VIJAYAKRISHNA RAPAKA E

@rgcet.edu.in

Professor and Mechanical Engineering
RAJIV GANDHI COLLEGE OF ENGINEERING AND TECHNOLOGY, PUDUCHERRY

VIJAYAKRISHNA RAPAKA E


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https://researchid.co/krishna12

EDUCATION

Ph.D. in Ocean Engineering from IIT Madras
M. Tech. in Energy Technology from Pondicherry University
B. Tech. in Mechanical Engineering from Pondicherry University

RESEARCH INTERESTS

Ocean Energy, Solar Energy
7

Scopus Publications

127

Scholar Citations

3

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Grey Wolf Optimizer with Deep Learning based Short Term Traffic Forecasting in Smart City Environment
    R Jegadeesan, E Vijayakrishna Rapaka, K. Himabindu, Nihar Ranjan Behera, Arvind Kumar Shukla, Arvind Kumar Dangi
    Proceedings 5th International Conference on Smart Systems and Inventive Technology Icssit 2023, 2023
    Intelligent Transportation System (ITS) is one of the revolutionary technologies in smart cities that aids in minimizing traffic congestion and improving traffic quality. ITS provides real-time analysis and very effective traffic management by utilizing big data and communication technology. Traffic Flow Prediction (TFP) becomes a dynamic component in smart city management and was utilized for predicting the future traffic conditions on transportation networks relevant to past data. Machine Learning (ML) and Neural Network (NN) techniques can be broadly used in resolving real-time problems as these techniques are capable of managing adaptive data for some time. Deep Learning (DL) is a sub-divison of ML methods which earns effective performance on prediction and data classification tasks. This article designs a Grey Wolf optimizer with Deep Learning Based Short Term Traffic Forecasting (GWODL-STTF) in smart city environment. The presented GWODL-STTF technique concentrates on the prediction of traffic flow in smart cities. The presented GWODL-STTF technique involves two major processes. At the initial stage, the GWODL-STTF technique employed gated recurrent unit-neural network (GRU-NN) model to forecast traffic flow. Next, in the second stage, the GWODLSTTF technique makes use of GWO algorithm as a hyperparameter optimizer. The simulation values of the GWODL-STTF method can be tested under several metrics and the outcomes show the significant performance of the GWODLSTTF method over recent approaches with minimum MSE of 105.627.
  • Modeling of Optimal Deep Learning Enabled Object Detection and Classification on Drone Imagery
    Nirmal Adhikari, Nihar Ranjan Behera, Vijayakrishna Rapaka E, Er. S. John Pimo, Vaibhav Chaturvedi, Vikas Tripathi
    Proceedings International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2022, 2022
    Object detection in unmanned aerial vehicle (UAV) images becomes a persistent problem in the domain of computer vision. Particularly, object detection in drone images is a difficult process because of the object of different scales namely, hills, buildings, and water bodies. The study presents an execution of ensemble transfer learning to improve the efficiency of the fundamental model for multi-scale object recognition in drone imagery. This study develops an Optimal Deep Learning Enabled Object Detection and Classification on Drone Imagery (ODL-ODCDI) technique. The presented ODL-ODCDI technique can recognize and classify the objects present in the images collected by the drones. It follows a two stage process. In the first level, the ODL-ODCDI technique employed YOLO-v5 as object detector with Nadam optimizer. Next, in the latter level, the ODL-ODCDI technique makes use of random forest (RF) classifier to identify objects in the drone images. To establish the enhanced performance of the ODL-ODCDI approach, a series of experiments were performed. The experimental values depicted the improved outcomes of the ODL-ODCDI method over other DL models.
  • Equilibrium Optimizer with Deep Learning Model for Autism Spectral Disorder Classification
    A. Praveena, N. Senthamilarasi, T. S. Karthik, Abirami S.K, Vijayakrishna Rapaka E, Shyamali Das
    International Conference on Automation Computing and Renewable Systems Icacrs 2022 Proceedings, 2022
