Pub Date : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936132
Yuemei Mao, Chong Luo
This article studies the important computer pharmacology and imaging assisted analysis for the treatment of liver disease. First, it introduces the computer pharmacology methods with virtual screening technology, various omics technologies and network pharmacology as the main content in recent years and their applications in the field of Chinese medicine research; combined with research and practice, the computer pharmacology method is used to analyze the treatment of chronic Chinese medicine. The progress of the effective components and mechanism of liver disease was reviewed. The results showed that there is a big difference between the chemical component-target interaction network of traditional Chinese medicine for the treatment of chronic kidney disease and the chemical component-target interaction network of western medicine.
{"title":"Computer Network Pharmacology Research and Imaging Assisted Analysis of Traditional Chinese Medicine for the Treatment of Liver Disease","authors":"Yuemei Mao, Chong Luo","doi":"10.1109/ICECAA55415.2022.9936132","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936132","url":null,"abstract":"This article studies the important computer pharmacology and imaging assisted analysis for the treatment of liver disease. First, it introduces the computer pharmacology methods with virtual screening technology, various omics technologies and network pharmacology as the main content in recent years and their applications in the field of Chinese medicine research; combined with research and practice, the computer pharmacology method is used to analyze the treatment of chronic Chinese medicine. The progress of the effective components and mechanism of liver disease was reviewed. The results showed that there is a big difference between the chemical component-target interaction network of traditional Chinese medicine for the treatment of chronic kidney disease and the chemical component-target interaction network of western medicine.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117177242","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 : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936483
Animesh Malviya, M. Dutta
Detecting gastrointestinal illnesses accurately is crucial to early cancer detection and treatment. In spite of this, manual analysis is time-consuming, requiring the assistance of a gastrointestinal. A multi-class classification framework for screening gastrointestinal diseases is proposed that is efficient and robust. A neural network known as gastrointestinal GI-Net was developed to extract features that could differentiate between normal and diseased images taken by endoscopy device. In order to achieve the most optimal classification network, a variety of optimization techniques are used. For the classification network to be more effective, the framework can handle the challenges present in the dataset. It is 88% accurate in diagnosing using unseen endoscopy images. In comparison with other deep learning networks, the developed architecture is highly effective. Compared to other networks, in limited computation environments, the proposed network is likely to perform better.
{"title":"Gastrointestinal Disease Classification And Analysis Using GI-Net Model","authors":"Animesh Malviya, M. Dutta","doi":"10.1109/ICECAA55415.2022.9936483","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936483","url":null,"abstract":"Detecting gastrointestinal illnesses accurately is crucial to early cancer detection and treatment. In spite of this, manual analysis is time-consuming, requiring the assistance of a gastrointestinal. A multi-class classification framework for screening gastrointestinal diseases is proposed that is efficient and robust. A neural network known as gastrointestinal GI-Net was developed to extract features that could differentiate between normal and diseased images taken by endoscopy device. In order to achieve the most optimal classification network, a variety of optimization techniques are used. For the classification network to be more effective, the framework can handle the challenges present in the dataset. It is 88% accurate in diagnosing using unseen endoscopy images. In comparison with other deep learning networks, the developed architecture is highly effective. Compared to other networks, in limited computation environments, the proposed network is likely to perform better.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129877847","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 : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936555
S. S. Aravinth, M. Ramesh Kumar, R. Ranganathan, P. M, M. Sasikala
Every day a huge amount of unstructured and semi structured data is used in all the business sectors. Those data are very complicated to store and process for applying into the decision-making system. Especially, the medical data, clinical data and patient history data are to be accessed in a faster way to bring the feasible solution. In view of this, a high speed, reliable and fault tolerant programming framework is needed [1].Apache Pig is a high level and globally accepted programming language to execute the map reduce tasks over the Hadoop cluster while dealing with unstructured data. This language works on Hadoop Distributed File System (HDFS) and this language is written in Java.In this proposed work, the medical history data of patients are considered to be processed. The existing approaches such as oracle SQL queries and mongo DB based results have been producing the very slower time to process these records. But in pig programming language, these gaps are rectified and produced an efficient result.The data dictionary of this implemented dataset is having 7 fields of records to be process in a phased approach. Each and every phase of analysis, the various fields are considered for further processing and interpretation. With the help of relationship operator’s, the relationship of these dataset fields is identified. Followed by this, the functions are applied to produce the faster segregation on the given dataset. Two types of functions are used here such as math function and evaluation function [2].
