An Intelligent and Automatic Attendance Tracking System: A Survey
Authors:- Rakshith J, Sarvajith, Shravan K G, Vinay M, Associate Professor Nagaraj.A,
Abstract- Taking attendance manually in classrooms can be a laborious and inefficient process that can lead to several problems. One issue is that it can be time- consuming, especially in large classes. Teachers have to spend valuable class time collecting and recording attendance, which can disrupt the flow of the lesson. Additionally, manually recording attendance is prone to errors, as it is easy to misspell names or mis record attendance. This can lead to inaccuracies in the attendance records, which can have consequences for students and teachers. Another problem with manually taking attendance is that it is inflexible. If a student is absent and then returns to class, it can be difficult to update the attendance records accurately. This can be particularly problematic in situations where attendance is used to track student progress or participation. Manually recording attendance on paper or in a spreadsheet can also present security concerns. The records may be lost or stolen, which can compromise the privacy of the students and the accuracy of the attendance records. Overall, manually taking attendance in classrooms can be an inefficient and burdensome process that can lead to a variety of problems. It is important for schools and teachers to consider alternative methods of tracking attendance, such as electronic systems or mobile apps, that can be more efficient and accurate. A web-based real- time attendance management system is a tool that allows teachers and administrators to track and record student attendance electronically. This type of system is typically accessed through a web browser and can be used from any device with an internet connection. One of the main benefits of a web-based real-time attendance management system is that it is efficient and convenient. Teachers can easily record attendance in real-time, without the need to spend valuable class time collecting and recording the data. The attendance records are also automatically saved and can be accessed by administrators and teachers as needed. Another benefit of a web-based real-time attendance management system is that it is accurate. The system can automatically record attendance based on a variety of factors, such as the student’s face. This helps to ensure that the attendance records are accurate and up-to-date. Web-based real- time attendance management systems can also provide additional features and benefits, such as the ability to send notifications to students or parents about attendance, the ability to track tardiness or absences, and overall, a web-based real-time attendance management system can be a useful tool for schools and teachers looking to streamline and improve their attendance tracking processes.
A Study on Consumer’s Perception towards Handicraft Products with Special Reference to Tiruppur City
Authors:- Assistant Prof. M.Gunasekaran, J.Praveen
Abstract- Handicraft is an art of craft in which people create something solely with their hands or using simple instruments. Handicraft industries are those that manufacture items by hand, rather than utilising machines, to suit the needs of the people in their community. Artistry, crafting, and handcrafting are all names used to describe handicrafts. Handicrafts emerge with the rise of human creative activity.
Improvement Wsn Protocol Performance in Modified Genetic Algorithm
Authors:- Madhuri Singh Chouhan, Prof. Amit Thakur
Abstract- Wireless sensor networks (WSNs) has recently drawn lots of attention due to its application in multiple domains. The sensors have limited power sources and in many applications they cannot be recharged or replaced due to hostile nature of the environment. Finding near optimal solutions for the energy problem is still an issue in WSNs. A new era is opened with algorithms inspired by nature to solve optimization problems. In this paper, we propose genetic algorithm based approaches for clustering and routing in WSNs. The objective of this mechanism is to prolong lifetime of a sensor and increase the quality of service. We perform extensive simulations of the proposed algorithms.
A Wsn Energy Efficient Routing Protocol Implementation Based On Ai
Authors:- Meharban Singh Parmar, Prof. Amit Thakur
Abstract- Recent developments in low-power communication and signal processing technologies have led to the extensive implementation of wireless sensor networks (WSNs). In a WSN environment, cluster formation and cluster head (CH) selection consume significant energy. Typically, the CH is chosen probabilistically, without considering the real-time factors such as the remaining energy, number of clusters, distance, location, and number of functional nodes to boost network lifetime. Based on the real-time issues, different strategies must be incorporated to design a generic protocol suited for applications such as environment and health monitoring, animal tracking, and home automation. Elementary protocols such as LEACH and centralized-LEACH are well proven, but gradually limitations evolved due to increasing desire and need for proper modification over time. Since the selection of CHs has always been an important criterion for clustered networks, this paper overviews the modifications in the threshold value of CH selection in the network.
