Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63736
Dhanikonda Ratna Bhavani
Abstract: Breast cancer, the most common cancer among women after skin cancer, significantly contributes to the rising mortality rate. Screening mammography is an effective method for detecting masses and abnormalities related to breast cancer. Digital mammograms are especially useful for early cancer detection in asymptomatic women and diagnosing cancer in women with symptoms such as lumps or nipple discharge, thereby reducing mortality and increasing survival rates. Clinicians often face time constraints that can lead to medical errors and incorrect diagnoses due to insufficient time to review patient history thoroughly.
摘要：乳腺癌是继皮肤癌之后妇女中最常见的癌症，是死亡率上升的重要原因。乳房 X 光筛查是检测乳腺癌相关肿块和异常的有效方法。数字乳房 X 光检查尤其适用于无症状妇女的早期癌症检测，以及有肿块或乳头溢液等症状妇女的癌症诊断，从而降低死亡率并提高存活率。临床医生经常面临时间限制，由于没有足够的时间彻底检查病人的病史，可能导致医疗失误和错误诊断。
{"title":"Harnessing Deep Learning for Accurate Detection of Breast Cancer in Histopathological Imagery","authors":"Dhanikonda Ratna Bhavani","doi":"10.22214/ijraset.2024.63736","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63736","url":null,"abstract":"Abstract: Breast cancer, the most common cancer among women after skin cancer, significantly contributes to the rising mortality rate. Screening mammography is an effective method for detecting masses and abnormalities related to breast cancer. Digital mammograms are especially useful for early cancer detection in asymptomatic women and diagnosing cancer in women with symptoms such as lumps or nipple discharge, thereby reducing mortality and increasing survival rates. Clinicians often face time constraints that can lead to medical errors and incorrect diagnoses due to insufficient time to review patient history thoroughly.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"18 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795241","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.2024.63682
Mr. Perumalla Durgaprasad
Abstract: This paper explores the profound impact of Artificial Intelligence (AI) on Human Intelligence (HI), examining both the enhancements and challenges AI introduces. AI, defined as the capability of machines to perform tasks requiring humanlike intelligence, has evolved significantly, influencing various domains such as education, healthcare, and the workforce. AI enhances human cognitive processes by assisting in decision-making, problem-solving, and creativity, thereby augmenting HI. In education, AI-driven tools offer personalized learning experiences, while in healthcare; AI improves diagnostics and patient care. However, the integration of AI raises ethical concerns, including privacy, data security, and algorithmic bias. The potential for AI to surpass human intelligence, known as the singularity, poses existential questions about human autonomy. This paper underscores the importance of responsible AI development, emphasizing the need for ethical frameworks to balance technological advancements with human values. As AI continues to advance, fostering effective human-AI collaboration and preparing society for an AI-enhanced future are crucial for maximizing the benefits and minimizing the risks associated with AI's influence on HI.
{"title":"Effect of AI on HI","authors":"Mr. Perumalla Durgaprasad","doi":"10.22214/ijraset.2024.63682","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63682","url":null,"abstract":"Abstract: This paper explores the profound impact of Artificial Intelligence (AI) on Human Intelligence (HI), examining both the enhancements and challenges AI introduces. AI, defined as the capability of machines to perform tasks requiring humanlike intelligence, has evolved significantly, influencing various domains such as education, healthcare, and the workforce. AI enhances human cognitive processes by assisting in decision-making, problem-solving, and creativity, thereby augmenting HI. In education, AI-driven tools offer personalized learning experiences, while in healthcare; AI improves diagnostics and patient care. However, the integration of AI raises ethical concerns, including privacy, data security, and algorithmic bias. The potential for AI to surpass human intelligence, known as the singularity, poses existential questions about human autonomy. This paper underscores the importance of responsible AI development, emphasizing the need for ethical frameworks to balance technological advancements with human values. As AI continues to advance, fostering effective human-AI collaboration and preparing society for an AI-enhanced future are crucial for maximizing the benefits and minimizing the risks associated with AI's influence on HI.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"15 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795472","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.2024.63618
Tedlapu Narayana Rao, Dr. Uppu Venkata Subbarao, Prof. S. Rajani
Abstract: This paper investigates the factors influencing stress and resilience among high school students. We employed a binary logistic regression model to assess the relationship between independent variables (academic workload, family support, extracurricular activities, peer relationships, etc.) and dependent variables (stress and resilience). A diverse sample of 85 high school students (grades 10-12) from various schools in the region of Visakhapatnam was collected by using stratified random sampling. In this sample, using the proportional allocation technique, 37 are from grade 10, and 48 are from grade 11 and 12. Data was collected through a questionnaire, and binary logistic regression was fitted using the statistical software package SPSS and gave valid conclusions and recommendations.
