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.
IRJET- Automated Attendance System using Face RecognitionIRJET Journal
1) The document describes an automated attendance system using face recognition from video frames with deep learning. The system captures real-time video and can generate attendance reports with improved accuracy.
2) It reviews previous works on automated attendance systems using face recognition. Some key approaches discussed include using Local Binary Pattern Histograms and correlations for face detection and recognition, principal component analysis, and combining principal component analysis with artificial neural networks.
3) The proposed system aims to develop an accurate and efficient automated attendance management system using video surveillance and face recognition to capture and mark the presence of students and employees in real-time.
Face Recognition Based Attendance System with Auto Alert to Guardian using Ca...ijtsrd
This document presents a face recognition based attendance system that automatically marks student attendance using image processing techniques. It uses the Viola-Jones face detection algorithm to detect faces in images and then performs face recognition using algorithms like PCA to identify students and mark their attendance in a database. It also provides alerts to guardians if a student is marked absent by sending SMS or making phone calls. The system aims to automate the manual attendance marking process which is time-consuming and error-prone. It discusses the architecture of the system and the face detection and recognition algorithms used in detail. The paper concludes that the automatic attendance system replaces the manual process and is faster, more efficient and saves time and costs.
This documentation provides a brief insight of face recognition based attendance system using neural networks in terms of product architecture which can be used for educational purpose.
Smart application for ams using face recognitioncseij
Attendance Management System (AMS) can be made into smarter way by using face recognition technique, where we use a CCTV camera to be fixed at the entry point of a classroom, which automatically captures the image of the person and checks the observed image with the face database using android enhanced smart phone.
It is typically used for two purposes. Firstly, marking attendance for student by comparing the face images produced recently and secondly, recognition of human who are strange to the environment i.e. an unauthorized person
For verification of image, a newly emerging trend 3D Face Recognition is used which claims to provide more accuracy in matching the image databases and has an ability to recognize a subject at different view angles.
The document discusses using facial recognition for attendance tracking in a school setting. It proposes developing a system that uses real-time face detection and Principal Component Analysis to match detected faces to staff members and automatically record their attendance. This would eliminate the manual and time-consuming process of logging attendance. The system would enroll staff faces during a one-time process and then identify and update their attendance in a database system in real-time. Research shows this type of automatic attendance tracking outperforms manual systems and provides more efficient leave and interface management.
Project synopsis on face recognition in e attendanceNitesh Dubey
This document provides a project synopsis for a face recognition-based e-attendance system. It discusses developing an automated attendance system using face recognition technology to address issues with traditional manual attendance methods, such as being time-consuming and allowing for fraudulent attendance. The objectives are to help teachers track and manage student attendance and absenteeism more efficiently. The proposed system uses face detection and recognition algorithms to automatically mark student attendance based on detecting faces in the classroom. It includes modules for image capture, face detection, preprocessing, database development, and postprocessing for recognition. Feasibility analysis indicates the technical feasibility of the system using existing technologies. Methodology diagrams show the training and recognition workflows that involve face detection, feature extraction, and classification.
Automated attendance system using Face recognitionIRJET Journal
This document describes an automated attendance system using face recognition. The system uses image capture to take photos of students entering the classroom. It then uses the Viola-Jones algorithm for face detection and PCA for feature selection and SVM for classification to recognize students' faces and mark their attendance automatically. When compared to traditional attendance methods, this system saves time and helps monitor students. It discusses related work using RFID, fingerprints, and iris recognition for attendance systems. It outlines the proposed system's modules for image capture, face detection, preprocessing, database development, and postprocessing. Finally, it discusses results, conclusions, and opportunities for future work to improve recognition rates under various conditions.
Face Recognition Based Attendance System using Machine LearningYogeshIJTSRD
In the era of modern technologies emerging at rapid pace there is no reason why a crucial event in education sector such as attendance should be done in the old boring traditional way. Attendance monitoring system will save a lot of time and energy for the both parties teaching staff as well as the students. Attendance will be monitored by the face recognition algorithm by recognizing only the face of the students from the rest of the objects and then marking the students as present. The system will be pre feed with the images of all the students enrolled in the class and with the help of this pre feed data the algorithm will detect the students who are present and match the features with the already saved images of the students in the database. Benazir Begum A | Sreeyuktha R | Haritha M P | Vishnuprasad "Face Recognition Based Attendance System using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39856.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/39856/face-recognition-based-attendance-system-using-machine-learning/benazir-begum-a
IRJET- Automated Attendance System using Face RecognitionIRJET Journal
1) The document describes an automated attendance system using face recognition from video frames with deep learning. The system captures real-time video and can generate attendance reports with improved accuracy.
2) It reviews previous works on automated attendance systems using face recognition. Some key approaches discussed include using Local Binary Pattern Histograms and correlations for face detection and recognition, principal component analysis, and combining principal component analysis with artificial neural networks.
3) The proposed system aims to develop an accurate and efficient automated attendance management system using video surveillance and face recognition to capture and mark the presence of students and employees in real-time.