Novel Approach To Wsn Pdr Enhancement In Manet Routing Control Approach
Authors:- Diksha Yadav, Prof. Amit Thakur
Abstract- Mobile device users use their devices any time anywhere. Hence there are different constraints we discussed on routing in MANET. Several routing protocols have been proposed in recent years for deployment of MANET. There are three type sof MANET routing protocols reactive, proactive and hybrid. In this paper we have analyzed all these approaches and discussed their pros and cons. The practical reason behind failure of these approaches is asymmetric link. From analysis we have proposed Novel Approach for Routing in MANET (NARM) which is combination of three approaches reactive, proactive and zone based.
Chessbase Niet: A Chess Automation
Authors:- Project Mentor Miss Divya Chaudhary, Mihir Srivastava, Arshdeep Singh, Sakshi Jaiswal, Gourav Singh
Abstract- Chess has enthralled humans for ages, and with the development of technology, the game’s rules and methods of analysis have undergone tremendous change. This study introduces Chessbase Niet, a project that digitises a real chessboard using computer vision and machine learning. Users can take a photo of the chessboard with their smartphone’s camera, and the system will automatically recognise the position of the pieces and create a digital image of the board. You can play against the computer, analyse the game, and forecast the winning move with this digital chessboard.
Review On Classification And Prediction Of Ecg Morphology And Intervals Features
Authors:- Vedant Verma, Hemant Amhia
Abstract-The electrocardiogram (ECG) provides essential characteristics of the human heart’s multiple cardiac conditions. The classification of arrhythmias provides a major part in the diagnosis of cardiac disease. Any deviation from the normal sequence of electrical impulses is considered an arrhythmia. Traditional methods of signal processing, machine learning and its sub-branches, such as deep learning, are popular techniques for ECG signal analysis and classification and, above all, for the development of early detection and treatment applications for cardiac conditions and arrhythmias. This article presents a detailed literature survey on ECG signal analysis. This paper aims to analyze the most recent studies on data utilized, features, and machine learning approaches that can address the time computational challenge and be implemented in wearable technology. The study methodology began with a search for relevant papers, followed by a study of the data provided. The second stage was to explore the evaluated ECG characteristics and the machine learning method used to identify arrhythmia. According to the analysis, a significant number of studies selected the MIT-BIH database, even though it needs a substantial ratio of pre-processing effort. We address a detailed existing research work review on the data of real-time signal collection, pre-recorded diagnostic ECG data, analysis and denoising of ECG signals, identification of ECG spectrographic states based upon function technologies, and classification of ECG signals, as well as comparative discussions between the studies analyzed.
Literature Review on Thermal Absorber Design in Photovoltaic Thermal System
Authors:- Mr. Pravin M. Bale, Mr. Ganesh B. Thakar, Mr. Nilesh D. Langhi, Mr. Mantoo Kumar Razak
Abstract-This paper concerned with work performed by the various researchers in the field of solar energy. A literature survey was performed considering design, material, performance, economics, and application of solar energy with the different solar collector. Literature deals with thermal performance improvement technique and application of photovoltaic in the field of solar energy were included in the paper.
Patient Healthcare Monitoring System Using IOT
Authors:- Prof. Anand D.G. Donald, Mrunali Khadilkar, Pummy Biswas, Falguni Tajne, Prajakta Shinde
Abstract-India is a most populous country in the world. Due to over populous the wellbeing of people is one of the serious issues in recent time. The thought of this project is to save the life of many people who are taken their last breath. With the help of IOT we can make it possible. This paper highlights and identifies the application of IOT in healthcare system using ARDUINO In this project the critical condition of the patient can send to the doctors present in nearby hospital. By using different sensors are connected in the ambulance will give the overall information of patient and notification will be generate in the application which is already downloaded in doctors smart phone. If the patient, chances is less than the app will suggest nearby hospital and doctor can start their treatment until the recovery of the patient. All these sensors are connected to the cloud.
