1) The document discusses a personalized e-learning model that calculates a learner's capability score (LCS) based on performance, learning style, and time to determine an optimal learning path.
2) The LCS algorithm uses parameters like time, performance on tests, learning style, objective, difficulty of concepts, and question level to analyze a learner's capabilities and provide personalized course sequencing.
3) The proposed model involves developing an application where learners can register for courses, take tests on concepts, and receive personalized sequencing of concepts based on their calculated LCS.
The document provides details of the revised syllabus for the Bachelor of Engineering in Information Technology program at the University of Mumbai effective from the 2016-17 academic year onwards. It includes the program structure, course details, course objectives and outcomes for the third semester. The syllabus covers topics like applied mathematics, logic design, data structures, databases, communications and includes labs. It aims to incorporate latest technologies and improve employability. The revised syllabus was prepared by faculty involving industry experts and focuses on outcome-based education.
This document summarizes a personalized e-learning scheme called SPERO for teachers. SPERO aims to estimate teachers' ICT (information and communication technologies) levels through online questionnaires. It uses an architecture based on the IEEE e-learning reference model. SPERO automatically extracts user profiles from questionnaire responses to provide personalized learning resources and feedback to teachers. The system creates initial profiles when users first complete a questionnaire, then continually re-evaluates and updates profiles as users provide new information.
The document outlines the program structure for the second year of engineering studies at the University of Mumbai. It details the courses, credits, teaching and examination schemes for Semesters III and IV. It includes guidelines for a Mini Project that students must complete in groups of 3-4 over the two semesters to identify problems, propose solutions, build prototypes, and demonstrate their work. The Mini Project aims to develop students' problem-solving, communication, and lifelong learning skills through hands-on work addressing societal needs.
IRJET- Clustering Students through Data Mining and Gamified LearningIRJET Journal
This document discusses a proposed system to cluster students through data mining and gamified learning. The system would develop a game for students to play that analyzes their performance data. This data would then be used to cluster students based on similar scores and provide personalized recommendations to improve learning. Specifically, it would:
1. Have students play an online game related to their course module.
2. Analyze student performance data and cluster students with similar scores.
3. Provide clustered student data and recommendations to faculty to personalize learning.
The goal is to improve student motivation and learning through gamification while obtaining data to evaluate student skills and provide targeted feedback.
Selection of Learning Materials Based on Students’ Behaviors in 3DMUVLETELKOMNIKA JOURNAL
Learning in 3-dimensional virtual environments has been widely used as a complement to traditional learning. Multi User Virtual Learning Environment in 3 Dimensions (3DMUVLE) provides many benefits and can support lifelong learning. In its implementation, this learning has not supported personal learning. This study aims to build a 3DMUVLE with personalized materials based on students' models. The system development model uses the Linear Sequence model by integrating MOODLE, SLOODLE and OPENSIM. Student's model in this research is Myer Briggs Type Indicator (MBTI) and determination of type uses fuzzy logic. The results of this study are 16 types of students and each type consists of 3 levels: low, medium and high. Each level has a specific learning material. The implication of this research is the level of MBTI type so that the learning material is more specific.
IRJET- Ontology based E-Learning System for Undergraduate Students using FPN ...IRJET Journal
This document discusses the development of an ontology-based e-learning system for undergraduate students using fuzzy Petri nets (FPN) and hidden Markov models (HMM). The system aims to provide personalized adaptive learning through tracking student performance with FPN and adjusting the learning path using HMM. It will include course content modeled with Petri nets and fuzzy rules. Student tests will be generated using mini-batch k-means clustering of questions. The system architecture involves students, tutors, and an administrator, and will report student and tutor activities. It aims to help students learn effectively through distance learning and enable performance monitoring.
This document discusses the analysis of using virtual simulation models and real learning systems in mechatronics education. It describes a module combining virtual and real systems to teach mechatronics. Students are first introduced to a real pneumatic distribution station to observe its functions. They then use a 3D simulation software to model the system, allowing individual practice. A survey found that combining real and virtual systems improves learning by increasing motivation, reducing time, and enabling system modeling. However, interaction with real industrial systems is still needed to develop professional skills.