Face Recognition Based Attendance System with Auto Alert to Guardian using Ca...ijtsrd
This document presents a face recognition based attendance system that automatically marks student attendance using image processing techniques. It uses the Viola-Jones face detection algorithm to detect faces in images and then performs face recognition using algorithms like PCA to identify students and mark their attendance in a database. It also provides alerts to guardians if a student is marked absent by sending SMS or making phone calls. The system aims to automate the manual attendance marking process which is time-consuming and error-prone. It discusses the architecture of the system and the face detection and recognition algorithms used in detail. The paper concludes that the automatic attendance system replaces the manual process and is faster, more efficient and saves time and costs.
This documentation provides a brief insight of face recognition based attendance system using neural networks in terms of product architecture which can be used for educational purpose.
Smart application for ams using face recognitioncseij
Attendance Management System (AMS) can be made into smarter way by using face recognition technique, where we use a CCTV camera to be fixed at the entry point of a classroom, which automatically captures the image of the person and checks the observed image with the face database using android enhanced smart phone.
It is typically used for two purposes. Firstly, marking attendance for student by comparing the face images produced recently and secondly, recognition of human who are strange to the environment i.e. an unauthorized person
For verification of image, a newly emerging trend 3D Face Recognition is used which claims to provide more accuracy in matching the image databases and has an ability to recognize a subject at different view angles.
The document discusses using facial recognition for attendance tracking in a school setting. It proposes developing a system that uses real-time face detection and Principal Component Analysis to match detected faces to staff members and automatically record their attendance. This would eliminate the manual and time-consuming process of logging attendance. The system would enroll staff faces during a one-time process and then identify and update their attendance in a database system in real-time. Research shows this type of automatic attendance tracking outperforms manual systems and provides more efficient leave and interface management.
Project synopsis on face recognition in e attendanceNitesh Dubey
This document provides a project synopsis for a face recognition-based e-attendance system. It discusses developing an automated attendance system using face recognition technology to address issues with traditional manual attendance methods, such as being time-consuming and allowing for fraudulent attendance. The objectives are to help teachers track and manage student attendance and absenteeism more efficiently. The proposed system uses face detection and recognition algorithms to automatically mark student attendance based on detecting faces in the classroom. It includes modules for image capture, face detection, preprocessing, database development, and postprocessing for recognition. Feasibility analysis indicates the technical feasibility of the system using existing technologies. Methodology diagrams show the training and recognition workflows that involve face detection, feature extraction, and classification.
Automated attendance system using Face recognitionIRJET Journal
This document describes an automated attendance system using face recognition. The system uses image capture to take photos of students entering the classroom. It then uses the Viola-Jones algorithm for face detection and PCA for feature selection and SVM for classification to recognize students' faces and mark their attendance automatically. When compared to traditional attendance methods, this system saves time and helps monitor students. It discusses related work using RFID, fingerprints, and iris recognition for attendance systems. It outlines the proposed system's modules for image capture, face detection, preprocessing, database development, and postprocessing. Finally, it discusses results, conclusions, and opportunities for future work to improve recognition rates under various conditions.
Face Recognition Based Attendance System using Machine LearningYogeshIJTSRD
In the era of modern technologies emerging at rapid pace there is no reason why a crucial event in education sector such as attendance should be done in the old boring traditional way. Attendance monitoring system will save a lot of time and energy for the both parties teaching staff as well as the students. Attendance will be monitored by the face recognition algorithm by recognizing only the face of the students from the rest of the objects and then marking the students as present. The system will be pre feed with the images of all the students enrolled in the class and with the help of this pre feed data the algorithm will detect the students who are present and match the features with the already saved images of the students in the database. Benazir Begum A | Sreeyuktha R | Haritha M P | Vishnuprasad "Face Recognition Based Attendance System using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39856.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/39856/face-recognition-based-attendance-system-using-machine-learning/benazir-begum-a
A Real-time Classroom Attendance System Utilizing Viola–Jones for Face Detect...Nischal Lal Shrestha
This document provides a minor project report on developing a real-time classroom attendance system using face detection and recognition. The system utilizes the Viola-Jones algorithm for face detection and Local Binary Patterns Histogram (LBPH) for face recognition. It was developed by 4 students as a partial fulfillment of their Bachelor of Software Engineering degree at Nepal College of Information Technology. The report describes the methodology, system implementation including image acquisition, preprocessing, detection, recognition, and GUI development, as well as the deliverables, schedule, and future work.
Attendance Management System using Face RecognitionNanditaDutta4
The project ppt presentation is made for the academic session for the completion of the work from Bharati Vidyapeeth Deemed University(IMED) MCA department
In this project autonomous face detection and face recognition was achieved in MatLab through a standalone computer with web-cam. Face detection is utilized to locate the position of face region within the frame captured and face recognition is used for identification of the individual and the automate the attendance process. The database of all the students in the class is stored and when the face of the individual student matches with one of the faces stored in the database then the attendance is recorded.
IRJET - Facial Recognition based Attendance Management SystemIRJET Journal
This document summarizes a facial recognition-based attendance management system. The system uses facial recognition techniques to automatically take attendance by comparing photos of students in class to images stored in a database. It involves taking photos of students to create a training dataset, using those images to train a model to recognize faces, taking photos of classrooms, cropping out faces, running those cropped faces through the trained model to identify students, and recording attendance in a database. The system aims to automate attendance tracking to reduce workload for teachers and prevent issues like duplicate signatures.
