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- 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
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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.
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This document summarizes an automated attendance system using video-based face recognition. The system works by capturing a video of students in a classroom and using face detection and recognition algorithms to identify and mark the attendance of each student. It first detects faces in each video frame using the Haar cascade classifier, then recognizes the faces by comparing them to a training database of student faces using the Eigenfaces algorithm. Finally, it registers the attendance in an Excel sheet. The system aims to make the attendance process more efficient and accurate compared to traditional manual methods.
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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.
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This document presents a real-time advanced automated attendance system using the Face-Net algorithm. The system uses facial recognition technology to automate the attendance tracking process. It involves developing facial detection and recognition algorithms, a database to store student information, and interfaces for educators. The system captures images of students' faces and matches them to stored data to record attendance in real-time while maintaining privacy. Testing showed the system could accurately detect and recognize faces in classroom settings. The authors aim to contribute to digitizing education administration and allowing educators to focus on teaching.
IRJET- Computerized Attendance System using Face RecognitionIRJET Journal
1. The document describes a computerized attendance system using face recognition for educational institutions. It uses OpenCV with face recognition and detection algorithms like Viola-Jones, PCA, and Eigenfaces.
2. Faces are detected using Viola-Jones algorithm. PCA is used to train detected faces and create a database of known faces. During attendance, faces are compared to the database to identify individuals and mark attendance automatically in an Excel file.
3. This automated system provides benefits over manual attendance systems by saving time, reducing errors, and preventing forgery. It is a more convenient and accurate way to take attendance.
IRJET- Computerized Attendance System using Face RecognitionIRJET Journal
1) The document proposes an automated attendance system using face recognition for educational institutions to replace traditional manual attendance marking.
2) The system uses OpenCV with face detection algorithms like Viola-Jones and PCA to detect faces, create face databases, and compare faces to identities to automatically mark attendance in an excel file.
3) During use, faces will be detected in images from a webcam, compared to stored databases to identify individuals, and their attendance marked electronically without needing physical interaction like ID cards.
Face Recognition based Smart Attendance System Using IoTIRJET Journal
This document describes a face recognition-based smart attendance system using IoT. The system uses a Raspberry Pi connected to a webcam to take pictures of students' faces as they enter the classroom. It then applies face detection and recognition techniques to identify the students and mark them as present in an Excel attendance sheet along with their details. The system aims to automate attendance taking and eliminate issues like proxy attendance. It stores student data and images to create a dataset, which it then uses for real-time face recognition and attendance marking as students' faces are detected by the webcam. The results show this system can accurately and efficiently automate attendance taking in a contactless manner.
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
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- Autonamy of Attendence using Face RecognitionIRJET Journal
This document summarizes an automated attendance system using video-based face recognition. The system works by capturing a video of students in a classroom and using face detection and recognition algorithms to identify and mark the attendance of each student. It first detects faces in each video frame using the Haar cascade classifier, then recognizes the faces by comparing them to a training database of student faces using the Eigenfaces algorithm. Finally, it registers the attendance in an Excel sheet. The system aims to make the attendance process more efficient and accurate compared to traditional manual methods.
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.
A Real Time Advance Automated Attendance System using Face-Net AlgorithmIRJET Journal
This document presents a real-time advanced automated attendance system using the Face-Net algorithm. The system uses facial recognition technology to automate the attendance tracking process. It involves developing facial detection and recognition algorithms, a database to store student information, and interfaces for educators. The system captures images of students' faces and matches them to stored data to record attendance in real-time while maintaining privacy. Testing showed the system could accurately detect and recognize faces in classroom settings. The authors aim to contribute to digitizing education administration and allowing educators to focus on teaching.
IRJET- Computerized Attendance System using Face RecognitionIRJET Journal
1. The document describes a computerized attendance system using face recognition for educational institutions. It uses OpenCV with face recognition and detection algorithms like Viola-Jones, PCA, and Eigenfaces.
2. Faces are detected using Viola-Jones algorithm. PCA is used to train detected faces and create a database of known faces. During attendance, faces are compared to the database to identify individuals and mark attendance automatically in an Excel file.
3. This automated system provides benefits over manual attendance systems by saving time, reducing errors, and preventing forgery. It is a more convenient and accurate way to take attendance.
IRJET- Computerized Attendance System using Face RecognitionIRJET Journal
1) The document proposes an automated attendance system using face recognition for educational institutions to replace traditional manual attendance marking.
2) The system uses OpenCV with face detection algorithms like Viola-Jones and PCA to detect faces, create face databases, and compare faces to identities to automatically mark attendance in an excel file.
3) During use, faces will be detected in images from a webcam, compared to stored databases to identify individuals, and their attendance marked electronically without needing physical interaction like ID cards.
