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.
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This document discusses using data mining techniques to analyze student performance data and predict student outcomes. It begins with an introduction to data mining and its applications in education. The paper then reviews related work using classification and clustering algorithms to predict student grades, classify students, and identify at-risk students. The proposed methodology would apply clustering algorithms to student data from a college to group students and identify relationships that can help understand performance. The system architecture and requirements are then outlined along with advantages of the system and a conclusion.
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This document describes a proposed student placement recommender and evaluator system. The system would allow students to create profiles, companies to view student resumes, and an admin to moderate the system. It would assess student aptitude through tests and compatibility with domains. Machine learning algorithms like decision trees would analyze student data like marks and skills to predict placement and recommend domains. The system aims to help students, companies, and colleges by facilitating the placement process and providing career guidance to students.
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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.
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This document presents a conceptual framework for predicting student academic performance using classification algorithms. The framework uses factors like socioeconomic status, psychological attributes, cognitive attributes, and lifestyle to analyze student performance based on their semester GPA. The document proposes classifying student performance into three classes (first class, second class, third class) based on their first semester GPA. Various classification algorithms like Naive Bayes, random forest, and bagging are evaluated on the student data to identify the best model for predicting performance. The conceptual framework is intended to guide the development of a recommendation system that can help educational institutions identify at-risk students early and improve student outcomes.
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This document summarizes a research paper that reviewed techniques for course recommendation systems. It discussed four main recommendation approaches: content-based, collaborative filtering, knowledge-based, and hybrid systems. For each approach, it provided examples of previous research studies that utilized each approach. It also discussed challenges like cold starts, data sparsity, and privacy issues. Machine learning algorithms commonly used included clustering, classification, and association rule mining. The paper analyzed selected publications to evaluate different recommendation systems for online education. Overall, the document provided a comprehensive overview of course recommendation techniques and issues.
This document summarizes a literature review on predicting student academic performance using data mining techniques. It discusses two key aspects: important factors that influence student performance and commonly used prediction algorithms.
The most important factors found to impact student performance are academic attributes like GPA, grades, attendance as well as family attributes. Prediction algorithms frequently used are classification models like decision trees, which can predict performance with over 95% accuracy when using influential attributes. Overall, the review aims to identify factors influencing performance and effective data mining methods for forecasting student outcomes.
A WEB BASED APPLICATION FOR TUTORING SUPPORT IN HIGHER EDUCATION USING EDUCAT...IRJET Journal
This document describes a web-based application for tutoring support in higher education using educational data mining. The application aims to help students select appropriate colleges based on previous college cut-off performances. It uses data mining techniques to predict colleges based on attributes like student aggregate percentage, category, branch, and college information from previous years. The application has three modules - Admin, College, and Student. Colleges can register and provide cut-off details. Students can search for matching colleges based on their profile. The document discusses the literature review, system design, algorithms, and results of the study. It aims to minimize student confusion and help them select colleges without losing admission opportunities.
IRJET- Analysis of Student Performance using Machine Learning TechniquesIRJET Journal
This document discusses using machine learning techniques to analyze student performance data and predict student outcomes. It begins with an abstract describing how educational data has become important for supporting student success. It then discusses prior related work applying classification algorithms like decision trees to predict student grades or performance. The document goes on to describe applying various classification algorithms like J48 decision trees, K-nearest neighbors, and others to student data and comparing their performance at predicting outcomes. It discusses preprocessing the data with k-means clustering before classification. The goal is to identify at-risk students early to better support them.
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This document discusses using data mining techniques to analyze student performance data and predict student outcomes. It begins with an introduction to data mining and its applications in education. The paper then reviews related work using classification and clustering algorithms to predict student grades, classify students, and identify at-risk students. The proposed methodology would apply clustering algorithms to student data from a college to group students and identify relationships that can help understand performance. The system architecture and requirements are then outlined along with advantages of the system and a conclusion.