This document summarizes a research paper that proposes an automated attendance monitoring system using face recognition. The system works by capturing images of students in a classroom, detecting faces in the images, recognizing the faces and comparing them to a database of student faces. Faces that do not match the database are identified as absent students. The system then sends SMS alerts about the absent students to their mobile numbers. The paper describes the methodology, hardware and software components of the system including the camera, display unit, microcontroller and MATLAB software. It provides results of testing the system and concludes the automated attendance system can help reduce issues with traditional manual attendance methods.
IRJET- Automation Software for Student Monitoring SystemIRJET Journal
This document proposes and evaluates an automated student monitoring system using various technologies. The system aims to more efficiently track student attendance by automating the process and eliminating issues like proxy attendance. It explores methods like face recognition using parameters like pose, sharpness and brightness. Other approaches examined include voiceprint recognition, RFID tags, and an Android-based system using barcodes and fingerprint sensors. The proposed system would make attendance tracking faster, more accurate, and paperless by automating the process through electronic sensors. It could prevent cheating but may have issues with lighting conditions or noise affecting biometric systems. An evaluation found such a semi-automated system using smartphone Wi-Fi fingerprinting and a k-NN algorithm could provide an inexpensive and effective
ANALYZING THE IMPACT OF INTERDEPENDENT DIMENSION ON TARGET ATTRIBUTEJournal For Research
Until today, most lecturers in universities are found still using the conventional methods of taking students attendance either by calling out the student names or by passing around an attendance sheet for students to sign confirming their presence.This project is absolutely on the android-based attendance management system. Android based attendance system provides efficient means of determining eligibility criteria for students to meet examination requirements. [1] The core idea of research project is to implement Android based application for attendance management system for advancement of institution and educational system [2]. This system enables student to learn anywhere, anytime and at their own convenience. This system makes students to be active, responsive while learning their academic. Another application that is provided by this system is smart attendance evaluation and report generation. [2]This makes the work even easier for the lecturers. Also there is a separate module for analyzing the results of the test exams of the students. There is a certain criterion to be met for each and every student to appearing for the test exam. The main objective of this paper is to provide an overview on the data mining techniques that have been used to predict students performance. [3]A certain action can be taken on students not fulfilling the criteria. This process basically aims at improving the overall student performance by taking into consideration student attendance and test marks.
This document summarizes a face recognition attendance system project. The project uses face recognition technology to take attendance by comparing captured images to stored student records. It has a completed status. The methodology follows a waterfall model. System diagrams include context, data flow, and architecture diagrams. The database stores student data like name, roll number, attendance, and captured images. The system allows for student registration by capturing images, training the model, and recognizing faces to mark attendance. Developing this project provided experience with real-world software development processes.
IRJET- Attendance Monitoring System using Face Detection &Face RecognitionIRJET Journal
This document describes an attendance monitoring system that uses face detection and face recognition technologies. A camera is installed in the classroom to capture images of students as they enter. Faces are detected and then recognized by comparing the images to a stored database of student faces. If a match is found, the student's attendance is marked. The system aims to automate the attendance process and make it more secure than traditional manual methods. Future work could involve automatically sending messages to parents if a student is detected as absent.
IRJET - A Review on: Face Recognition using LaplacianfaceIRJET Journal
This document reviews face recognition using LaplacianFace, an appearance-based method that maps face images into a subspace using Locality Preserving Projections (LPP) to analyze local information and detect essential face manifold structure. The Laplacianfaces are optimal linear approximations of the eigenfunctions of the Laplace Beltrami operator on the face manifold, which can eliminate unwanted variations from lighting, expression, and pose. The paper compares LaplacianFace to Eigenface and Fisherface methods on three datasets, finding Laplacianface provides better representation and lower error rates. It also surveys related work applying PCA, LDA, LPP and other techniques to challenges like single image training and discusses the LaplacianFace method's modules for loading images, res
IRJET- Syllabus and Timetable Generation SystemIRJET Journal
The document describes a proposed system called the Syllabus and Timetable Generation System that aims to automatically generate timetables and syllabi for educational institutions. It uses an algorithm that takes inputs like number of classes, subjects, days in a week, and lectures per day to randomly generate timetables for multiple classes without clashes. The algorithm employs recursion to prevent clashes across class timetables. It also includes a static faculty assignment method. The proposed system was able to automatically generate timetables and syllabi for 4 classes with 10 subjects, demonstrating the effectiveness of the algorithm in solving the complex task of timetable scheduling.
industrial training report on Ethical hackingNitesh Dubey
This document outlines an industrial training report on ethical hacking conducted at Alison Online Training Institute. It begins with an introduction to ethical hacking and the different types of hacking. It then discusses the role of security and penetration testers and different penetration testing methodologies. The document provides an overview of what can and cannot be done legally as an ethical hacker. It also discusses the basics of networking and what it takes to be a successful security tester.
Performance Analysis of Supervised Machine Learning Techniques for Sentiment ...Biswaranjan Samal
Wide use of internet and web applications like, feedback collection systems are now making peoples smarter. In these applications, peoples used to give their feedback about the movies, products, services, etc through which they have gone, and this feedback are publicly available for future references. It is a tedious task for the machines to identify the feedback types, i:e positive or negative. And here Machine Learning Techniques plays vital roles to train the machine and make it intelligent so that the machine will be able to identify the feedback type which may give more benefits and features for those web applications and the users. There are many supervised machine learning techniques are available so it is a difficult task to choose the best one. In this paper, we have collected the movie review datasets of different sizes and have selected some of the widely used and popular supervised machine learning algorithms, for training the model. So that the model will be able to categorize the review. Python's NLTK package along with the WinPython and Spyder are used for processing the movie reviews. Then Python's sklearn package is used for training the model and finding the accuracy of the model.