{"title":"Statistical Analysis of Factors Influencing Stress and Resilience in High School Students in Visakhapatnam Region","authors":"Tedlapu Narayana Rao, Dr. Uppu Venkata Subbarao, Prof. S. Rajani","doi":"10.22214/ijraset.2024.63618","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63618","url":null,"abstract":"Abstract: This paper investigates the factors influencing stress and resilience among high school students. We employed a binary logistic regression model to assess the relationship between independent variables (academic workload, family support, extracurricular activities, peer relationships, etc.) and dependent variables (stress and resilience). A diverse sample of 85 high school students (grades 10-12) from various schools in the region of Visakhapatnam was collected by using stratified random sampling. In this sample, using the proportional allocation technique, 37 are from grade 10, and 48 are from grade 11 and 12. Data was collected through a questionnaire, and binary logistic regression was fitted using the statistical software package SPSS and gave valid conclusions and recommendations.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"9 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795726","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.2024.63567
Vikas Kumar
Abstract: Several administrations, including programming, gathering, and coordinating equipment assets, are included in Cloud Computing (CC) and made available to service users online. The advantages of Cloud Computing are flexibility, competence, and high unwavering quality. Numerous organizations are already exchanging data to the Cloud, and as a result, this data needs to be protected against unauthorized assaults, service rejection, and other threats. Information is deemed secure if classification, accessibility, and uprightness are all available. The challenges and problems related to Cloud Computing security are illustrated in this paper. Additionally, research on security protocols for Cloud-based settings is carried out.
{"title":"A Review: Security Mechanisms in Cloud Computing","authors":"Vikas Kumar","doi":"10.22214/ijraset.2024.63567","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63567","url":null,"abstract":"Abstract: Several administrations, including programming, gathering, and coordinating equipment assets, are included in Cloud Computing (CC) and made available to service users online. The advantages of Cloud Computing are flexibility, competence, and high unwavering quality. Numerous organizations are already exchanging data to the Cloud, and as a result, this data needs to be protected against unauthorized assaults, service rejection, and other threats. Information is deemed secure if classification, accessibility, and uprightness are all available. The challenges and problems related to Cloud Computing security are illustrated in this paper. Additionally, research on security protocols for Cloud-based settings is carried out.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"7 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795594","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.2024.63354
S. M. Wandare
Abstract: There are various fields in which Drone Technology is becoming significant. Surveying and Mapping, Construction Industry, Inspection and Surveillance, Military and Agriculture are the various areas where drone technology playing an important role of reducing time for this tedious work. Drone technology is the most effective among those technologies which helps in efficient project management by addressing the challenges in a construction project like surveying, monitoring activities, safety of labours, quality and cost control and getting timely on-site progress reports.
{"title":"Application of Drone Technology in Construction Industry","authors":"S. M. Wandare","doi":"10.22214/ijraset.2024.63354","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63354","url":null,"abstract":"Abstract: There are various fields in which Drone Technology is becoming significant. Surveying and Mapping, Construction Industry, Inspection and Surveillance, Military and Agriculture are the various areas where drone technology playing an important role of reducing time for this tedious work. Drone technology is the most effective among those technologies which helps in efficient project management by addressing the challenges in a construction project like surveying, monitoring activities, safety of labours, quality and cost control and getting timely on-site progress reports.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"27 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795092","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.2024.63691
Sanjay Kumar
Abstract: This research investigates the economic optimization and performance enhancement of rooftop solar power systems through the integration of concentrated solar technology and advanced materials. The aim is to assess the viability and effectiveness of these innovations in both residential and commercial settings. By focusing on improving energy efficiency and reducing costs, the study provides a comprehensive economic perspective on the adoption of these advanced solar technologies. Key aspects of the research include the evaluation of lifecycle costs, energy yield, and payback periods, offering insights into the long-term financial benefits and feasibility of implementing such systems. The integration of concentrated solar technology enhances the intensity of solar energy captured, thereby significantly boosting the efficiency of rooftop solar panels. Advanced materials, such as perovskites, multi-junction cells, and nanomaterials, are examined for their potential to improve energy absorption, durability, and overall performance of solar panels. The research employs simulation software to model the performance of these optimized systems under various environmental conditions, providing a detailed analysis of their energy output and efficiency.
