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Ultra-miniaturized dGS-based Meander Line Multi-band Filters with/without resonators for Satellite Band Applications

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Journal of The Institution of Engineers (India): Series B 2022年第1期103卷 213-223页

作者： Oudaya coumar, S. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sakunthala R&D Institute of Science and Technology Tamilnadu Chennai India

An ultra-miniaturized meander line inspired dual-band filters with and without open stub loaded rectangular resonator defected on the ground plane are presented. The dual-band characteristic is obtained from half wavelength rectangular resonator which eliminating certain frequency bands forming dual-band operation. The transmission zero in the pass band is determined by modifying the dimensions of the resonator. The miniaturized meander line dGS-based filter is analyzed with and without rectangular resonator. The rectangular resonator incorporated with meander line coupling acts a crucial part in dual-band filters (dBFs). The miniaturization of dGS-based meander line inspired filters can be realised by varying the overall substrate size for (20 × 20) mm, (10 × 10) mm and (5 × 5) mm. The proposed dBF with rectangular resonator produces tremendous bandwidth ranges from 1.2 to 6.8 GHz (Band I) and 7.2–12.4 GHz (Band II) whose bandwidths are 5.6 GHz and 5.2 GHz, respectively. The filter characteristics show the filter’s return loss (S11) of − 29.55 dB and insertion loss (S21) of − 2.45 dB. The proposed dBF without rectangular resonator produces tremendous bandwidth ranges from 1.2 to 8.2 GHz (Band III) and 9–13.8 GHz (Band IV) whose bandwidths are 7 GHz and 4.8 GHz, respectively. The filter characteristics show the filter’s return loss (S11) of − 32.2 dB and insertion loss (S21) of − 1.35 dB. The performances of both filters are evaluated and analysed through S-parameters. Also, the measured results of both the filters obey the simulated results. The proposed filter is confined with the size of (10 × 10 × 1.6) mm3 or (0.15) λg2 which is nearly 200% less when compared with other existing design. © 2021, The Institution of Engineers (India).

关键词： Bandwidth

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A comparative study on the various alternative materials for fine aggregate in concrete

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Materials Today: Proceedings 2022年 65卷 1614-1622页

作者： Jayadurgalakshmi, M. Kandasamy, S. Department of Civil Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai 600 062 India

At present, concrete is an important construction material for every infrastructure because of mechanization and enlargement. Increasing population puts a lot of pressure on civil engineers to develop cost-effective and eco-friendly infrastructure. Concrete is made of binding material (cement or lime), coarse aggregate, fine aggregate and water in various proportions. Building industry has been impacted by fine aggregate availability due to its shortage in quantity from the sources. That necessitated the development of new alternative material to replace the fine aggregate in order to reduce the environmental harm. Numerous researchers are finding different materials to replace fine aggregate such as Cenosphere, Vermiculite, Ceramic Waste, Egg Shell, Walnut Shell, etc which is made up of waste and used as the partial replacement of fine aggregate. In this study, the researchers have reviewed previous researches on the use of other waste materials and concluded that Cenosphere being used as partial replacement of fine aggregate, that produce lightweight concrete. © 2022

关键词： Cost effectiveness

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Endoscopic Bladder Tissue Classification Using Seventeen Layered deep Convolutional Neural Network 2

Endoscopic Bladder Tissue Classification Using Seventeen Lay...