This document describes the development of an online intelligence quotient (IQ) tester system. The system is designed to test IQ for three different age groups (children, teens, adults) based on the Wechsler scales. It uses a Fisher-Yates shuffling algorithm to randomly select questions from a database to avoid repetition and improve accuracy. Users register with an age and take a 10 question test tailored to their age group. The system generates a report with the user's IQ score, level, and tips. It allows viewing past results for comparison over time. The goal is to provide a self-awareness tool and reduce issues with existing IQ tests.
Optimized Active Learning for User’s Behavior Modelling based on Non-Intrusiv...IJECEIAES
In order to protect the data in the smartphone, there is some protection mechanism that has been used. The current authentication uses PIN, password, and biometric-based method. These authentication methods are not sufficient due to convenience and security issue. Non-Intrusive authentication is more comfortable because it just collects user’s behavior to authenticate the user to the smartphone. Several non-intrusive authentication mechanisms were proposed but they do not care about the training sample that has a long data collection time. This paper propose a method to collect data more efficient using Optimized Active Learning. The Support Vector Machine (SVM) used to identify the effect of some small amount of training data. This proposed system has two main functionalities, to reduce the training data using optimized stop rule and maintain the Error Rate using modified model analysis to determine the training data that fit for each user.Finally, after we done the experiment, we conclude that our proposed system is better than Threshold-based Active Learning. The time required to collect the data can reduced to 41% from 17 to 10 minutes with the same Error Rate.
Ignou MCA 4th semester mini project report. College admission system. This project is based on real working system of University seat allocation to affiliate colleges. College admission system provide seat allocation process for various UG PG programs for every academic session.
Survey Paper on : College Automation System using Face Recognition with RFIDIRJET Journal
This document summarizes a proposed college automation system using face recognition and RFID technologies. The system aims to automate student attendance tracking to reduce manual work. It would use face recognition cameras at the college entrance to identify students and mark partial attendance. In classrooms, an RFID reader would record when students scan their RFID tags to mark full attendance. The face recognition and RFID records would be merged to generate attendance reports. The reports along with other student and college information would be available on a web portal and mobile apps for teachers, students, and parents. The system is intended to streamline attendance tracking and information sharing between stakeholders while reducing proxies and manual effort.
The document describes a project report submitted by 5 students for their Bachelor of Technology degree. It outlines the development of an IIMSR Student Management System. The system will manage student records like personal details, contact details, marks details, and other functions like student/faculty profiles, marks submission, attendance records, examination results, and timetable management. It conducted a feasibility study and identified problems with the current manual system. The project aims to automate the process and make it more efficient by reducing paperwork.
This document describes an online assignment system that allows students and faculty to communicate about assignments digitally. Key features include:
1) Students can submit assignments online and faculty can grade them and provide feedback without paper.
2) The system uses keyword matching to automatically determine the best student answer by comparing responses to keywords provided by the faculty. This answer can then be highlighted for other students.
3) Faculty can generate practice question papers from the pool of assignment questions.
4) The paperless system aims to improve efficiency by reducing paperwork and human effort for both students and faculty.
The document describes a proposed student information system that would allow institutions to more easily manage student data. It would include functions for recording, searching, modifying, and deleting student records. The system would use a prototyping model since requirements are not yet fully defined. It then provides details on the hardware, software, and functional requirements including use of a SQL database, Windows OS, and securing student data.
IRJET- Intelligent Automated Attendance System based on Facial RecognitionIRJET Journal
This document presents a proposed intelligent automated attendance system based on facial recognition. The system aims to automate the attendance marking process in educational institutions to make it faster and less error-prone compared to manual methods. It works by using computer vision techniques like haar cascade classification for face detection and local binary pattern histograms for face recognition. The system architecture involves capturing images, detecting faces, recognizing students by matching faces to a training database, and marking the attendance automatically. Algorithms like haar cascade and local binary patterns are used for face detection and recognition. The proposed system aims to solve issues with existing manual and automated attendance systems like time consumption, errors, and lack of accuracy.
IRJET - Facial Recognition based Attendance System with LBPHIRJET Journal
This document presents a facial recognition based attendance system using LBPH (Local Binary Pattern Histograms). It begins with an abstract describing the system which takes student attendance using facial identification from classroom camera images. It then discusses related work in attendance and face recognition systems. The proposed system workflow is described involving face detection, feature extraction using LBPH, template matching, and attendance recording. Experimental results demonstrate the system's ability to detect multiple faces and record attendance accurately in an Excel sheet with date/time. The conclusion discusses how the system reduces human effort for attendance and increases learning time compared to traditional methods.