Embedded System Practicum Module for Increase Student Comprehension of Microc...TELKOMNIKA JOURNAL
The result of applying the embedded system in education for students is successfully applied in
university. On the other side, many people in Indonesia use smart equipment’s (Hand phone, Remote), but
none of those equipments are used in education. University as the source of knowledge should overcome
the problem by encouraging the students to use a technology with learning about it first. Embedded
System Practicum Module Design needs a prototype method so that the practicum module that is desired
can be made. This method is often used in real life. A prototype considered of a part of a product that
expresses logic and physical of external interface that is being displayed and this method will fully depend
on user contentment. Embedded System Practicum Module Design is made to increase student
comprehension of embedded system course and to encourage students to innovate, so that many
technologies will be developed and also to help lecturers deliver course subjects. With this practicum it is
hoped that the student comprehension will increase significantly. The result of this research is a decent
practicum module, hardware or software that can help students to know better about technology and the
course subjects so that it will encourage the students to create an embedded system technology. The
result of the test has been done; there is an increase of learning value obtained by 7.8%.
The document provides details of the revised syllabus for the Bachelor of Engineering in Information Technology program at the University of Mumbai effective from the 2016-17 academic year onwards. It includes the program structure, course details, course objectives and outcomes for the third semester. The syllabus covers topics like applied mathematics, logic design, data structures, databases, communications and includes labs. It aims to incorporate latest technologies and improve employability. The revised syllabus was prepared by faculty involving industry experts and focuses on outcome-based education.
This document summarizes a personalized e-learning scheme called SPERO for teachers. SPERO aims to estimate teachers' ICT (information and communication technologies) levels through online questionnaires. It uses an architecture based on the IEEE e-learning reference model. SPERO automatically extracts user profiles from questionnaire responses to provide personalized learning resources and feedback to teachers. The system creates initial profiles when users first complete a questionnaire, then continually re-evaluates and updates profiles as users provide new information.
The document outlines the program structure for the second year of engineering studies at the University of Mumbai. It details the courses, credits, teaching and examination schemes for Semesters III and IV. It includes guidelines for a Mini Project that students must complete in groups of 3-4 over the two semesters to identify problems, propose solutions, build prototypes, and demonstrate their work. The Mini Project aims to develop students' problem-solving, communication, and lifelong learning skills through hands-on work addressing societal needs.
IRJET- Clustering Students through Data Mining and Gamified LearningIRJET Journal
This document discusses a proposed system to cluster students through data mining and gamified learning. The system would develop a game for students to play that analyzes their performance data. This data would then be used to cluster students based on similar scores and provide personalized recommendations to improve learning. Specifically, it would:
1. Have students play an online game related to their course module.
2. Analyze student performance data and cluster students with similar scores.
3. Provide clustered student data and recommendations to faculty to personalize learning.
The goal is to improve student motivation and learning through gamification while obtaining data to evaluate student skills and provide targeted feedback.
Selection of Learning Materials Based on Students’ Behaviors in 3DMUVLETELKOMNIKA JOURNAL
Learning in 3-dimensional virtual environments has been widely used as a complement to traditional learning. Multi User Virtual Learning Environment in 3 Dimensions (3DMUVLE) provides many benefits and can support lifelong learning. In its implementation, this learning has not supported personal learning. This study aims to build a 3DMUVLE with personalized materials based on students' models. The system development model uses the Linear Sequence model by integrating MOODLE, SLOODLE and OPENSIM. Student's model in this research is Myer Briggs Type Indicator (MBTI) and determination of type uses fuzzy logic. The results of this study are 16 types of students and each type consists of 3 levels: low, medium and high. Each level has a specific learning material. The implication of this research is the level of MBTI type so that the learning material is more specific.
IRJET- Ontology based E-Learning System for Undergraduate Students using FPN ...IRJET Journal
This document discusses the development of an ontology-based e-learning system for undergraduate students using fuzzy Petri nets (FPN) and hidden Markov models (HMM). The system aims to provide personalized adaptive learning through tracking student performance with FPN and adjusting the learning path using HMM. It will include course content modeled with Petri nets and fuzzy rules. Student tests will be generated using mini-batch k-means clustering of questions. The system architecture involves students, tutors, and an administrator, and will report student and tutor activities. It aims to help students learn effectively through distance learning and enable performance monitoring.
This document discusses the analysis of using virtual simulation models and real learning systems in mechatronics education. It describes a module combining virtual and real systems to teach mechatronics. Students are first introduced to a real pneumatic distribution station to observe its functions. They then use a 3D simulation software to model the system, allowing individual practice. A survey found that combining real and virtual systems improves learning by increasing motivation, reducing time, and enabling system modeling. However, interaction with real industrial systems is still needed to develop professional skills.