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： devi, M. Shyamala Pandian, J. Arun Umanandhini, d. Viknesh, V. Vishal, G.P. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Computer Science & Engineering Tamilnadu Chennai India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350370188

After a diagnosis of bladder cancer, endoscopic surgery is carried out as it is thought to be the most efficient and appropriate method of treating superficial tumors. It is essential to classify the bladder tissues accurately using MrI since early diagnosis of the problem can aid in treatment and perhaps save lives. Early-stage diagnosis is still challenging due to the delayed onset of indications and tiny alterations in urinary tract tissue that are imperceptible to the naked eye for diagnosis. The automated approach might be utilized to automatically determine the type of endoscopic bladder tissue by using the proper deep learning model with the necessary convolutional layers. This paper suggests the Seventeen Layered deep Convolutional Neural Network (17-dCNN) to classify the bladder tissue classes effectively. The Endoscopic bladder tissue dataset from Kaggle is used for the implementation of dOMN that contains 1785 images with four classes as HGC, LGC, NTL, and NST. The 17-dCNN model's initial phase is an analysis of distribution of bladder tissue data images. After data preparation, the existing CNN like denseNet121, resNet152, VGG19Net, InceptionV3Net and proposed 17-dCNN model is chosen by fitting the Endoscopic bladder tissue images. The accuracy of the proposed 17-dCNN was 99.32% when compared to other CNN models after implementation. © 2024 IEEE.

关键词： Convolutional neural networks

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IoT Based Electric Vehicle Battery with Protection Against Fire 3

IoT Based Electric Vehicle Battery with Protection Against F...

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3rd International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2023

作者： Prakash, S.Vinoth John Kesavan, d. Sathyanathan, P. Barathi, K. Priya, r.A. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Chennai India Sona College of Technology Salem India

ISBN: (纸本)9798350306989

The electric vehicle battery system with fire protection system is done in this work. The proposed system is designed to enhance the safety of EV batteries by preventing overcharging and protecting against events causes fire. The charge monitor system continuously monitors the battery's state of charge and prevents overcharging by cutting of the charging current when the battery reaches its maximum capacity. This system designed using Arduino Nano (ATMEGA328p), sensors and GSM Module. The fire protection system uses temperature sensor to detect the heat. The proposed electric vehicle battery system with charge monitor and fire protection can enhance the safety of EV batteries. © 2023 IEEE.

关键词： Internet of things

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Logistic Multilayer Perceptron Neural Network Classification based driving Behavior Prediction through Vehicle Motion data 3

Logistic Multilayer Perceptron Neural Network Classification...

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3rd International Conference on Advances in Electrical, Computing, Communication and Sustainable technologies, ICAECT 2023

作者： devi, M. Shyamala ranjani, r. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Computer Science & Engineering Tamil Nadu Chennai India

ISBN: (纸本)9781665494007

Traffic accidents are caused in effect through driver's negligent driving habits. driving aggressively is a significant component that can rapidly result in risky driving. Safe and efficient erratic driving detection techniques, which allow for the creation of driving behavior analysis and early warning systems, are critically required in order to decrease traffic injuries and enhance road safety. With this motivation, this work uses 'Vehicle motion dataset' which contains the motion information gathered by a phone affixed to the vehicle's accelerometer and gyroscope. This paper aims to forecast the driving behavior of the driver by suggesting 'Logistic Multilayer Perceptron Neural Network (LMPNN)' uses the vehicle motion dataset retrieved from the KAGGLE database. The vehicle motion dataset consists of 8 features that collectively contain 3084 driving movement data. The LMPNN begins by interpreting exploratory data, which had been processed with insufficient data. The information was then divided in an 80:20 ratio for testing and learning. Geforce Nvidia V100 Graphics card processor with 30 learning iterations, each subject to a 64-batch threshold, was used to code Python scripts. To test the effectiveness of predicting driving behavior, the dataset was run through all the classifiers and a multilayer perceptron with relu, identity, tanh, and logistic activation layer. Execution results portrays that suggested LMPNN that is MLP model with logistic layer having 99% of Accuracy when compared to other existing classifiers. © 2023 IEEE.

关键词： Multilayer neural networks

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deep Q-Network Based reinforcement Learning for Bitcoin Future Price Prediction 2

Deep Q-Network Based Reinforcement Learning for Bitcoin Futu...