A Real-time Classroom Attendance System Utilizing Viola–Jones for Face Detect...Nischal Lal Shrestha
This document provides a minor project report on developing a real-time classroom attendance system using face detection and recognition. The system utilizes the Viola-Jones algorithm for face detection and Local Binary Patterns Histogram (LBPH) for face recognition. It was developed by 4 students as a partial fulfillment of their Bachelor of Software Engineering degree at Nepal College of Information Technology. The report describes the methodology, system implementation including image acquisition, preprocessing, detection, recognition, and GUI development, as well as the deliverables, schedule, and future work.
Attendance Management System using Face RecognitionNanditaDutta4
The project ppt presentation is made for the academic session for the completion of the work from Bharati Vidyapeeth Deemed University(IMED) MCA department
In this project autonomous face detection and face recognition was achieved in MatLab through a standalone computer with web-cam. Face detection is utilized to locate the position of face region within the frame captured and face recognition is used for identification of the individual and the automate the attendance process. The database of all the students in the class is stored and when the face of the individual student matches with one of the faces stored in the database then the attendance is recorded.
IRJET - Facial Recognition based Attendance Management SystemIRJET Journal
This document summarizes a facial recognition-based attendance management system. The system uses facial recognition techniques to automatically take attendance by comparing photos of students in class to images stored in a database. It involves taking photos of students to create a training dataset, using those images to train a model to recognize faces, taking photos of classrooms, cropping out faces, running those cropped faces through the trained model to identify students, and recording attendance in a database. The system aims to automate attendance tracking to reduce workload for teachers and prevent issues like duplicate signatures.
This document summarizes a research paper that proposes an automated attendance monitoring system using face recognition. The system works by capturing images of students in a classroom, detecting faces in the images, recognizing the faces and comparing them to a database of student faces. Faces that do not match the database are identified as absent students. The system then sends SMS alerts about the absent students to their mobile numbers. The paper describes the methodology, hardware and software components of the system including the camera, display unit, microcontroller and MATLAB software. It provides results of testing the system and concludes the automated attendance system can help reduce issues with traditional manual attendance methods.
IRJET- Automation Software for Student Monitoring SystemIRJET Journal
This document proposes and evaluates an automated student monitoring system using various technologies. The system aims to more efficiently track student attendance by automating the process and eliminating issues like proxy attendance. It explores methods like face recognition using parameters like pose, sharpness and brightness. Other approaches examined include voiceprint recognition, RFID tags, and an Android-based system using barcodes and fingerprint sensors. The proposed system would make attendance tracking faster, more accurate, and paperless by automating the process through electronic sensors. It could prevent cheating but may have issues with lighting conditions or noise affecting biometric systems. An evaluation found such a semi-automated system using smartphone Wi-Fi fingerprinting and a k-NN algorithm could provide an inexpensive and effective
ANALYZING THE IMPACT OF INTERDEPENDENT DIMENSION ON TARGET ATTRIBUTEJournal For Research
Until today, most lecturers in universities are found still using the conventional methods of taking students attendance either by calling out the student names or by passing around an attendance sheet for students to sign confirming their presence.This project is absolutely on the android-based attendance management system. Android based attendance system provides efficient means of determining eligibility criteria for students to meet examination requirements. [1] The core idea of research project is to implement Android based application for attendance management system for advancement of institution and educational system [2]. This system enables student to learn anywhere, anytime and at their own convenience. This system makes students to be active, responsive while learning their academic. Another application that is provided by this system is smart attendance evaluation and report generation. [2]This makes the work even easier for the lecturers. Also there is a separate module for analyzing the results of the test exams of the students. There is a certain criterion to be met for each and every student to appearing for the test exam. The main objective of this paper is to provide an overview on the data mining techniques that have been used to predict students performance. [3]A certain action can be taken on students not fulfilling the criteria. This process basically aims at improving the overall student performance by taking into consideration student attendance and test marks.
This document summarizes a face recognition attendance system project. The project uses face recognition technology to take attendance by comparing captured images to stored student records. It has a completed status. The methodology follows a waterfall model. System diagrams include context, data flow, and architecture diagrams. The database stores student data like name, roll number, attendance, and captured images. The system allows for student registration by capturing images, training the model, and recognizing faces to mark attendance. Developing this project provided experience with real-world software development processes.
IRJET- Attendance Monitoring System using Face Detection &Face RecognitionIRJET Journal
This document describes an attendance monitoring system that uses face detection and face recognition technologies. A camera is installed in the classroom to capture images of students as they enter. Faces are detected and then recognized by comparing the images to a stored database of student faces. If a match is found, the student's attendance is marked. The system aims to automate the attendance process and make it more secure than traditional manual methods. Future work could involve automatically sending messages to parents if a student is detected as absent.
