis. Untimely separatio...
{"title":"Factor analysis model of the result of hospitalised patients with neurosis","authors":"Sun Shanhui, Li Hong, L. Zhuangzhuang, Zhang Bingqiu","doi":"10.1504/IJRIS.2018.10013289","DOIUrl":"https://doi.org/10.1504/IJRIS.2018.10013289","url":null,"abstract":"To study the diagnosis of hospitalised patients with neurosis and its influencing factors, this article, on the basis of the data of treating hospitalised patients with neurosis hospitalisation, empirically analyses the relationship between the treating effect and personal basic situation, personal social relations, personal original condition, and makes the corresponding regression analysis and factor analysis. The results show that the patient's social relationship and personal character are obviously related to the diagnosis of neurosis. There are obvious correlations between the original condition in the early diagnosis and patients with neurosis, so it is important to strengthen the understanding and analysis of the original condition. We should strengthen publicity and education of mental health knowledge, encourage people from all walks of life to actively participate in it and improve their awareness of neurosis, and thus to effectively reduce the bias in patients with neurosis. Untimely separatio...","PeriodicalId":38715,"journal":{"name":"International Journal of Reasoning-based Intelligent Systems","volume":"10 1","pages":"102-108"},"PeriodicalIF":0.0,"publicationDate":"2018-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66701674","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：