Embedded System Practicum Module for Increase Student Comprehension of Microc...TELKOMNIKA JOURNAL
The result of applying the embedded system in education for students is successfully applied in
university. On the other side, many people in Indonesia use smart equipment’s (Hand phone, Remote), but
none of those equipments are used in education. University as the source of knowledge should overcome
the problem by encouraging the students to use a technology with learning about it first. Embedded
System Practicum Module Design needs a prototype method so that the practicum module that is desired
can be made. This method is often used in real life. A prototype considered of a part of a product that
expresses logic and physical of external interface that is being displayed and this method will fully depend
on user contentment. Embedded System Practicum Module Design is made to increase student
comprehension of embedded system course and to encourage students to innovate, so that many
technologies will be developed and also to help lecturers deliver course subjects. With this practicum it is
hoped that the student comprehension will increase significantly. The result of this research is a decent
practicum module, hardware or software that can help students to know better about technology and the
course subjects so that it will encourage the students to create an embedded system technology. The
result of the test has been done; there is an increase of learning value obtained by 7.8%.
A new-method-of-adaptation-in-integrated-learning-environmentCemal Ardil
This document describes a new method of adaptation in a partially integrated learning environment that includes an electronic textbook and integrated tutoring system. The method establishes interconnections between operations and concepts to determine relevant educational material based on tutorial problem results. The algorithm estimates concept mastery levels, student non-mastery on textbook pages, and creates a ranked list of textbook pages for repeated study. The method was integrated into software tools to dynamically determine relevant educational content for each student step.
A Study on Learning Factor Analysis – An Educational Data Mining Technique fo...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IRJET- Survey on Various Techniques of Attendance marking and Attention D...IRJET Journal
The document summarizes various techniques for automated attendance marking and detecting student attention levels in classrooms. It discusses methods using facial recognition, biometrics, Bluetooth beacons, sensors to track eye movements, posture and brain waves. Researchers have achieved over 95% accuracy using these techniques compared to traditional manual attendance marking methods. The techniques described can save time, reduce human errors and help teachers identify students who are inattentive or not focusing in class.
Using Ontology in Electronic Evaluation for Personalization of eLearning Systemsinfopapers
I. Pah, F. Stoica, L. F. Cacovean, E. M. Popa, Using Ontology in Electronic Evaluation for Personalization of eLearning Systems, Proceedings of the 8th WSEAS International Conference on APPLIED INFORMATICS and COMMUNICATIONS (AIC’08), Rhodes, Greece, August 20-22, ISSN: 1790-5109, ISBN: 978-960-6766-94-7, pp. 332-337, 2008
Abstract The main objective of higher education institutions is to provide quality education to its students. The faculties employed by the educational institute’s plays the dominant role to achieve highest level of quality in higher education. The faculty having excellent subject knowledge and teaching skills have the major impact upon the performance of students resulting in good academic results, placements and hereby increasing the quality intake of students. This paper will assist the academic planners in distribution of subjects among the faculties in the department such that the students can make the optimum use of faculty knowledge, experience and teaching skills to reach the new heights. Keywords: Data Mining, Business Intelligence, WEKA, Data Visualization, Decision Tree, J48.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This multiple instance e-learning activity committal to writing project is developed to method the training system through web. The most aim of the project is to supply courses through on-line to the members. World Health Organization wishes to be told the courses without planning to computer centers. This technique approach the learners can get relevant info regarding e learning net system. During this project, whenever student gets new Arcanum to access the E learning web site. They‟ll watch video regarding the subject. It guides the coed for on-line check. Student register course here. This technique accepts payment through PayPal. This project proposes activity code idea for questioner question and answer pattern.
Microlearning based mobile application for preparation to CCNA examinationronan messi
2014 11th International Conference on Electronics, Computer and Computation (ICECCO) - Microlearning based mobile application for preparation to CCNA examination
Recently we conducted a one credit course in Mount Carmel, wherein the students were exposed to a new way of learning using activity. The response we received was simply amazing.
This report presents the findings of an evaluation by the Inspectorate of the Department of Education and Science on the impact of information and communications technology (ICT) on teaching and learning in Irish primary and post-primary schools. The evaluation was based on surveys of principals and teachers, case studies of over 50 schools, and observations of over 180 schools. It found that while ICT infrastructure has expanded, challenges remain around supporting teachers' professional development and integrating ICT into the curriculum. Recommendations focus on providing adequate and sustainable ICT infrastructure, supporting teachers to develop necessary ICT skills, and promoting planning to effectively embed ICT in teaching and learning.
Kalvi: An Adaptive Tamil m-Learning System paperarivolit
The document proposes Kalvi, an adaptive Tamil mobile learning system built on the Sakai learning management system platform. The Kalvi system collects student activity data and uses data mining, machine learning and analytics techniques to adaptively deliver personalized Tamil language content based on individual student needs and preferences. It features both web and mobile clients so students can access courses on devices like iPad and iPhone. The system aims to address limitations of existing Tamil LMSs by making content delivery dynamic and adaptive rather than static. Future work includes further incorporating these adaptive techniques into educational processes and culture.