IRJET - A Review on: Face Recognition using LaplacianfaceIRJET Journal
This document reviews face recognition using LaplacianFace, an appearance-based method that maps face images into a subspace using Locality Preserving Projections (LPP) to analyze local information and detect essential face manifold structure. The Laplacianfaces are optimal linear approximations of the eigenfunctions of the Laplace Beltrami operator on the face manifold, which can eliminate unwanted variations from lighting, expression, and pose. The paper compares LaplacianFace to Eigenface and Fisherface methods on three datasets, finding Laplacianface provides better representation and lower error rates. It also surveys related work applying PCA, LDA, LPP and other techniques to challenges like single image training and discusses the LaplacianFace method's modules for loading images, res
IRJET- Syllabus and Timetable Generation SystemIRJET Journal
The document describes a proposed system called the Syllabus and Timetable Generation System that aims to automatically generate timetables and syllabi for educational institutions. It uses an algorithm that takes inputs like number of classes, subjects, days in a week, and lectures per day to randomly generate timetables for multiple classes without clashes. The algorithm employs recursion to prevent clashes across class timetables. It also includes a static faculty assignment method. The proposed system was able to automatically generate timetables and syllabi for 4 classes with 10 subjects, demonstrating the effectiveness of the algorithm in solving the complex task of timetable scheduling.
industrial training report on Ethical hackingNitesh Dubey
This document outlines an industrial training report on ethical hacking conducted at Alison Online Training Institute. It begins with an introduction to ethical hacking and the different types of hacking. It then discusses the role of security and penetration testers and different penetration testing methodologies. The document provides an overview of what can and cannot be done legally as an ethical hacker. It also discusses the basics of networking and what it takes to be a successful security tester.
Performance Analysis of Supervised Machine Learning Techniques for Sentiment ...Biswaranjan Samal
Wide use of internet and web applications like, feedback collection systems are now making peoples smarter. In these applications, peoples used to give their feedback about the movies, products, services, etc through which they have gone, and this feedback are publicly available for future references. It is a tedious task for the machines to identify the feedback types, i:e positive or negative. And here Machine Learning Techniques plays vital roles to train the machine and make it intelligent so that the machine will be able to identify the feedback type which may give more benefits and features for those web applications and the users. There are many supervised machine learning techniques are available so it is a difficult task to choose the best one. In this paper, we have collected the movie review datasets of different sizes and have selected some of the widely used and popular supervised machine learning algorithms, for training the model. So that the model will be able to categorize the review. Python's NLTK package along with the WinPython and Spyder are used for processing the movie reviews. Then Python's sklearn package is used for training the model and finding the accuracy of the model.
This document describes the development of an online intelligence quotient (IQ) tester system. The system is designed to test IQ for three different age groups (children, teens, adults) based on the Wechsler scales. It uses a Fisher-Yates shuffling algorithm to randomly select questions from a database to avoid repetition and improve accuracy. Users register with an age and take a 10 question test tailored to their age group. The system generates a report with the user's IQ score, level, and tips. It allows viewing past results for comparison over time. The goal is to provide a self-awareness tool and reduce issues with existing IQ tests.
Optimized Active Learning for User’s Behavior Modelling based on Non-Intrusiv...IJECEIAES
In order to protect the data in the smartphone, there is some protection mechanism that has been used. The current authentication uses PIN, password, and biometric-based method. These authentication methods are not sufficient due to convenience and security issue. Non-Intrusive authentication is more comfortable because it just collects user’s behavior to authenticate the user to the smartphone. Several non-intrusive authentication mechanisms were proposed but they do not care about the training sample that has a long data collection time. This paper propose a method to collect data more efficient using Optimized Active Learning. The Support Vector Machine (SVM) used to identify the effect of some small amount of training data. This proposed system has two main functionalities, to reduce the training data using optimized stop rule and maintain the Error Rate using modified model analysis to determine the training data that fit for each user.Finally, after we done the experiment, we conclude that our proposed system is better than Threshold-based Active Learning. The time required to collect the data can reduced to 41% from 17 to 10 minutes with the same Error Rate.
Ignou MCA 4th semester mini project report. College admission system. This project is based on real working system of University seat allocation to affiliate colleges. College admission system provide seat allocation process for various UG PG programs for every academic session.
Survey Paper on : College Automation System using Face Recognition with RFIDIRJET Journal
This document summarizes a proposed college automation system using face recognition and RFID technologies. The system aims to automate student attendance tracking to reduce manual work. It would use face recognition cameras at the college entrance to identify students and mark partial attendance. In classrooms, an RFID reader would record when students scan their RFID tags to mark full attendance. The face recognition and RFID records would be merged to generate attendance reports. The reports along with other student and college information would be available on a web portal and mobile apps for teachers, students, and parents. The system is intended to streamline attendance tracking and information sharing between stakeholders while reducing proxies and manual effort.
The document describes a project report submitted by 5 students for their Bachelor of Technology degree. It outlines the development of an IIMSR Student Management System. The system will manage student records like personal details, contact details, marks details, and other functions like student/faculty profiles, marks submission, attendance records, examination results, and timetable management. It conducted a feasibility study and identified problems with the current manual system. The project aims to automate the process and make it more efficient by reducing paperwork.
This document describes an online assignment system that allows students and faculty to communicate about assignments digitally. Key features include:
1) Students can submit assignments online and faculty can grade them and provide feedback without paper.
2) The system uses keyword matching to automatically determine the best student answer by comparing responses to keywords provided by the faculty. This answer can then be highlighted for other students.
3) Faculty can generate practice question papers from the pool of assignment questions.
4) The paperless system aims to improve efficiency by reducing paperwork and human effort for both students and faculty.
The document describes a proposed student information system that would allow institutions to more easily manage student data. It would include functions for recording, searching, modifying, and deleting student records. The system would use a prototyping model since requirements are not yet fully defined. It then provides details on the hardware, software, and functional requirements including use of a SQL database, Windows OS, and securing student data.
