Pub Date : 2020-12-30DOI: 10.23940/IJPE.20.12.P2.18531861
A. Ivanov, V. Mikhailova, D. Savelev, I. Skrypnik, T. Kaverzneva
{"title":"Use of Hydrogel Composition to Increase Efficiency of Thermal Protection of Oil Product Tanks","authors":"A. Ivanov, V. Mikhailova, D. Savelev, I. Skrypnik, T. Kaverzneva","doi":"10.23940/IJPE.20.12.P2.18531861","DOIUrl":"https://doi.org/10.23940/IJPE.20.12.P2.18531861","url":null,"abstract":"","PeriodicalId":39483,"journal":{"name":"International Journal of Performability Engineering","volume":"16 1","pages":"1853"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46957095","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 : 2020-12-30DOI: 10.23940/IJPE.20.12.P1.18451852
K. Anupama, Y. Rao, V. Gurrala
{"title":"A Machine Learning Approach to Monitor Water Quality in Aquaculture","authors":"K. Anupama, Y. Rao, V. Gurrala","doi":"10.23940/IJPE.20.12.P1.18451852","DOIUrl":"https://doi.org/10.23940/IJPE.20.12.P1.18451852","url":null,"abstract":"","PeriodicalId":39483,"journal":{"name":"International Journal of Performability Engineering","volume":"16 1","pages":"1845"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48395072","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 : 2020-12-30DOI: 10.23940/IJPE.20.12.P8.19211932
Huo Tingting, Yan Zhang, Chunyan Xia, Zijiang Yang, Weisong Sun
{"title":"Large-Scale Test Case Prioritization using Viterbi Algorithm","authors":"Huo Tingting, Yan Zhang, Chunyan Xia, Zijiang Yang, Weisong Sun","doi":"10.23940/IJPE.20.12.P8.19211932","DOIUrl":"https://doi.org/10.23940/IJPE.20.12.P8.19211932","url":null,"abstract":"","PeriodicalId":39483,"journal":{"name":"International Journal of Performability Engineering","volume":"16 1","pages":"1921"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49127376","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 : 2020-12-30DOI: 10.23940/IJPE.20.12.P13.19651974
Bo Song, Y. Ma
{"title":"Intelligent School Talent Information Fusion Management and Talent Training System Optimization based on Data Mining","authors":"Bo Song, Y. Ma","doi":"10.23940/IJPE.20.12.P13.19651974","DOIUrl":"https://doi.org/10.23940/IJPE.20.12.P13.19651974","url":null,"abstract":"","PeriodicalId":39483,"journal":{"name":"International Journal of Performability Engineering","volume":"16 1","pages":"1965"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44858633","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 : 2019-12-18DOI: 10.23940/ijpe.19.11.p5.28712881
Liu Hui, Jinlong Xu, Ding Lili
GCC compiler is a retargetable compiler program that was developed to increase the efficiency of programs in the GNU system. In recent years, compiler optimization based on data dependency analysis has become an important research area of modern compilers. Existing GCC compilers can only conduct dependency analysis on perfect nested loops. In order to better explore the coarse-grained parallelism of the nested loops, we propose a dependence test method that can deal with the branch nested loops. Firstly, we identify the branch nested loop in the programs. Then, we analyze the relationship between the array subscript and the outer index variable of the branch nested loop. Finally, we calculate the distance vector of the outer loop index variable and determine whether the loop has dependence through distance vector detection. Experimental results show that our method can correctly and effectively analyze the dependence relationship of branch nested loops.