Santosh Poloju is seeking a position in computer hardware and networking where he can learn and contribute his skills. He has a B.Tech degree from Jawaharlal Nehru University and one year of experience working at Gayathri Engineering Works. Santosh has certifications in Microsoft Certified Technology Specialist and completed a hardware and networking course from Jetking Institute. His technical skills include PC hardware, operating systems, networking devices, routing protocols, server hardware, and Active Directory. He received awards for chess and his performance at Jetking Institute.
Kalvi: An Adaptive Tamil m-Learning Systemjayaradhaa
The document proposes Kalvi, an adaptive Tamil m-Learning system based on the open-source Sakai learning management system. It would use data mining, machine learning, and analytics to make course delivery and content adaptive based on a learner's profile, skills, and activity. This would help address issues with existing static Tamil LMS that do not tailor learning. The system would have a server to host courses and a client for mobile access. It aims to improve education by incorporating adaptive learning into the Tamil language experience.
This presentation provides an overview of an e-learning management system. It discusses the objectives of providing a user-friendly environment for incremental learning. It analyzes the functional requirements for admins, teachers, and students, as well as non-functional requirements like security, maintainability, and scalability. Sequence diagrams and class diagrams are presented, as well as use case diagrams for each user type. The conclusion states that the system will automate the manual process and enable long-term storage and easy access to information.
Student’s Career Interest Prediction using Machine LearningIRJET Journal
This document discusses various machine learning techniques for predicting students' career interests. It begins with an abstract describing the challenges students face in choosing careers and how machine learning can help by predicting interests based on a student's academic and extracurricular history. It then reviews related work applying machine learning algorithms like SVM, random forest decision trees, and XGBoost for career recommendations. The document compares the performance of these algorithms on different datasets and identifies decision trees and SVM as commonly used techniques. It outlines several algorithms studied, including one-hot encoding to prepare categorical data for machine learning models.
This document describes a student grade prediction system called StudGrad developed by four students. It uses a linear regression machine learning model to predict student grades based on factors like study hours, attendance, previous grades, and extracurricular activities. The document outlines the data collection, model training, evaluation, and deployment process. It also discusses using an Agile software development process and performs a feasibility analysis and SWOT analysis of the project.
University Recommendation Support System using ML AlgorithmsIRJET Journal
This document presents a university recommendation system that uses machine learning algorithms like KNN and SVM to analyze student profile data and recommend top universities with the highest chance of admission. The system collects data on student attributes and admission outcomes from 45 universities on the edulix.com forum. It cleans, pre-processes and selects important features from the data. Models are trained using KNN and SVM classification and used to suggest a top 10 university list customized for new student profiles to maximize chances of acceptance. The system aims to help students struggling with the complex university selection process.
Learning Analytics for Computer Programming EducationIRJET Journal
This document describes a study that uses learning analytics and predictive modeling to identify computer science students who may be struggling and provide targeted feedback. The study collects both static student data (like academic history) and dynamic data (like time spent on assignments) to train predictive models. Different machine learning algorithms are tested, and K-nearest neighbors performs best at predicting exam outcomes. Based on model predictions, students receive personalized weekly emails with feedback and resources. The goal is to guide struggling students before exams and reduce failure rates.
IRJET- Evaluation Technique of Student Performance in various CoursesIRJET Journal
The document proposes a system to evaluate student performance in various courses using techniques like machine learning. It discusses challenges in predicting student performance and developing a model that incorporates students' academic records and evolving progress. The proposed system aims to track student academic and extracurricular information to predict suitable courses and analyze growth.
IRJET- Tracking and Predicting Student Performance using Machine LearningIRJET Journal
This document describes a study that uses machine learning models to predict student performance and whether students will complete their degrees based on their academic records and other features. The study collected data on scholarship students from various universities. It applied learning analytics, discriminative, and generative classification models to the data. Experimental results showed the proposed method, which considered features like family expenditures and personal information, outperformed existing methods that primarily used academic performance, family income, and assets. The document discusses using k-means clustering and support vector machines (SVM) algorithms to analyze the data and predict student performance. It concludes that past academic performance significantly influences students' future performance and that predictive performance increases with larger datasets.
An Intelligent Career Guidance System using Machine LearningIRJET Journal
This document summarizes an intelligent career guidance system that uses machine learning. The system aims to help students choose an appropriate career path by assessing their skills and predicting a suitable field of study. It uses an online assessment to evaluate students' skill sets in areas like analytical skills and logical reasoning. A machine learning model then analyzes the assessment results and uses algorithms like K-Nearest Neighbors and K-Means clustering to predict a recommended career path and secondary options. The system is intended to provide more accurate guidance than traditional counseling methods and help reduce the number of students who choose a wrong career path.