{"title":"Apache Pig Programming for Processing the Big Medical Data of Patients with Distributed Environment","authors":"S. S. Aravinth, M. Ramesh Kumar, R. Ranganathan, P. M, M. Sasikala","doi":"10.1109/ICECAA55415.2022.9936555","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936555","url":null,"abstract":"Every day a huge amount of unstructured and semi structured data is used in all the business sectors. Those data are very complicated to store and process for applying into the decision-making system. Especially, the medical data, clinical data and patient history data are to be accessed in a faster way to bring the feasible solution. In view of this, a high speed, reliable and fault tolerant programming framework is needed [1].Apache Pig is a high level and globally accepted programming language to execute the map reduce tasks over the Hadoop cluster while dealing with unstructured data. This language works on Hadoop Distributed File System (HDFS) and this language is written in Java.In this proposed work, the medical history data of patients are considered to be processed. The existing approaches such as oracle SQL queries and mongo DB based results have been producing the very slower time to process these records. But in pig programming language, these gaps are rectified and produced an efficient result.The data dictionary of this implemented dataset is having 7 fields of records to be process in a phased approach. Each and every phase of analysis, the various fields are considered for further processing and interpretation. With the help of relationship operator’s, the relationship of these dataset fields is identified. Followed by this, the functions are applied to produce the faster segregation on the given dataset. Two types of functions are used here such as math function and evaluation function [2].","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129887286","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 : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936543
Gan Liyong
This paper analyzes the government's electronic management system from the perspective of Internet platform-assisted economic development, and points out that the government must increase coordination while strengthening the network formation. The key to effective government governance lies in the synergy and co-evolution of technology and system. E-government is of great value to improve government field stress, government policy capability, government efficiency, realize open government and responsible government, and ultimately improve national competitiveness. This paper analyzes the significance of e-government construction to government governance, analyzes the problems existing in its current e-government construction by taking Shanghai as a case, and puts forward some countermeasures to promote government information governance.
{"title":"Internet Cloud Platform Assists the Design of Electronic Information System for Economic Development and Government Governance","authors":"Gan Liyong","doi":"10.1109/ICECAA55415.2022.9936543","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936543","url":null,"abstract":"This paper analyzes the government's electronic management system from the perspective of Internet platform-assisted economic development, and points out that the government must increase coordination while strengthening the network formation. The key to effective government governance lies in the synergy and co-evolution of technology and system. E-government is of great value to improve government field stress, government policy capability, government efficiency, realize open government and responsible government, and ultimately improve national competitiveness. This paper analyzes the significance of e-government construction to government governance, analyzes the problems existing in its current e-government construction by taking Shanghai as a case, and puts forward some countermeasures to promote government information governance.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128419141","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 : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936054
Ashish Narayan T, Giridhar G, S. T., S. S, Ravisankar Malladi
Coronavirus is the cause of the pandemic illness. The Reverse Transcription–Polymerase Chain Reaction (RT-PCR) test is frequently used to identify coronavirus. On Computed Tomography (CT) images, the extent to which the virus has impacted the lungs can be seen clearly. In 15 minutes, CT data are accessible, but RT-PCR takes 24 hours. The proposed model looks for the virus in the lungs, which is more accurate than PCR, which only looks for it in the nose or throat. More accurate and dependable data can be obtained, if Computed Tomography scans are employed. The proposed innovative model has an accuracy with Gabor filter and without Gabor filter is 0.83 and 0.75 in recognizing the coronavirus in Lung Computed Tomography Scans. The accuracy of the preceding models VGG16, VGG19, ResNet50, and Mobile Net with the Gabor filter is 0.79,0.81,0.81,0.81 and 0.68,0.61,0.71 and 0.79 without it. Gabor filter is a linear filter that is sensitive to orientation and can assist reduce noise from data. Our model obtains an accuracy of 0.83, which is higher than the Gabor Filter models VGG16, VGG19, ResNet50, and Mobile Net.
