Pub Date : 2024-02-12DOI: 10.17485/ijst/v17i6.2703
Suyog C Dharmadhikari, S. S. Jamkar
Objectives: This research is aimed at comparing the performance of two sets of treatments. The first set of treatments tests the performance of heated, abrasioned, and fly ash-treated recycled concrete aggregates (RCA), while the other set of treatments examines the performance of heated, abrasioned, and silica fume-treated aggregates. Though previous research has examined the performance of the standalone treatment methods for enhancing RCA properties, there is a research gap that attempts to study the performance of the combinations of various treatments and their merits. To bridge the gap in the literature, this study compares the combination of two sets of treatment methods to investigate the relative effectiveness of the combination of the treatment methods that can improve RCA properties. Methods: The study was conducted using the concrete mix design procedure outlined in IS 10262-2019 in the laboratory. As part of the experimentation program, a total of 24 sample cubes were casted and tested. Findings: A 14.5% reduction in water absorption was observed for 10mm heated, abrasioned, and fly ash-treated aggregates, whereas a 15.2% reduction in water absorption was observed for 20mm heat-treated, abrasioned, and fly ash-treated aggregates compared to untreated aggregates. Similarly, for heat-treated, abrasioned, and silica fume-treated aggregates, a 41.7% reduction in water absorption was observed for 10mm aggregates, and a 45% reduction was observed for 20mm aggregates over untreated aggregates. A 133% increase in slump value was observed for heated, abrasioned, and fly ash-treated aggregates, whereas a 150% increase in slump value was observed in the case of heated, abrasioned, and silica fume-treated aggregates. Further, a 150 % increase in compressive strength was observed for heated, abrasioned, and fly ash-treated aggregates, and a 165% increase in compressive strength was observed for heated, abrasioned, and silica fume-treated aggregates over untreated aggregates. Novelty: This research addresses the ninth United Nations Sustainability Development Goal, i.e., Industry, Innovation, and Infrastructure, as it promotes the use of eco-friendly construction practices. Moreover, the present research offers a manifold contribution to the state-of-the-art literature on construction management and offers numerous implications for the construction industry. Keywords: Recycled concrete aggregates, Silica fume treatment, Fly ash treatment, Water absorption, Workability, Compressive strength
{"title":"Comparative Analysis of Two Different Combinations of Pretreatment Methods for Treating Recycled Concrete Aggregates","authors":"Suyog C Dharmadhikari, S. S. Jamkar","doi":"10.17485/ijst/v17i6.2703","DOIUrl":"https://doi.org/10.17485/ijst/v17i6.2703","url":null,"abstract":"Objectives: This research is aimed at comparing the performance of two sets of treatments. The first set of treatments tests the performance of heated, abrasioned, and fly ash-treated recycled concrete aggregates (RCA), while the other set of treatments examines the performance of heated, abrasioned, and silica fume-treated aggregates. Though previous research has examined the performance of the standalone treatment methods for enhancing RCA properties, there is a research gap that attempts to study the performance of the combinations of various treatments and their merits. To bridge the gap in the literature, this study compares the combination of two sets of treatment methods to investigate the relative effectiveness of the combination of the treatment methods that can improve RCA properties. Methods: The study was conducted using the concrete mix design procedure outlined in IS 10262-2019 in the laboratory. As part of the experimentation program, a total of 24 sample cubes were casted and tested. Findings: A 14.5% reduction in water absorption was observed for 10mm heated, abrasioned, and fly ash-treated aggregates, whereas a 15.2% reduction in water absorption was observed for 20mm heat-treated, abrasioned, and fly ash-treated aggregates compared to untreated aggregates. Similarly, for heat-treated, abrasioned, and silica fume-treated aggregates, a 41.7% reduction in water absorption was observed for 10mm aggregates, and a 45% reduction was observed for 20mm aggregates over untreated aggregates. A 133% increase in slump value was observed for heated, abrasioned, and fly ash-treated aggregates, whereas a 150% increase in slump value was observed in the case of heated, abrasioned, and silica fume-treated aggregates. Further, a 150 % increase in compressive strength was observed for heated, abrasioned, and fly ash-treated aggregates, and a 165% increase in compressive strength was observed for heated, abrasioned, and silica fume-treated aggregates over untreated aggregates. Novelty: This research addresses the ninth United Nations Sustainability Development Goal, i.e., Industry, Innovation, and Infrastructure, as it promotes the use of eco-friendly construction practices. Moreover, the present research offers a manifold contribution to the state-of-the-art literature on construction management and offers numerous implications for the construction industry. Keywords: Recycled concrete aggregates, Silica fume treatment, Fly ash treatment, Water absorption, Workability, Compressive strength","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139844130","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 : 2024-02-12DOI: 10.17485/ijst/v17i6.2711
C. G. Betsurmath, Hadal Kumaraswamy Mamatha, Saravanabau Chidambaram, Vishwanath Prashant