Uber Data Analysis
Authors:- Yog Patil, Aryan Raskar, Sonal Singh, Ayush Shukla, Prof. Rajendra Pawar
Abstract- By giving customers convenient and affordable transportation options, ride-sharing services like Uber have revolutionised the transportation sector. In order to understand the variables that affect fare prices, this study focuses on analysing Uber fare data. This study tries to determine the major contributors to fare unpredictability by analysing a large dataset of ride characteristics, including pick-up and drop-off locations, trip lengths, distance travelled, and fare amounts. Regression analysis and machine learning algorithms are used as advanced statistical tools for analysis. The findings show a strong correlation between several variables and fare prices. Distance, time of day, day of the week, and surge pricing all have a significant impact on how much a fare will cost. For a thorough knowledge of fare changes, additional factors including weather, traffic, and geographic areas are also taken into account. The conclusions drawn from this study have applications for both Uber and its users. Understanding the elements that affect price pricing helps Uber optimise its fare structures, effectively handle surge pricing, and raise overall profitability. Customers can benefit from the insights gained from this analysis by using them to inform their choice of trip and prepare for fare adjustments in various scenarios.
Study on Determining Taylor Vortex Flow Mode Development Process Using Various Physical Quantities
Authors:- Hiroyuki Furukawa, Takeomi Yamazaki
Abstract- In recent years, technology that harnesses the unlimited potential of microorganisms has become important as a modest but long-lasting technology. In order to maximize the power of microorganisms, it is necessary to control the flow of culture medium to mix them uniformly, light, carbon dioxide. Taylor vortices are considered suitable for agitated culture of plant and animal cells or microorganisms because they are easy to create and are resistant to disturbances, stable, and have little local shear flow. In this study, we constructed a system that can automatically discriminate the flow mode using numerical results of Taylor vortex flow generated between rotating double cylinders as input data by using deep learning. By comparing the loss and accuracy rate of test data for various physical quantities and comparing the accuracy rate and loss of training data, the physical quantities that can efficiently predict the mode development process of the Taylor vortex were shown. The results show that among the various physical quantities, the radius u is the most accurate when comparing the final loss after learning and the accuracy rate and can efficiently predict mode development process of the Taylor vortex.
Face- Based Voting System With Fingerprint Authentication
Authors:- Prof. Neelamma Shinannavar , Gayatri S. Vharambale, Pratiksha A. Naik, Maithali B. Patil
Abstract- Voting and security related to voting has always been a topic of greater research. Different voting methodologies are implemented yet the security related to voting still plays a major role in wide-scale implementation of different voting systems. This project deals with the development of a face-based voting system with fingerprint authentication. The proposed project deals with the development of a Raspberry-based system using IOT which can use facial data as well as fingerprint-based data to implement a voting system online to vote for candidates. This system can implement an additional layer of security in voting since it is based on the biometric data of the user using face recognition and fingerprint authentication. The voting panel is developed for registering votes and display of results which is hosted on the IOT cloud.
Video Forgery Detection Using Machine Learning
Authors:-Ankita Malage, Vidya Kesarakar, Bhavana Sarapure, Asma Nadaf, Prof. Neelamma
Shinannavar
Abstract- Region duplication is a very easy and effective method to create digital image forgeries, where a continuous portion of pixels in an image are copied and pasted to a different location in the same image. Nowadays Video and image copy move forgery detection is one of the major hot topics in multimedia forensics to protect digital videos and images from malicious use. The Number of techniques has been presented through analyzing the side effect caused by the copy-move operation. In this paper, we propose a novel approach to detect copy-move forgery. And also coarse-to-fine detection strategy based on optical flow (OF) and stable parameters is designed to detect. The detected image is initially divided into overlapping blocks. After the creation of overlapped blocks, the feature extraction technique is applied to the image to extract the features from specific blocks of the image to identify duplicate blocks of an image.
CollabX : Empowering Student Collaboration and Career Development Through Project-Based Collaboration and Skill Analysis
Authors:-Durgesh Ahire, Mayuresh Shinde, Pavan Sargar, Neha Koli
Abstract- CollabX is a dynamic portal designed to facilitate student collaboration and support career growth. By offering features such as project collaboration, skill analysis via GitHub integration, personalized roadmaps, problem posting, peer recommendation, and an inbuilt messaging platform, CollabX addresses the challenges students face in finding suitable project partners. It enables students to post their projects, collaborate with interested peers, and analyze their skills based on factors like GitHub repositories, contributions, programming languages, collaboration experience, and achievements. CollabX provides personalized roadmaps for career development and fosters connections between students through problem posting and peer recommendations. Overall, CollabX creates an inclusive environment where students can collaborate, enhance their skills, and achieve career growth.