{"title":"A CNN Model for Detecting Coronavirus in Chest Computed Tomography Scan Images using Gabor Filter in Pre-processing Stage","authors":"Ashish Narayan T, Giridhar G, S. T., S. S, Ravisankar Malladi","doi":"10.1109/ICECAA55415.2022.9936054","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936054","url":null,"abstract":"Coronavirus is the cause of the pandemic illness. The Reverse Transcription–Polymerase Chain Reaction (RT-PCR) test is frequently used to identify coronavirus. On Computed Tomography (CT) images, the extent to which the virus has impacted the lungs can be seen clearly. In 15 minutes, CT data are accessible, but RT-PCR takes 24 hours. The proposed model looks for the virus in the lungs, which is more accurate than PCR, which only looks for it in the nose or throat. More accurate and dependable data can be obtained, if Computed Tomography scans are employed. The proposed innovative model has an accuracy with Gabor filter and without Gabor filter is 0.83 and 0.75 in recognizing the coronavirus in Lung Computed Tomography Scans. The accuracy of the preceding models VGG16, VGG19, ResNet50, and Mobile Net with the Gabor filter is 0.79,0.81,0.81,0.81 and 0.68,0.61,0.71 and 0.79 without it. Gabor filter is a linear filter that is sensitive to orientation and can assist reduce noise from data. Our model obtains an accuracy of 0.83, which is higher than the Gabor Filter models VGG16, VGG19, ResNet50, and Mobile Net.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128513960","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 : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936425
Shan Yinxin
The new model of business exchanges has broken the balance between the traditional financial model and the emerging financial model. At the beginning, due to the downward rigidity of the value system, commercial banks adhered to the rules and lacked the initiative of transformation. Through the practice of teaching activities such as double teacher training, three-dimensional textbook development and "cloud appointment + two-step" teaching method reform, this paper deeply explores the practical significance of the "three education" reform in the talent training of the integration of industry and education, in order to provide reference for the reform of talent training mode in higher vocational colleges. But at the same time, the platform also exposed some problems in the inspection process, such as unreasonable live broadcast content arrangement, difficult virtual enterprise operation, imperfect grouping function, etc., which need to be further improved in the future.
{"title":"Cloud Center Intelligent Terminal Design for the Integration of Industry and Education in Local Higher Vocational Colleges under the Background of \"Internet +\" Transformation and Development","authors":"Shan Yinxin","doi":"10.1109/ICECAA55415.2022.9936425","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936425","url":null,"abstract":"The new model of business exchanges has broken the balance between the traditional financial model and the emerging financial model. At the beginning, due to the downward rigidity of the value system, commercial banks adhered to the rules and lacked the initiative of transformation. Through the practice of teaching activities such as double teacher training, three-dimensional textbook development and \"cloud appointment + two-step\" teaching method reform, this paper deeply explores the practical significance of the \"three education\" reform in the talent training of the integration of industry and education, in order to provide reference for the reform of talent training mode in higher vocational colleges. But at the same time, the platform also exposed some problems in the inspection process, such as unreasonable live broadcast content arrangement, difficult virtual enterprise operation, imperfect grouping function, etc., which need to be further improved in the future.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128670764","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 : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936107
Vinod Jain, Narendra Mohan
Lots of women are suffering from Breast Cancer all over the world. Various data set about breast cancer is available online. Machine Learning algorithms are very useful in predicting breast cancer. In this paper six standard machine learning algorithms are applied on a data set for breast cancer prediction. These algorithms are giving better results while applied diferent data sets for different diseases. After testing these algorithms, it is observed that Logistic Regression is best with 98.5% accuracy for breast cancer prediction.
{"title":"Breast Cancer Prediction using Standard Machine Learning Algorithms","authors":"Vinod Jain, Narendra Mohan","doi":"10.1109/ICECAA55415.2022.9936107","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936107","url":null,"abstract":"Lots of women are suffering from Breast Cancer all over the world. Various data set about breast cancer is available online. Machine Learning algorithms are very useful in predicting breast cancer. In this paper six standard machine learning algorithms are applied on a data set for breast cancer prediction. These algorithms are giving better results while applied diferent data sets for different diseases. After testing these algorithms, it is observed that Logistic Regression is best with 98.5% accuracy for breast cancer prediction.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129675144","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 : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936340
Yi Ke
The inheritance mechanism of national traditional sports culture is defined, and the connotation is explained, and five dimensions of driving mechanism, implementation mechanism, expression mechanism, guarantee mechanism and feedback mechanism are proposed to present the inheritance mechanism of national traditional sports culture in this paper. Moreover, the inheritance function of national traditional sports is optimized, new media and new technologies are innovated and integrated, the vigorous development of national traditional sports is comprehensively promoted, and the creative vitality of national culture is stimulated. This work further continues to inject vitality into inheritance, promote the development of national traditional sports industry, revitalize the consumption potential of the masses and the consumer market, take cultural protection and innovation as the concept, and broaden the way of inheritance.