{"title":"Coarse-Grained Automatic Parallelization Approach for Branch Nested Loop","authors":"Liu Hui, Jinlong Xu, Ding Lili","doi":"10.23940/ijpe.19.11.p5.28712881","DOIUrl":"https://doi.org/10.23940/ijpe.19.11.p5.28712881","url":null,"abstract":"GCC compiler is a retargetable compiler program that was developed to increase the efficiency of programs in the GNU system. In recent years, compiler optimization based on data dependency analysis has become an important research area of modern compilers. Existing GCC compilers can only conduct dependency analysis on perfect nested loops. In order to better explore the coarse-grained parallelism of the nested loops, we propose a dependence test method that can deal with the branch nested loops. Firstly, we identify the branch nested loop in the programs. Then, we analyze the relationship between the array subscript and the outer index variable of the branch nested loop. Finally, we calculate the distance vector of the outer loop index variable and determine whether the loop has dependence through distance vector detection. Experimental results show that our method can correctly and effectively analyze the dependence relationship of branch nested loops.","PeriodicalId":39483,"journal":{"name":"International Journal of Performability Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46464191","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 : 2019-12-18DOI: 10.23940/ijpe.19.11.p6.28822890
P. Cheng, He Jing, C. Hao, Yuan Xinpan, Deng Xiaojun
For the problem that fan blade icing failures cannot be accurately predicted in advance, a data-driven fault prediction method is proposed in this paper. Firstly, the delay window is introduced to the PCA algorithm to extract the fault mode related features from the SCADA high-dimensional data. Then, the trained Elman neural network is adopted to predict the future value of the relevant features. Finally, a BP self-clustering algorithm is designed to predict the icing fault of the blade with the multi-source data fusion. The results show that the proposed method can effectively predict the icing failure of wind turbine blades and has reference significance for the maintenance of wind turbines.
{"title":"Icing Prediction of Fan Blade based on a Hybrid Model","authors":"P. Cheng, He Jing, C. Hao, Yuan Xinpan, Deng Xiaojun","doi":"10.23940/ijpe.19.11.p6.28822890","DOIUrl":"https://doi.org/10.23940/ijpe.19.11.p6.28822890","url":null,"abstract":"For the problem that fan blade icing failures cannot be accurately predicted in advance, a data-driven fault prediction method is proposed in this paper. Firstly, the delay window is introduced to the PCA algorithm to extract the fault mode related features from the SCADA high-dimensional data. Then, the trained Elman neural network is adopted to predict the future value of the relevant features. Finally, a BP self-clustering algorithm is designed to predict the icing fault of the blade with the multi-source data fusion. The results show that the proposed method can effectively predict the icing failure of wind turbine blades and has reference significance for the maintenance of wind turbines.","PeriodicalId":39483,"journal":{"name":"International Journal of Performability Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68773791","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 : 2019-12-18DOI: 10.23940/ijpe.19.11.p2.28432851
A. Patil, V. Mariappan, Leslie C. D'souza, Reuben J. Nazareth
Education has a considerable role in the development of our future. Hence, the quality of education is of prime importance in crafting the future of our country. Services offered by education institutes articulate the quality of the education. This is also valid to higher education. Higher education institutes in India are increasing and thus, to remain competitive, they strive to improve the quality of education. Technical institutes are growing at a rapid pace compared to non-technical and the same is experienced in the Goa state. Hence, this paper focuses on technical higher education in Goa, India. This research investigates service attributes contributing towards the quality of technical education and suggests operating levels of these attributes to improve student performance in academics. To distinguish quality of technical education, a face to face survey with stakeholders was conducted. The SERVQUAL form questionnaire addresses five service quality dimensions. Further analysis was carried out using Signal to Noise ratio and Grey Relation Analysis to predict optimal levels of service attributes to improvised student performance.
{"title":"Quality Assessment of Technical Education using SERVQUAL: S/N Ratio and Grey Relation Analysis","authors":"A. Patil, V. Mariappan, Leslie C. D'souza, Reuben J. Nazareth","doi":"10.23940/ijpe.19.11.p2.28432851","DOIUrl":"https://doi.org/10.23940/ijpe.19.11.p2.28432851","url":null,"abstract":"Education has a considerable role in the development of our future. Hence, the quality of education is of prime importance in crafting the future of our country. Services offered by education institutes articulate the quality of the education. This is also valid to higher education. Higher education institutes in India are increasing and thus, to remain competitive, they strive to improve the quality of education. Technical institutes are growing at a rapid pace compared to non-technical and the same is experienced in the Goa state. Hence, this paper focuses on technical higher education in Goa, India. This research investigates service attributes contributing towards the quality of technical education and suggests operating levels of these attributes to improve student performance in academics. To distinguish quality of technical education, a face to face survey with stakeholders was conducted. The SERVQUAL form questionnaire addresses five service quality dimensions. Further analysis was carried out using Signal to Noise ratio and Grey Relation Analysis to predict optimal levels of service attributes to improvised student performance.","PeriodicalId":39483,"journal":{"name":"International Journal of Performability Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49212752","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 : 2019-12-18DOI: 10.23940/ijpe.19.11.p8.28992907
Wang Pengju, Xue Huifeng, Yu Zhe, Zhang Feng
In order to improve the decision-making level for public opinion responses and realize the semantic fusion of multi-level and multi-source heterogeneous public opinion information, an ontology-based public opinion information fusion method is proposed. Firstly, aiming at quick response decision-making, the situation assessment model of public opinion information fusion is studied, and the information fusion system is constructed. The multi-level evaluation model of situation recognition, situation understanding, and situation prediction is formed. Then, the multi-indicator ontology model and method for public opinion decision-making are constructed, and the public opinion data fusion model based on ontology semantics is proposed, which realizes the relevance analysis and semantic fusion of domain knowledge. Finally, a multi-level public opinion data fusion model is constructed, and the construction of the underlying emergency information knowledge base to support the above functions is deeply studied. The simulation results show that the feasibility and efficiency of the situation assessment problem are solved by this method, the time complexity and space complexity of attribute reduction and value reduction are reduced, and the matching efficiency of situation assessment rules is improved.