Objectives: In India, the professional performance of the academic faculty is assessed annually using Academic Performance Indicator (API) as per the University Grants Commission (UGC), Government of India. This is a manual model is cumbersome in filling, and time-consuming. As a planned change and a measure to introduce technology-based platforms in JSS Academy of Higher Education & Research (JSSAHER), Mysuru, India, we have designed, developed, and validated digital platform technology to evaluate the annual performance of faculty working in medical, dental, pharmacy, life sciences fraternities. Methods: Academic Performance Indicator (API) guideline as per the University Grants Commission (UGC), Government of India, was used to design and develop the digital performance-based appraisal system (d-PBAS), and its performance was validated (20% random sampling) by comparing the manual and digital data entered by the faculty from different disciplines of JSSAHER. Findings: The present manuscript demonstrates the designing and validation methodology of d-PBAS. Software Development Life Cycle (SDLC) process and Waterfall model was adopted to develop d-PBAS. The digital platform was assessed for the performance and ranking of the faculty. More than 96% of the users expressed satisfaction and 4% expressed dissatisfaction in d-PBAS. Novelty: For the first of its kind in a university set up in India, JSSAHER designed and validated the digital performance-based appraisal system to evaluate academic performance. Since d-PBAS was developed using the SDLC process and Waterfall model it is easy and consumes less time to enter the data. The most important highlight is d-PBAS helps to rank the faculty performance automatically. The design and validation of d-PBAS described in the present manuscript are simple, robust, cost-effective, and have a go-green value. Keywords: Change Management, Higher Education Institutions, Performancebased, Appraisal System, academic Performance Indicator, digital technology
{"title":"Design, Development and Validation of a Digital Performance Based Appraisal System: A Planned Approach in Change Management","authors":"C. G. Betsurmath, Hadal Kumaraswamy Mamatha, Saravanabau Chidambaram, Vishwanath Prashant","doi":"10.17485/ijst/v17i6.2711","DOIUrl":"https://doi.org/10.17485/ijst/v17i6.2711","url":null,"abstract":"Objectives: In India, the professional performance of the academic faculty is assessed annually using Academic Performance Indicator (API) as per the University Grants Commission (UGC), Government of India. This is a manual model is cumbersome in filling, and time-consuming. As a planned change and a measure to introduce technology-based platforms in JSS Academy of Higher Education & Research (JSSAHER), Mysuru, India, we have designed, developed, and validated digital platform technology to evaluate the annual performance of faculty working in medical, dental, pharmacy, life sciences fraternities. Methods: Academic Performance Indicator (API) guideline as per the University Grants Commission (UGC), Government of India, was used to design and develop the digital performance-based appraisal system (d-PBAS), and its performance was validated (20% random sampling) by comparing the manual and digital data entered by the faculty from different disciplines of JSSAHER. Findings: The present manuscript demonstrates the designing and validation methodology of d-PBAS. Software Development Life Cycle (SDLC) process and Waterfall model was adopted to develop d-PBAS. The digital platform was assessed for the performance and ranking of the faculty. More than 96% of the users expressed satisfaction and 4% expressed dissatisfaction in d-PBAS. Novelty: For the first of its kind in a university set up in India, JSSAHER designed and validated the digital performance-based appraisal system to evaluate academic performance. Since d-PBAS was developed using the SDLC process and Waterfall model it is easy and consumes less time to enter the data. The most important highlight is d-PBAS helps to rank the faculty performance automatically. The design and validation of d-PBAS described in the present manuscript are simple, robust, cost-effective, and have a go-green value. Keywords: Change Management, Higher Education Institutions, Performancebased, Appraisal System, academic Performance Indicator, digital technology","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139844487","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 : 2024-02-12DOI: 10.17485/ijst/v17i6.2928
P. Muthulakshmi, M. Parveen
Objectives: Over the past few years, there prevails an abundance wealth of big data obtained via patients' electronic health records. One of the leading causes of mortality globally is the cardiovascular disease. Based on the present test and history cardiovascular disease diagnosing of patients can be done. Therefore, early and quick diagnosis can reduce the mortality rate. To address their needs, several machine learning methods have been employed in the recent past in cardiovascular disease diagnosis and prediction. Previous research was also concentrated on acquiring the significant features to heart disease prediction however less importance was given to the time involved and error rate to identifying the strength of these features. Methods: In this work we plan to develop a method called, Regularized Principal Component and Quadratic Weighted Entropy Boosting (RPC-QWEB) for predicting heart disease. Initially in RPC-QWEB, relevant features are selected to avoid missing values in the input database by employing Regularized Principal Component Regressive Feature Selection (RPCRFS). Second, with the obtained dimensionality reduced features, Quadratic Weighted Entropy Boosting Classification (QWEBC) process is carried out to classify the patient data as normal or abnormal. The QWEBC process is an ensemble of several weak classifiers (i.e., Quadratic Classifier). The weak classifier results are combined to form strong classifier and provide final prediction results as normal or abnormal condition with minimal error rate. Findings: Experimental evaluation is carried out on factors with the cardiovascular disease dataset such as heart disease prediction accuracy, heart disease prediction time, sensitivity, error rate with respect to distinct numbers of patient data. The proposed RPC-QWEB method was compared with existing Heart Disease Prediction Framework (HDPF) and Swarm Artificial Neural Network (Swarm-ANN). Novelty: RPC-QWEB method outperforms the conventional learning methods in terms of numerous performance matrices. The RPC-QWEB method produces 3% and 5% increase in terms of accuracy and sensitivity and 7% and 29% reduced prediction time and error rate as compared to the existing benchmark methods. We may use this method to predict the heart disease at early stage there by we can reduce the death rate. Keywords: Big data, Regularized Principal Component, Quadratic Weighted Entropy Boosting, Regressive Feature Selection, Classification