    Autism Spectrum Disorder (ASD) is a developing disorder if the symptoms develop obvious in the initial years of age but it could be present in some age groups. ASD is mental health problem that affects communicational, social, and non-verbal performances. It could not be cured entirely but is decreased when identified initially. The primary analysis was hampered by the difference and severity of ASD symptoms and containing symptoms usually realized in other mental health problems as well. With the application of machine learning (ML) for the predictive and recognition of several diseases with optimum accuracy, a ray of hope to initial recognition of ASD dependent upon many physiological and physical parameters is projected. This article designs an Equilibrium Optimizer with Deep Learning Model for Autism Spectral Disorder Classification (EODL-ASDC) technique. The presented EODL-ASDC technique mainly focuses on the identification and classification of ASD. To attain this, the presented EODL-ASDC technique exploits the deep belief network (DBN) system to perform the classification procedure. In addition, the EO algorithm is employed for the optimal hyperparameter tuning of the DBN approach. To demonstrate the enhanced ASD classification result of the EODL-ASDC approach, an extensive range of experimental evaluates was executed. The experimental results demonstrate the improvements of the EODL-ASDC technique over other approaches.
  • Automated Intracranial Haemorrhage Detection and Classification using Rider Optimization with Deep Learning Model
    T. S. Karthik, Naziya Hussain, N K Anushkannan, Rajasekhar Pinnamaneni, Vijayakrishna Rapaka E, Shyamali Das
    International Conference on Automation Computing and Renewable Systems Icacrs 2022 Proceedings, 2022
    Intracranial haemorrhage (ICH) refers to a pathological disorder that requires quick decision-making and diagnosis. Computed tomography (CT) can be accurate and dependable diagnosis method for identifying haemorrhages. Automated recognition of ICH through CT scans with a computer-aided diagnosis (CAD) method will be useful to classify and detect the distinct grades of ICH. Due to the latest development of deep learning (DL) techniques in image processing applications, numerous medical imaging methods use it. Thus, this article develops an automated ICH detection and classification using Rider Optimization with Deep Learning (ICHDC-RODL) model. The presented ICHDC-RODL technique mainly determines the presence of ICH using DL concepts. In the presented ICHDCRODL technique, the features are generated by the use of Xtended Central Symmetric Local Binary Pattern (XCS-LBP) model. Moreover, the bidirectional long short-term memory (BiLSTM) method is employed for ICH diagnosis. At last, the rider optimization algorithm (ROA) is exploited for the hyperparameter tuning procedure of the BiLSTM method. To demonstrate the enhanced outcomes of the ICHDC-RODL technique, a series of simulations were performed and the results are examined under various aspects. The simulation outcomes indicate the enhancements of the ICHDC-RODL technique over recent approaches.
  • Experimental investigation on the dynamic response of a moored wave energy device under regular sea waves
    E Vijayakrishna Rapaka, R Natarajan, S Neelamani
    Ocean Engineering, 2004
  • Experimental study on the dynamic response of a moored floating wave energy device
    E. Vijayakrishna Rapaka, R. Natarajan, S. Neelamani
    Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering OMAE, 2003
    A detailed experimental investigation conducted on a moored Oscillating Water Column (OWC) wave energy device has been reported in this paper. The experiments were conducted on 1:20 scale model of the wave energy device, which was moored to the bed using 6 mooring lines in a 2m wide (deep and shallow water) wave flume at Ocean Engineering Department, IITM, Chennai. A range of hydrodynamic parameters with different damping ratio of the OWC chamber at scope 4 (length of the mooring line/depth of water) for a constant water depth was used. The effect of non-dimensionalized parameters like non-dimensionlized wave frequency parameter (ω2B/2g) and device breadth to wave length ratio (B/L) on the mooring force and on the efficiency of the wave energy device has been studied. The motion responses and mooring forces were measured and the test results are analysed and presented with discussions in this paper.
  • On the efficiency and transmission characteristics of a 1:20 model fixed wave energy device
    E. Vijayakrishna Rapaka, S. Neelamani, R. Natarajan
    Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering OMAE, 2003
    Wave transmission and pneumatic efficiency of an oscillating water column (OWC) type wave energy device resting on group of piles is investigated using physical model study. The caisson blocks 45% of the water depth. The co-efficient of transmission of the device varies from 0.1 to 0.4 for B/L range of 0.1 to 0.7, where ‘B’ is the width of the caisson in the direction of wave propagation and ‘L’ is the wavelength. The pneumatic efficiency varies from 20% to 50% with an average value of 0.35. The results of the present study can be used in the design of OWC caisson used for both wave energy conversion and breakwater in deeper water.

