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.
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.
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This document describes research on developing an Android application for face detection and face recognition. It discusses using techniques like skin segmentation, facial feature extraction, and classification algorithms from the OpenCV library. The application detects faces in images and compares them to a dataset for recognition. It addresses challenges like scale and lighting changes. The architecture involves preprocessing images, extracting Local Binary Patterns features, and matching them to the database for identification. Common mistakes like inability to retrieve detected faces are also outlined.
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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.
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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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Automatic attendance system is one of the significant issues of today’s research. Among other methods, human face recognition is highly used technique for attendance automation. Many systems have been proposed in literature using face recognition. Most of the systems are using fixed camera and desktop computers. We propose a system using mobile phones where an image is captured of group of peoples and face detection is done automatically. While considering computational and storage power of mobile devices, extracted local binary features for detected faces are then transferred to server machine using firebase database. Matching is done on server side, if face recognized than attendance is marked and feedback is sent back to client side. Experiments show effectiveness of proposed techniques with 95% correct recognition rate.
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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.
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The document describes a face detection and recognition system that uses machine learning algorithms. It analyzes facial structures in images and compares them to a dataset of facial models to identify matches. The system performs background subtraction, face detection, face recognition, and tracking. It was created to provide quick, accurate and contactless biometric security but could also be used for applications like attendance tracking. The system architecture includes modules for motion detection, face detection, face recognition and tracking a detected face. It was designed to be easily adaptable and allow additional functionality to be added.
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.
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This document describes research on developing an Android application for face detection and face recognition. It discusses using techniques like skin segmentation, facial feature extraction, and classification algorithms from the OpenCV library. The application detects faces in images and compares them to a dataset for recognition. It addresses challenges like scale and lighting changes. The architecture involves preprocessing images, extracting Local Binary Patterns features, and matching them to the database for identification. Common mistakes like inability to retrieve detected faces are also outlined.
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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.
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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.
AN IMAGE BASED ATTENDANCE SYSTEM FOR MOBILE PHONESAM Publications
Automatic attendance system is one of the significant issues of today’s research. Among other methods, human face recognition is highly used technique for attendance automation. Many systems have been proposed in literature using face recognition. Most of the systems are using fixed camera and desktop computers. We propose a system using mobile phones where an image is captured of group of peoples and face detection is done automatically. While considering computational and storage power of mobile devices, extracted local binary features for detected faces are then transferred to server machine using firebase database. Matching is done on server side, if face recognized than attendance is marked and feedback is sent back to client side. Experiments show effectiveness of proposed techniques with 95% correct recognition rate.
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.
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This document summarizes a research paper that proposes an automated attendance system using facial recognition technology. It begins by outlining the limitations of current manual and RFID card-based attendance systems. It then describes a new system that uses MTCNN for face detection and CNN for facial recognition. The system captures images and identifies recognized students as present by matching faces to a database of stored images. The document provides details on the various stages of the proposed method, including face detection using MTCNN, face alignment, feature extraction with FaceNet, and classification with SVM. It presents the overall algorithm and concludes by discussing modelling and analysis.
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The document discusses Nivritti, a web application that uses face recognition technology to help solve issues with India's pension system. It aims to simplify the pension process and increase transparency. The application would allow online verification of life certificates and transfer of pension funds through facial recognition rather than long in-person processes. The document then reviews several existing face recognition methods and their performance based on datasets used, including DeepFace, DeepID, FaceNet, OpenFace, and FAREC. It finds that methods requiring fewer images for training and faster predictions are needed for a deployable system like Nivritti.
Attendance System using Face RecognitionIRJET Journal
This document describes an automated attendance system using face recognition. It discusses using algorithms like Viola-Jones for face detection and PCA for feature extraction and SVM for classification. The system works by capturing images of students' faces with a camera as they enter the classroom. It then detects faces, recognizes the students, and automatically marks their attendance on an attendance sheet. The system is presented as an improvement over previous biometric-based attendance systems in that it is faster, more convenient, and helps monitor students.
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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.
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.
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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.
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.
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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.
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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.
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.
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This document proposes a library management system using facial recognition for biometric authentication. It would automate the entry and exit logging of users and reduce wait times. The system involves two phases: 1) enrolling images of authorized users in a dataset during initial setup and 2) verifying users in real-time by comparing their images to those in the stored dataset. If a match is found, the user is granted access, and if not, they are denied entry. The system aims to eliminate manual logging and prevent unauthorized access to library resources.
IRJET- Library Management System with Facial Biometric AuthenticationIRJET Journal
1. The document proposes a facial recognition system using OpenCV for biometric authentication in a library management system.
2. The system has two phases: a data generation phase that enrolls user images in a database, and a recognition phase that identifies users by comparing input images to the database.
3. In the recognition phase, preprocessing such as grayscale conversion and histogram equalization is performed before feature extraction using algorithms like LBPH, SIFT, LDA, and PCA to generate faceprints for comparison and verification against the database.
IRJET - Automated Attendance System using Multiple Face Detection and Rec...IRJET Journal
This document describes an automated attendance system using multiple face detection and recognition. The system aims to save time by detecting and recognizing multiple faces in a classroom simultaneously to mark students as present, rather than having each student manually mark their attendance. The system works by capturing images of the classroom at intervals, using a Haar cascade classifier for face detection to locate faces. It then uses face recognition algorithms like LBPH to identify each detected face and check it against a stored database of student faces to mark the student as present or absent in the attendance records. The system is proposed to eliminate the time wasted in traditional manual attendance taking methods while still ensuring accurate attendance marking for students.
A Web-based Attendance System Using Face RecognitionIRJET Journal
This document presents a web-based attendance system using facial recognition. It aims to provide a contactless solution for recording student attendance amidst the COVID-19 pandemic. The proposed system uses a facial recognition model to identify students from webcam footage and automatically record their attendance in a database. Key features include attendance reports, classrooms, statistics, and notifications. It was found to accurately recognize faces with 98% average accuracy. The system provides a safer alternative to traditional paper-based attendance methods while automating attendance tracking and analysis for instructors.
This document presents a proposed automated attendance management system using face recognition. The system would use machine learning algorithms and deep learning approaches to recognize students' faces from images and track attendance. It discusses how face recognition works, including face detection, alignment, feature extraction, and recognition. It reviews similar existing systems and their limitations. The document tests several machine learning algorithms on their dataset and finds that an SVM classifier achieves the highest accuracy of 99.3%. Results are presented showing the system labeling and recognizing faces to mark attendance. The system aims to automate the attendance process to ease the burden on teachers, especially in online learning settings.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
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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
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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.
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.
An In-Depth Exploration of Natural Language Processing: Evolution, Applicatio...DharmaBanothu
Natural language processing (NLP) has
recently garnered significant interest for the
computational representation and analysis of human
language. Its applications span multiple domains such
as machine translation, email spam detection,
information extraction, summarization, healthcare,
and question answering. This paper first delineates
four phases by examining various levels of NLP and
components of Natural Language Generation,
followed by a review of the history and progression of
NLP. Subsequently, we delve into the current state of
the art by presenting diverse NLP applications,
contemporary trends, and challenges. Finally, we
discuss some available datasets, models, and
evaluation metrics in NLP.
Sachpazis_Consolidation Settlement Calculation Program-The Python Code and th...Dr.Costas Sachpazis
Consolidation Settlement Calculation Program-The Python Code
By Professor Dr. Costas Sachpazis, Civil Engineer & Geologist
This program calculates the consolidation settlement for a foundation based on soil layer properties and foundation data. It allows users to input multiple soil layers and foundation characteristics to determine the total settlement.