{"title":"Big Data Analytics for Heart Disease Prediction using Regularized Principal and Quadratic Entropy Boosting","authors":"P. Muthulakshmi, M. Parveen","doi":"10.17485/ijst/v17i6.2928","DOIUrl":"https://doi.org/10.17485/ijst/v17i6.2928","url":null,"abstract":"Objectives: Over the past few years, there prevails an abundance wealth of big data obtained via patients' electronic health records. One of the leading causes of mortality globally is the cardiovascular disease. Based on the present test and history cardiovascular disease diagnosing of patients can be done. Therefore, early and quick diagnosis can reduce the mortality rate. To address their needs, several machine learning methods have been employed in the recent past in cardiovascular disease diagnosis and prediction. Previous research was also concentrated on acquiring the significant features to heart disease prediction however less importance was given to the time involved and error rate to identifying the strength of these features. Methods: In this work we plan to develop a method called, Regularized Principal Component and Quadratic Weighted Entropy Boosting (RPC-QWEB) for predicting heart disease. Initially in RPC-QWEB, relevant features are selected to avoid missing values in the input database by employing Regularized Principal Component Regressive Feature Selection (RPCRFS). Second, with the obtained dimensionality reduced features, Quadratic Weighted Entropy Boosting Classification (QWEBC) process is carried out to classify the patient data as normal or abnormal. The QWEBC process is an ensemble of several weak classifiers (i.e., Quadratic Classifier). The weak classifier results are combined to form strong classifier and provide final prediction results as normal or abnormal condition with minimal error rate. Findings: Experimental evaluation is carried out on factors with the cardiovascular disease dataset such as heart disease prediction accuracy, heart disease prediction time, sensitivity, error rate with respect to distinct numbers of patient data. The proposed RPC-QWEB method was compared with existing Heart Disease Prediction Framework (HDPF) and Swarm Artificial Neural Network (Swarm-ANN). Novelty: RPC-QWEB method outperforms the conventional learning methods in terms of numerous performance matrices. The RPC-QWEB method produces 3% and 5% increase in terms of accuracy and sensitivity and 7% and 29% reduced prediction time and error rate as compared to the existing benchmark methods. We may use this method to predict the heart disease at early stage there by we can reduce the death rate. Keywords: Big data, Regularized Principal Component, Quadratic Weighted Entropy Boosting, Regressive Feature Selection, Classification","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139844680","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 : 2024-02-12DOI: 10.17485/ijst/v17i6.2703
Suyog C Dharmadhikari, S. S. Jamkar
Objectives: This research is aimed at comparing the performance of two sets of treatments. The first set of treatments tests the performance of heated, abrasioned, and fly ash-treated recycled concrete aggregates (RCA), while the other set of treatments examines the performance of heated, abrasioned, and silica fume-treated aggregates. Though previous research has examined the performance of the standalone treatment methods for enhancing RCA properties, there is a research gap that attempts to study the performance of the combinations of various treatments and their merits. To bridge the gap in the literature, this study compares the combination of two sets of treatment methods to investigate the relative effectiveness of the combination of the treatment methods that can improve RCA properties. Methods: The study was conducted using the concrete mix design procedure outlined in IS 10262-2019 in the laboratory. As part of the experimentation program, a total of 24 sample cubes were casted and tested. Findings: A 14.5% reduction in water absorption was observed for 10mm heated, abrasioned, and fly ash-treated aggregates, whereas a 15.2% reduction in water absorption was observed for 20mm heat-treated, abrasioned, and fly ash-treated aggregates compared to untreated aggregates. Similarly, for heat-treated, abrasioned, and silica fume-treated aggregates, a 41.7% reduction in water absorption was observed for 10mm aggregates, and a 45% reduction was observed for 20mm aggregates over untreated aggregates. A 133% increase in slump value was observed for heated, abrasioned, and fly ash-treated aggregates, whereas a 150% increase in slump value was observed in the case of heated, abrasioned, and silica fume-treated aggregates. Further, a 150 % increase in compressive strength was observed for heated, abrasioned, and fly ash-treated aggregates, and a 165% increase in compressive strength was observed for heated, abrasioned, and silica fume-treated aggregates over untreated aggregates. Novelty: This research addresses the ninth United Nations Sustainability Development Goal, i.e., Industry, Innovation, and Infrastructure, as it promotes the use of eco-friendly construction practices. Moreover, the present research offers a manifold contribution to the state-of-the-art literature on construction management and offers numerous implications for the construction industry. Keywords: Recycled concrete aggregates, Silica fume treatment, Fly ash treatment, Water absorption, Workability, Compressive strength