{"title":"Economic Optimization and Performance Enhancement of Rooftop Solar Power Systems Using Concentrated Solar Technology and Advanced Materials","authors":"Sanjay Kumar","doi":"10.22214/ijraset.2024.63691","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63691","url":null,"abstract":"Abstract: This research investigates the economic optimization and performance enhancement of rooftop solar power systems through the integration of concentrated solar technology and advanced materials. The aim is to assess the viability and effectiveness of these innovations in both residential and commercial settings. By focusing on improving energy efficiency and reducing costs, the study provides a comprehensive economic perspective on the adoption of these advanced solar technologies. Key aspects of the research include the evaluation of lifecycle costs, energy yield, and payback periods, offering insights into the long-term financial benefits and feasibility of implementing such systems. The integration of concentrated solar technology enhances the intensity of solar energy captured, thereby significantly boosting the efficiency of rooftop solar panels. Advanced materials, such as perovskites, multi-junction cells, and nanomaterials, are examined for their potential to improve energy absorption, durability, and overall performance of solar panels. The research employs simulation software to model the performance of these optimized systems under various environmental conditions, providing a detailed analysis of their energy output and efficiency.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"47 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795155","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.2024.63706
Anurag Bharati
Abstract: The growing field of real-time intelligence (RTI) in sustainable restaurant management addresses the imperative to enhance restaurant efficiency and sustainability through data-driven strategies. As the restaurant industry faces pressure to balance environmental impact with service quality, embracing modern technologies becomes crucial. This study aims to explore and assess the potential of RTI systems for managing reservations and predicting food demand in sustainable restaurants. The methodology involves rigorous desk-based research, drawing from reputable scholarly sources, industry reports, and credible online platforms. Findings highlight the multifaceted benefits of RTI, including data-driven optimization of labor, inventory, and green initiatives. RTI also optimizes table bookings and resource allocation, minimizing wait times and food waste for a more sustainable operation. However, data privacy concerns present challenges that demand comprehensive strategies, including privacy-by-design principles and adherence to regulatory standards. Future recommendations encompass cloud-based deployment, structural evolution, data and machine learning enhancements, and further refinements. This research contributes to advancing the integration of RTI systems to foster efficient, sustainable, and customer-centric restaurant management practices.
{"title":"Real-time Intelligence in Sustainable Restaurant Management","authors":"Anurag Bharati","doi":"10.22214/ijraset.2024.63706","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63706","url":null,"abstract":"Abstract: The growing field of real-time intelligence (RTI) in sustainable restaurant management addresses the imperative to enhance restaurant efficiency and sustainability through data-driven strategies. As the restaurant industry faces pressure to balance environmental impact with service quality, embracing modern technologies becomes crucial. This study aims to explore and assess the potential of RTI systems for managing reservations and predicting food demand in sustainable restaurants. The methodology involves rigorous desk-based research, drawing from reputable scholarly sources, industry reports, and credible online platforms. Findings highlight the multifaceted benefits of RTI, including data-driven optimization of labor, inventory, and green initiatives. RTI also optimizes table bookings and resource allocation, minimizing wait times and food waste for a more sustainable operation. However, data privacy concerns present challenges that demand comprehensive strategies, including privacy-by-design principles and adherence to regulatory standards. Future recommendations encompass cloud-based deployment, structural evolution, data and machine learning enhancements, and further refinements. This research contributes to advancing the integration of RTI systems to foster efficient, sustainable, and customer-centric restaurant management practices.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"42 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795169","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.2024.63668
Marapally Sai Charan
Abstract: High-performance electric propulsion systems are becoming increasingly important as the automotive industry rapidly shifts to electric cars (EVs). The electric motor is an essential part of these systems as it determines the power, efficiency, and overall performance of the vehicle.This project uses Altair Flux, a full-featured finite element analysis (FEA) software suite, to build and optimize a radial flux motor (RFM) with permanent magnet synchronous motor (pmsm) . The main goal is to increase the power density and efficiency of the electric propulsion system for electric cars by utilizing Altair Flux's simulation and analytical capabilities.