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This document describes a proposed student placement recommender and evaluator system. The system would allow students to create profiles, companies to view student resumes, and an admin to moderate the system. It would assess student aptitude through tests and compatibility with domains. Machine learning algorithms like decision trees would analyze student data like marks and skills to predict placement and recommend domains. The system aims to help students, companies, and colleges by facilitating the placement process and providing career guidance to students.
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.
IRJET- A Conceptual Framework to Predict Academic Performance of Students usi...IRJET Journal
This document presents a conceptual framework for predicting student academic performance using classification algorithms. The framework uses factors like socioeconomic status, psychological attributes, cognitive attributes, and lifestyle to analyze student performance based on their semester GPA. The document proposes classifying student performance into three classes (first class, second class, third class) based on their first semester GPA. Various classification algorithms like Naive Bayes, random forest, and bagging are evaluated on the student data to identify the best model for predicting performance. The conceptual framework is intended to guide the development of a recommendation system that can help educational institutions identify at-risk students early and improve student outcomes.
A Comprehensive Review of Relevant Techniques used in Course Recommendation S...IRJET Journal
This document summarizes a research paper that reviewed techniques for course recommendation systems. It discussed four main recommendation approaches: content-based, collaborative filtering, knowledge-based, and hybrid systems. For each approach, it provided examples of previous research studies that utilized each approach. It also discussed challenges like cold starts, data sparsity, and privacy issues. Machine learning algorithms commonly used included clustering, classification, and association rule mining. The paper analyzed selected publications to evaluate different recommendation systems for online education. Overall, the document provided a comprehensive overview of course recommendation techniques and issues.
This document summarizes a literature review on predicting student academic performance using data mining techniques. It discusses two key aspects: important factors that influence student performance and commonly used prediction algorithms.
The most important factors found to impact student performance are academic attributes like GPA, grades, attendance as well as family attributes. Prediction algorithms frequently used are classification models like decision trees, which can predict performance with over 95% accuracy when using influential attributes. Overall, the review aims to identify factors influencing performance and effective data mining methods for forecasting student outcomes.
A WEB BASED APPLICATION FOR TUTORING SUPPORT IN HIGHER EDUCATION USING EDUCAT...IRJET Journal
This document describes a web-based application for tutoring support in higher education using educational data mining. The application aims to help students select appropriate colleges based on previous college cut-off performances. It uses data mining techniques to predict colleges based on attributes like student aggregate percentage, category, branch, and college information from previous years. The application has three modules - Admin, College, and Student. Colleges can register and provide cut-off details. Students can search for matching colleges based on their profile. The document discusses the literature review, system design, algorithms, and results of the study. It aims to minimize student confusion and help them select colleges without losing admission opportunities.
IRJET- Analysis of Student Performance using Machine Learning TechniquesIRJET Journal
This document discusses using machine learning techniques to analyze student performance data and predict student outcomes. It begins with an abstract describing how educational data has become important for supporting student success. It then discusses prior related work applying classification algorithms like decision trees to predict student grades or performance. The document goes on to describe applying various classification algorithms like J48 decision trees, K-nearest neighbors, and others to student data and comparing their performance at predicting outcomes. It discusses preprocessing the data with k-means clustering before classification. The goal is to identify at-risk students early to better support them.
The document is a project report for a Student Information System. It includes an abstract describing the system as providing an interface to maintain student records and generate various reports. It also includes sections on the introduction, objectives, functions, methodology, requirements, diagrams, screenshots, and database design of the student information system project.
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.
This document describes a Dynamic Attendance Management System (DAMS) that was developed to more efficiently manage student and teacher attendance records using a centralized database and web interface. The system allows attendance to be taken and updated live, and personalized reports to be generated. It also functions as a student-teacher portal. Data mining techniques are applied to the attendance data to identify trends and predict student performance. Classification algorithms like ID3 and C4.5 are used to analyze factors like attendance, test scores, and past academic performance to generate performance predictions. The system aims to make attendance management simpler and more accessible through an easy-to-use interface and database backend.