{"title":"Mining of Online Communication Network of National Traditional Sports Culture based on Computer New Media Technology","authors":"Yi Ke","doi":"10.1109/ICECAA55415.2022.9936340","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936340","url":null,"abstract":"The inheritance mechanism of national traditional sports culture is defined, and the connotation is explained, and five dimensions of driving mechanism, implementation mechanism, expression mechanism, guarantee mechanism and feedback mechanism are proposed to present the inheritance mechanism of national traditional sports culture in this paper. Moreover, the inheritance function of national traditional sports is optimized, new media and new technologies are innovated and integrated, the vigorous development of national traditional sports is comprehensively promoted, and the creative vitality of national culture is stimulated. This work further continues to inject vitality into inheritance, promote the development of national traditional sports industry, revitalize the consumption potential of the masses and the consumer market, take cultural protection and innovation as the concept, and broaden the way of inheritance.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130008058","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 : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936189
Shankarlal B, P. Sathya
This methodology consists of preprocessing of ultra sound thyroid images, feature computations and diagnosis stage. The preprocessing stage of the proposed method detects and reduces the noise contents in the source ultra sound thyroid images. Then, the texture features are computed from the preprocessed ultra sound thyroid image. Finally, these features are diagnosed into normal, mild and severe case using spatial Fuzzy-C-Mean classification (SFCM) approach. This method is tested on the ultra sound thyroid images in both DDTI and Open-CAS dataset with respect to accuracy, precision, recall and diagnosis rate
{"title":"Thyroid Tumor Diagnosis System using Spatial Fuzzy C-Means (SFCM) Classification Approach","authors":"Shankarlal B, P. Sathya","doi":"10.1109/ICECAA55415.2022.9936189","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936189","url":null,"abstract":"This methodology consists of preprocessing of ultra sound thyroid images, feature computations and diagnosis stage. The preprocessing stage of the proposed method detects and reduces the noise contents in the source ultra sound thyroid images. Then, the texture features are computed from the preprocessed ultra sound thyroid image. Finally, these features are diagnosed into normal, mild and severe case using spatial Fuzzy-C-Mean classification (SFCM) approach. This method is tested on the ultra sound thyroid images in both DDTI and Open-CAS dataset with respect to accuracy, precision, recall and diagnosis rate","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130070666","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 : 2022-10-13DOI: 10.1109/ICECAA55415.2022.9936561
Xin Ma
This study is based on the theoretical framework of the evaluation system of Chinese college students’ cross-cultural communicative competence - the integration of knowledge and action, and then conducts exploratory factor analysis, reliability analysis, validity analysis and confirmatory factor analysis on the scale. A distributed scheme of college students’ cross-cultural communicative competence is proposed. The software and hardware design scheme and secondary development platform of the intelligent terminal platform are introduced, and intelligent application cases are shown. The teaching mode pays too much attention to the test results and neglects to increase the relevant knowledge of cross-cultural training; the curriculum setting and test evaluation system involve little knowledge of cross-cultural communication; there is a lack of relevant cross-cultural learning and training in English classrooms, etc.
{"title":"Intelligent Terminal Design for Improving College Students’ Cross-Cultural Communicative Ability Under Cross-IP and Media Computer Network Environment","authors":"Xin Ma","doi":"10.1109/ICECAA55415.2022.9936561","DOIUrl":"https://doi.org/10.1109/ICECAA55415.2022.9936561","url":null,"abstract":"This study is based on the theoretical framework of the evaluation system of Chinese college students’ cross-cultural communicative competence - the integration of knowledge and action, and then conducts exploratory factor analysis, reliability analysis, validity analysis and confirmatory factor analysis on the scale. A distributed scheme of college students’ cross-cultural communicative competence is proposed. The software and hardware design scheme and secondary development platform of the intelligent terminal platform are introduced, and intelligent application cases are shown. The teaching mode pays too much attention to the test results and neglects to increase the relevant knowledge of cross-cultural training; the curriculum setting and test evaluation system involve little knowledge of cross-cultural communication; there is a lack of relevant cross-cultural learning and training in English classrooms, etc.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122380327","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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