Dr.V.BALAJI
@lms.mcet.edu.er
ASSOCIATE PROFESSOR
MAI- NEFHI COLLEGE OF ENGINEERING AND TECHNOLOGY
Prof. Dr. BALAJI V has 22years of teaching experience. Now he is working as an Associate Professor in the Department of Electrical and Electronics Engineering at MAI –NEFHI COLLEGE OF ENGINEERING AND TECCHNOLOGY, Asmara, Eritrea. He Completed his Post-Doctoral Fellow in the field of Artificial Intelligence at Srinivas University Mangalore. His current areas of research are model predictive control, process control, and Fuzzy and Neural Networks. He has received Abdul Kalam Award for Young Scientist, Excellence in Education Award, Best Teacher Award, World’s greatest person Award He has published 105 research papers in national and international journals conferences, and 6 textbooks in the field of electrical and of Artificial Intelligence. website was created by him and the study materials were uploaded. He has guided eight research scholars in various universities. He is an active member of ISTE, IAENG, IAOE, IACSIT, FMIAEME, LMIAOE, LM IACSIT, SMIRED.
EDUCATION
B.E,M.Tech, PhD, PDF,
RESEARCH, TEACHING, or OTHER INTERESTS
Engineering, Artificial Intelligence, Control and Systems Engineering, Electrical and Electronic Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
N. P. G. Bhavani, Kailash Harne, Satendar Singh, Ostonokulov Azamat Abdukarimovich, V. Balaji, Bharat Singh, K. Vengatesan, and Sachi Nandan Mohanty
IWA Publishing
Abstract Reverse osmosis desalination facilities operating on microgrids (MGs) powered by renewable energy are becoming more significant. A leader-follower structured optimization method underlies the suggested algorithm. The desalination plant is divided into components, each of which can be operated separately as needed. MGs are becoming an important part of smart grids, which incorporate distributed renewable energy sources (RESs), energy storage devices, and load control strategies. This research proposes novel techniques in economic saline water treatment based on MG architecture integrated with a renewable energy systems. This study offers an optimization framework to simultaneously optimize saline as well as freshwater water sources, decentralized renewable and conventional energy sources to operate water-energy systems economically and efficiently. The radial Boltzmann basis machine is used to analyse the salinity of water. Data on water salinity were used to conduct the experimental analysis, which was evaluated for accuracy, precision, recall, and specificity as well as computational cost and kappa coefficient. The proposed method achieved 88% accuracy, 65% precision, 59% recall, 65% specificity, 59% computational cost, and 51% kappa coefficient.
T. Sathish, S. Uma Maheswari, V. Balaji, P. Nirupama, Hitesh Panchal, Zhixiong Li, and Iskander Tlili
Elsevier BV
Imran Khan, S P Maniraj, K Santosh Reddy, V Balaji, K Kalaivani, and Mukesh Singh
IEEE
Chronic heart failure, also known as Congestive Heart Failure (CHD, is characterized by incapacitating symptoms that lead to higher rates of mortality and morbidity as well as higher medical costs and a lower quality of life. Detectable alterations on an Electrocardiogram (ECG) may be indicative of CHF using a simple and noninvasive diagnostic technique. The monitoring of cardiac patients with the use of heart signals has the potential to significantly increase life expectancy. For the past decade, patients and doctors have placed a premium on being able to classify and predict cardiac illnesses based on ECG data. Preprocessing, feature extraction, and model training were the three stages via which the research was conducted. Preprocessing often employs adaptive filters based on an LMS, however this can be time-consuming because of the filter’s long critical path. This issue is addressed by implementing a novel adaptive filter that makes use of a delayed error normalized LMS algorithm to achieve high speed and low latency. The preprocessed signal undergoes R-peak identification using wavelets for HRV feature extraction, and the resulting model is trained using these features CNN -GRU-AM. The experimental findings showed that compared to the CNN model (94%) and GRU (92%) model, the proposed model was significantly more accurate at 99.8%.
V. N. Senthil Kumaran, Shaik Fairooz, R. Krishna Priya, Dayadi Lakshmaiah, J. V. Subramanyam, V. S. Balaji, and V. Elamaran
Springer Science and Business Media LLC
Enas Abdulhay, Elamaran V., Chandrasekar M., Balaji V.S., and Narasimhan K.
