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An algorithm for IoT based vehicle verification system using RFID
The verification of vehicle documents is an important role of transport department which is rising day by day due to the mass registration of the vehicles. An automated vehicle verification system can improve the efficiency of this process. In this paper, we propose an IOT based vehicle verification system using RFID technology. As a result, the vehicle checking which is done now manually can be replaced by automation. There is a loss of a significant amount of time when the normal vehicle checking is done manually. The proposed system will make this process automated. The present verification process is using inductive loops that are placed in a roadbed for detecting vehicles as they pass through the loop of the magnetic field. Similarly, the sensing devices spread along the road can detect passing vehicles through the Bluetooth mechanism. The fixed audio detection devices that can be used to identify the type of vehicles on the road. Other measurements are fixed cameras installed in specific points of roads for categorising the vehicles. But all these mechanisms cannot verify the documents and certificates of the vehicles. In our work, we have suggested an algorithm using RFID technology to automate the documentation verification process of the vehicles like Pollution, Insurance, Rc book etc with the help of RFID reader placed at road checking areas. This documents will be updated by the motor vehicle department at specific periods. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Differential Approach of Bioremediation by Sclerotium rolfsii Towards Textile Dye
Synthetic dyes are extensively used in various industries and are one of the major contaminants of industrial effluents. Dyes being xenobiotic, carcinogenic, and toxic there is need for their effective removal and detoxification to conserve water resources. Tremendous research has been carried out to identify potent microorganisms that facilitate bioremediation of these harmful dyes. A static batch culture has proved white rot fungi Sclerotium.rolfsii as an efficient catalyst in bioremediation of textile dyes and to compare their efficiency in decolourisation of two different azo dyes. Studies revealed the organism employ different remedial approach to cationic dye (Malachite green) and anionic dyes (Rose Bengal). Decolourisation of malachite green was a gradual with degradation and bio-transformation to colourless, non-toxic by products while Decolourisation of rose Bengal was quick process of biosorption. S.rolfsii exhibited 89% of decolourisation of malachite green dyes at higher concentration of 900mg/L while 96% for rose Bengal at 900mg/L. The mechanism of dye decolourisation was proposed using the UV Vis spectrophotometry, FTIR, XRD, HPLC and SEM. Microbial toxicity studies confirmed the dye metabolites of degraded malachite green was less toxic compared to original dye. Com- prehensively studies illustrate the sustained application of S. rolfsii as model organism for bioremediation of complex industrial effluents due to its differential bio remedial approach can potentially decolourise or remove various dyes. 2023, Association of Biotechnology and Pharmacy. All rights reserved. -
Hybrid botnet detection using ensemble approach
Botnets are one of the most threatening cyber-attacks available today. This paper proposes a hybrid system which can effectively detect the presence of C&C, P2P and hybrid botnets in the network. The powerful machine learning algorithms like BayesNet, IBk, KStar, J48 and Random Tree have been deployed for detecting these malwares. The performance and accuracy of the individual classifiers are compared with the ensemble approach. Labelled dataset of botnet logs were collected from the Malware Facility. Secured data was collected from Christ university network and the combined dataset is tested using virtual test bed. The performance of the algorithms is studied in this paper. Ensemble approach out performed individual classifiers. 2005 ongoing JATIT & LLS. -
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A comparative study of magnetite and MnZn ferrite nanoliquids flow inspired by nonlinear thermal radiation
The characteristics of the magnetohydrodynamic (MHD) stagnation point flow of ferrofluids are investigated. The effects of nonlinear thermal radiation, heat generation and viscous dissipation are considered. Two different nanoparticles (Fe3O4 and MnZnFe2O4) are comprised in the base fluid (water). The ordinary differential equations are formed using suitable similarity transformations from the governing partial differential equations. The subsequent nonlinear ordinary differential equations are solved numerically using RKF-45 method. The influence of governing parameters on the results are analysed. It is found that the thermal boundary layer thickens due to the influence of nonlinear radiation and heat generation for both the fluids. The rate of heat transfer is higher for MnZn ferrite-nanofluid in comparison with magnetite nanofluid. 2017 by American Scientific Publishers All rights reserved. -
Quadratic convective flow of radiated nano-Jeffrey liquid subject to multiple convective conditions and Cattaneo-Christov double diffusion