M-Learners Performance Using Intelligence and Adaptive E-Learning Classify th...IRJET Journal
This document discusses using machine learning classification algorithms to predict student performance based on educational data. It compares the performance of five classification algorithms - J48, Naive Bayes, Bayes Net, Backpropagation Network, and Radial Basis Function Network - in predicting student academic achievement using attributes like demographic information, test scores, and academic factors. The experiment found that the Radial Basis Function Network algorithm achieved the highest accuracy, correctly classifying 100% of instances, compared to 75-95% accuracy for the other algorithms. Convolutional neural networks are also discussed as a powerful tool for image and language processing in educational data mining.
IRJET- Student Performance Analysis System for Higher Secondary EducationIRJET Journal
This document presents a student performance analysis system that was developed to analyze educational data and student performance. The system allows students to log in, enter their details and exam marks. It then provides graphical analysis of student performance individually and overall by subject. Reports can also be generated showing a student's marks, percentage and pass/fail status. The system aims to identify weaker students and help improve their academic results. It was developed using data mining concepts to analyze data from higher secondary students. Future work could expand it to predict student performance and guide them in their education and career paths.
IRJET - Recommendation of Branch of Engineering using Machine LearningIRJET Journal
This document describes a machine learning system that recommends engineering branches to students based on their scores. It uses K-nearest neighbors and collaborative filtering techniques. The system aims to help students select an engineering branch that matches their abilities and reduces confusion. It analyzes student data like marks to make personalized recommendations. The document reviews similar existing recommendation systems and the techniques they use. The proposed system seeks to guide students towards suitable engineering fields and reduce the workload on counselors.
This document discusses the planning and design of a web-based teaching evaluation system. It begins by outlining the limitations of traditional paper-based evaluation systems, such as being labor intensive and resulting in delays. The document then proposes moving to an online system, which offers increased efficiency, flexibility and accessibility. It discusses stakeholder needs assessment, literature reviews of existing university systems, and design considerations such as customization options, data security, and response rates. The proposed system would use a client-server model with a MYSQL database to store evaluation responses. The goal is to create a flexible system that integrates with other university systems and meets stakeholder needs.
This document discusses the development of a web-based teaching evaluation system for Jerash University in Jordan. It begins with an introduction that outlines the typical paper-based teaching evaluation process used in higher education and its limitations. The document then discusses the benefits of moving to an online system, including increased efficiency, flexibility, and the ability to customize evaluations. It describes the methodology used to develop recommendations for the system, which included analyzing stakeholder needs, researching best practices, and reviewing literature on existing university evaluation systems. The goal of the project is to design and implement a new online evaluation system for Jerash University using technologies like PHP and MySQL.
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.
Multiple educational data mining approaches to discover patterns in universit...IJICTJOURNAL
This paper presented the utilization of pattern discovery techniques by using multiple relationships and clustering educational data mining approaches to establish a knowledge base that will aid in the prediction of ideal college program selection and enrollment forecasting for incoming freshmen. Results show a significant level of accuracy in predicting college programs for students by mining two years of student college admission and graduation final grade scholastic records. The results of educational predictive data mining methods can be applied in improving the services of the admission department of an educational institution, particularly in its course alignment, student mentoring, admission forecast, marketing, and enrollment preparedness.
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- Performance for Student Higher Education using Decision Tree to Predic...IRJET Journal
This document discusses using decision trees to predict career decisions for 12th grade students in India. It first provides background on the challenges in the Indian education system and how data mining can help improve decision making. It then reviews previous studies applying various data mining techniques like decision trees and random forests to predict student performance. The paper proposes using a decision tree approach on student data to distinguish slow and fast learners and help students make better career choices based on their interests and skills. The decision tree approach achieved 80% accuracy in predicting student career decisions, helping students choose appropriate paths.