Semantic web technologies have been attracting interest in many domains. E-learning is not an exception which also involves with many activities or tasks such as instructional design, content development, authoring, delivery, assessment, feedback and etc. which can be sequenced and composed as workflow. Web based E-learning services should be focused in this aspect to fulfill variant e-learners’ requirements. This paper focuses on the Adaptive instructional design framework in which three significant facets are considered 1) Knowledge extraction from user’s behavior, interactions and actions and convert them into semantics 2) Detection of learners style from the semantics defined in the knowledge base and 3) Composition of the workflow for the variant learners to satisfy their requirements dynamically. In this paper we have proposed SEALMS –Semantically Enhanced Adaptive Learning Management System a theoretical framework tracks the learners profile and composes the services for learners using OWL-S. Modules of SEALMS include intelligent agents which perform a kind of reasoning and deriving results from the input fed, finally personalized workflow has been recommended for the elearner.SEALMS is also a cyclic model where the feedback can be taken and reviving process can be initiated from the start to obtain the better results.
A new-method-of-adaptation-in-integrated-learning-environmentCemal Ardil
This document describes a new method of adaptation in a partially integrated learning environment that includes an electronic textbook and integrated tutoring system. The method establishes interconnections between operations and concepts to determine relevant educational material based on tutorial problem results. The algorithm estimates concept mastery levels, student non-mastery on textbook pages, and creates a ranked list of textbook pages for repeated study. The method was integrated into software tools to dynamically determine relevant educational content for each student step.
A Study on Learning Factor Analysis – An Educational Data Mining Technique fo...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IRJET- Survey on Various Techniques of Attendance marking and Attention D...IRJET Journal
The document summarizes various techniques for automated attendance marking and detecting student attention levels in classrooms. It discusses methods using facial recognition, biometrics, Bluetooth beacons, sensors to track eye movements, posture and brain waves. Researchers have achieved over 95% accuracy using these techniques compared to traditional manual attendance marking methods. The techniques described can save time, reduce human errors and help teachers identify students who are inattentive or not focusing in class.
Using Ontology in Electronic Evaluation for Personalization of eLearning Systemsinfopapers
I. Pah, F. Stoica, L. F. Cacovean, E. M. Popa, Using Ontology in Electronic Evaluation for Personalization of eLearning Systems, Proceedings of the 8th WSEAS International Conference on APPLIED INFORMATICS and COMMUNICATIONS (AIC’08), Rhodes, Greece, August 20-22, ISSN: 1790-5109, ISBN: 978-960-6766-94-7, pp. 332-337, 2008
Abstract The main objective of higher education institutions is to provide quality education to its students. The faculties employed by the educational institute’s plays the dominant role to achieve highest level of quality in higher education. The faculty having excellent subject knowledge and teaching skills have the major impact upon the performance of students resulting in good academic results, placements and hereby increasing the quality intake of students. This paper will assist the academic planners in distribution of subjects among the faculties in the department such that the students can make the optimum use of faculty knowledge, experience and teaching skills to reach the new heights. Keywords: Data Mining, Business Intelligence, WEKA, Data Visualization, Decision Tree, J48.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This multiple instance e-learning activity committal to writing project is developed to method the training system through web. The most aim of the project is to supply courses through on-line to the members. World Health Organization wishes to be told the courses without planning to computer centers. This technique approach the learners can get relevant info regarding e learning net system. During this project, whenever student gets new Arcanum to access the E learning web site. They‟ll watch video regarding the subject. It guides the coed for on-line check. Student register course here. This technique accepts payment through PayPal. This project proposes activity code idea for questioner question and answer pattern.
Microlearning based mobile application for preparation to CCNA examinationronan messi
2014 11th International Conference on Electronics, Computer and Computation (ICECCO) - Microlearning based mobile application for preparation to CCNA examination
Recently we conducted a one credit course in Mount Carmel, wherein the students were exposed to a new way of learning using activity. The response we received was simply amazing.
This report presents the findings of an evaluation by the Inspectorate of the Department of Education and Science on the impact of information and communications technology (ICT) on teaching and learning in Irish primary and post-primary schools. The evaluation was based on surveys of principals and teachers, case studies of over 50 schools, and observations of over 180 schools. It found that while ICT infrastructure has expanded, challenges remain around supporting teachers' professional development and integrating ICT into the curriculum. Recommendations focus on providing adequate and sustainable ICT infrastructure, supporting teachers to develop necessary ICT skills, and promoting planning to effectively embed ICT in teaching and learning.
