Pub Date : 2023-01-01DOI: 10.56042/ijems.v1i1.65437
{"title":"Optimisation of Diffusion Welding Parameters in Al-Cu Bimetal for Shaped Charge Application","authors":"","doi":"10.56042/ijems.v1i1.65437","DOIUrl":"https://doi.org/10.56042/ijems.v1i1.65437","url":null,"abstract":"","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"54 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87999708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.56042/ijems.v29i6.70290
{"title":"Modeling of Dry Conditioned Sliding Wear And Friction Behavior of Heat-Treated Silicon Nitride Strengthened Al Metal Matrix Nanocomposites","authors":"","doi":"10.56042/ijems.v29i6.70290","DOIUrl":"https://doi.org/10.56042/ijems.v29i6.70290","url":null,"abstract":"","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"2 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88938332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.56042/ijems.v29i5.46433
{"title":"Production and Characterisation of Biodiesel with the mixture of Ambadi oil and Waste Cooking Oil","authors":"","doi":"10.56042/ijems.v29i5.46433","DOIUrl":"https://doi.org/10.56042/ijems.v29i5.46433","url":null,"abstract":"","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"51 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88980226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.56042/ijems.v29i4.47943
Madhuvanthani Rajendran, Sundar Govindasamy
The objective of this paper is to present a comprehensive review of the various droop control strategies employed to control the operation of the parallel inverters present in a microgrid, based onits output impedance. Predominantly, the output impedances of the inverters are inductive due to the line impedance and filter but in low power systems, the inverter has a resistive output impedance. The various categories under which the droop control strategies of inverters with inductive output impedance fall have been reviewed, along with its pros and cons. Although most of the inverters have inductive output impedance, inverters with resistive output impedance are superior due to the easier compensation of harmonics. Along with their advantages the various disadvantages present in the droop control strategies utilized for inverters with resistive output impedance and the solutions to overcome these problems are presented. Recent studies have shown that inverters with capacitive output impedance provide the lowest Total Harmonic Distortion along with reliable regulation of voltage and accurate power sharing. The technique of obtaining an inverter with capacitive output impedance along with its various advantages has also been presented. The universal droop strategy utilized for all types of inverters without prior knowledge of their output impedances is reviewed along with an example, to overcome the problem of having to change the droop equations according to the output impedance of the inverter. Lastly a few case studies related to microgrid implementation have been analyzed along with its challenges as well as standards and policies.
{"title":"Influence of output impedance of an inverter on its droop control strategies in a microgrid","authors":"Madhuvanthani Rajendran, Sundar Govindasamy","doi":"10.56042/ijems.v29i4.47943","DOIUrl":"https://doi.org/10.56042/ijems.v29i4.47943","url":null,"abstract":"The objective of this paper is to present a comprehensive review of the various droop control strategies employed to control the operation of the parallel inverters present in a microgrid, based onits output impedance. Predominantly, the output impedances of the inverters are inductive due to the line impedance and filter but in low power systems, the inverter has a resistive output impedance. The various categories under which the droop control strategies of inverters with inductive output impedance fall have been reviewed, along with its pros and cons. Although most of the inverters have inductive output impedance, inverters with resistive output impedance are superior due to the easier compensation of harmonics. Along with their advantages the various disadvantages present in the droop control strategies utilized for inverters with resistive output impedance and the solutions to overcome these problems are presented. Recent studies have shown that inverters with capacitive output impedance provide the lowest Total Harmonic Distortion along with reliable regulation of voltage and accurate power sharing. The technique of obtaining an inverter with capacitive output impedance along with its various advantages has also been presented. The universal droop strategy utilized for all types of inverters without prior knowledge of their output impedances is reviewed along with an example, to overcome the problem of having to change the droop equations according to the output impedance of the inverter. Lastly a few case studies related to microgrid implementation have been analyzed along with its challenges as well as standards and policies.","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"26 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90105972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.56042/ijems.v29i6.70313
{"title":"Waste Tyre Recycling: potential applications with a focus on permeable pavements","authors":"","doi":"10.56042/ijems.v29i6.70313","DOIUrl":"https://doi.org/10.56042/ijems.v29i6.70313","url":null,"abstract":"","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"61 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90702285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.56042/ijems.v29i4.48695
{"title":"Synthesis of diamagnetic ZnO nano-crystallites via sol-gel method and their photocatalytic activity","authors":"","doi":"10.56042/ijems.v29i4.48695","DOIUrl":"https://doi.org/10.56042/ijems.v29i4.48695","url":null,"abstract":"","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"56 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73406037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.56042/ijems.v29i5.46911
{"title":"Surface Tension of Polyurethane Solution and Thermodynamic Model","authors":"","doi":"10.56042/ijems.v29i5.46911","DOIUrl":"https://doi.org/10.56042/ijems.v29i5.46911","url":null,"abstract":"","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"89 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77620271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.56042/ijems.v29i5.48825
{"title":"Structure Determination of Al2CuMg Precipitates in AlCu15Mg5 Alloys by High-Resolution Electron Microscopy","authors":"","doi":"10.56042/ijems.v29i5.48825","DOIUrl":"https://doi.org/10.56042/ijems.v29i5.48825","url":null,"abstract":"","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"41 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77636876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.56042/ijems.v29i2.46466
A. M. Moshi, S. Bharathi
Optimization is ruling the entire field of machining and material processing technology from the time at which the revolution took place in machining processes. Various types of machining algorithms have been developed so far for optimizing the independent control factors in order to get the improved results of desirable output responses. Each algorithm has its own special features which made them useful in deriving the optimized solutions under different conditions. Suitable algorithm is chosen for the required case depending upon the nature of the problem, the requirement of the order of precision and the availability of optimization tools. In this review article, the general flow of few important algorithms has been explained in a simpler manner to be understood by the recent researchers. Also, required numbers of case studies for each algorithm have been provided extensively. This consolidated work will surely be helpful for the new researchers those who have entered into the domain of optimization.
