Pub Date : 2023-01-01DOI: 10.1504/ijnvo.2023.10059397
Yueying Xiao
{"title":"AGA-BP algorithm for the evaluation model of teaching quality of dance drama performance","authors":"Yueying Xiao","doi":"10.1504/ijnvo.2023.10059397","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.10059397","url":null,"abstract":"","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"135750358","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/ijnvo.2023.134280
Nilmini Wickramasinghe, Rima Gibbings
{"title":"Using digital health to support superior preparedness to enable better preparedness and readiness to combat pandemics: a scoping review","authors":"Nilmini Wickramasinghe, Rima Gibbings","doi":"10.1504/ijnvo.2023.134280","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.134280","url":null,"abstract":"","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"135006895","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/ijnvo.2023.133833
Junmei Guo
Evaluating the quality of classroom teaching in higher education can improve teachers' teaching, but the evaluating results are currently inaccurate. The study combines the binary tree support vector machine (BT-SVM) and the Euclidean distance method to obtain the distance binary tree support vector machine (DBT-SVM) algorithm. The performance of DBT-SVM algorithm is tested and compared with one versus one (OVO) algorithm and one versus rest (OVR) algorithm. The results show that the accuracy of the DBT-SVM is 92.2% and the test time is 0.02 s; it is superior to the traditional algorithms. In the empirical analysis of the evaluation model, the accuracy rate of the DBT-SVM algorithm model is 97.85%, which is superior to TW-SVM and traditional algorithm models. The results show that the performance of the optimised DBT-SVM algorithm has greatly improved the accuracy and test time of the traditional SVM algorithm.
{"title":"Evaluation and analysis of classroom teaching quality of art design specialty based on DBT-SVM","authors":"Junmei Guo","doi":"10.1504/ijnvo.2023.133833","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.133833","url":null,"abstract":"Evaluating the quality of classroom teaching in higher education can improve teachers' teaching, but the evaluating results are currently inaccurate. The study combines the binary tree support vector machine (BT-SVM) and the Euclidean distance method to obtain the distance binary tree support vector machine (DBT-SVM) algorithm. The performance of DBT-SVM algorithm is tested and compared with one versus one (OVO) algorithm and one versus rest (OVR) algorithm. The results show that the accuracy of the DBT-SVM is 92.2% and the test time is 0.02 s; it is superior to the traditional algorithms. In the empirical analysis of the evaluation model, the accuracy rate of the DBT-SVM algorithm model is 97.85%, which is superior to TW-SVM and traditional algorithm models. The results show that the performance of the optimised DBT-SVM algorithm has greatly improved the accuracy and test time of the traditional SVM algorithm.","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"136002578","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/ijnvo.2023.133867
Jing Qiu, Feng Gao
To overcome the problems of low coverage and detection accuracy in traditional detection methods, a multidimensional sliding window based active sleep node detection method for sensor networks is proposed. Firstly, we set up an active sleep node simulator and controller in the sensor network space to determine the active sleep range. Secondly, we design a multidimensional sliding window algorithm to determine anomalies in the transmission link by calculating the standard deviation of sensing information in the sliding window. Finally, the total length of data transmission is dimensionally transformed to achieve reliable detection of active sleep nodes. The experimental results show that the coverage rate of the detection results of this method is closer to 1, and its detection accuracy remains between 94.84% -97.32%, and the detection process time remains between 1.72 s-232 s. It has the advantages of strong reliability and high efficiency in applications.
针对传统检测方法覆盖率低、检测精度低等问题，提出了一种基于多维滑动窗口的传感器网络主动睡眠节点检测方法。首先，我们在传感器网络空间中设置主动睡眠节点模拟器和控制器来确定主动睡眠范围。其次，设计了一种多维滑动窗口算法，通过计算滑动窗口中传感信息的标准差来判断传输链路中的异常;最后，对数据传输的总长度进行维数变换，实现对活动睡眠节点的可靠检测。实验结果表明，该方法检测结果的覆盖率更接近于1，检测准确率保持在94.84% ~ 97.32%之间，检测过程时间保持在1.72 s ~ 232 s之间。在实际应用中具有可靠性强、效率高等优点。
{"title":"Study on active sleeping node detection method in sensor network based on multi-dimensional sliding window","authors":"Jing Qiu, Feng Gao","doi":"10.1504/ijnvo.2023.133867","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.133867","url":null,"abstract":"To overcome the problems of low coverage and detection accuracy in traditional detection methods, a multidimensional sliding window based active sleep node detection method for sensor networks is proposed. Firstly, we set up an active sleep node simulator and controller in the sensor network space to determine the active sleep range. Secondly, we design a multidimensional sliding window algorithm to determine anomalies in the transmission link by calculating the standard deviation of sensing information in the sliding window. Finally, the total length of data transmission is dimensionally transformed to achieve reliable detection of active sleep nodes. The experimental results show that the coverage rate of the detection results of this method is closer to 1, and its detection accuracy remains between 94.84% -97.32%, and the detection process time remains between 1.72 s-232 s. It has the advantages of strong reliability and high efficiency in applications.","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"136002852","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/ijnvo.2023.10057569
Xifeng Qin
{"title":"Research on the Application of Deep-Learning Algorithm based PS Design Software Technology in Oil Painting Teaching","authors":"Xifeng Qin","doi":"10.1504/ijnvo.2023.10057569","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.10057569","url":null,"abstract":"","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"66788200","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/ijnvo.2023.10060107
P. Malathi, Minaxi Doorwar
{"title":"SMNBMQR: Optimization of Sleep Schedules in Multimedia Networks via Bioinspired Modelling for QoS-aware Routing operations","authors":"P. Malathi, Minaxi Doorwar","doi":"10.1504/ijnvo.2023.10060107","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.10060107","url":null,"abstract":"","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"135261275","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/ijnvo.2023.133861
Li Ling
{"title":"A study on the development of English reading skills in the MOOC model of English language teaching","authors":"Li Ling","doi":"10.1504/ijnvo.2023.133861","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.133861","url":null,"abstract":"","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"136002567","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/ijnvo.2023.133873
Yan Yang
In order to improve the effect of user music personalised recommendation, a hybrid music personalised recommendation model based on attention mechanism and multi-layer LSTM is proposed from the perspective of user music emotion and behaviour data. Using multi-layer LSTM to mine users' long-term and short-term music preferences, the model can analyse users' music emotional attributes in combination with attention mechanism. The research results show that the recommendation accuracy of the AM-LSTPM model is 97.86%, the recall rate is 98.91%, and the NDCG@10 values of the model on the two datasets are 0.5771 and 0.5437, which can effectively provide users with targeted personalised music recommendation services. The research, based on the modelling of users' long-term and short-term music preferences and integrating users' music emotional attention analysis, provide users with high-quality targeted music recommendation services, and have important value in promoting the improvement of music streaming media service quality.
