Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63711
Sunil Kumar Sagar
Abstract: The seismic assessment prepare comprises of exploring in case the structure meets the defined target structural performance levels. The main goal during earthquakes is to assure to people is minimized and beyond that to satisfy postearthquake performance level for defined range of seismic hazards. Rehabilitation prepares points to progress seismic execution and adjust the lacks by increasing quality, firmness or distortion capacity and making strides associations. Hence, a proposed retrofit execution can be said to be fruitful in the event that it comes about an increment in strength and ductility capacity of the structure which is more noteworthy than the requests forced by earthquakes. Seismic force, predominantly being an inertia force depends on the mass of the structure. As the mass of the structure increases the seismic forces also increase causing the requirement of even heavier sections to counter that heavy forces. And these heavy sections further increase the mass of the structure leading to even heavier seismic forces. Structural designers are met with huge challenge to balance these contradictory physical phenomena to make the structure safe. The structure no more can afford to be rigid. This introduces the concept of ductility. The structures are made ductile, allowing it yield in order to dissipate the seismic forces. A framed structure can be easily made ductile by properly detailing of the reinforcement. But again, as the building height goes beyond a certain limit, these framed structure sections (columns) get larger and larger to the extent that they are no more practically feasible in a structure. There comes the role of shear walls. Shear walls provide ample amount of stiffness to the building frame resisting loads through in plane bending. But they inherently make the structure stiffer. So, there must be a balance between the amount of shear walls and frame elements present in a structure for safe and economic design of high-rise structures
{"title":"Seismic Upgradation of Building Using Shear Wall and Bracing","authors":"Sunil Kumar Sagar","doi":"10.22214/ijraset.2024.63711","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63711","url":null,"abstract":"Abstract: The seismic assessment prepare comprises of exploring in case the structure meets the defined target structural performance levels. The main goal during earthquakes is to assure to people is minimized and beyond that to satisfy postearthquake performance level for defined range of seismic hazards. Rehabilitation prepares points to progress seismic execution and adjust the lacks by increasing quality, firmness or distortion capacity and making strides associations. Hence, a proposed retrofit execution can be said to be fruitful in the event that it comes about an increment in strength and ductility capacity of the structure which is more noteworthy than the requests forced by earthquakes. Seismic force, predominantly being an inertia force depends on the mass of the structure. As the mass of the structure increases the seismic forces also increase causing the requirement of even heavier sections to counter that heavy forces. And these heavy sections further increase the mass of the structure leading to even heavier seismic forces. Structural designers are met with huge challenge to balance these contradictory physical phenomena to make the structure safe. The structure no more can afford to be rigid. This introduces the concept of ductility. The structures are made ductile, allowing it yield in order to dissipate the seismic forces. A framed structure can be easily made ductile by properly detailing of the reinforcement. But again, as the building height goes beyond a certain limit, these framed structure sections (columns) get larger and larger to the extent that they are no more practically feasible in a structure. There comes the role of shear walls. Shear walls provide ample amount of stiffness to the building frame resisting loads through in plane bending. But they inherently make the structure stiffer. So, there must be a balance between the amount of shear walls and frame elements present in a structure for safe and economic design of high-rise structures","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"54 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795105","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63667
Bhavika C. Donga, Piyush D. Pitroda, Dr. Hasmukh B. Domadiya, D. H. Domadiya
Abstract: In the current scenario of the 4th Industrial Revolution (4IR or Industry 4.0), the digital world is a full of data, such as Internet of Things (IoT) data, business data, mobile data, cyber security data, social media data, etc. To intelligently analyze these data and develop the corresponding smart and automated applications, the knowledge of artificial intelligence (AI), particularly, machine learning (ML) is the key. Supervised, unsupervised, semi-supervised and reinforcement learning are the different types of machine learning algorithms. In addition to the deep learning is part of a broader family of machine learning methods that can wisely analyze the data on a large scale. This study's primary contribution is its explanation of the fundamentals of numerous machine learning techniques and how they can be applied in a wide range of real-world application areas, including e-commerce, cyber security systems, smart cities, healthcare, and agriculture, among many others. The main use of machine learning is to show off its potential for generating consistently accurate estimations. This review paper's primary objective is to give an overview of machine learning and provide machine learning approaches
{"title":"Decoding the Future: A Comprehensive Review of Machine Learning Innovations and Applications","authors":"Bhavika C. Donga, Piyush D. Pitroda, Dr. Hasmukh B. Domadiya, D. H. Domadiya","doi":"10.22214/ijraset.2024.63667","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63667","url":null,"abstract":"Abstract: In the current scenario of the 4th Industrial Revolution (4IR or Industry 4.0), the digital world is a full of data, such as Internet of Things (IoT) data, business data, mobile data, cyber security data, social media data, etc. To intelligently analyze these data and develop the corresponding smart and automated applications, the knowledge of artificial intelligence (AI), particularly, machine learning (ML) is the key. Supervised, unsupervised, semi-supervised and reinforcement learning are the different types of machine learning algorithms. In addition to the deep learning is part of a broader family of machine learning methods that can wisely analyze the data on a large scale. This study's primary contribution is its explanation of the fundamentals of numerous machine learning techniques and how they can be applied in a wide range of real-world application areas, including e-commerce, cyber security systems, smart cities, healthcare, and agriculture, among many others. The main use of machine learning is to show off its potential for generating consistently accurate estimations. This review paper's primary objective is to give an overview of machine learning and provide machine learning approaches","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"43 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795157","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63597