Face Recognition based Smart Attendance System Using IoTIRJET Journal
This document describes a face recognition-based smart attendance system using IoT. The system uses a Raspberry Pi connected to a webcam to take pictures of students' faces as they enter the classroom. It then applies face detection and recognition techniques to identify the students and mark them as present in an Excel attendance sheet along with their details. The system aims to automate attendance taking and eliminate issues like proxy attendance. It stores student data and images to create a dataset, which it then uses for real-time face recognition and attendance marking as students' faces are detected by the webcam. The results show this system can accurately and efficiently automate attendance taking in a contactless manner.
IRJET- Free & Generic Facial Attendance System using AndroidIRJET Journal
This document proposes a free and generic facial attendance system using Android that can automatically detect students' faces and mark attendance. It uses face detection and recognition algorithms to capture images from a camera and identify students by matching faces to a database. If a face is detected, attendance is marked as present. The system then creates a Google Sheet to store and access attendance records. This provides a low-cost alternative to commercial biometric systems for tracking student attendance.
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.
Real Time Image Based Attendance System using PythonIRJET Journal
The document describes a proposed real-time image-based attendance system using facial recognition in Python. It involves four main steps: 1) capturing images using a webcam, 2) preprocessing the images by converting them to grayscale, 3) applying facial recognition algorithms like Haar Cascade and LBPH to detect and recognize faces, and 4) storing the attendance data in a database like CSV files. Previous related works that implemented similar systems using techniques like OpenCV, Viola-Jones, and deep learning algorithms are also discussed. The proposed system aims to provide an accurate, efficient and user-friendly alternative to traditional paper-based attendance methods.
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.
Student Attendance Management Automation Using Face Recognition AlgorithmIRJET Journal
The document describes a proposed student attendance management system that uses real-time face recognition. The system uses a camera to capture student faces and the Haar cascading algorithm to detect faces. It then applies the Local Binary Pattern Histogram (LBPH) algorithm to recognize the faces and mark attendance in the database. The system provides automated attendance tracking and reporting to replace manual attendance marking. Administrators can access attendance reports and add new student details. The proposed system aims to save time, increase accuracy and prevent fraudulent attendance recording compared to traditional methods.
This document summarizes a student project to develop an attendance management system using face recognition. The system uses machine learning and image processing techniques to recognize students' faces and automatically mark attendance. A group of students contributed different modules to the project, including image training, login, attendance marking, and a website to display results. The system was created using Python, OpenCV, Tkinter for the GUI, and Firebase for the cloud database. It aims to provide a more efficient alternative to traditional paper-based attendance systems.
The document describes an attendance management system using face recognition. The system uses machine learning and image processing techniques to recognize students' faces and mark attendance automatically. It trains on images of students' faces and then detects and identifies faces in real-time to record attendance. The system is designed to reduce time spent on manual attendance processes. It stores attendance data in the cloud on Firebase and has a website interface to view records. The system aims to make attendance tracking more efficient through automated face recognition.
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
Implementation of Automatic Attendance Management System Using Harcascade and...IRJET Journal
This document proposes an automatic attendance management system using facial recognition algorithms. It aims to reduce human error and resources required for manual attendance recording. The system uses a camera to capture faces at the entrance and matches them to employee photos stored in a database using Haar cascade detection and local binary pattern recognition. If a match is found, the employee is marked present and their attendance updated in real time to an Excel sheet for administrators to view. The system is intended to help organizations more efficiently track attendance compared to traditional paper-based methods.
IRJET- Student Attendance System by Face DetectionIRJET Journal
This document describes a student attendance system using face detection and recognition. The system automatically takes attendance by identifying students' faces using image processing techniques. It stores a database of student faces during a training process. When students enter the classroom, the system detects faces in real-time camera footage and compares them to the stored database to identify and mark present any matching students. The system aims to make the attendance process more efficient and accurate compared to traditional manual methods. It provides automated attendance tracking to help monitor student performance without lengthy paperwork.
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.
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.
Neural Net: Machine Learning Web ApplicationIRJET Journal
The document describes a machine learning web application called Neural Net that implements various machine learning algorithms. It includes two live projects - a COVID predictor and used car price predictor. The COVID predictor takes user symptoms and predicts the probability of infection using logistic regression. The car price predictor takes vehicle details and predicts the selling price using linear regression. The web application was created using HTML, CSS, JavaScript for the front-end and Python Flask for the back-end integration of machine learning models. The models were trained on various datasets to provide predictions with minimal error.
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.
This document describes a proposed next-generation attendance management system using face recognition technology. The system aims to automate the attendance tracking process for students in an educational institution. It works by enrolling students into the system by capturing their facial images and extracting facial features to create unique encodings for each student. When taking attendance, the system uses these encodings to identify students' faces in captured images or video and marks their attendance automatically. This reduces the burden on teachers of manually taking and entering attendance. The system also calculates and stores attendance records in a database for viewing and analysis. The proposed system aims to address limitations of traditional attendance tracking methods like errors, time consumption and lack of data analysis capabilities.