RECENT SCHOLAR PUBLICATIONS

  • Synthesis of porous CuCo2O4 nanorods/reduced graphene oxide composites via a facile microwave hydrothermal method for high-performance hybrid supercapacitor applications
    S Jayasubramaniyan, S Balasundari, SJ Yeom, N Naresh, T Rani, ...
    Electrochimica Acta 390, 138865 , 2021
    2021.0
    Citations: 43
  • A Study on the Influence of Higher Secondary Subjects Scores on Engineering Performance
    JJ Jasmine, EV Rapaka
    International Journal of Engineering and Management Research (IJEMR) 7 (4 … , 2017
    2017.0
  • Experimental Investigations on a 1.00 m 2 Solar Gel Pond
    N Sozhan, T Senthilvelan, T Kaliyappan, EV Rapaka, SP Sivapirakasam
    Applied Mechanics and Materials 592, 2360-2364 , 2014
    2014.0
    Citations: 1
  • Experimental investigation on a 0.25 m2 solar gel pond
    N Sozhan, T Senthilvelan, T Kaliyappan, EV Rapaka
    International journal of innovative research in science, engineering and … , 2013
    2013.0
    Citations: 13
  • Experimental investigation on the dynamic response of a moored wave energy device under regular sea waves
    EV Rapaka, R Natarajan, S Neelamani
    Ocean Engineering 31 (5-6), 725-743 , 2004
    2004.0
    Citations: 70
  • 39. Thermal Studies on a Salt Gradient Solar Pond for Possible Application in Dairy Industries at Pondicherry Region–A Case Study
    N Sozhan, EV Rapaka
    Water and Energy Abstracts 14 (4), 19-20 , 2004
    2004.0
  • Thermal studies on a salt gradient solar pond for possible application in dairy industries at Pondicherry region-A case study
    E VIJAYAKRISHNA
    First International Conference, Renewable Energy, 6-8 October 2004, New … , 2004
    2004.0
  • Experimental Study on the Dynamic Response of a Moored Floating Wave Energy Device
    EV Rapaka, R Natarajan, S Neelamani
    International Conference on Offshore Mechanics and Arctic Engineering 36835 … , 2003
    2003.0
  • On the Efficiency and Transmission Characteristics of a 1: 20 Model Fixed Wave Energy Device
    EV Rapaka, S Neelamani, R Natarajan
    International Conference on Offshore Mechanics and Arctic Engineering 36835 … , 2003
    2003.0
  • Mathematical Modelling Of A Plate Type Heat Exchanger For A 0.1 MWe OTEC Plant
    E Vijayakrishna Rapaka, D Michael Bakkiyanathan
  • A SPECIAL TYPE OF MILLING FIXTURE FOR DISCONTINUOUS THREADS
    SM Ali, EV Rapaka, P Sivakumar
  • Modeling of Hydrogen Production through an Ocean Thermal Energy Conversion System
    E Vijayakrishna Rapaka, S Rajagopan, V Pranitha, R Kathambari
  • OMAE2003-37083
    EV Rapaka, S Neelamani, R Natarajan
  • PERFORMANCE OF A REFRIGERATOR USING ECO-FRIENDLY HC BLEND REFRIGERANT R290/R 600a (CARE 30)
    EV Rapaka, B Hemananth, D Kannan, V Sukumaran
    Energy 2, 3.04 , 0
  • SPECIFIC POWER OPTIMIZATION OF 0.1 MWe CLOSED CYCLE OTEC POWER PLANT
    EV Rapaka
  • ON THE EFFICIENCY, TRANSMISSION & DYNAMIC RESPONSE OF A MOORED OWC WAVE ENERGY DEVICE
    EV Rapaka, R Natarajan, S Neelamani