{"title":"Comparative Analysis of Two Different Combinations of Pretreatment Methods for Treating Recycled Concrete Aggregates","authors":"Suyog C Dharmadhikari, S. S. Jamkar","doi":"10.17485/ijst/v17i6.2703","DOIUrl":"https://doi.org/10.17485/ijst/v17i6.2703","url":null,"abstract":"Objectives: This research is aimed at comparing the performance of two sets of treatments. The first set of treatments tests the performance of heated, abrasioned, and fly ash-treated recycled concrete aggregates (RCA), while the other set of treatments examines the performance of heated, abrasioned, and silica fume-treated aggregates. Though previous research has examined the performance of the standalone treatment methods for enhancing RCA properties, there is a research gap that attempts to study the performance of the combinations of various treatments and their merits. To bridge the gap in the literature, this study compares the combination of two sets of treatment methods to investigate the relative effectiveness of the combination of the treatment methods that can improve RCA properties. Methods: The study was conducted using the concrete mix design procedure outlined in IS 10262-2019 in the laboratory. As part of the experimentation program, a total of 24 sample cubes were casted and tested. Findings: A 14.5% reduction in water absorption was observed for 10mm heated, abrasioned, and fly ash-treated aggregates, whereas a 15.2% reduction in water absorption was observed for 20mm heat-treated, abrasioned, and fly ash-treated aggregates compared to untreated aggregates. Similarly, for heat-treated, abrasioned, and silica fume-treated aggregates, a 41.7% reduction in water absorption was observed for 10mm aggregates, and a 45% reduction was observed for 20mm aggregates over untreated aggregates. A 133% increase in slump value was observed for heated, abrasioned, and fly ash-treated aggregates, whereas a 150% increase in slump value was observed in the case of heated, abrasioned, and silica fume-treated aggregates. Further, a 150 % increase in compressive strength was observed for heated, abrasioned, and fly ash-treated aggregates, and a 165% increase in compressive strength was observed for heated, abrasioned, and silica fume-treated aggregates over untreated aggregates. Novelty: This research addresses the ninth United Nations Sustainability Development Goal, i.e., Industry, Innovation, and Infrastructure, as it promotes the use of eco-friendly construction practices. Moreover, the present research offers a manifold contribution to the state-of-the-art literature on construction management and offers numerous implications for the construction industry. Keywords: Recycled concrete aggregates, Silica fume treatment, Fly ash treatment, Water absorption, Workability, Compressive strength","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139784370","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 : 2024-01-31DOI: 10.17485/ijst/v17i5.1174
Kirti Makwana
Objectives: To present a textual data analysis of the Union Budgets of India for financial years 2019-20 to 2023-24). Examining the policy narratives, key announcements, and thematic emphasis in Budget speeches to explore about the government's priorities. Methods : The analysis is centered on the budget presented by Nirmala Sitharaman, the Finance Minister of India. The study emphases on the budget speeches conveyed by her and serves a combination of quantitative and qualitative techniques to classify the main themes and primacy of the budget. To categorize the discourse into diverse subjects, Natural Language Processing (NLP), Topic Modeling and Sentiment Analysis methods are used. Findings: The outcomes recommend that the budget emphases on encouraging commercial growth, improving living standard, and providing liberation to many sectors affected by the COVID-19 pandemic. “India”, “Government”, “Infrastructure”, “Sector” etc. are some of the words which are used repeatedly in each budget presented. Further high value of Term Frequency-Inverse Document Frequency (TF-IDF) suggests that India (0.323), Government (0.315), Tax (0.268), Crores (0.380) are some of the words which are the most important and relevant words during Budget presentations. Correlation matrix suggests that topic 1 is highly negatively correlated with topic 2 (coefficient value – (-0.832)). The paper concludes by deliberating the repercussions of the budget on the Indian economy and the challenges that are to be addressed to attain the budget's intents. Novelty : Largely, the research paper delivers an all-inclusive understanding of the Indian Union Budget and its possible influence on the country's economic and social development. Keywords: Textual Data Analysis, Union Budget, Nirmala Sitharaman, Bag of Words, Sentiment Analysis, TF-IDF
{"title":"A Textual Data Analysis of the Union Budget of India","authors":"Kirti Makwana","doi":"10.17485/ijst/v17i5.1174","DOIUrl":"https://doi.org/10.17485/ijst/v17i5.1174","url":null,"abstract":"Objectives: To present a textual data analysis of the Union Budgets of India for financial years 2019-20 to 2023-24). Examining the policy narratives, key announcements, and thematic emphasis in Budget speeches to explore about the government's priorities. Methods : The analysis is centered on the budget presented by Nirmala Sitharaman, the Finance Minister of India. The study emphases on the budget speeches conveyed by her and serves a combination of quantitative and qualitative techniques to classify the main themes and primacy of the budget. To categorize the discourse into diverse subjects, Natural Language Processing (NLP), Topic Modeling and Sentiment Analysis methods are used. Findings: The outcomes recommend that the budget emphases on encouraging commercial growth, improving living standard, and providing liberation to many sectors affected by the COVID-19 pandemic. “India”, “Government”, “Infrastructure”, “Sector” etc. are some of the words which are used repeatedly in each budget presented. Further high value of Term Frequency-Inverse Document Frequency (TF-IDF) suggests that India (0.323), Government (0.315), Tax (0.268), Crores (0.380) are some of the words which are the most important and relevant words during Budget presentations. Correlation matrix suggests that topic 1 is highly negatively correlated with topic 2 (coefficient value – (-0.832)). The paper concludes by deliberating the repercussions of the budget on the Indian economy and the challenges that are to be addressed to attain the budget's intents. Novelty : Largely, the research paper delivers an all-inclusive understanding of the Indian Union Budget and its possible influence on the country's economic and social development. Keywords: Textual Data Analysis, Union Budget, Nirmala Sitharaman, Bag of Words, Sentiment Analysis, TF-IDF","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140479552","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 : 2024-01-31DOI: 10.17485/ijst/v17i5.1663
Vandana N Mahajan, M. J. Sable, S. P. Shekhawat, Suhas R Patil
Objectives: To determine the best combination of blends of TiO2 /ZnO coated on SUS for obtaining a minimum corrosion rate. Methods: Different TiO2 /ZnO thin film blends are coated on SUS 304 substrates. The sol-gel dip-coating process is used for coating application. Also, withdrawal rates, calcination temperature, and doping percentage are the parameters used for the study of the anti-corrosion property. L9 array, using the Taguchi method, is applied for the design of the experiment. P.G-Lyte 1.0 model was used for the anticorrosion test. The Potentiosatic polarization method was applied for anti-corrosion testing. Findings: The results show that the percentage of ZnO doping (60%, 40%, and 20%) is the most significant factor in controlling the corrosion of the sample with plate number 1. The withdrawal rate (0.5 mm/sec, 1 mm/sec, and 1.5 mm/sec) has a minimal impact on the corrosion rate of the coated sample. The calcination temperature (300◦C, 400◦C, and 500◦C) has a greater impact than the withdrawal rate. There is a good agreement between the predicted and actual corrosion current. Novelty: Investigation of mechanical properties like corrosion resistance is essential for increasing the durability of automobile components by applying a coating of blends of TiO2 and ZnO with a rare blending combination that was not applied before for the investigation. In this research, efforts are made to reduce the corrosion rate by applying different blends of TiO2 and ZnO. Also, withdrawal rate and calcination temperature are varied in the process which was also not considered in the earlier studies. Keywords: Taguchi method; Corrosion current; Signal to Noise ratio; Coating; Design of experiments
{"title":"Optimization of Corrosion Behaviour of Blended TiO2 /ZnO Coating on SUS 304 using Taguchi Method","authors":"Vandana N Mahajan, M. J. Sable, S. P. Shekhawat, Suhas R Patil","doi":"10.17485/ijst/v17i5.1663","DOIUrl":"https://doi.org/10.17485/ijst/v17i5.1663","url":null,"abstract":"Objectives: To determine the best combination of blends of TiO2 /ZnO coated on SUS for obtaining a minimum corrosion rate. Methods: Different TiO2 /ZnO thin film blends are coated on SUS 304 substrates. The sol-gel dip-coating process is used for coating application. Also, withdrawal rates, calcination temperature, and doping percentage are the parameters used for the study of the anti-corrosion property. L9 array, using the Taguchi method, is applied for the design of the experiment. P.G-Lyte 1.0 model was used for the anticorrosion test. The Potentiosatic polarization method was applied for anti-corrosion testing. Findings: The results show that the percentage of ZnO doping (60%, 40%, and 20%) is the most significant factor in controlling the corrosion of the sample with plate number 1. The withdrawal rate (0.5 mm/sec, 1 mm/sec, and 1.5 mm/sec) has a minimal impact on the corrosion rate of the coated sample. The calcination temperature (300◦C, 400◦C, and 500◦C) has a greater impact than the withdrawal rate. There is a good agreement between the predicted and actual corrosion current. Novelty: Investigation of mechanical properties like corrosion resistance is essential for increasing the durability of automobile components by applying a coating of blends of TiO2 and ZnO with a rare blending combination that was not applied before for the investigation. In this research, efforts are made to reduce the corrosion rate by applying different blends of TiO2 and ZnO. Also, withdrawal rate and calcination temperature are varied in the process which was also not considered in the earlier studies. Keywords: Taguchi method; Corrosion current; Signal to Noise ratio; Coating; Design of experiments","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140475669","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}
A. Pal, Poulami Chakraborty, Radhika Jitesh Gandhi
Objectives: To demonstrate the nutritional and functional characteristics of the developed phytochemical containing prebiotic-enriched chocolates. Methods: Methods of Association of Official Analytical Chemists and standard biochemical procedures were employed for the determination of nutrient and phytochemical composition. Antioxidant and prebiotic activity were calculated through DPPH, the reducing potential assay, as well as the growth kinetics and plate count of Lactobacillus rhamnosus GG, respectively (p ≤ 0.01, 95% confidence interval). The functionality of the products was also analyzed in an in vitro simulated human intestinal digestion environment. Findings: Variation 3 (V3) chocolates prepared through the incorporation of cocoa powder (64%), cocoa butter (22.5%), stevia (3%), inulin (10%), and soy lecithin (0.5%), scored the highest sensory rating amongst all the prepared products. V3 revealed a desired proportion of proximate components (low fat and high fibre), minerals, vitamins, and phytochemicals such as polyphenol (25mg/g), alkaloids (189 mg/mL), and flavonoids (46mg/g), versus the standard chocolate (S), along with a low calorific value of the former (541.2Kcal). Furthermore, V3 could efficiently scavenge 2, 2-diphenyl-1-picryl-hydrazyl (86.04±0.4%), display reducing power (2.84±0.02), and accelerate the growth of probiotic Lactobacillus rhamnosus GG (OD 0.59, 11.61 Log CFU/mL at 20 hours), portraying antioxidant and prebiotic properties. Interestingly, V3 was found to sustain a significant proportion of antioxidant and prebiotic potential under imitated intestinal digestion, indicating their effectiveness in propagating benefits in the human body post-consumption. Novelty: Considerable retention of the antioxidant and prebiotic effects post intestinal digestion, besides the nutritional and phytochemical constitution of V3, may promote well-being consequent to its adaption alternative to conventional chocolates. Keywords: Antioxidant, Chocolate, Nutrients, Phytochemicals, Prebiotic