1. The document discusses various techniques that have been proposed for face detection and attendance systems, including Haar classifiers, improved support vector machines, and local binary patterns algorithms.
2. It reviews several papers that have implemented different methods for face recognition for attendance systems, such as using HOG features and PCA for dimensionality reduction along with SVM classification.
3. The document also summarizes a paper that proposed a context-aware local binary feature learning method for face recognition that exploits contextual information between adjacent image bits.
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.
A VISUAL ATTENDANCE SYSTEM USING FACE RECOGNITIONIRJET Journal
This document describes a visual attendance system using face recognition. The system was created to make the traditional paper-based attendance process more efficient and less prone to errors. It uses computer vision and face recognition techniques, including the RetinaFace and Arcnet algorithms, to detect and identify students' faces from video feeds or images taken in the classroom. When taking attendance, the system captures photos of students present and searches its database of student faces to automatically record attendance without disrupting the class. The document discusses the methodology and system structure, including face detection, face recognition modeling, and an overall workflow flowchart. It aims to provide an improved digital solution for tracking attendance at universities and colleges.
ATTENDANCE BY FACE RECOGNITION USING AIIRJET Journal
This document describes a proposed face recognition system for automated student attendance. The system would use a camera situated at a school entrance to capture frontal images of students as they enter. It would then use face recognition algorithms to identify each student and automatically record their attendance. Some key advantages of this system include reducing the time spent on manual attendance recording and increasing accuracy by eliminating proxy attendance issues. The proposed system aims to provide a hassle-free automated solution for tracking student attendance using biometric face recognition technologies.
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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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.
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.
Covid Management System Project Report.pdfKamal Acharya
CoVID-19 sprang up in Wuhan China in November 2019 and was declared a pandemic by the in January 2020 World Health Organization (WHO). Like the Spanish flu of 1918 that claimed millions of lives, the COVID-19 has caused the demise of thousands with China, Italy, Spain, USA and India having the highest statistics on infection and mortality rates. Regardless of existing sophisticated technologies and medical science, the spread has continued to surge high. With this COVID-19 Management System, organizations can respond virtually to the COVID-19 pandemic and protect, educate and care for citizens in the community in a quick and effective manner. This comprehensive solution not only helps in containing the virus but also proactively empowers both citizens and care providers to minimize the spread of the virus through targeted strategies and education.
Sri Guru Hargobind Ji - Bandi Chor Guru.pdfBalvir Singh
Sri Guru Hargobind Ji (19 June 1595 - 3 March 1644) is revered as the Sixth Nanak.
• On 25 May 1606 Guru Arjan nominated his son Sri Hargobind Ji as his successor. Shortly
afterwards, Guru Arjan was arrested, tortured and killed by order of the Mogul Emperor
Jahangir.
• Guru Hargobind's succession ceremony took place on 24 June 1606. He was barely
eleven years old when he became 6th Guru.
• As ordered by Guru Arjan Dev Ji, he put on two swords, one indicated his spiritual
authority (PIRI) and the other, his temporal authority (MIRI). He thus for the first time
initiated military tradition in the Sikh faith to resist religious persecution, protect
people’s freedom and independence to practice religion by choice. He transformed
Sikhs to be Saints and Soldier.
• He had a long tenure as Guru, lasting 37 years, 9 months and 3 days
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.
Particle Swarm Optimization–Long Short-Term Memory based Channel Estimation w...IJCNCJournal
Paper Title
Particle Swarm Optimization–Long Short-Term Memory based Channel Estimation with Hybrid Beam Forming Power Transfer in WSN-IoT Applications
Authors
Reginald Jude Sixtus J and Tamilarasi Muthu, Puducherry Technological University, India
Abstract
Non-Orthogonal Multiple Access (NOMA) helps to overcome various difficulties in future technology wireless communications. NOMA, when utilized with millimeter wave multiple-input multiple-output (MIMO) systems, channel estimation becomes extremely difficult. For reaping the benefits of the NOMA and mm-Wave combination, effective channel estimation is required. In this paper, we propose an enhanced particle swarm optimization based long short-term memory estimator network (PSOLSTMEstNet), which is a neural network model that can be employed to forecast the bandwidth required in the mm-Wave MIMO network. The prime advantage of the LSTM is that it has the capability of dynamically adapting to the functioning pattern of fluctuating channel state. The LSTM stage with adaptive coding and modulation enhances the BER.PSO algorithm is employed to optimize input weights of LSTM network. The modified algorithm splits the power by channel condition of every single user. Participants will be first sorted into distinct groups depending upon respective channel conditions, using a hybrid beamforming approach. The network characteristics are fine-estimated using PSO-LSTMEstNet after a rough approximation of channels parameters derived from the received data.
Keywords
Signal to Noise Ratio (SNR), Bit Error Rate (BER), mm-Wave, MIMO, NOMA, deep learning, optimization.
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