This document describes a web application called "Placements Analytics and Dashboard" that is designed to store, analyze, and visualize placement data for students who have secured jobs in software companies. The application provides interactive dashboards, reports, and visualizations like pie charts and bar graphs to analyze trends in placements over time. This includes insights into the most in-demand skills, top hiring companies, and placement trends by year. The goal is to empower students to make informed choices about their education and career paths based on data-driven insights into the job market and software industry.
Result generation system for cbgs scheme in educational organizationeSAT Journals
generation system. We will try to implement the rules as per University norms
according to the CBGS system. The necessity of this system is to ease the process of result generation and once the data is fed in
the system, could be used to calculate the result and generate it in the desired format. We can analyze this data and generate
various reports needed using some data mining techniques. The objective is to generate result that will be semester wise for each
student. Analyzing these reports would give various parameters such as students passing or failing, semester wise as well as
subject wise. The software will be accessible only to authorized users so that security could be maintained.
Key Words: CBGS System
A Review on Student Result Management SystemIRJET Journal
The document discusses the development of a web-based student result management system. It provides context on the current manual process used at the Catholic University of Mozambique to manage student results. The goal of the new system is to save time, effort and money while improving security. The system was developed using technologies like PHP, MySQL database, Apache Tomcat server, and the MVC architecture pattern. It allows students to check their results and faculty to view pass/fail rates. The document also reviews related literature on existing student information and result management systems and their features.
The document discusses the development of a computer-based grading system for the Technological University of the Philippines. It aims to replace the current manual grading system by automatically importing grades from teacher records and printing them in different formats. The proposed system would also allow storage and access of old student data. It seeks to address problems with the current system like delays in grade submission and issuance. The computer-based grading system would create a more user-friendly interface using a database to store student information. It is intended to benefit faculty by reducing effort, students by lessening delays, and the university by improving processing of grade reports. The scope is limited to implementation of the system using Visual Basic and Microsoft Access.
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.
A New Approach of Analysis of Student Results by using MapReduceIRJET Journal
1) The document proposes using Hadoop and MapReduce to analyze student result data to provide predictive modeling and insights. This can help students, faculty, and administrators improve outcomes.
2) Traditional data analysis methods take a long time when dealing with large datasets. Hadoop can distribute the work across clusters to speed up analysis. MapReduce breaks the work into smaller tasks that can run in parallel.
3) The proposed system would use Hadoop to extract and analyze accident data, then use predictive modeling to forecast times and locations of high accident rates. Encryption would secure the data during network transfer.
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.
This paper introduces the competency models for Operations Manager, User Interface
Designer, and Application Developers. It will serve as a guide for Information Systems students
to identify which among the three of the offered tracks would be most suited for them to pursue
according to their knowledge, skills, values and interests. The Holland’s RIASEC model and the
Values Search model of Bronwyn and Holt were utilized to determine the most dominant interest
and most dominant values of the industry computing experts. Survey assessment forms were sent
to IT Operations Manager, User Interface Designer, and Application Developer. Most dominant
values and interests of industry computing experts were determined as well as the knowledge
and skills which are mostly required by the industry in their particular area. Based on the result
of the survey, it shows that application developer and user interface designer have a closely
related values. Thus a second round of a survey would be needed to come up with the most
exclusive dominant values for the particular information systems specialization track.
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
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This document describes a machine learning system that recommends engineering branches to students based on their scores. It uses K-nearest neighbors and collaborative filtering techniques. The system aims to help students select an engineering branch that matches their abilities and reduces confusion. It analyzes student data like marks to make personalized recommendations. The document reviews similar existing recommendation systems and the techniques they use. The proposed system seeks to guide students towards suitable engineering fields and reduce the workload on counselors.
This document discusses the planning and design of a web-based teaching evaluation system. It begins by outlining the limitations of traditional paper-based evaluation systems, such as being labor intensive and resulting in delays. The document then proposes moving to an online system, which offers increased efficiency, flexibility and accessibility. It discusses stakeholder needs assessment, literature reviews of existing university systems, and design considerations such as customization options, data security, and response rates. The proposed system would use a client-server model with a MYSQL database to store evaluation responses. The goal is to create a flexible system that integrates with other university systems and meets stakeholder needs.