IRJET- Intelligent Automated Attendance System based on Facial RecognitionIRJET Journal
This document presents a proposed intelligent automated attendance system based on facial recognition. The system aims to automate the attendance marking process in educational institutions to make it faster and less error-prone compared to manual methods. It works by using computer vision techniques like haar cascade classification for face detection and local binary pattern histograms for face recognition. The system architecture involves capturing images, detecting faces, recognizing students by matching faces to a training database, and marking the attendance automatically. Algorithms like haar cascade and local binary patterns are used for face detection and recognition. The proposed system aims to solve issues with existing manual and automated attendance systems like time consumption, errors, and lack of accuracy.
IRJET - Facial Recognition based Attendance System with LBPHIRJET Journal
This document presents a facial recognition based attendance system using LBPH (Local Binary Pattern Histograms). It begins with an abstract describing the system which takes student attendance using facial identification from classroom camera images. It then discusses related work in attendance and face recognition systems. The proposed system workflow is described involving face detection, feature extraction using LBPH, template matching, and attendance recording. Experimental results demonstrate the system's ability to detect multiple faces and record attendance accurately in an Excel sheet with date/time. The conclusion discusses how the system reduces human effort for attendance and increases learning time compared to traditional methods.
Smart Attendance System using Face-RecognitionIRJET Journal
The document describes a proposed smart attendance system using face recognition. The system aims to simplify the traditional manual attendance marking process by using advances in image processing and face recognition technology. It would identify and recognize faces in real-time, match them to data in a student database, and automatically record attendance. This would make the attendance process more efficient and accurate compared to existing systems, while avoiding issues like proxy attendance due to the uniqueness of biometric facial traits. The proposed system uses OpenCV, dlib and face recognition libraries to perform face detection and recognition with a one-shot learning approach requiring only one image per student.
Monitoring Students Using Different Recognition Techniques for Surveilliance ...IRJET Journal
This document discusses using computer vision techniques like convolutional neural networks to monitor students and enforce dress codes in educational institutions. It proposes a system using cameras and image processing to identify whether students are properly dressed according to the dress code. The system would classify images of students as either following or not following the dress code. It also discusses related work on using technologies like biometrics and RFID cards for automated student attendance tracking and implications for security and discipline in schools.
IRJET- Implementation of Attendance System using Face RecognitionIRJET Journal
This document describes a study that implemented an attendance tracking system using face recognition. The system aims to automatically record students' attendance during lectures using facial recognition technology instead of manual methods. It discusses existing manual and computer-based attendance systems and proposes a system that uses PCA (Principal Component Analysis) face recognition techniques to detect and recognize students' faces from images captured during lectures in order to mark their attendance automatically. The system architecture involves enrolling students by taking their images and extracting features, then acquiring new images during lectures, enhancing them, detecting and recognizing faces to mark attendance on a server database. The study implemented this system using Visual Studio 2010 and MS SQL Server 2008 and found it could successfully recognize faces and record attendance.
This document describes a face recognition attendance system. The system uses face recognition techniques to automatically take attendance by detecting and identifying students' faces from live classroom video streams. It aims to address issues with traditional manual attendance methods, which are tedious and prone to errors. The system works in four stages: data collection, face detection, face preprocessing, and face recognition & attendance updating. Faces are detected using Haar Cascade classifiers and further processed using Local Binary Pattern histograms for recognition. When a known face is identified, the student's attendance is automatically marked. The system is designed to provide a more efficient alternative to manual attendance marking.
This document describes a face recognition attendance system that was designed to automate the manual attendance marking process in colleges and universities. The system uses face recognition techniques including face detection, preprocessing, feature extraction, and recognition to identify students from images captured in the classroom and automatically mark their attendance. It discusses related works on biometric attendance systems using technologies like iris recognition and fingerprints. The system design incorporates a teacher module, student module, and functionality for processing images, extracting features, classifying faces, and updating attendance records. It evaluates the methodology used for face recognition, preprocessing, and non-real time recognition and concludes the automated system helps improve accuracy and speed compared to manual attendance marking.
AUTOMATION OF ATTENDANCE USING DEEP LEARNINGIRJET Journal
This document describes a proposed system to automate student attendance using deep learning techniques like face detection and recognition. The system would take pictures of the classroom and use these techniques to identify which students are present, addressing issues with current manual attendance systems. It reviews previous literature on automated attendance systems and face recognition methods. The proposed system would use Python with OpenCV for face detection and an LBPH model for face recognition. It would generate reports with student attendance data and photos/videos from the classroom.
Face Recognition Smart Attendance System- A SurveyIRJET Journal
This document surveys 15 research papers on face recognition smart attendance systems. It summarizes each paper's methodology, including the databases and images used, feature extraction and matching algorithms like PCA, LDA, CNN, techniques for addressing issues like lighting and pose variations, and the accuracy and limitations of each system. Overall, the papers presented a variety of approaches to developing face recognition systems for automated student attendance, comparing methods like PCA, LDA, HOG, and deep learning algorithms and evaluating factors like recognition rate, robustness, and speed.
project synopsis face recognition attendance systemAnkitRao82
This document summarizes the proposed development of a face recognition system for student attendance. The key objectives are to automate attendance tracking through facial recognition to reduce manual errors and increase efficiency. The methodology uses image capture, face detection, preprocessing, database development and post processing. Features will be extracted from images using LBP and PCA for classification and recognition. A feasibility study found the system would be operationally and technically feasible with no need for additional hardware or software costs.