{"title":"Nutritional and Functional Properties of Prebiotic Enriched Chocolates","authors":"A. Pal, Poulami Chakraborty, Radhika Jitesh Gandhi","doi":"10.17485/ijst/v17i5.522","DOIUrl":"https://doi.org/10.17485/ijst/v17i5.522","url":null,"abstract":"Objectives: To demonstrate the nutritional and functional characteristics of the developed phytochemical containing prebiotic-enriched chocolates. Methods: Methods of Association of Official Analytical Chemists and standard biochemical procedures were employed for the determination of nutrient and phytochemical composition. Antioxidant and prebiotic activity were calculated through DPPH, the reducing potential assay, as well as the growth kinetics and plate count of Lactobacillus rhamnosus GG, respectively (p ≤ 0.01, 95% confidence interval). The functionality of the products was also analyzed in an in vitro simulated human intestinal digestion environment. Findings: Variation 3 (V3) chocolates prepared through the incorporation of cocoa powder (64%), cocoa butter (22.5%), stevia (3%), inulin (10%), and soy lecithin (0.5%), scored the highest sensory rating amongst all the prepared products. V3 revealed a desired proportion of proximate components (low fat and high fibre), minerals, vitamins, and phytochemicals such as polyphenol (25mg/g), alkaloids (189 mg/mL), and flavonoids (46mg/g), versus the standard chocolate (S), along with a low calorific value of the former (541.2Kcal). Furthermore, V3 could efficiently scavenge 2, 2-diphenyl-1-picryl-hydrazyl (86.04±0.4%), display reducing power (2.84±0.02), and accelerate the growth of probiotic Lactobacillus rhamnosus GG (OD 0.59, 11.61 Log CFU/mL at 20 hours), portraying antioxidant and prebiotic properties. Interestingly, V3 was found to sustain a significant proportion of antioxidant and prebiotic potential under imitated intestinal digestion, indicating their effectiveness in propagating benefits in the human body post-consumption. Novelty: Considerable retention of the antioxidant and prebiotic effects post intestinal digestion, besides the nutritional and phytochemical constitution of V3, may promote well-being consequent to its adaption alternative to conventional chocolates. Keywords: Antioxidant, Chocolate, Nutrients, Phytochemicals, Prebiotic","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140477628","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 : 2024-01-31DOI: 10.17485/ijst/v17i5.1645
S. Subha, J. Sathiaseelan
Objectives: This study addresses the concept drift issue in anomaly detection for IoT systems. The objective is to develop a novel approach that effectively handles the dynamic nature of IoT data. Methods: The proposed COMCADSET (Combination of One-Class and Multi-Class Anomaly Detection Using Under-Sampling and Ensemble Technique) addresses the concept drift challenge. It adapts to evolving data distributions, detects anomalies in IoT healthcare data, mitigates class distribution imbalances through under-sampling, and enhances performance with ensemble techniques. The approach involves four phases: multi-class anomaly spotting, one-class anomaly isolation, concept-drift-free dataset creation, and robust anomaly detection using ensembles. Evaluation utilizes the "Heart Failure Prediction" dataset from Kaggle, with comprehensive experiments and three classification algorithms. COMCADSET's innovation merges one-class and multi-class anomaly detection, under-sampling, and ensemble classification. It's compared against gold standards for classification accuracy, concept drift management, and anomaly detection performance. Findings: Conduct comprehensive experiments using a concept drift dataset and three classification algorithms to evaluate the efficacy of the COMCADSET technique. The experimental result shows the proposed COMCADSET technique attains an impressive 98.401% accuracy, decisively enhancing classification accuracy by adeptly addressing concept drift and identifying anomalies in IoT data. Early detection of abnormal behaviour prevents more significant issues and potential security vulnerabilities in IoT systems. Novelty: The novelty of the COMCADSET technique lies in its ability to address the concept drift issue and improve anomaly detection accuracy in IoT systems. By integrating one-class and multi-class anomaly detection, under-sampling, and ensemble techniques, the proposed approach provides a robust solution for handling the dynamic nature of IoT data. Keywords: Anomaly Detection, Concept Drift, Ensemble Classification, Internet of Things, UnderSampling