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： devi, M. Shyamala Pandian, J. Arun Umanandhini, d. Surekha, B. Sree, K. Bhavya Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Computer Science & Engineering Tamilnadu Chennai India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350370188

Bitcoin is the very first decentralized digital money in the entire world. Bitcoin is exceptionally reliable since it uses a block chain instead of a service provider like a banking institution. As a type of digital precious metal like gold, the price of a single bitcoin seems to have been significantly increasing since the year 2010. As a result, bitcoin is extremely risky for speculators as its value varies often. Since prices may now be predicted in real time, traditional techniques to price forecasting have failed to provide sufficient information and responses. This paper recommends deep Q-Network based reinforcement Learning technique (dQNrL) to predict the bitcoin price more effectively. The Binance Bitcoin Futures Price dataset from Kaggle that contains 3082284 samples and is used towards the bitcoin future cost prediction for dQNrL. The dQNrL model starts with the data exploration that portray the bitcoin price with the standard deviation and mean, log transformation of data. After data preparation, the Binance Bitcoin Futures Price dataset is fitted with the existing regression technique and proposed dQNrL model and the performance is analyzed with MAE, MSE and rMSE. The proposed dQNrL exhibits low MAE with 0.2471, low MSE with 0.061 and low rMSE of 0.2469 when compared to other existing regression models after implementation. © 2024 IEEE.

关键词： Metadata

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Effect of dielectric medium on electro-discharge machining of aluminium metal matrix composites

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Materials Today: Proceedings 2023年 92卷 61-65页

作者： Muniamuthu S. rathinasuriyan C. Santhosh kumar V. Department of Mechanical Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi Chennai-62 India Department of Mechanical Engineering Vel Tech Chennai-62 India

Aluminium Metal Matrix Composites (AMMCs) are used in several engineering demands because it has a higher strength-to-weight ratio. In this study, aluminium grade 7075 composites have been machined using an unconventional EdM machine. The reinforcements of SiC and Al2O3 with 2 %, 4 %, 6 %, and 8% are used for producing aluminium MMC using an electronically controlled bottom die pouring stir casting machine. The effect of dielectric mediums like liquid nitrogen and deionized water on the electro-discharge machining of aluminium MMC has been analyzed. Gap voltage, pulse-on time, pulse-off time, and current were the controllable input parameters. Material removal rate (Mrr), Tool Wear rate (TWr), and Surface roughness (Sr) are considered the machining output parameters for this work. The result revealed that Mrr, TWr, and Sr values have less while machining silicon carbide (SiC) reinforcements than alumina for both dielectric mediums. Mrr has been gradually declining as the SiC reinforcement fraction on aluminium matrix material has increased. This is due to the presence of SiC ceramic particles in the aluminium matrix material, which reduce the mobility of electrons within the workpiece. The microstructure results presented that the liquid nitrogen EdM techniques produced fewer globules and damaged layers than the deionized water EdM approaches. © 2023

关键词： deionised water Electro discharge Machining (EdM) Liquid Nitrogen (LN2) Metal Matrix Composite

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Optic disc and optic cup segmentation based on deep learning methods

Optic disc and optic cup segmentation based on deep learning...

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Alex david, S. ruth Naveena, N. ravikumar, S. Carmel Mary Belinda, M.J. Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu India Department of Mathematics Hindustan Institute of Technology & Science Tamil Nadu Chennai India

ISBN: (纸本)9781032669663

A lethal eye ailment called glaucoma causes the retina to gradually degrade over time. Although there is no complete cure, early detection helps slow the disease’s course. Early diagnosis is very rare because there are usually no obvious symptoms present in the early stages. Early glaucoma detection is essential because delayed diagnosis might result in permanent vision loss. The Optic Nerve Head is harmed by glaucoma, which then damages the retina (ONH). The measurements of the retina’s Optic Cup (OC) and Optic disc (Od) are necessary for its diagnosis. Glaucoma can be effectively and accurately diagnosed using computer vision techniques with minimum overhead. These methods employ classification and segmentation algorithms that are based on machine learning to measure OC and OC dimensions. This article’s objective is to give a thorough overview of the many methods used to identify and diagnose glaucoma using fundus pictures. readers can recognise the gaps in existing works and comprehend the difficulties that glaucoma presents from the perspectives of image processing and machine learning. © 2024, CrC Press/Balkema. All rights reserved.