Kalvi: An Adaptive Tamil m-Learning System paperarivolit
The document proposes Kalvi, an adaptive Tamil mobile learning system built on the Sakai learning management system platform. The Kalvi system collects student activity data and uses data mining, machine learning and analytics techniques to adaptively deliver personalized Tamil language content based on individual student needs and preferences. It features both web and mobile clients so students can access courses on devices like iPad and iPhone. The system aims to address limitations of existing Tamil LMSs by making content delivery dynamic and adaptive rather than static. Future work includes further incorporating these adaptive techniques into educational processes and culture.
Santosh Poloju is seeking a position in computer hardware and networking where he can learn and contribute his skills. He has a B.Tech degree from Jawaharlal Nehru University and one year of experience working at Gayathri Engineering Works. Santosh has certifications in Microsoft Certified Technology Specialist and completed a hardware and networking course from Jetking Institute. His technical skills include PC hardware, operating systems, networking devices, routing protocols, server hardware, and Active Directory. He received awards for chess and his performance at Jetking Institute.
Kalvi: An Adaptive Tamil m-Learning Systemjayaradhaa
The document proposes Kalvi, an adaptive Tamil m-Learning system based on the open-source Sakai learning management system. It would use data mining, machine learning, and analytics to make course delivery and content adaptive based on a learner's profile, skills, and activity. This would help address issues with existing static Tamil LMS that do not tailor learning. The system would have a server to host courses and a client for mobile access. It aims to improve education by incorporating adaptive learning into the Tamil language experience.
This presentation provides an overview of an e-learning management system. It discusses the objectives of providing a user-friendly environment for incremental learning. It analyzes the functional requirements for admins, teachers, and students, as well as non-functional requirements like security, maintainability, and scalability. Sequence diagrams and class diagrams are presented, as well as use case diagrams for each user type. The conclusion states that the system will automate the manual process and enable long-term storage and easy access to information.
Student’s Career Interest Prediction using Machine LearningIRJET Journal
This document discusses various machine learning techniques for predicting students' career interests. It begins with an abstract describing the challenges students face in choosing careers and how machine learning can help by predicting interests based on a student's academic and extracurricular history. It then reviews related work applying machine learning algorithms like SVM, random forest decision trees, and XGBoost for career recommendations. The document compares the performance of these algorithms on different datasets and identifies decision trees and SVM as commonly used techniques. It outlines several algorithms studied, including one-hot encoding to prepare categorical data for machine learning models.
This document describes a student grade prediction system called StudGrad developed by four students. It uses a linear regression machine learning model to predict student grades based on factors like study hours, attendance, previous grades, and extracurricular activities. The document outlines the data collection, model training, evaluation, and deployment process. It also discusses using an Agile software development process and performs a feasibility analysis and SWOT analysis of the project.
University Recommendation Support System using ML AlgorithmsIRJET Journal
This document presents a university recommendation system that uses machine learning algorithms like KNN and SVM to analyze student profile data and recommend top universities with the highest chance of admission. The system collects data on student attributes and admission outcomes from 45 universities on the edulix.com forum. It cleans, pre-processes and selects important features from the data. Models are trained using KNN and SVM classification and used to suggest a top 10 university list customized for new student profiles to maximize chances of acceptance. The system aims to help students struggling with the complex university selection process.
Learning Analytics for Computer Programming EducationIRJET Journal
This document describes a study that uses learning analytics and predictive modeling to identify computer science students who may be struggling and provide targeted feedback. The study collects both static student data (like academic history) and dynamic data (like time spent on assignments) to train predictive models. Different machine learning algorithms are tested, and K-nearest neighbors performs best at predicting exam outcomes. Based on model predictions, students receive personalized weekly emails with feedback and resources. The goal is to guide struggling students before exams and reduce failure rates.
IRJET- Evaluation Technique of Student Performance in various CoursesIRJET Journal
The document proposes a system to evaluate student performance in various courses using techniques like machine learning. It discusses challenges in predicting student performance and developing a model that incorporates students' academic records and evolving progress. The proposed system aims to track student academic and extracurricular information to predict suitable courses and analyze growth.
IRJET- Tracking and Predicting Student Performance using Machine LearningIRJET Journal
This document describes a study that uses machine learning models to predict student performance and whether students will complete their degrees based on their academic records and other features. The study collected data on scholarship students from various universities. It applied learning analytics, discriminative, and generative classification models to the data. Experimental results showed the proposed method, which considered features like family expenditures and personal information, outperformed existing methods that primarily used academic performance, family income, and assets. The document discusses using k-means clustering and support vector machines (SVM) algorithms to analyze the data and predict student performance. It concludes that past academic performance significantly influences students' future performance and that predictive performance increases with larger datasets.