Madhav Gupta
Abstract: This research paper explores the advantages and applications of scrap flow simulation in sheet metal dies manufacturing processes. Scrap flow simulation provides valuable insights into material utilization, die design optimization, and overall efficiency in sheet metal forming operations. The study investigates the impact of scrap flow simulation on reducing waste, improving tool life, and enhancing the quality of sheet metal components, ultimately contributing to the advancement of manufacturing processes.
{"title":"Sheet Flow Simulation for Sheet Metal Die Optimization Using Simcenter 3D Software","authors":"Madhav Gupta","doi":"10.22214/ijraset.2024.63597","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63597","url":null,"abstract":"Abstract: This research paper explores the advantages and applications of scrap flow simulation in sheet metal dies manufacturing processes. Scrap flow simulation provides valuable insights into material utilization, die design optimization, and overall efficiency in sheet metal forming operations. The study investigates the impact of scrap flow simulation on reducing waste, improving tool life, and enhancing the quality of sheet metal components, ultimately contributing to the advancement of manufacturing processes.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"24 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795235","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63672
Riju Kumari, Gautam Kumar
Abstract: The seismic analysis of buildings is crucial for ensuring structural safety and resilience against earthquake forces. Irregularities in building configurations pose unique challenges, influencing the distribution of seismic forces throughout the structure. This study focuses on the seismic analysis of a G+12 building characterized by irregularities in plan and elevation using STAAD.Pro software. Here we have taken four models consisting of bare bay frame , bay frame with shear wall on one corner, , bay frame with shear wall on two opposite corners, , bay frame with shear wall on all corners for the further analysis. This research contributes to enhancing understanding and design practices for irregular high-rise buildings, emphasizing the importance of advanced analytical tools in seismic engineering. From this analysis we can conclude that within all four models ,building having shear wall on all four sides shows minimal deflection attributed to its maximum stiffness characteristics, hence considered most stable
{"title":"Seismic Analysis of Irregular Multistorey Building","authors":"Riju Kumari, Gautam Kumar","doi":"10.22214/ijraset.2024.63672","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63672","url":null,"abstract":"Abstract: The seismic analysis of buildings is crucial for ensuring structural safety and resilience against earthquake forces. Irregularities in building configurations pose unique challenges, influencing the distribution of seismic forces throughout the structure. This study focuses on the seismic analysis of a G+12 building characterized by irregularities in plan and elevation using STAAD.Pro software. Here we have taken four models consisting of bare bay frame , bay frame with shear wall on one corner, , bay frame with shear wall on two opposite corners, , bay frame with shear wall on all corners for the further analysis. This research contributes to enhancing understanding and design practices for irregular high-rise buildings, emphasizing the importance of advanced analytical tools in seismic engineering. From this analysis we can conclude that within all four models ,building having shear wall on all four sides shows minimal deflection attributed to its maximum stiffness characteristics, hence considered most stable","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"16 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795256","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63622
Patil Rutuja Avinash
{"title":"Comparative Analysis of CROYOGENIC and MQL Machining of EN-19 Steel","authors":"Patil Rutuja Avinash","doi":"10.22214/ijraset.2024.63622","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63622","url":null,"abstract":"","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"50 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795277","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63554
Aditi Chavan
Abstract: The integration of data science and machine learning is revolutionizing the assessment of pesticide impact in organic vegetable farming. This review explores methodologies, applications, and research examples showcasing the transformative potential of data-driven approaches. Remote sensing, including satellite imagery and drones, is essential for monitoring crop health and detecting pesticide impacts on vegetable crops like tomatoes, lettuce, and red peppers. By synthesizing research and trends, the review underscores technology's significance in informed decision-making for sustainable vegetable organic farming practices. Spectral analysis and vegetation indices quantify changes in crop health, informing pesticide efficacy and environmental impact. Sensor networks and IoT devices allow real-time monitoring of environmental conditions and pesticide dynamics, optimizing application practices to minimize contamination while maximizing yield. Machine learning, particularly decision tree-based models like random forests, predicts and mitigates pesticide impacts by analyzing complex datasets. Incorporating variables such as soil type and climate, these models accurately forecast pesticide fate, aiding in targeted mitigation strategies. Deep learning, such as convolutional neural networks (CNNs), identifies pesticide stress symptoms from digital images of vegetable leaves, facilitating rapid intervention. Challenges like data integration and model interpretability persist, yet ongoing research addresses these through data fusion and explainable AI. This review emphasizes the progress in leveraging data science and machine learning for pesticide impact evaluation in organic vegetable farming. By synthesizing research and trends, it offers insights for future sustainable agriculture applications.