关键词： Ophthalmology

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deep Learning-Based FOPId Controller for Cascaded dC-dC Converters

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Computer Systems science & Engineering 2023年第8期46卷 1503-1519页

作者： S.Hema Y.Sukhi Department of EEE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India Department of EEE R.M.K.Engineering CollegeKavaraipettaiChennai601206India

Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power ***-linear phenomena in power systems,such as voltage collapse and oscillatory phenomena,can be investigated by chaos ***,renewable energy resources,such as wind turbines,and solar photovoltaic(PV)arrays,have been widely used for electric power *** design of the controller for the direct Current(dC)converter in a PV system is performed based on the linearized model at an appropriate operating ***,these operating points are everchanging in a PV system,and the design of the controller is usually accomplished based on a low irradiance *** study designs a fractional-order proportional-integrated-derivative(FOPId)controller using deep learning(dL)with quasi-oppositional Archimedes Optimization algorithm(FOPId-QOAOA)for cascaded dC-dC converters in micro-grid *** presented FOPIdQOAOA model is designed to enhance the overall efficiency of the cascaded dC-dC boost *** addition,the proposed model develops a FOPId controller using a stacked sparse autoencoder(SSAE)model to regulate the converter output *** tune the hyper-parameters related to the SSAE model,the QOAOA is derived by the including of the quasi-oppositional based learning(QOBL)with traditional ***,an objective function with the including of the integral of time multiplied by squared error(ITSE)is considered in this *** validating the efficiency of the FOPId-QOAOA method,a sequence of simulations was performed under distinct aspects.A comparative study on cascaded buck and boost converters is carried out to authenticate the effectiveness and performance of the designed techniques.

关键词： Micro-grid deep learning archimedes optimization algorithm FOPId controller objective function

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An Edge Computing Enabled Internet of Medical Things device for remote Patient Health Monitoring Applications

An Edge Computing Enabled Internet of Medical Things Device ...

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2024 IEEE Students Conference on Engineering and Systems, SCES 2024

作者： Manoj, Ashwin Paramasivam, A. Vijayalakshmi, S. Bhaskar, K.B. Thriumbiga, S.K. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Biomedical Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Elect. Comm. Engg. Chennai India Adhi College of Engineering and Technology Department of Elec. and Electro. Engg. Kanchipuram India

ISBN: (纸本)9798350374711

recent days, Patient Monitoring helps the medical professionals to monitor patient throughout the day. Also, the use of Internet of Medical Things (IoMT) enables this process to be done remotely. IoMT is a subset of Internet of Things, specialized in medical applications. Moreover, Artificial Intelligence (AI) based image classification algorithms can be incorporated to improvise and automate the process, to detect the patients' health state. In this work, an edge computing enabled Internet of Medical Things (IoMT) device is designed and developed for remote health monitoring applications. Further, a less expensive ESP32 CAM device is utilized as an edge computing enabled IoMT device in which a MobileNetV2 version 0.35 model Algorithm is integrated to predict two different patient activities such as asleep and critical conditions. results demonstrate that the MobileNetV2 version 0.35 model has a better classification accuracy of 97.5%. Also, it is observed that the proposed AI-enabled edge computing device is capable of identifying the patient's conditions and it alerts the physician about the patient's critical conditions using Short Messaging Service (SMS). This work appears to be of high societal relevance since the proposed device helps the physician to monitor the patient's conditions in a remote manner. © 2024 IEEE.

关键词： Electronic health record

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