Review on Inversion of Short-Time Fourier Transform Magnitude in EMG signal by using MATLAB modelling
Authors:-Tanmay Gupta, Assistant Professor Hemant Amhia
Abstract- Electromyography (EMG) signal is the type of biomedical signal, which is obtained from the neuromuscular activities. Typically, an electromyogram instrument is used to capture the EMG signals. These signals are used to monitor medical abnormalities, activation level, and also to analyze the biomechanics of any animal movements. In this current work, we provide a short review of EMG signal acquisition and processing techniques. We found that the average efficiency to capture EMG signals with the current technologies is around 70 %. Once the signal is captured, the signal processing algorithms applied decides the recognition accuracy, with which signals are decoded for their corresponding purpose (e.g. moving robotic arm, speech recognition, gait analysis, etc). The recognition accuracy can go as high as 99.8 %. The accuracy with which the EMG signal is decoded has already crossed 99 %, and with the upcoming deep learning technology, there is a scope of improvement to design hardware, that can efficiently capture EMG signals.
Sustainability in Aviation Industry
Authors:-Pavithra Guru
Abstract- Air travel has become an extremely important factor to our global society, because it is the primary force behind global social, economic and cultural growth around the world. Approximately 3% of the world’s CO2 emissions are now produced by the aviation industry, with jet fuel consumption accounting for the majority of these emissions. However, improving the sustainability of air travel is not that easy. Lifting people and objects into the air and transporting them over great distances requires a lot of energy. On that account, our mini project will be dealing with the actions that airlines can take to lower their environmental impact by incorporating sustainability into every aspect of the regular tasks. This paper reviews the ways to improve the aviation’s long-term viability by emphasising on attaining sustainable aviation fuel and also by looking at new materials and coating technologies to make planes lighter and more aerodynamic. Furthermore, explore the challenges of introducing Operational improvements – on the ground, during departure and arrival and also in cruise. Additionally, in the last part of our study we have researched some approaches of different airlines through case studies and thrown light into failed theories to support our discussion.
Cervical Cancer Prediction Using Deep Learning
Authors:-Niveditha V, Sanjay S , Shalini K, Sumukh K Murthy, Dr. Neha Singhal, Prof. Pavithra N
Abstract- Given that gynecological cancers are among the most frequently diagnosed cancers, they pose a serious public health concern for women. Many women have a tendency to report their cancer at advanced stages in undeveloped countries with little cancer awareness programs, such as India, inconsistent pathology, and insufficient screening facilities, which negatively affects their prognosis and clinical outcomes. While cervical cancer continues to be second-most prevalent cancer after breast cancer, ovarian cancer is becoming more common in Indian women. Smoking, oral contraceptives, HPV (Human Papilloma Virus), and multiple pregnancies are just a few of the many causes of cervical cancer. Through early detection Adult women can avoid cervical cancer by getting timely treatment and taking tests like the PAP and HPV tests. PAP and HPV tests can detect.
Movie Recommendation System
Authors:- Kuldeep Kumar Singh, Priyanshu Bora, Arman Grover, Sajal Singh Masand, Yadender Singh
Abstract- In the era of information overload, it is very difficult for users to get information that they are really interested in. The mission of Recommendation System is to connect users and information, which in one way helps users to find information valuable to them and in another way push the information to specific users. The need for the hour is to develop some code that can tell at a beginner level the matching pattern of the customer trend and recommend him the best item of his interest level. This will help us in making the customer experience satisfactory and able to achieve good ratings and popularity as well.