A nonlinear flow of Jeffrey liquid with Cattaneo-Christov heat flux is investigated in the presence of nanoparticles. The features of thermophoretic and Brownian movement are retained. The effects of nonlinear radiation, magnetohydrodynamic (MHD), and convective conditions are accounted. The conversion of governing equations into ordinary differential equations is prepared via stretching transformations. The consequent equations are solved using the Runge-Kutta-Fehlberg (RKF) method. Impacts of physical constraints on the liquid velocity, the temperature, and the nanoparticle volume fraction are analyzed through graphical illustrations. It is established that the velocity of the liquid and its associated boundary layer width increase with the mixed convection parameter and the Deborah number. 2018, Shanghai University and Springer-Verlag GmbH Germany, part of Springer Nature. -
Radiative nonlinear 3D flow of ferrofluid with Joule heating, convective condition and Coriolis force
Characteristics of heat transport mechanism in three-dimensional ferrofluid flow past a deformed surface subjected to the Coriolis and Lorentz forces are analyzed. The impacts of Joule heating, nonlinear thermal radiation, viscous dissipation and convective condition are also accounted. The carrier fluid (water) is embedded by Fe3O4 nanoparticles. The boundary layer approximations are employed in problem statement. Stretching transformations are utilized to form nonlinear ODE system from governed PDE system. The subsequent system is treated numerically via Runge-Kutta-Fehlberg method. Effects of relevant parameters on different flow fields are discussed comprehensively with help of graphs. It is established that the heat transfer rate is enhanced due to Coriolis and Lorentz forces. Furthermore, Fe3O4 nanoparticles enhance the Nusselt number significantly in comparison with Al2O3 nanoparticles. 2017 -
Thermal analysis of nanofluid flow containing gyrotactic microorganisms in bioconvection and second-order slip with convective condition
Bioconvection in magneto-nanoliquid embedded with gyrotactic microorganisms across an elongated sheet with velocity slip of second order is addressed. Nonlinear thermal radiation and chemical reaction aspects are retained in energy and concentration equations. Numerical simulations for the modeled problem are proposed via RungeKuttaFehlberg-based shooting technique. Special attention is given to the impact of involved parameters on the profiles of motile microorganisms, nanoparticle volume fraction, temperature and velocity. Our simulations figured out that assisting flow generates more heat transfer than the opposing flow situation. The motile microorganisms boundary layer decayed for higher bioconvection Peclet and bioconvection Lewis numbers. 2018, Akadiai Kiad Budapest, Hungary. -
Design of pseudo stator generator
In today's energy generation scenario, the extensive use of conventional sources are causing lot of environmental issues. It is necessary that humankind should come up with a strategy to produce clean energy. Even though we cannot completely stop relying on non-renewable sources of energy, lot of research is happening to find the ideal substitute for conventional sources of energy and also for migrating towards renewable energy sources from conventional sources. Its gaining popularity because of the fact that availability of fossil fuels are reducing at an alarming rate. Thus, these research works will aid in producing clean energy and also make the existing systems more efficient. A better substitution would be to design a machine which would use less conventional sources of energy and gives required output. Thus it is necessary to come up with a new technology which would suffice the above stated requirements. The proposed project is an novel idea aimed at designing an alternator which has higher power output at lower RPM when compared to conventional alternators. This model finds application in automobiles, WECS, Aerospace, hybrid vehicles in the near future. 2016 IEEE. -
Experimenting with ONOS scalability on software defined network
In traditional network, a developer cannot change the configuration of a router with software programs to control the behavior of the network switches due to closed vendor specific configuration scripts. In order to make the routers/switches programmable, a new architecture of network has to be developed and this gave rise to Software defined networks. It is the new architecture for Computer Networks in which, the old traditional architecture is slowly depreciated. It is very difficult to adapt new technology especially to decide upon which controller has to be considered and what may be its scalability to compete the dynamic circumstances of networks. Many researches are working on possible solutions and look upon SDN to overcome the traditional network limitations. There are many SDN controllers existing amongst them, some are OpenDaylight, Floodlight, Onos, Ryu, Beacon etc. From the existing multiple controllers serving the SDN services to the network, Onos is one of the Controller. ONOS can be deployed on Docker container and it is accessed using its IP as a host. In this paper, authors are contributing for the evaluation of the Performance to check the Scalability of ONOS controller by taking many scenarios which are experimented on the simulation tool of Mininet, Onos Controller, Docker and iPerf. ONOS Controller?s simulated environments are observed for its throughput evaluated in dynamic conditions of a network over Mesh topology by gradually increasing the number of hosts until its supported by the system with optimum resource utilization. 2018, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
Triple diffusive convection in a vertically oscillating oldroyd-b liquid /
International Journal of Mechanical and Mechatronics Engineering, Vol.12, Issue 9, pp.863-869, ISSN No: 1307-6892. -
An artificial intelligence based smart cap with voice assistant for blind person /
Patent number: 202241013502, Applicant: Dr. Aruna S K.