MOST CITED SCHOLAR PUBLICATIONS

  • Experimental investigation on the dynamic response of a moored wave energy device under regular sea waves
    EV Rapaka, R Natarajan, S Neelamani
    Ocean Engineering 31 (5-6), 725-743 , 2004
    2004.0
    Citations: 70
  • Synthesis of porous CuCo2O4 nanorods/reduced graphene oxide composites via a facile microwave hydrothermal method for high-performance hybrid supercapacitor applications
    S Jayasubramaniyan, S Balasundari, SJ Yeom, N Naresh, T Rani, ...
    Electrochimica Acta 390, 138865 , 2021
    2021.0
    Citations: 43
  • Experimental investigation on a 0.25 m2 solar gel pond
    N Sozhan, T Senthilvelan, T Kaliyappan, EV Rapaka
    International journal of innovative research in science, engineering and … , 2013
    2013.0
    Citations: 13
  • Experimental Investigations on a 1.00 m 2 Solar Gel Pond
    N Sozhan, T Senthilvelan, T Kaliyappan, EV Rapaka, SP Sivapirakasam
    Applied Mechanics and Materials 592, 2360-2364 , 2014
    2014.0
    Citations: 1
  • A Study on the Influence of Higher Secondary Subjects Scores on Engineering Performance
    JJ Jasmine, EV Rapaka
    International Journal of Engineering and Management Research (IJEMR) 7 (4 … , 2017
    2017.0
  • 39. Thermal Studies on a Salt Gradient Solar Pond for Possible Application in Dairy Industries at Pondicherry Region–A Case Study
    N Sozhan, EV Rapaka
    Water and Energy Abstracts 14 (4), 19-20 , 2004
    2004.0
  • Thermal studies on a salt gradient solar pond for possible application in dairy industries at Pondicherry region-A case study
    E VIJAYAKRISHNA
    First International Conference, Renewable Energy, 6-8 October 2004, New … , 2004
    2004.0
  • Experimental Study on the Dynamic Response of a Moored Floating Wave Energy Device
    EV Rapaka, R Natarajan, S Neelamani
    International Conference on Offshore Mechanics and Arctic Engineering 36835 … , 2003
    2003.0
  • On the Efficiency and Transmission Characteristics of a 1: 20 Model Fixed Wave Energy Device
    EV Rapaka, S Neelamani, R Natarajan
    International Conference on Offshore Mechanics and Arctic Engineering 36835 … , 2003
    2003.0
  • Mathematical Modelling Of A Plate Type Heat Exchanger For A 0.1 MWe OTEC Plant
    E Vijayakrishna Rapaka, D Michael Bakkiyanathan
  • A SPECIAL TYPE OF MILLING FIXTURE FOR DISCONTINUOUS THREADS
    SM Ali, EV Rapaka, P Sivakumar
  • Modeling of Hydrogen Production through an Ocean Thermal Energy Conversion System
    E Vijayakrishna Rapaka, S Rajagopan, V Pranitha, R Kathambari
  • OMAE2003-37083
    EV Rapaka, S Neelamani, R Natarajan
  • PERFORMANCE OF A REFRIGERATOR USING ECO-FRIENDLY HC BLEND REFRIGERANT R290/R 600a (CARE 30)
    EV Rapaka, B Hemananth, D Kannan, V Sukumaran
    Energy 2, 3.04 , 0
  • SPECIFIC POWER OPTIMIZATION OF 0.1 MWe CLOSED CYCLE OTEC POWER PLANT
    EV Rapaka
  • ON THE EFFICIENCY, TRANSMISSION & DYNAMIC RESPONSE OF A MOORED OWC WAVE ENERGY DEVICE
    EV Rapaka, R Natarajan, S Neelamani