{"title":"Harvesting Knowledge: Data Science and Machine Learning Techniques for Evaluating Pesticide Impact in Vegetable Organic Farming","authors":"Aditi Chavan","doi":"10.22214/ijraset.2024.63554","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63554","url":null,"abstract":"Abstract: The integration of data science and machine learning is revolutionizing the assessment of pesticide impact in organic vegetable farming. This review explores methodologies, applications, and research examples showcasing the transformative potential of data-driven approaches. Remote sensing, including satellite imagery and drones, is essential for monitoring crop health and detecting pesticide impacts on vegetable crops like tomatoes, lettuce, and red peppers. By synthesizing research and trends, the review underscores technology's significance in informed decision-making for sustainable vegetable organic farming practices. Spectral analysis and vegetation indices quantify changes in crop health, informing pesticide efficacy and environmental impact. Sensor networks and IoT devices allow real-time monitoring of environmental conditions and pesticide dynamics, optimizing application practices to minimize contamination while maximizing yield. Machine learning, particularly decision tree-based models like random forests, predicts and mitigates pesticide impacts by analyzing complex datasets. Incorporating variables such as soil type and climate, these models accurately forecast pesticide fate, aiding in targeted mitigation strategies. Deep learning, such as convolutional neural networks (CNNs), identifies pesticide stress symptoms from digital images of vegetable leaves, facilitating rapid intervention. Challenges like data integration and model interpretability persist, yet ongoing research addresses these through data fusion and explainable AI. This review emphasizes the progress in leveraging data science and machine learning for pesticide impact evaluation in organic vegetable farming. By synthesizing research and trends, it offers insights for future sustainable agriculture applications.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"38 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795313","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 : 2024-07-31DOI: 10.22214/ijraset.2024.62980
Sushil Shah
{"title":"Project File in Circular Water Tank","authors":"Sushil Shah","doi":"10.22214/ijraset.2024.62980","DOIUrl":"https://doi.org/10.22214/ijraset.2024.62980","url":null,"abstract":"","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"20 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795416","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63579
Nidhi Sharma
Abstract: This paper explores the potential of machine learning to predict student success and personalize the learning experience. The research focuses on using Long Short-Term Memory (LSTM) networks and causal analysis to achieve these objectives. A comprehensive student dataset from Kaggle was employed in this study, and various machine-learning algorithms, including Logistic Regression, Decision Tree, Random Forest, and K-Nearest Neighbors, were systematically compared and evaluated. Logistic Regression emerged as the most effective model for predicting student success based on specific data characteristics. Beyond prediction, the paper delves into the application of causal analysis to identify factors influencing student performance. Understanding these factors enables the development of a system that recommends personalized learning interventions tailored to individual student needs. The potential benefits of this approach for students, educators, and society are significant, providing a pathway to more effective and personalized education. The paper also addresses the importance of responsible data practices and ethical considerations in the implementation of such technologies.