An Intelligent Career Guidance System using Machine LearningIRJET Journal
This document summarizes an intelligent career guidance system that uses machine learning. The system aims to help students choose an appropriate career path by assessing their skills and predicting a suitable field of study. It uses an online assessment to evaluate students' skill sets in areas like analytical skills and logical reasoning. A machine learning model then analyzes the assessment results and uses algorithms like K-Nearest Neighbors and K-Means clustering to predict a recommended career path and secondary options. The system is intended to provide more accurate guidance than traditional counseling methods and help reduce the number of students who choose a wrong career path.
Semantic web technologies have been attracting interest in many domains. E-learning is not an exception which also involves with many activities or tasks such as instructional design, content development, authoring, delivery, assessment, feedback and etc. which can be sequenced and composed as workflow. Web based E-learning services should be focused in this aspect to fulfill variant e-learners’ requirements. This paper focuses on the Adaptive instructional design framework in which three significant facets are considered 1) Knowledge extraction from user’s behavior, interactions and actions and convert them into semantics 2) Detection of learners style from the semantics defined in the knowledge base and 3) Composition of the workflow for the variant learners to satisfy their requirements dynamically. In this paper we have proposed SEALMS –Semantically Enhanced Adaptive Learning Management System a theoretical framework tracks the learners profile and composes the services for learners using OWL-S. Modules of SEALMS include intelligent agents which perform a kind of reasoning and deriving results from the input fed, finally personalized workflow has been recommended for the elearner.SEALMS is also a cyclic model where the feedback can be taken and reviving process can be initiated from the start to obtain the better results.
A comparative study of machine learning algorithms for virtual learning envir...IAESIJAI
Virtual learning environment is becoming an increasingly popular study option for students from diverse cultural and socioeconomic backgrounds around the world. Although this learning environment is quite adaptable, improving student performance is difficult due to the online-only learning method. Therefore, it is essential to investigate students' participation and performance in virtual learning in order to improve their performance. Using a publicly available Open University learning analytics dataset, this study examines a variety of machine learning-based prediction algorithms to determine the best method for predicting students' academic success, hence providing additional alternatives for enhancing their academic achievement. Support vector machine, random forest, Nave Bayes, logical regression, and decision trees are employed for the purpose of prediction using machine learning methods. It is noticed that the random forest and logistic regression approach predict student performance with the highest average accuracy values compared to the alternatives. In a number of instances, the support vector machine has been seen to outperform the other methods.
The document describes the design and evaluation of an electronic class record system for Makiling National High School. It discusses:
1) The development of an electronic class record using Microsoft Excel that automatically computes student grades based on inputs from teachers.
2) Testing the functionality and accuracy of the electronic class record system.
3) Evaluating the acceptability of the electronic class record system through surveys of teachers, finding it was rated positively and would be implemented in the upcoming school year.
IoT-based students interaction framework using attention-scoring assessment i...eraser Juan José Calderón
IoT-based students interaction framework using attention-scoring assessment in eLearning. Muhammad Farhan a,b, Sohail Jabbar a,c,d, Muhammad Aslam b, Mohammad Hammoudeh e, Mudassar Ahmad c, Shehzad Khalid f, Murad Khan g,Kijun Han d,
A Literature Survey on Student Profile Management SystemIRJET Journal
This document provides a literature review on student profile management systems. It discusses 10 academic papers related to developing a student profile system that allows educational institutions to efficiently store and access student records and profiles. The key aspects covered include using data mining and machine learning to classify students, implementing cloud-based student profile systems, ensuring security and privacy of student data stored in the cloud, and optimizing costs for cloud-based student data management systems. The goal of the literature review is to better understand existing approaches to developing an effective student profile management system.
A Comprehensive E-Learning Platform for Education: A Full-Stack Web Applicati...IRJET Journal
This document describes the development of a comprehensive e-learning platform for engineering education using EJS, MongoDB, Express.js, and Node.js. The platform aims to address limitations in traditional engineering education methods by providing personalized, flexible access to engaging learning content and activities. It was built with a React frontend, Node/Express backend, and MongoDB database. The platform offers features like interactive courses, personalized learning pathways, and analytics. It was deployed on AWS for scalability. Studies show e-learning improves outcomes in engineering education by enhancing engagement, satisfaction and performance compared to traditional methods.