{"title":"Combination of One-Class and Multi-Class Anomaly Detection Using Under-Sampling and Ensemble Technique in IoT Healthcare Data","authors":"S. Subha, J. Sathiaseelan","doi":"10.17485/ijst/v17i5.1645","DOIUrl":"https://doi.org/10.17485/ijst/v17i5.1645","url":null,"abstract":"Objectives: This study addresses the concept drift issue in anomaly detection for IoT systems. The objective is to develop a novel approach that effectively handles the dynamic nature of IoT data. Methods: The proposed COMCADSET (Combination of One-Class and Multi-Class Anomaly Detection Using Under-Sampling and Ensemble Technique) addresses the concept drift challenge. It adapts to evolving data distributions, detects anomalies in IoT healthcare data, mitigates class distribution imbalances through under-sampling, and enhances performance with ensemble techniques. The approach involves four phases: multi-class anomaly spotting, one-class anomaly isolation, concept-drift-free dataset creation, and robust anomaly detection using ensembles. Evaluation utilizes the \"Heart Failure Prediction\" dataset from Kaggle, with comprehensive experiments and three classification algorithms. COMCADSET's innovation merges one-class and multi-class anomaly detection, under-sampling, and ensemble classification. It's compared against gold standards for classification accuracy, concept drift management, and anomaly detection performance. Findings: Conduct comprehensive experiments using a concept drift dataset and three classification algorithms to evaluate the efficacy of the COMCADSET technique. The experimental result shows the proposed COMCADSET technique attains an impressive 98.401% accuracy, decisively enhancing classification accuracy by adeptly addressing concept drift and identifying anomalies in IoT data. Early detection of abnormal behaviour prevents more significant issues and potential security vulnerabilities in IoT systems. Novelty: The novelty of the COMCADSET technique lies in its ability to address the concept drift issue and improve anomaly detection accuracy in IoT systems. By integrating one-class and multi-class anomaly detection, under-sampling, and ensemble techniques, the proposed approach provides a robust solution for handling the dynamic nature of IoT data. Keywords: Anomaly Detection, Concept Drift, Ensemble Classification, Internet of Things, UnderSampling","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140478961","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 : 2024-01-31DOI: 10.17485/ijst/v17i5.2866
Ameer Ali Hassan, Haider F. Hasheem, Mohsin F AL-Ruwashdi
Objectives: Study and find the absorption and fluorescence parameters for the Ho: YAP laser crystal, such as branching ratios, intensity parameters, oscillation strength, fluorescence line strength, absorption line strength, the spontaneous emission factor, the time life of the upper irritated level, the emission cross-section, and the absorption cross-section and prove that this laser is Ho: YAP laser. Method: Absorption and fluorescence parameters are calculated by employing the equations of the Judd-Oflet model and using the absorption coefficient to calculate the area under the curve. Findings: The properties of the compelling medium were calculated theoretically using the Judd-Oflet Model. These include branching ratios β2 = 0.27, β3 = 0.72, intensity parameters Ω2=1.41*10-20 cm2 Ω4=2.91*10-20 cm2, Ω6= 1.72*10-20 cm2, oscillation strength 1.48*10-6, fluorescence line strength Sf1 =0, Sf2 = 3.24*10-23, Sf3 = 4.9*10-23, absorption line strength 3.2439*10-23, the spontaneous emission factor 167 s-1, and the time life of the upper irritated level 5.99 ms, the emission cross-2.239*10-18 cm2, the absorption cross-section 0.92*10-20 cm2, these values are evidence that the active medium to be studied is Ho: YAP. Also, the ratio of the probability of spontaneous emission to stimulated emission was calculated, which is much less than one, which indicates that the laser system operates in this medium, and a laser is emitted through it. Novelty: In this article, we succeeded in using a mathematical model to calculate the properties of absorption and fluorescence, which are of great importance in laser work, instead of experimental work that could expose the crystal to damage and also require money, effort, and time. Keywords: Judd-Oflet Model, Ho: YAP laser, Absorption Parameters, Fluorescence Parameters, absorption coefficient, intensity parameters
{"title":"Studying the Absorption and Fluorescence Parameters of Ho: YAP Laser Using the Judd-Oflet Model","authors":"Ameer Ali Hassan, Haider F. Hasheem, Mohsin F AL-Ruwashdi","doi":"10.17485/ijst/v17i5.2866","DOIUrl":"https://doi.org/10.17485/ijst/v17i5.2866","url":null,"abstract":"Objectives: Study and find the absorption and fluorescence parameters for the Ho: YAP laser crystal, such as branching ratios, intensity parameters, oscillation strength, fluorescence line strength, absorption line strength, the spontaneous emission factor, the time life of the upper irritated level, the emission cross-section, and the absorption cross-section and prove that this laser is Ho: YAP laser. Method: Absorption and fluorescence parameters are calculated by employing the equations of the Judd-Oflet model and using the absorption coefficient to calculate the area under the curve. Findings: The properties of the compelling medium were calculated theoretically using the Judd-Oflet Model. These include branching ratios β2 = 0.27, β3 = 0.72, intensity parameters Ω2=1.41*10-20 cm2 Ω4=2.91*10-20 cm2, Ω6= 1.72*10-20 cm2, oscillation strength 1.48*10-6, fluorescence line strength Sf1 =0, Sf2 = 3.24*10-23, Sf3 = 4.9*10-23, absorption line strength 3.2439*10-23, the spontaneous emission factor 167 s-1, and the time life of the upper irritated level 5.99 ms, the emission cross-2.239*10-18 cm2, the absorption cross-section 0.92*10-20 cm2, these values are evidence that the active medium to be studied is Ho: YAP. Also, the ratio of the probability of spontaneous emission to stimulated emission was calculated, which is much less than one, which indicates that the laser system operates in this medium, and a laser is emitted through it. Novelty: In this article, we succeeded in using a mathematical model to calculate the properties of absorption and fluorescence, which are of great importance in laser work, instead of experimental work that could expose the crystal to damage and also require money, effort, and time. Keywords: Judd-Oflet Model, Ho: YAP laser, Absorption Parameters, Fluorescence Parameters, absorption coefficient, intensity parameters","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140474635","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 : 2024-01-31DOI: 10.17485/ijst/v17i5.2627
