Murali Krishna Kodimenu1,, Dr Satyanarayana S2,, Dr Thayabba Katoon3
The ascent of the digital payments industry is accelerating as the global economy increasingly adopts online and card-based payment systems. This transition, however, brings with it an elevated risk of cyber threats and fraud, now more prevalent than ever before. For banks and financial institutions, bolstering the detection of credit card fraud is of utmost importance. Machine learning (ML) is revolutionizing this domain, making the identification of fraudulent activities both simpler and more effective. ML- powered fraud detection systems are adept at identifying patterns and halting irregular transactions. The hurdles faced in this area are significant: vast quantities of data are processed daily, with the vast majority of transactions (99.8%) being legitimate; the data, largely confidential, is not readily accessible; not all fraudulent activities are detected and reported; and fraudsters continually develop new strategies to outsmart the detection models. Machine learning algorithms are capable of pinpointing atypical credit card transactions and instances of fraud, ensuring that cardholders are not billed for purchases they did not make. These ML algorithms outperform traditional fraud detection systems, capable of discerning thousands of patterns within extensive datasets. Moreover, ML provides valuable insights into consumer behavior through the analysis of app usage, payment, and transaction patterns. The advantages of deploying machine learning in the fight against credit card fraud are manifold, including swifter detection, enhanced precision, and increased efficiency when dealing with large volumes of data. Key Words: Credit Card Frauds, Fraud Detection, Correlation matrix, principal components, Random Forest.
随着全球经济越来越多地采用在线支付和刷卡支付系统，数字支付行业正在加速崛起。然而，这种转变也带来了网络威胁和欺诈风险的上升，现在比以往任何时候都更加普遍。对于银行和金融机构来说，加强信用卡欺诈检测至关重要。机器学习（ML）正在彻底改变这一领域，使欺诈活动的识别变得更简单、更有效。由 ML 驱动的欺诈检测系统善于识别模式并阻止异常交易。这一领域面临的障碍非常大：每天要处理大量数据，而绝大多数交易（99.8%）都是合法的；数据大多是保密的，不容易获取；并非所有欺诈活动都能被发现和报告；欺诈者不断开发新的策略，以超越检测模型。机器学习算法能够精确定位非典型信用卡交易和欺诈事件，确保持卡人不会为他们没有进行的消费支付账单。这些 ML 算法优于传统的欺诈检测系统，能够在广泛的数据集中识别成千上万种模式。此外，通过对应用程序使用、支付和交易模式的分析，机器学习还能提供对消费者行为的宝贵见解。在打击信用卡欺诈中部署机器学习的优势是多方面的，包括检测速度更快、精度更高，以及在处理大量数据时效率更高。关键字信用卡欺诈、欺诈检测、相关矩阵、主成分、随机森林。
{"title":"Credit Card Fraud Detection Using ML & DL","authors":"Murali Krishna Kodimenu1,, Dr Satyanarayana S2,, Dr Thayabba Katoon3","doi":"10.55041/ijsrem36686","DOIUrl":"https://doi.org/10.55041/ijsrem36686","url":null,"abstract":"The ascent of the digital payments industry is accelerating as the global economy increasingly adopts online and card-based payment systems. This transition, however, brings with it an elevated risk of cyber threats and fraud, now more prevalent than ever before. For banks and financial institutions, bolstering the detection of credit card fraud is of utmost importance. Machine learning (ML) is revolutionizing this domain, making the identification of fraudulent activities both simpler and more effective. ML- powered fraud detection systems are adept at identifying patterns and halting irregular transactions. The hurdles faced in this area are significant: vast quantities of data are processed daily, with the vast majority of transactions (99.8%) being legitimate; the data, largely confidential, is not readily accessible; not all fraudulent activities are detected and reported; and fraudsters continually develop new strategies to outsmart the detection models. Machine learning algorithms are capable of pinpointing atypical credit card transactions and instances of fraud, ensuring that cardholders are not billed for purchases they did not make. These ML algorithms outperform traditional fraud detection systems, capable of discerning thousands of patterns within extensive datasets. Moreover, ML provides valuable insights into consumer behavior through the analysis of app usage, payment, and transaction patterns. The advantages of deploying machine learning in the fight against credit card fraud are manifold, including swifter detection, enhanced precision, and increased efficiency when dealing with large volumes of data. Key Words: Credit Card Frauds, Fraud Detection, Correlation matrix, principal components, Random Forest.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"115 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820130","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}
Compact heat exchangers are now essential parts of many industrial processes that aim to reduce their environmental impact and increase energy efficiency. The experimental inquiry presented in this paper aims to improve the performance of heat transfer in compact heat exchangers by adding nanoparticles to the fluid used for heat transfer.A range of experiments were carried out with different nanoparticle concentrations, flow rates, and temperatures to evaluate the effects of nanofluids.To explore the effects on heat transfer enhancement, a variety of nanoparticle materials, including graphene oxide, copper oxide, titanium dioxide, zinc oxide, and aluminum oxide, were dispersed in the base fluids. According to experimental data, adding nanofluids significantly improved heat transfer performance; these nanofluids demonstrated greater heat transfer coefficients than conventional heat transfer fluids.