{"title":"Predicting Student Success and Tailoring Learning Experiences: An Exploration of LSTMs and Causal Analysis","authors":"Nidhi Sharma","doi":"10.22214/ijraset.2024.63579","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63579","url":null,"abstract":"Abstract: This paper explores the potential of machine learning to predict student success and personalize the learning experience. The research focuses on using Long Short-Term Memory (LSTM) networks and causal analysis to achieve these objectives. A comprehensive student dataset from Kaggle was employed in this study, and various machine-learning algorithms, including Logistic Regression, Decision Tree, Random Forest, and K-Nearest Neighbors, were systematically compared and evaluated. Logistic Regression emerged as the most effective model for predicting student success based on specific data characteristics. Beyond prediction, the paper delves into the application of causal analysis to identify factors influencing student performance. Understanding these factors enables the development of a system that recommends personalized learning interventions tailored to individual student needs. The potential benefits of this approach for students, educators, and society are significant, providing a pathway to more effective and personalized education. The paper also addresses the importance of responsible data practices and ethical considerations in the implementation of such technologies.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"40 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795435","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63555
Abdulsalam A. A, Aliyu S, Bashar B. L, Danillela U. Y, Ahmad Z. U, Aminu M. B, Gbadamosi L. A
Abstract: Fossil fuel dependence is a growing concern due to its contribution to greenhouse gas emission, climatic change and environmental pollution. This highlights the urgency for alternative source of energy that is renewable, environmental friendly, stability in price, and attractive for sustainable development. Bioethanol, a biofuel has emerged as the most acceptable liquid fuel and as a promising alternative to gasoline. Bioethanol, derived from sugars and starch, has raised sustainability concern as it can lead to competition for land use and potentially driven-up food prices especially in developing countries. Meanwhile, Lignocellulosic biomass, a non-food resources, abundant in cellulose and hemicellulose, present a more sustainable feedstock for bioethanol production. This approach could offer advantages like affordability, environmental friendliness, reduce reliance on traditional fuels and compensate for fuel scarcity. Furthermore, bioconversion technology of lignocellulosic biomass to bioethanol is required to improve its efficiency and cost effectiveness, making it a highly attractive option for a greener energy in the future.
{"title":"Bioethanol: A Sustainable Liquid Fuel as Substitute to Gasoline","authors":"Abdulsalam A. A, Aliyu S, Bashar B. L, Danillela U. Y, Ahmad Z. U, Aminu M. B, Gbadamosi L. A","doi":"10.22214/ijraset.2024.63555","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63555","url":null,"abstract":"Abstract: Fossil fuel dependence is a growing concern due to its contribution to greenhouse gas emission, climatic change and environmental pollution. This highlights the urgency for alternative source of energy that is renewable, environmental friendly, stability in price, and attractive for sustainable development. Bioethanol, a biofuel has emerged as the most acceptable liquid fuel and as a promising alternative to gasoline. Bioethanol, derived from sugars and starch, has raised sustainability concern as it can lead to competition for land use and potentially driven-up food prices especially in developing countries. Meanwhile, Lignocellulosic biomass, a non-food resources, abundant in cellulose and hemicellulose, present a more sustainable feedstock for bioethanol production. This approach could offer advantages like affordability, environmental friendliness, reduce reliance on traditional fuels and compensate for fuel scarcity. Furthermore, bioconversion technology of lignocellulosic biomass to bioethanol is required to improve its efficiency and cost effectiveness, making it a highly attractive option for a greener energy in the future.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"10 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795713","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63689
N. C. Das
Abstract: The chelating ion exchange copolymer 2,4-DHP-4-PAF-II has been synthesized by condensing 2,4- dihydroxypropiophenone, 4-pyridylamine and formaldehyde in the presence of 2M hydrochloric acid as catalyst using 2:1:3 molar proportion of reacting monomers. The resulting resin has been characterized by elemental analysis, UV-Visible, FT-IR, and 1H-NMR. The morphological feature of copolymer has been studied by scanning electron microscopy (SEM) .
{"title":"Metal Ion Uptake Properties of Chelating Ion-Exchange Copolymer Synthesized from 2, 4- Dihydroxypropiophenone and 4-Pyridylamine","authors":"N. C. Das","doi":"10.22214/ijraset.2024.63689","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63689","url":null,"abstract":"Abstract: The chelating ion exchange copolymer 2,4-DHP-4-PAF-II has been synthesized by condensing 2,4- dihydroxypropiophenone, 4-pyridylamine and formaldehyde in the presence of 2M hydrochloric acid as catalyst using 2:1:3 molar proportion of reacting monomers. The resulting resin has been characterized by elemental analysis, UV-Visible, FT-IR, and 1H-NMR. The morphological feature of copolymer has been studied by scanning electron microscopy (SEM) .","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"10 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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