P. K. Shashidhar, T. C. Thanuja, Rajashekar Kunabeva
Objectives: The main objectives of this research endeavor encompass the development of the Adaptive RPL Optimization (ARPLO) model to enhance data transmission efficiency within IoT networks. This includes constructing a grid-based network structure optimized for data transfer, selecting the most suitable nodes as grid head nodes to maximize network lifespan while minimizing energy consumption, implementing an innovative objective function-driven approach to optimize parent node selection, and integrating an Adaptive Deep Neural Network (ADNN) to accurately classify medical data. Methods: The research methodology entails several key steps. A grid-based network structure is established with IoT nodes and root nodes, where a DODAG process incorporating DIO messages is utilized for node ranking. To enhance energy efficiency, the Trickle algorithm is employed for control message optimization. Grid head nodes are chosen based on metrics such as root node fairness, residual energy, and load influence index. The novel Middle Order Optimal Routing (MOOR) objective function is utilized to optimize routing decisions. ADNN is implemented for precise medical data classification. The proposed model's performance is evaluated through simulation in a Python environment. Findings: The research findings demonstrate that the ARPLO model yields notable benefits compared to existing models. It achieves higher energy efficiency, improved throughput, enhanced packet delivery ratio (PDR), and an extended network lifespan. The Trickle algorithm contributes to efficient control message optimization. The MOOR-based routing approach improves multimedia medical data transfer. Moreover, the integration of ADNN enhances the accuracy of data classification, particularly in healthcare applications. The research outcomes align with the broader field's existing values and reports while offering novel insights that contribute to enhancing the existing knowledge base. ARPLO protocol performance reveals that there is increase of throughput of 31.2%, PDR by 7.12%, lifetime of 10.7 % with reduction of energy consumption by 12.72%, control overhead by 31.01% and end-to-end delay by 33.01%. Novelty: The novelty of this research lies in its comprehensive approach that integrates a grid-based network structure, MOOR-based optimization, and ADNN-based classification. The incorporation of the Trickle algorithm for energy-efficient communication is an innovative feature. The introduction of new metrics for grid head node selection, along with the application of the MOOR objective function for multimedia medical data routing, showcases the research's innovative contributions. Keywords: Internet of Things (IoT), RPL (Routing Protocol for LowPower and Lossy Networks), Optimization, Routing, Multimedia, Healthcare
{"title":"Adaptive RPL Routing Optimization Model for Multimedia Data Transmission using IOT","authors":"P. K. Shashidhar, T. C. Thanuja, Rajashekar Kunabeva","doi":"10.17485/ijst/v17i5.2627","DOIUrl":"https://doi.org/10.17485/ijst/v17i5.2627","url":null,"abstract":"Objectives: The main objectives of this research endeavor encompass the development of the Adaptive RPL Optimization (ARPLO) model to enhance data transmission efficiency within IoT networks. This includes constructing a grid-based network structure optimized for data transfer, selecting the most suitable nodes as grid head nodes to maximize network lifespan while minimizing energy consumption, implementing an innovative objective function-driven approach to optimize parent node selection, and integrating an Adaptive Deep Neural Network (ADNN) to accurately classify medical data. Methods: The research methodology entails several key steps. A grid-based network structure is established with IoT nodes and root nodes, where a DODAG process incorporating DIO messages is utilized for node ranking. To enhance energy efficiency, the Trickle algorithm is employed for control message optimization. Grid head nodes are chosen based on metrics such as root node fairness, residual energy, and load influence index. The novel Middle Order Optimal Routing (MOOR) objective function is utilized to optimize routing decisions. ADNN is implemented for precise medical data classification. The proposed model's performance is evaluated through simulation in a Python environment. Findings: The research findings demonstrate that the ARPLO model yields notable benefits compared to existing models. It achieves higher energy efficiency, improved throughput, enhanced packet delivery ratio (PDR), and an extended network lifespan. The Trickle algorithm contributes to efficient control message optimization. The MOOR-based routing approach improves multimedia medical data transfer. Moreover, the integration of ADNN enhances the accuracy of data classification, particularly in healthcare applications. The research outcomes align with the broader field's existing values and reports while offering novel insights that contribute to enhancing the existing knowledge base. ARPLO protocol performance reveals that there is increase of throughput of 31.2%, PDR by 7.12%, lifetime of 10.7 % with reduction of energy consumption by 12.72%, control overhead by 31.01% and end-to-end delay by 33.01%. Novelty: The novelty of this research lies in its comprehensive approach that integrates a grid-based network structure, MOOR-based optimization, and ADNN-based classification. The incorporation of the Trickle algorithm for energy-efficient communication is an innovative feature. The introduction of new metrics for grid head node selection, along with the application of the MOOR objective function for multimedia medical data routing, showcases the research's innovative contributions. Keywords: Internet of Things (IoT), RPL (Routing Protocol for LowPower and Lossy Networks), Optimization, Routing, Multimedia, Healthcare","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140480106","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：