{"title":"Experimental Analysis on Using Nanoparticles to Improve Heat Transfer in Compact Heat Exchangers","authors":"Dr.T Balusamy, Leni Cinthana. S","doi":"10.55041/ijsrem36624","DOIUrl":"https://doi.org/10.55041/ijsrem36624","url":null,"abstract":"Compact heat exchangers are now essential parts of many industrial processes that aim to reduce their environmental impact and increase energy efficiency. The experimental inquiry presented in this paper aims to improve the performance of heat transfer in compact heat exchangers by adding nanoparticles to the fluid used for heat transfer.A range of experiments were carried out with different nanoparticle concentrations, flow rates, and temperatures to evaluate the effects of nanofluids.To explore the effects on heat transfer enhancement, a variety of nanoparticle materials, including graphene oxide, copper oxide, titanium dioxide, zinc oxide, and aluminum oxide, were dispersed in the base fluids. According to experimental data, adding nanofluids significantly improved heat transfer performance; these nanofluids demonstrated greater heat transfer coefficients than conventional heat transfer fluids.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"16 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819608","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}
In residential refrigerators, R134a is the most often used refrigerant. The Kyoto Protocol requires that it be phased out as soon as possible because to its high global warming potential (GWP) of 1300. In the current study, a 200l single evaporator home refrigerator using a hydrocarbon refrigerant combination (made up of R290 and R600a in a weight ratio of 45.2:54.8) has been used as an alternative to R134a. While cycling running (ON/OFF) testing were only conducted at 32 ◦C ambient temperature, continuous running tests were conducted at various ambient temperatures (24, 28, 32, 38, and 43 ◦C). The hydrocarbon mixture was found to have a 3.25–3.6% higher coefficient of performance (COP) and lower values of energy consumption, draw down time, and ON time ratio by around 11.1%, 11.6%, and 13.2%, respectively. It was discovered that the hydrocarbon mixture's discharge temperature was between 8.5 and 13.4 K lower than R134a's. Overall performance has demonstrated that the hydrocarbon refrigerant mixture mentioned above may be the most suitable long-term replacement for R134a as it phases out.