IRJET- A Study on Automated Attendance System using Facial RecognitionIRJET Journal
The document discusses an automated attendance system using facial recognition. It begins with an introduction to facial recognition and the motivation for developing an automated attendance system. It then reviews previous work on facial recognition algorithms such as PCA, Viola-Jones, and neural networks. The proposed system is described as using SVM on LBP features for facial recognition due to its high accuracy. Key advantages of the proposed system include being cost-efficient, easy to deploy, and preventing time fraud. The document concludes facial recognition can effectively automate attendance tracking in educational or commercial organizations.
Face Recognition Smart Attendance System: (InClass System)IRJET Journal
- The document describes a face recognition system called "InClass" to automate student attendance tracking. It aims to address issues with traditional manual attendance systems like being inaccurate, time-consuming, and difficult to maintain.
- The InClass system uses a CNN face detector to detect and identify students' faces from images captured with a camera. It can handle variations in lighting, angles, and occlusions. Matching faces to a database allows for automated attendance marking.
- The system aims to simplify the attendance process, reduce time and errors compared to existing biometric systems, and make attendance records easily accessible and storable digitally rather than on paper.
IRJET- Attendance Management System using Real Time Face RecognitionIRJET Journal
This document proposes an attendance management system using real-time face recognition. The system uses computer vision algorithms like face detection and recognition to automatically detect students attending a lecture without interfering with the teaching process. It aims to provide a more efficient and detailed attendance reporting system. The system architecture involves capturing images of the classroom, detecting faces, recognizing the faces by comparing them to a database of student photos, and updating the attendance register. The system could help increase education quality by ensuring more accurate tracking of student attendance.
IRJET - Face Recognition based Attendance System: ReviewIRJET Journal
This document provides a literature review of face recognition-based attendance systems. It summarizes several past studies that developed systems to automatically detect students' faces in images and use face recognition algorithms to mark attendance. The review finds that while many algorithms have been implemented, including Haar Cascade, Viola Jones, Eigenface, PCA, LDA, and LBPH, accurately verifying each student in a classroom remains challenging. The document analyzes the performance of previous systems and the issues that still exist, in order to provide suggestions for improving future work on automatic attendance tracking using face recognition.
Development of an Automatic & Manual Class Attendance System using Haar Casca...IRJET Journal
This document presents a proposed system for an automatic and manual class attendance system using facial recognition. The system uses Haar cascade classifiers for facial detection and recognition. A camera would be installed at the entrance of a classroom to capture images of students' faces as they enter. Using local binary patterns histograms (LBPH) algorithm, the captured faces would be matched to images stored in a database to automatically record attendance. For students not registered in the database, a manual attendance process would allow attendance to be marked by providing enrollment ID and name. The proposed system aims to digitize and streamline traditional paper-based attendance systems while addressing issues like proxy attendance.
Student Attendance Using Face RecognitionIRJET Journal
This document describes a student attendance system using face recognition from group photos. The system works by taking a single group photo of students, detecting faces using a Haar cascade classifier, and recognizing faces to match them to student profiles stored in a database. The recognized student names are then marked as present in a Google Sheet for attendance tracking. The system provides a more efficient alternative to manual attendance marking and avoids costs of individual cameras. Face recognition is performed using the LBPH algorithm to extract face features and compare them to the training database for matching. The target is to complete attendance marking from a single group photo in under 30 seconds for ease of use.
IRJET- Automated Student’s Attendance Management using Convolutional Neural N...IRJET Journal
This document describes a proposed system to automate student attendance management using convolutional neural networks and face recognition. The system would take attendance automatically by detecting faces in the classroom and comparing them to a database of student faces. This would make the attendance process more efficient than current manual methods like calling roll numbers or paper sign-ins. The system would use a CNN algorithm and face detection/recognition techniques like PCA to detect and identify student faces during lectures and automatically update attendance records.
This document proposes a facial recognition-based attendance system for schools as an alternative to traditional ID card-based systems. It discusses collecting facial images of students and training a neural network using Haar wavelet and deep learning techniques to recognize faces and mark attendance automatically. The system was tested on 70 students across two classes and showed high accuracy in recognizing students and recording their attendance quickly without human error. Some benefits highlighted include improved security, automation, and elimination of buddy punching or manual errors compared to traditional ID card systems. Overall, the research demonstrates that facial recognition can effectively be used to develop an automated attendance management system for schools.
METandance: A Smart Classroom Management And AnalysisIRJET Journal
This document describes a proposed smart classroom management and analysis system called METandance that uses facial recognition for automated student attendance marking. The system was developed by four students at MET's Institute of Engineering in Nashik, India. It aims to automate and streamline classroom tasks like taking attendance, posting notices, and analyzing attendance data. The system has three user types - admin, faculty, and students. It uses facial recognition to identify students from video feeds and automatically mark attendance. Admin can manage student and faculty data, faculty can take attendance and view analytics, and students can view their attendance and notices. The document provides details on the system design, including the facial recognition process and module workflows. It suggests this system can save time over
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.
Similar to IRJET- Survey on Various Techniques of Attendance marking and Attention Detection (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.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
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
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
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%.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.