This document discusses the development of a web-based teaching evaluation system for Jerash University in Jordan. It begins with an introduction that outlines the typical paper-based teaching evaluation process used in higher education and its limitations. The document then discusses the benefits of moving to an online system, including increased efficiency, flexibility, and the ability to customize evaluations. It describes the methodology used to develop recommendations for the system, which included analyzing stakeholder needs, researching best practices, and reviewing literature on existing university evaluation systems. The goal of the project is to design and implement a new online evaluation system for Jerash University using technologies like PHP and MySQL.
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This document describes a web application called "Placements Analytics and Dashboard" that is designed to store, analyze, and visualize placement data for students who have secured jobs in software companies. The application provides interactive dashboards, reports, and visualizations like pie charts and bar graphs to analyze trends in placements over time. This includes insights into the most in-demand skills, top hiring companies, and placement trends by year. The goal is to empower students to make informed choices about their education and career paths based on data-driven insights into the job market and software industry.
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generation system. We will try to implement the rules as per University norms
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subject wise. The software will be accessible only to authorized users so that security could be maintained.
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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
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This paper introduces the competency models for Operations Manager, User Interface
Designer, and Application Developers. It will serve as a guide for Information Systems students
to identify which among the three of the offered tracks would be most suited for them to pursue
according to their knowledge, skills, values and interests. The Holland’s RIASEC model and the
Values Search model of Bronwyn and Holt were utilized to determine the most dominant interest
and most dominant values of the industry computing experts. Survey assessment forms were sent
to IT Operations Manager, User Interface Designer, and Application Developer. Most dominant
values and interests of industry computing experts were determined as well as the knowledge
and skills which are mostly required by the industry in their particular area. Based on the result
of the survey, it shows that application developer and user interface designer have a closely
related values. Thus a second round of a survey would be needed to come up with the most
exclusive dominant values for the particular information systems specialization track.
Similar to University Recommendation Support System using ML Algorithms (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.
Better Builder Magazine brings together premium product manufactures and leading builders to create better differentiated homes and buildings that use less energy, save water and reduce our impact on the environment. The magazine is published four times a year.
Sachpazis_Consolidation Settlement Calculation Program-The Python Code and th...Dr.Costas Sachpazis
Consolidation Settlement Calculation Program-The Python Code
By Professor Dr. Costas Sachpazis, Civil Engineer & Geologist
This program calculates the consolidation settlement for a foundation based on soil layer properties and foundation data. It allows users to input multiple soil layers and foundation characteristics to determine the total settlement.
This is an overview of my current metallic design and engineering knowledge base built up over my professional career and two MSc degrees : - MSc in Advanced Manufacturing Technology University of Portsmouth graduated 1st May 1998, and MSc in Aircraft Engineering Cranfield University graduated 8th June 2007.
Data Communication and Computer Networks Management System Project Report.pdfKamal Acharya
Networking is a telecommunications network that allows computers to exchange data. In
computer networks, networked computing devices pass data to each other along data
connections. Data is transferred in the form of packets. The connections between nodes are
established using either cable media or wireless media.
An In-Depth Exploration of Natural Language Processing: Evolution, Applicatio...DharmaBanothu
Natural language processing (NLP) has
recently garnered significant interest for the
computational representation and analysis of human
language. Its applications span multiple domains such
as machine translation, email spam detection,
information extraction, summarization, healthcare,
and question answering. This paper first delineates
four phases by examining various levels of NLP and
components of Natural Language Generation,
followed by a review of the history and progression of
NLP. Subsequently, we delve into the current state of
the art by presenting diverse NLP applications,
contemporary trends, and challenges. Finally, we
discuss some available datasets, models, and
evaluation metrics in NLP.