{"title":"Experimental Investigation on the Performance Analysis Domestic Refrigeration Using Eco Friendly R290 & R600a Refrigerant","authors":"Prof.M. Periyasamy, D.Jagan Mohan","doi":"10.55041/ijsrem36643","DOIUrl":"https://doi.org/10.55041/ijsrem36643","url":null,"abstract":"In residential refrigerators, R134a is the most often used refrigerant. The Kyoto Protocol requires that it be phased out as soon as possible because to its high global warming potential (GWP) of 1300. In the current study, a 200l single evaporator home refrigerator using a hydrocarbon refrigerant combination (made up of R290 and R600a in a weight ratio of 45.2:54.8) has been used as an alternative to R134a. While cycling running (ON/OFF) testing were only conducted at 32 ◦C ambient temperature, continuous running tests were conducted at various ambient temperatures (24, 28, 32, 38, and 43 ◦C). The hydrocarbon mixture was found to have a 3.25–3.6% higher coefficient of performance (COP) and lower values of energy consumption, draw down time, and ON time ratio by around 11.1%, 11.6%, and 13.2%, respectively. It was discovered that the hydrocarbon mixture's discharge temperature was between 8.5 and 13.4 K lower than R134a's. Overall performance has demonstrated that the hydrocarbon refrigerant mixture mentioned above may be the most suitable long-term replacement for R134a as it phases out.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"23 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819509","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}
Plant disease early detection has a major impact on crop quality and financial stability, makingit essential for India's agriculture. The precision of current detection techniques is lacking, which puts yields at risk. In order to identify cotton leaf illnesses and classify leaves as healthy, unhealthy, or sick, this study suggests a prediction method. This focused strategy enables focused therapies and aids in the prevention of disease spread. The framework can also be modified to identify diseases that affect tomato plants with the goal of increasing agricultural yields, lowering costs, and promoting environmentally friendly farming methods. Keyword: Leaf, Diseases, Support Vector Machine (SVM), Convolutional Neural Networks(CNN).
{"title":"RECOGNITION OF LEAF ILLNESS DETECTION","authors":"Nayan Naik M, R. R","doi":"10.55041/ijsrem36642","DOIUrl":"https://doi.org/10.55041/ijsrem36642","url":null,"abstract":"Plant disease early detection has a major impact on crop quality and financial stability, makingit essential for India's agriculture. The precision of current detection techniques is lacking, which puts yields at risk. In order to identify cotton leaf illnesses and classify leaves as healthy, unhealthy, or sick, this study suggests a prediction method. This focused strategy enables focused therapies and aids in the prevention of disease spread. The framework can also be modified to identify diseases that affect tomato plants with the goal of increasing agricultural yields, lowering costs, and promoting environmentally friendly farming methods. Keyword: Leaf, Diseases, Support Vector Machine (SVM), Convolutional Neural Networks(CNN).","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"111 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820299","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}
Voice-activated email is a big step forward for people with visual impairments since it lets them use voice commands to check their inbox, send and receive emails, and manage their accounts. The platform combines state-of-the-art machine learning and speech recognition technologies with an easy-to-use interface to provide safe authentication, email reading, and smooth interaction using only voice commands. This invention empowers visually impaired persons to fully engage in digital communication with ease and confidence, improving accessibility and productivity while also promoting independence and inclusivity. Keyword: Text-to-speech (TTS), Machine learning algorithms, Voice-based email system.
{"title":"VOICE BASED EMAIL SYSTEM FOR BLIND USING ML","authors":"K. H M, D. M","doi":"10.55041/ijsrem36636","DOIUrl":"https://doi.org/10.55041/ijsrem36636","url":null,"abstract":"Voice-activated email is a big step forward for people with visual impairments since it lets them use voice commands to check their inbox, send and receive emails, and manage their accounts. The platform combines state-of-the-art machine learning and speech recognition technologies with an easy-to-use interface to provide safe authentication, email reading, and smooth interaction using only voice commands. This invention empowers visually impaired persons to fully engage in digital communication with ease and confidence, improving accessibility and productivity while also promoting independence and inclusivity. Keyword: Text-to-speech (TTS), Machine learning algorithms, Voice-based email system.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"55 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819060","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}
The linear construction method is an essential and widely utilized approach in roadwork projects, known for its systematic and sequential execution. This method plays a critical role in the organized and efficient development of infrastructure, which is pivotal for economic growth and societal advancement. Roads are integral to the transportation network, and their construction requires meticulous planning and execution to ensure longevity, safety, and functionality. By adhering to a clear, phase-by-phase framework, the linear construction method provides a robust mechanism for project managers and engineers to plan, allocate resources, and implement roadwork projects effectively.