Sustainability in Aviation Industry
Authors:- Pavithra Guru
Abstract- Air travel has become an extremely important factor to our global society, because it is the primary force behind global social, economic and cultural growth around the world. Approximately 3% of the world’s CO2 emissions are now produced by the aviation industry, with jet fuel consumption accounting for the majority of these emissions. However, improving the sustainability of air travel is not that easy. Lifting people and objects into the air and transporting them over great distances requires a lot of energy. On that account, our mini project will be dealing with the actions that airlines can take to lower their environmental impact by incorporating sustainability into every aspect of the regular tasks. This paper reviews the ways to improve the aviation’s long-term viability by emphasising on attaining sustainable aviation fuel and also by looking at new materials and coating technologies to make planes lighter and more aerodynamic. Furthermore, explore the challenges of introducing Operational improvements – on the ground, during departure and arrival and also in cruise. Additionally, in the last part of our study we have researched some approaches of different airlines through case studies and thrown light into failed theories to support our discussion.
A Review on Fake Currency Detection and Image Quality Improvement
Authors:- Diksha Bharti, Professor A.K. Sharma
Abstract- Counterfeit currency detection is a major issue around the world, influencing the economy of pretty much every nation including. The utilization of fake money is one of the significant issues looked all through the world now days. The forgers are getting more earnestly to find as a result of their utilization of profoundly trend setting innovation. One of the best techniques to quit forging can be the utilization of fake location programming that is effectively accessible and is proficient.
A Comprehensive Analysis of PID Based Electric Vehicle Model Design in Matlab 2015a Software
Authors:- Sabeer Pinjari, Prof. Madhu Upadhyay
Abstract- The Solar powered plug-in electric vehicle is an economic vehicle with minimum maintenance. The main drawback of electric vehicles is the limitation of driving distance. By adding a solar PV module the vehicle battery can be charged while on drive. Here the mechanical parts like gearbox and differential are avoided. Direct drive to wheels allows efficient drive.
Gesture Based Drawing – Gesdraw
Authors:- Asst. Prof Ms. Geeta N. Brijwani, Mr. Pranav Patel, Mr. Moinuddin Mansoori
Abstract- Using a trackpad or a pen tab might be restricting the artistic flow of people. The system suggested in this research seeks to address this issue. The solution is an application to track the user gestures and relay the drawing as such using only a web camera for the detection. There is a MediaPipe model that has been utilized with CV2, to allow real-time gesture detection and capture and thus it allows free flow of creativity.
Review on ECG Signal Entropy Assessment and PR Intervals Allocation in Malignant Venticilar Arrhythmias
Authors:- Shivani Patel, Hemant Amhia
Abstract- This work is an attempt to discuss and investigate various techniques of extracting and selecting the vital features from the ECG signal in order to analyze the ECG signal automatically. Feature extraction, classification of feature and optimization of extracted feature are some of the common steps of automatically analyze the ECG data. Morphological and statistical features of the ECG signals play very important role in detecting the heart related diseases. A morphological feature gives good result in arrhythmia classification while statistical feature are also useful because of variation in ECG signal for different patients.
Brain Controlled Robotic Arm Using BCI
Authors:- Dr.Priyanka Dubey
Abstract- In this paper we proposed a non-invasive BCI system for controlling a robotic arm. Brain-Computer Interface (BCI) technology has produced the best success in allowing people with motor disabilities to control robots and robotic gadgets through brain signals. The key component of this suggested system is an electroencephalography (EEG) signal recorder. It will capture scalp signals and then use machine learning techniques to classify the user’s intent.
Divisional Production of Micro-Electrodes by Electric Discharge Machining and It’s Performance Evaluation
Authors:- Sumit, Krishna Kumar, Lalla Singh, Mayank Patel
Abstract- Micro-EDM is widely used in micro-holes and 3D microstructures. However, micro-EDM applications are limited due to their rarity. Therefore, microelectrode fabrication is one of the most challenging and hot topics in the EDM field. In this study, EDM is used in the fabrication of microelectrodes. Parametric testing is necessary to ensure high dimensional accuracy of microelectrodes. It is performed by replicating a 1 mm diameter copper electrode on a steel block using a segmented fabrication method. A relationship is established between the excavated cavities of the block and the function of the microelectrodes. Editing effect of parameters (current, pulse width, and pulse pause) is seen on response variables (electrode underside length, electrode length, material removal, velocity, surface roughness and lateral deviation rate). Current and pulse width dominate over otherselected process parameters. Using parameters optimized from parametric studies, copper microelectrodes with a bottom length of 40 µm and a length of 1700 µm is produced. A 1100 μm long, 80μm wide and 30μm deep microchannel was machined on the copperseat.