{"title":"Effective utilization of optimization algorithms on machining operations","authors":"A. M. Moshi, S. Bharathi","doi":"10.56042/ijems.v29i2.46466","DOIUrl":"https://doi.org/10.56042/ijems.v29i2.46466","url":null,"abstract":"Optimization is ruling the entire field of machining and material processing technology from the time at which the revolution took place in machining processes. Various types of machining algorithms have been developed so far for optimizing the independent control factors in order to get the improved results of desirable output responses. Each algorithm has its own special features which made them useful in deriving the optimized solutions under different conditions. Suitable algorithm is chosen for the required case depending upon the nature of the problem, the requirement of the order of precision and the availability of optimization tools. In this review article, the general flow of few important algorithms has been explained in a simpler manner to be understood by the recent researchers. Also, required numbers of case studies for each algorithm have been provided extensively. This consolidated work will surely be helpful for the new researchers those who have entered into the domain of optimization.","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"73 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77811084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.56042/ijems.v29i4.46838
Anshu Parashar, Kuljot Singh Saggu, Anupam Garg
Cybersecurity issues are increasing day by day, and it is becoming essential to address them aggressively. An efficient IDS system should be placed to identify abnormal behaviour by dynamically tracing the network traffic pattern. In this work, we proposed a framework for Network Intrusion Detection System using stacking ensemble technique of machine learning, which is testified on Random Forest Regressor and Extra Tree Classifier approaches for feature selections from the subjected dataset. The extensive experimentation has been done by applying 11 states of the art and hybrid machine learning algorithms to select the best performing algorithms. During the investigation, Random Forest, ID3 and XGBoost algorithms are found as best performers among different machine learning algorithms based on accuracy, precision, recall, F1-score and time to increase real-time attack detection performance. Three case studies have been carried out. Our results indicate that the proposed stacking ensemble-based framework of NIDS outperformed compared to the different state of art machine learning algorithms with average 0.99 prediction accuracy.
{"title":"Machine learning based framework for network intrusion detection system using stacking ensemble technique","authors":"Anshu Parashar, Kuljot Singh Saggu, Anupam Garg","doi":"10.56042/ijems.v29i4.46838","DOIUrl":"https://doi.org/10.56042/ijems.v29i4.46838","url":null,"abstract":"Cybersecurity issues are increasing day by day, and it is becoming essential to address them aggressively. An efficient IDS system should be placed to identify abnormal behaviour by dynamically tracing the network traffic pattern. In this work, we proposed a framework for Network Intrusion Detection System using stacking ensemble technique of machine learning, which is testified on Random Forest Regressor and Extra Tree Classifier approaches for feature selections from the subjected dataset. The extensive experimentation has been done by applying 11 states of the art and hybrid machine learning algorithms to select the best performing algorithms. During the investigation, Random Forest, ID3 and XGBoost algorithms are found as best performers among different machine learning algorithms based on accuracy, precision, recall, F1-score and time to increase real-time attack detection performance. Three case studies have been carried out. Our results indicate that the proposed stacking ensemble-based framework of NIDS outperformed compared to the different state of art machine learning algorithms with average 0.99 prediction accuracy.","PeriodicalId":13464,"journal":{"name":"Indian Journal of Engineering and Materials Sciences","volume":"173 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78028709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","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：