{"title":"Public Opinion Data Fusion Method based on Ontology Semantics","authors":"Wang Pengju, Xue Huifeng, Yu Zhe, Zhang Feng","doi":"10.23940/ijpe.19.11.p8.28992907","DOIUrl":"https://doi.org/10.23940/ijpe.19.11.p8.28992907","url":null,"abstract":"In order to improve the decision-making level for public opinion responses and realize the semantic fusion of multi-level and multi-source heterogeneous public opinion information, an ontology-based public opinion information fusion method is proposed. Firstly, aiming at quick response decision-making, the situation assessment model of public opinion information fusion is studied, and the information fusion system is constructed. The multi-level evaluation model of situation recognition, situation understanding, and situation prediction is formed. Then, the multi-indicator ontology model and method for public opinion decision-making are constructed, and the public opinion data fusion model based on ontology semantics is proposed, which realizes the relevance analysis and semantic fusion of domain knowledge. Finally, a multi-level public opinion data fusion model is constructed, and the construction of the underlying emergency information knowledge base to support the above functions is deeply studied. The simulation results show that the feasibility and efficiency of the situation assessment problem are solved by this method, the time complexity and space complexity of attribute reduction and value reduction are reduced, and the matching efficiency of situation assessment rules is improved.","PeriodicalId":39483,"journal":{"name":"International Journal of Performability Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47962662","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 : 2019-12-18DOI: 10.23940/ijpe.19.11.p9.29082915
Wang Lin, Tian Bing, Li Yan, Qu Yan-sheng
In order to improve the information security ability of the network information platform, an information security evaluation method is proposed based on artificial neural networks. Based on the comprehensive analysis of the security events in the construction of the network information platform, the risk assessment model of the network information platform is constructed based on the artificial neural network theory. The weight calculation algorithm of artificial neural networks and the minimum artificial neural network pruning algorithm are also given, which can realize the quantitative evaluation of network information security. The fuzzy neural network weighted control method is used to control the information security, and the non-recursive traversal method is adopted to realize the adaptive training of the information security assessment process. The adaptive learning of the artificial neural network is carried out according, and the ability of information encryption and transmission is improved. The information security assessment is realized. The simulation results show that the method is accurate, and the information security is ensured.
{"title":"Information Security Evaluation based on Artificial Neural Network","authors":"Wang Lin, Tian Bing, Li Yan, Qu Yan-sheng","doi":"10.23940/ijpe.19.11.p9.29082915","DOIUrl":"https://doi.org/10.23940/ijpe.19.11.p9.29082915","url":null,"abstract":"In order to improve the information security ability of the network information platform, an information security evaluation method is proposed based on artificial neural networks. Based on the comprehensive analysis of the security events in the construction of the network information platform, the risk assessment model of the network information platform is constructed based on the artificial neural network theory. The weight calculation algorithm of artificial neural networks and the minimum artificial neural network pruning algorithm are also given, which can realize the quantitative evaluation of network information security. The fuzzy neural network weighted control method is used to control the information security, and the non-recursive traversal method is adopted to realize the adaptive training of the information security assessment process. The adaptive learning of the artificial neural network is carried out according, and the ability of information encryption and transmission is improved. The information security assessment is realized. The simulation results show that the method is accurate, and the information security is ensured.","PeriodicalId":39483,"journal":{"name":"International Journal of Performability Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45251859","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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