Using an Adapted Hybrid Intelligent Framework to Make Predictions Regarding Heart Diseases
Authors:- Ms. Tanya Jain, Dr. Anurag Jain
Abstract- The effects of heart disease on a person’s life can be devastating, making it one of the world’s most serious health problems. Patients with heart disease have a compromised ability of the heart to pump blood throughout the entire body. A proper and prompt diagnosis of cardiac disease is the first step in preventing and treating heart failure. Diagnosing heart illness has a long history of being fraught with difficulty. Machine learning-based noninvasive technology can accurately and quickly distinguish between healthy people and those with heart disease. In the proposed research, we used heart illness datasets to develop a machine-learning-based detection system for predicting cardiovascular disease. In order to measure the efficacy of our machine learning algorithms, feature selection algorithms, and classifiers in terms of metrics like accuracy and specificity, we employed cross-validation. Our method allows for quick and easy differentiation between those with heart illness and healthy people. Analysis of the receiver optimistic curves and area under the curves for each classifier was performed. Classifiers, feature selection algorithms, preprocessing techniques, validation strategies, and performance metrics for classifiers have all been discussed in this work. The performance of the suggested system has been evaluated using both the full set of features and a subset. The results include a comparison of recall, F1 score, and false positive rate. Decreases in the number of features used to make a classification have a notable effect on both the classifier’s accuracy and the time it takes to run. The anticipated machine-learning-based decision support system would help doctors make more precise diagnoses of cardiac illness.
Literature Survey on Orthogonal Matching Pursuit For Different Applications
Authors:-Research Scholar Rukmini Kumari, Associate Prof. & HOD Dr. Bharti Chourasia
Abstract- Matching pursuit has been applied to FPGA, VLSI, signal, image and video coding, shape representation and recognition, 3D objects coding, and in interdisciplinary applications like structural health monitoring. Within all the practical applications, one critical issue that the compressive sensing needs to solve is how to reliably recover the original signals from the measured signal in an efficient way. Various algorithms have been proposed to reconstruct signals from the compressively sensed samples. There are several approaches, such as matching pursuit (MP). This paper presents review of orthogonal matching pursuit for VLSI applications.
Bidirectional Single Power Converter Using Low Battery Voltage
Authors:- Diksha Vinod Punshi, Vitthal S. Gutthe
School of Computer Engineering and Technology
Abstract- This paper provides a detailed survey of the past work in the power conversion converter area. The theoretical and experimental works from various types of single and bidirectional power conversion converter are discussed. This section briefly describes various improvements in performance in terms quality factor, efficiency etc. The following reviews provide a comprehensive survey about the developments in the state of art power conversion converter technology around the world.
Asystematic Review of Prevalence and Risk Factors That Affect Nutritional Status of Adolescents
Authors:-Dr. Evayline Nkirigacha-Miriti
Abstract- Adolescents are nutritionally vulnerable due to their high requirements for growth and development and sex maturation. Inadequate nutrition also puts them at high risk of chronic diseases and their detrimental effects appear after a long time during adulthood. Prevalence of malnutrition in adolescent is brought about by their overconsumption of processed foods, junk foods, failure to consume high fiber diets and lack of physical exercise. They also suffer stunting and underweight especially during childhood which is due to poverty and food insecurity in such households where such adolescents reside. Double burden of malnutrition in children and adolescents has such indicators as over nutrition such as overweight and obesity and those of underweight such as stunting, wasting and underweight and these occur simultaneously in both young children and adolescents.Adolescents’ high prevalence of malnutrition is brought about by food insecurity in households, poor hygiene and unsafe water consumption due to gastrointestinal infections. Poor diets which include processed carbohydrates and junk foods bring about high prevalence of overweight and obesity in adolescents and so is lack of physical activities. There is need therefore to engage adolescents in nutrition education and enlighten them on need to engage in physical activities.