Qualitative Analysis of Electronic Class Record.pdfChristopher Lee
The Electronic Class Record (E-Class Record) from Department of Education
(DepEd) is an Information Software used by Faculty Members in different schools
depending on their level status of the Students at present. This Information System tool
is designed to facilitate proper evaluations, assessment reports and effectively getting
the total progress and performance grading results exclusively for the Senior High
School Students in Diliman College - Quezon City.
The E-Class Record which is formatted by using a Microsoft Excel spreadsheet
file document gives the teachers an important grading information and evaluations on
which class recording of grades are now more reliable and efficient.
The construction of the Qualitative research study is for me to gather the
descriptive analysis statements made from the respondents’ point of view, and how they
have been assessed and satisfied by their own experiences in using the Electronic Class
Record (E-Class Record) effectively and efficiently.
This document describes a student result analysis system that was developed to automatically parse student result data from excel files into a database. It allows teachers to log in and view analysis of student results including rankings, subject performance, and passing/failing rates. The system uses PHP, MySQL, and JavaScript to fetch and display the student data. It also generates PDF reports of individual student results. The goal was to create an easier way for teachers to analyze student performance compared to manual entry of results.
IRJET- Predicting Academic Performance based on Social ActivitiesIRJET Journal
This document discusses predicting student academic performance based on their social media activities in an online learning environment. It presents a study of 343 students in a computer science course that used social tools like wikis, blogs, and microblogging for collaboration. The study collected data on student activities and used regression algorithms, including a novel Large Margin Nearest Neighbor Regression approach, to predict student grades based on their social media usage. The models achieved good prediction accuracy, outperforming other common regression algorithms.
Online Examination and Evaluation SystemIRJET Journal
This document summarizes research on existing online examination and evaluation systems. It reviews 20 papers on different approaches for objective and subjective answer evaluation, including keyword matching, cosine similarity, machine learning algorithms, and natural language processing. The papers describe systems that automate the grading of exams through online proctoring, question banks, and tools to analyze student responses against model answers. The document concludes that a comprehensive examination system is needed that incorporates proctoring, online testing, and evaluation of both subjective and objective question types.
IRJET- Design and Development of Ranking System using Sentimental AnalysisIRJET Journal
1) The document presents RANKBOX, a ranking system that mines complex relationships in college/school data based on user feedback.
2) It uses sentiment analysis and machine learning to automatically personalize rankings according to user preferences and continuously improve based on user feedback.
3) The system was implemented as a web application that allows users to provide simple feedback on colleges/schools and view personalized rankings of subsequent queries based on their feedback.
Online Intelligent Semantic Performance Based Solution: The Milestone towards...AM Publications
As we analyse the computer application undergraduate logical-based courses in an assorted
environment of online assignments and exams and offline lectures, and exhibit the impact on academic routine of
factors such as classroom attendance, web-based course complement, and homework. We present grades from both
ordinary front ends and where the latter method controls for unobserved variation among students. A system
tailored intelligent instructional evaluation will generate the students, teachers & administration concepts,
discussing the predisposition in estimation when the ordinary evaluation method is used, resulting from the fact
that it ignores unobserved assorted. It also reduces the administrator’s load and helps provide the flexibility to
teacher’s need for mass evaluation. The Online Intelligent Semantic Performance based Solution is web
applications that ascertain an association between the institutes and the students. Institutes enter on the site, the
concepts they want in the exam. The questions based on the relevant concept and the syllabus is displayed as a test
to the eligible students. The answers entered by the students are then evaluated and their score is calculated and
saved. This score then can be accessed by the institutes to determine the passes students or to evaluate their
performance. It has been successfully applied to the distance evaluation of basic operating skills of computer
science, such as the course of computer skills in Universities and the local examination for the under graduates in
faridabad, Haryana.
CRITERION BASED AUTOMATIC GENERATION OF QUESTION PAPERvivatechijri
In any educational course curriculum, the courses are defined with learning objectives. Teachers conduct assessments to know if students have achieved certain learning objectives or not. The Proposed System provides a solution to choose challenging, well framed questions and make it easy for the user to generate it within a short period of time. The existing tools are rigid and support very basic or limited parameters. In our system we allow admin and user to input a set of questions and mark them with parameters such as difficulty level, complexity, type of question, module, min and max weightage. It contains two modules namely admin module and user module and the question management makes it an effortless task. From the entered input the paper is generated and saved as a .pdf file which can be kept for own or distributed as per the user or admin requirements. The required software and hardware are easily available and easy to work with. The goal is to simplify its current manual method, by means of computerised equipment and complete computer applications, in order to meet its needs, so that its important data/information can be stored for a longer period of time with easy access and manipulation. Basically the project describes how to manage for good performance and better services for the clients.
Similar to IRJET- Personalized E-Learning using Learner’s Capability Score (LCS) (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network