{"title":"Design of Radial Flux PM Synchronous Motor for EV Applications","authors":"Marapally Sai Charan","doi":"10.22214/ijraset.2024.63668","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63668","url":null,"abstract":"Abstract: High-performance electric propulsion systems are becoming increasingly important as the automotive industry rapidly shifts to electric cars (EVs). The electric motor is an essential part of these systems as it determines the power, efficiency, and overall performance of the vehicle.This project uses Altair Flux, a full-featured finite element analysis (FEA) software suite, to build and optimize a radial flux motor (RFM) with permanent magnet synchronous motor (pmsm) . The main goal is to increase the power density and efficiency of the electric propulsion system for electric cars by utilizing Altair Flux's simulation and analytical capabilities.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"47 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795289","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.2024.63657
G. Lokesh
Abstract: For precision workpiece manufacturing, the system should have good dimensional accuracy and surface finish. In applications such as drilling, punching, marking, boring, tapping, etc., the workpiece is first positioned, and then the tool executes its action while the moving axis remains stationary. In the traditional method of such applications, manufacturers use very expensive CNC machines to program the cycle and perform the same work. Large manufacturers can afford such expensive machines, but for the small machinery manufacturing industry, we must consider low-cost solutions that can provide highquality output. In this study, we tried to propose a low-cost design that can be used to achieve functions similar to CNC. By applying this machine in industry, multiple generations can be obtained in a short time. It is very difficult to estimate the drilling depth when manually drilling with a traditional drilling machine, and the work will usually fail due to over-drilling. In many cases, it is difficult to measure the depth after the drilling is completed; especially the depth of the fine hole cannot be measured. Therefore, an automatic drilling machine that performs the drilling function according to the generated drilling depth and transmitted to the control circuit is indispensable; therefore, undertaking the study, it exposed the technology of the dedicated drilling machine. The automatic drilling machine designed here is very useful for the mechanical workshop. The machine is built with power feed technology and is designed to drill the job to a certain specified depth.
{"title":"Fabrication and Automation of Drilling Machine by Arduino Control","authors":"G. Lokesh","doi":"10.22214/ijraset.2024.63657","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63657","url":null,"abstract":"Abstract: For precision workpiece manufacturing, the system should have good dimensional accuracy and surface finish. In applications such as drilling, punching, marking, boring, tapping, etc., the workpiece is first positioned, and then the tool executes its action while the moving axis remains stationary. In the traditional method of such applications, manufacturers use very expensive CNC machines to program the cycle and perform the same work. Large manufacturers can afford such expensive machines, but for the small machinery manufacturing industry, we must consider low-cost solutions that can provide highquality output. In this study, we tried to propose a low-cost design that can be used to achieve functions similar to CNC. By applying this machine in industry, multiple generations can be obtained in a short time. It is very difficult to estimate the drilling depth when manually drilling with a traditional drilling machine, and the work will usually fail due to over-drilling. In many cases, it is difficult to measure the depth after the drilling is completed; especially the depth of the fine hole cannot be measured. Therefore, an automatic drilling machine that performs the drilling function according to the generated drilling depth and transmitted to the control circuit is indispensable; therefore, undertaking the study, it exposed the technology of the dedicated drilling machine. The automatic drilling machine designed here is very useful for the mechanical workshop. The machine is built with power feed technology and is designed to drill the job to a certain specified depth.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"40 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795440","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.2024.63659
Abeer Ali Saeed Amer
Abstract: This research aims to predict student academic performance using historical data and machine learning algorithms. The dataset includes parental, and academic information about students. The study focuses on three machine learning algorithms: Logistic Regression, Decision Tree, and Support Vector Machine (SVM). To begin, we conducted data analysis to understand the distribution and relationships within the data. Visualizations such as homogeneity analysis of parental education, race, and gender, as well as count plots for gender according to parental education and race, were created to identify patterns and insights. The data was then pre-processed and used to train the three models. Each model's performance was evaluated based on accuracy, precision, recall, and F1 score. Confusion matrices and ROC curves were also generated to provide a comprehensive evaluation of each model's predictive power.
摘要：本研究旨在利用历史数据和机器学习算法预测学生的学习成绩。数据集包括学生家长和学业信息。研究重点是三种机器学习算法：逻辑回归、决策树和支持向量机（SVM）。首先，我们进行了数据分析，以了解数据的分布和关系。我们创建了可视化图表，如父母教育程度、种族和性别的同质性分析，以及根据父母教育程度和种族划分的性别计数图，以确定模式和见解。然后对数据进行预处理，并用于训练三个模型。根据准确度、精确度、召回率和 F1 分数来评估每个模型的性能。此外，还生成了混淆矩阵和 ROC 曲线，以全面评估每个模型的预测能力。
{"title":"Predictive Model for Student’s Academic Performance Using Machine Learning Techniques","authors":"Abeer Ali Saeed Amer","doi":"10.22214/ijraset.2024.63659","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63659","url":null,"abstract":"Abstract: This research aims to predict student academic performance using historical data and machine learning algorithms. The dataset includes parental, and academic information about students. The study focuses on three machine learning algorithms: Logistic Regression, Decision Tree, and Support Vector Machine (SVM). To begin, we conducted data analysis to understand the distribution and relationships within the data. Visualizations such as homogeneity analysis of parental education, race, and gender, as well as count plots for gender according to parental education and race, were created to identify patterns and insights. The data was then pre-processed and used to train the three models. Each model's performance was evaluated based on accuracy, precision, recall, and F1 score. Confusion matrices and ROC curves were also generated to provide a comprehensive evaluation of each model's predictive power.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"21 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795549","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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