People who are completely blind or have reduced eyesight confront numerous challenges while navigating. Every day, they face a variety of challenges, particularly in terms of mobility. Several systems have been developed to assist visually impaired people and improve their quality of life. This invention helps the blind to navigate independently using smart cap. It enables visually impaired people to see the world by voice assistance. It enables the blind and visually impaired to navigate freely by allowing them to experience their surroundings through audio output that describes the identified things. -
AI-based online interview bot with an interactive dashboard
In recent years, video interviews have become increasingly popular in the recruitment process due to their convenience and efficiency. However, evaluating a candidates communication skills and perceived personality traits from a video interview can be challenging. The agent utilizes natural language processing and computer vision techniques to analyze the candidates verbal and nonverbal behavior during the interview. Specifically, the agent focuses on linguistic features such as fluency, grammar, and vocabulary, as well as nonverbal cues such as facial expressions and body language. Based on these features, the agent predicts the candidates communication skills and perceived personality traits. To validate the effectiveness of the agent, a Talk was conducted with a group of participants who completed video interviews with and without the agent. The results show that the agents predictions of communication skills and perceived personality traits are highly correlated with the ratings given by human evaluators. Additionally, the agent is able to provide valuable insights into the candidates performance that may not be immediately apparent to human evaluators. Overall, the intelligent video interview agent proposed here has the potential to improve the recruitment process by providing more accurate and objective evaluations of candidates communication skills and perceived personality traits. 2025 selection and editorial matter, A. Vadivel, K. Meena, P. Sumathy, Henry Selvaraj, P. Shanmugavadivu and Shaila S. G.; individual chapters, the contributors. -
Enhanced Level Brain Tumor Identification Using CNN, VGG16 and ResNet Models
The comprehension of brain growths is significantly improved through the identification and categorization of these disorders. Still, their discovery is relatively grueling due to their variability in terms of position, shape, and size. Fortunately, deep literacy has revolutionized the field and significantly improved recognition, prediction, and opinion in various healthcare areas, including brain excrescences. The main goal of this study is to thoroughly review exploration that utilizes CNN, VGG16, and RESNET infrastructures to classify brain excrescences using MRI images. The performance of these models varied significantly, with CNN, VGG16, and RESNET achieving an emotional delicacy of 99.6. Additionally, ResNet and VGG16 achieved rigor of 92.4 and 89.7 independently. Likewise, the visualization of the decision-making processes of these models has provided valuable insight into the features they prioritize. By incorporating these models into their practice, healthcare professionals have the opportunity to enhance their individual capabilities, eventually leading to improved patient outcomes. 2024 IEEE. -
Comparison of Machine Learning-Based Intrusion Detection Systems Using UNSW-NB15 Dataset
Various machine learning classifiers have been employed recently to enhance network intrusion detection. In the literature, researchers have put forth a wide range of intrusion detection solutions. The accuracy of the machine learning classifiers intrusion detection is limited by the fact that they were trained on dated samples. Therefore, the most recent dataset must be used to train the machine learning classifiers. In this study, UNSW-NB15, machine learning classifiers are trained using the most recent dataset. A taxonomy of classifiers based on eager and lazy learners is used to train the chosen classifiers, such as K-Means (KNN), Polynomial Features, Random Forest (RF), and Naive Bayes (NB), Linear Regression. In order to decrease the redundant and unnecessary features in the UNSW-NB15 dataset, chi-Square, a filter-based feature selection technique, is used in this study. When comparing these machine learning classifiers, performance is measured in terms of accuracy, mean squared error (MSE), precision, recall, and F1-score with or without feature selection technique. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024. -
Optical Character Recognition (OCR) based Vehicle's License Plate Recognition System Using Python and OpenCV
License Platform Detection is a computer technology that enables us to identify digital images on the platform automatically. Different operations are covered in this system, such as imaging, number pad locations, alphanumeric character truncation and OCR. The final objective of the system is to construct and create efficient image processing procedures and techniques to position a licensing platter on the Open Computer View Library picture. It was used and implemented the K-NN algorithm and python programming language. The technology can be used in different industries such as security, highway speed detection, lighting violations, manuscript documents, automatic charging system, etc. Auto plate recognition is an integrated technology which identifies the auto licence plate. Auto plate auto recognition. Multiple applications include complex safety systems, public spaces, parking and urban traffic control. Automatic Vehicle License Plate Recognition (AVLPR) has undesirable aspects because of many effects, such as light and speed. This work presents an alternative technique to leverage free software for the implementation of AVLPR systems including Python and the Open Computer Vision (openCV). 2021 IEEE. -
Pen mouse/14-02
Patent Number: 365494-001, Applicant: Ritwika Das Gupta. -
Model of ICT based blended education system: Productive implementation for sector skills development /
Patent Number: 202141055854, Applicant: Suplab Podder. -
Toy telephone /
Patent Number: 346943-001, Applicant: Ritwika Das Gupta. -
Creativity and innovation in quality education and sustainability /
Patent Number: 202141034649, Applicant: Suplab Podder.
Quality education and sustainability is the interconnected aspiration for the modern society that can ensure the development of employability skills and create a sustainable society. The economists, scientists, management experts and research initiators are putting their efforts to develop a certain sustainable system in quality education through education 4.0. This is about digital equity, customised education, borderless classrooms, where the human mind is in synchronising with the technology to explore new possibilities of learning and accomplishment.