{"title":"AN EXAMINING ANALYSIS OF THE LINEAR CONSTRUCTION METHOD FOR ROADWORK’S","authors":"Mr.AKASH T","doi":"10.55041/ijsrem36649","DOIUrl":"https://doi.org/10.55041/ijsrem36649","url":null,"abstract":"The linear construction method is an essential and widely utilized approach in roadwork projects, known for its systematic and sequential execution. This method plays a critical role in the organized and efficient development of infrastructure, which is pivotal for economic growth and societal advancement. Roads are integral to the transportation network, and their construction requires meticulous planning and execution to ensure longevity, safety, and functionality. By adhering to a clear, phase-by-phase framework, the linear construction method provides a robust mechanism for project managers and engineers to plan, allocate resources, and implement roadwork projects effectively.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"64 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819033","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}
Machine learning has evolved as a potent tool for predicting outcomes in numerous sports, including cricket. This study investigates the potential of machine learning for run chase prediction in Indian Premier League (IPL) matches. We explore the effectiveness of five algorithms - Random Forest, Logistic Regression, Gradient Boosting, K-Nearest Neighbors and Decision Tree Classifier - in developing models to predict the success of a team chasing a set target in the second innings. Historical data on batting/bowling teams, target score, wickets lost, and other factors was used to train various models. The Random Forest model achieved the highest accuracy (99.81%) in predicting win/loss compared to other algorithms (80.06% - 98.73%). Our research emphasizes the potential of machine learning, particularly Random Forest, for accurate IPL run-chase prediction. This offers valuable insights for cricket fans, analysts, and potentially even strategists. Key Words: Random Forest, Logistic Regression, Machine Learning Algorithms, Model Performance, Classification.
{"title":"A Comparative Study of Machine Learning Algorithms for Run Chase Prediction in IPL","authors":"Arya Bharne, Bhakti Miglani, Saundarya Raut","doi":"10.55041/ijsrem36677","DOIUrl":"https://doi.org/10.55041/ijsrem36677","url":null,"abstract":"Machine learning has evolved as a potent tool for predicting outcomes in numerous sports, including cricket. This study investigates the potential of machine learning for run chase prediction in Indian Premier League (IPL) matches. We explore the effectiveness of five algorithms - Random Forest, Logistic Regression, Gradient Boosting, K-Nearest Neighbors and Decision Tree Classifier - in developing models to predict the success of a team chasing a set target in the second innings. Historical data on batting/bowling teams, target score, wickets lost, and other factors was used to train various models. The Random Forest model achieved the highest accuracy (99.81%) in predicting win/loss compared to other algorithms (80.06% - 98.73%). Our research emphasizes the potential of machine learning, particularly Random Forest, for accurate IPL run-chase prediction. This offers valuable insights for cricket fans, analysts, and potentially even strategists. Key Words: Random Forest, Logistic Regression, Machine Learning Algorithms, Model Performance, Classification.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"77 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819190","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}
Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives ideas about how to efficiently use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system which can run independently of human given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.
{"title":"Comprehensive Study of Data Science","authors":"Chennu Ganesh Tiru Venkata Manikanta Sai, Kasaraneni Sri Harsha, Chennu Aryan Karthikeya","doi":"10.55041/ijsrem36535","DOIUrl":"https://doi.org/10.55041/ijsrem36535","url":null,"abstract":"Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives ideas about how to efficiently use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system which can run independently of human given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"27 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819732","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}
In the present paper, the some of first transition series metal complexes derived from 4-hydroxy-3-(3-(4- hydroxy-3,5-dimethoxyphenyl)acryloyl)-6-methyl-2H-pyran-2-one chalcone were synthesized from Dehydroacetic acid and 4-hydroxy-3,5-dimethoxy benzaldehyde (syringaldehyde). The ligand was characterized on the basis of elemental analysis, UV, IR, Mass, 1H NMR and antimicrobial activity. All the complexes were characterized by elemental analysis, UV, magnetic susceptibility measurements, IR, TGA-DTA & antimicrobial activity. The ligand acts as a bidentate chelate and coordinates through two oxygen atoms of ligand i.e complex formed by 1:2 ( metal: ligand ) ratio. The thermal stability of the complexes was studied by thermogravimetry and the decomposition schemes of the complexes are given. The ligand and its metal complexes were screened for antimicrobial activity against Bacillus Cereus, Bacillus Megaterium, Shigellaboydii and Escherichia Coli bacteria, and Saccharomyces Cerevisiae, Aspergillus Oryzae and Penicillium notatum fungi were studied. Antimicrobial activity it is found that the complexes are more active than their parent ligand. Keywords: Transition metal complexes; magnetic susceptibility; Chalcone; Oxygen donar ligand; TGA-DTA; Antimicrobial activity.