{"title":"Research on long- and short-term music preference recommendation method integrating music emotional attention","authors":"Yan Yang","doi":"10.1504/ijnvo.2023.133873","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.133873","url":null,"abstract":"In order to improve the effect of user music personalised recommendation, a hybrid music personalised recommendation model based on attention mechanism and multi-layer LSTM is proposed from the perspective of user music emotion and behaviour data. Using multi-layer LSTM to mine users' long-term and short-term music preferences, the model can analyse users' music emotional attributes in combination with attention mechanism. The research results show that the recommendation accuracy of the AM-LSTPM model is 97.86%, the recall rate is 98.91%, and the NDCG@10 values of the model on the two datasets are 0.5771 and 0.5437, which can effectively provide users with targeted personalised music recommendation services. The research, based on the modelling of users' long-term and short-term music preferences and integrating users' music emotional attention analysis, provide users with high-quality targeted music recommendation services, and have important value in promoting the improvement of music streaming media service quality.","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"136002600","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/ijnvo.2023.133872
Xifeng Qin
More and more minors are cultivating oil painting as a hobby. Beginners of oil painting often cannot correctly identify optimised styles and similar painting objects due to the lack of professional knowledge and insufficient aesthetic ability of oil painting. This research addresses this problem by designing a shared convolutional neural network and an improved global convolutional neural network, and combining the two with Photoshop (short name: PS) software processing steps to compose an intelligent oil painting recognition model for beginner teaching. The experimental results of model performance testing show that the recognition model designed in this study has lower training and computation speed. However, the recognition accuracy of various images in the test sample set is higher than that of the comparison oil painting recognition model. Which is significantly higher than the oil painting recognition model built based on GoogleNet, visual geometry group (VGG) and AlexNet neural network algorithms.
{"title":"Research on the application of deep learning algorithm based PS design software technology in oil painting teaching","authors":"Xifeng Qin","doi":"10.1504/ijnvo.2023.133872","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.133872","url":null,"abstract":"More and more minors are cultivating oil painting as a hobby. Beginners of oil painting often cannot correctly identify optimised styles and similar painting objects due to the lack of professional knowledge and insufficient aesthetic ability of oil painting. This research addresses this problem by designing a shared convolutional neural network and an improved global convolutional neural network, and combining the two with Photoshop (short name: PS) software processing steps to compose an intelligent oil painting recognition model for beginner teaching. The experimental results of model performance testing show that the recognition model designed in this study has lower training and computation speed. However, the recognition accuracy of various images in the test sample set is higher than that of the comparison oil painting recognition model. Which is significantly higher than the oil painting recognition model built based on GoogleNet, visual geometry group (VGG) and AlexNet neural network algorithms.","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"136003287","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/ijnvo.2023.133835
Jing Wang
Under the concept of sustainable development, the innovation and development of the knitted garment industry is crucial. In order to enhance the core competitiveness of the knitted garment industry, the study proposes a talent training strategy for the knitted garment industry based on a clustering algorithm, and constructs a talent-training model. The clustering algorithm showed a significant clustering effect, with a clustering accuracy of 93.66% in the real dataset. The knitwear talent development model obtained through the clustering analysis was applied in practice, and the application of talent development was able to significantly increase the proportion of elite talent in the company. The above results show that in the knitted garment industry under the concept of sustainable development, cluster analysis can effectively build a talent-training program, which is of great value to the sustainable development of the knitted garment industry and the production industry.
{"title":"The application of clustering algorithms in a new model of knitted garment talent training in the context of sustainable development","authors":"Jing Wang","doi":"10.1504/ijnvo.2023.133835","DOIUrl":"https://doi.org/10.1504/ijnvo.2023.133835","url":null,"abstract":"Under the concept of sustainable development, the innovation and development of the knitted garment industry is crucial. In order to enhance the core competitiveness of the knitted garment industry, the study proposes a talent training strategy for the knitted garment industry based on a clustering algorithm, and constructs a talent-training model. The clustering algorithm showed a significant clustering effect, with a clustering accuracy of 93.66% in the real dataset. The knitwear talent development model obtained through the clustering analysis was applied in practice, and the application of talent development was able to significantly increase the proportion of elite talent in the company. The above results show that in the knitted garment industry under the concept of sustainable development, cluster analysis can effectively build a talent-training program, which is of great value to the sustainable development of the knitted garment industry and the production industry.","PeriodicalId":52509,"journal":{"name":"International Journal of Networking and Virtual Organisations","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":"136003750","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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