{"title":"Thermo gravimetric and Antimicrobial analysis of 4-hydroxy-3-(3-(4-hydroxy-3,5-dimethoxyphenyl)acryloyl)-6-methyl-2H-pyran-2-one chalcone and their metal complexes","authors":"Balaji Jawale","doi":"10.55041/ijsrem36610","DOIUrl":"https://doi.org/10.55041/ijsrem36610","url":null,"abstract":"In the present paper, the some of first transition series metal complexes derived from 4-hydroxy-3-(3-(4- hydroxy-3,5-dimethoxyphenyl)acryloyl)-6-methyl-2H-pyran-2-one chalcone were synthesized from Dehydroacetic acid and 4-hydroxy-3,5-dimethoxy benzaldehyde (syringaldehyde). The ligand was characterized on the basis of elemental analysis, UV, IR, Mass, 1H NMR and antimicrobial activity. All the complexes were characterized by elemental analysis, UV, magnetic susceptibility measurements, IR, TGA-DTA & antimicrobial activity. The ligand acts as a bidentate chelate and coordinates through two oxygen atoms of ligand i.e complex formed by 1:2 ( metal: ligand ) ratio. The thermal stability of the complexes was studied by thermogravimetry and the decomposition schemes of the complexes are given. The ligand and its metal complexes were screened for antimicrobial activity against Bacillus Cereus, Bacillus Megaterium, Shigellaboydii and Escherichia Coli bacteria, and Saccharomyces Cerevisiae, Aspergillus Oryzae and Penicillium notatum fungi were studied. Antimicrobial activity it is found that the complexes are more active than their parent ligand. Keywords: Transition metal complexes; magnetic susceptibility; Chalcone; Oxygen donar ligand; TGA-DTA; Antimicrobial activity.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"110 40","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820450","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}
The, high-gain DC–DC converters dragged much attention among the researchers. But there is a concern that high-gain converters have less efficiency and high switching stresses. The converter topology has two quasi-impedance source network and a voltage multiplier cell unit to facilitate very high-gain output voltage. The input variations due to varying irradiation of photovoltaic are alleviated by employing the perturb and observe maximum power point tracking mechanism. The simulation of the work is realized in MATLAB/ Simulink arena, and hardware circuits are validated using the dsPIC30F2010 controller. Key Words: High-gain DC–DC converter, non-linear carrier controller, voltage regulation, perturb and observe maximum power point tracking, solar photovoltaic
{"title":"High Gain DC-DC Converter for Photovoltaic System","authors":"P. Thilothama, D. Ashokaraju","doi":"10.55041/ijsrem36526","DOIUrl":"https://doi.org/10.55041/ijsrem36526","url":null,"abstract":"The, high-gain DC–DC converters dragged much attention among the researchers. But there is a concern that high-gain converters have less efficiency and high switching stresses. The converter topology has two quasi-impedance source network and a voltage multiplier cell unit to facilitate very high-gain output voltage. The input variations due to varying irradiation of photovoltaic are alleviated by employing the perturb and observe maximum power point tracking mechanism. The simulation of the work is realized in MATLAB/ Simulink arena, and hardware circuits are validated using the dsPIC30F2010 controller. Key Words: High-gain DC–DC converter, non-linear carrier controller, voltage regulation, perturb and observe maximum power point tracking, solar photovoltaic","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"78 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141818979","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：