Elsevier BV
B. R. Sathishkumar, B. Sundaravadivazhagan, Betty Martin, G. Sasi, M. Chandrasekar, S. Rakesh Kumar, V. Elamaran, V. S. Balaji, and N. Arunkumar
Springer Science and Business Media LLC
K. Sujatha, V. Balaji, P. Vijaibabu, V. Karthikeyan, N. P. G. Bhavani, V. Srividhya, P. SaiKrishna, A. Kannan, N. Jayachitra, and Safia
Springer International Publishing
G. Sasi, P. Thanapal, V.S. Balaji, G. Venkat Babu, and V. Elamaran
IEEE
The prime motive of this study is to probe the basics of computer networking protocols. This article elucidates a few imperative views behind computer networks theory with a firsthand approach. This manuscript demonstrates ten important hands-on exercises using tools such as wireshark, nmap, and MS-DOS commands. Examples of IPv4 addressing scheme, Domain Name System (DNS) call through Nslookup, obtaining NS type DNS records, and a Transmission Control Protocol (TCP) 3-way handshake process are the first five exercises considered here. The other five tasks are such as a TCP termination, public versus private Internet Protocol (IP) addresses, identification of a firewall server, the role of a firewall server on Internet Control Message Protocol (ICMP) packet requests, and understanding of sequence and acknowledgment numbers during application data transfer in tcp. This type of research inspires the student community with self-learning, and hence, teachers may concentrate more on practice.
Weijie Wang, Gaopeng Zhang, Luming Yang, V.S. Balaji, V. Elamaran, and N. Arunkumar
Elsevier BV
K. Sujatha, V. Karthikeyan, V. Balaji, N.P.G. Bhavani, V. Srividhya, R. Krishnakumar, and R. Sridhar
MAFTREE
Power is utilized as the prime fuel for hybrid and module electric vehicles in order to build the productivity of commercial vehicles. This paper forecasts the emission factors utilizing discrete Fourier transform, artificial neural networks and hybridization of back propagation algorithm. The DFT facilitates the extraction of the performance indicators which are otherwise called the features. The coefficients of the power spectrum denote the performance indicators. The ANN learns the pattern for emissions from HEVs using these performance indicators. This ANN based strategy offers an optimal control action to detect and reduce the exhaust gas emissions which are hazardous. These vehicles are provided with automated highway traffic Jam assist. Hence the forecast of these emissions offers increased efficiency of 90% to 100% thereby ensuring optimal operating condition for the hybrid vehicles.
K. Sujatha, V. Balaji, Nallamilli P. G. Bhavani, and S. Jayalakshmi
Springer Singapore
K. Sujatha, K. SenthilKumar, V. Balaji, R. KrishnaKumar, and Nallamilli P. G. Bhavani
Springer Singapore
V. Elamaran, N. Arunkumar, G. Venkat Babu, V.S. Balaji, Jorge Gomez, Cristhian Figueroa, and Gustavo Ramirez-Gonzalez
Institute of Electrical and Electronics Engineers (IEEE)
Neurological signal processing is of significance not only the physiologist doing research and the clinician investigating patients but also to the biomedical engineer who is needed to collect, process, and interpret the physiological signals by prototyping systems and algorithms for their manipulations. While it is a fact that there does hold immense stuff (material) on the subject of digital neurological signal processing, however, it is dispersed in various scientific, technological, and physiological journals, databases also in various international conference proceedings. Consequently, it is a quite hard, more time-consuming, and often tiresome job, especially to the stranger to the domain. Hence, this study concentrates on how much time would require to access the databases belong to the brain signal/image collections, neurological signals, etc. The sixteen US-based Servers, ten UK-based Servers, and the five Servers from other countries are included in this study. Mainly, the domain name system, hyper text transfer protocol, and the Internet control message protocol query/response times are analyzed using a popular packet sniffer called Wireshark.
Saravanan Vasudevan, M. Aravindan, V. Balaji, and M. Arumugam
Institute of Advanced Engineering and Science
<p>A single phase Z source inverter is developed for better voltage boosting and inversion ability suited for photovoltaic power generation systems. The operation of the Z source inverter is described with relevant equations. Simple boost scheme is used for switching actions of the inverter. The performance of the inverter used for photovoltaic applications can be checked with simulation and experimental results, which prove that it has single-stage buck and boost capability and improved reliability.</p>
R. Malathy and V. Balaji
IOP Publishing
The major application of Induction motor includes the usage of the same in industries because of its high robustness, reliability, low cost, highefficiency and good self-starting capability. Even though it has the above mentioned advantages, it also have some limitations: (1) the standard motor is not a true constant-speed machine, itsfull-load slip varies less than 1 % (in high-horsepower motors).And (2) it is not inherently capable of providing variable-speedoperation. In order to solve the above mentioned problem smart motor controls and variable speed controllers are used. Motor applications involve non linearity features, which can be controlled by Fuzzy logic controller as it is capable of handling those features with high efficiency and it act similar to human operator. This paper presents individuality of the plant modelling. The fuzzy logic controller (FLC)trusts on a set of linguistic if-then rules, a rule-based Mamdani for closed loop Induction Motor model. Themotor model is designed and membership functions are chosenaccording to the parameters of the motor model. Simulation results contains non linearity in induction motor model. A conventional PI controller iscompared practically to fuzzy logic controller using Simulink.
M. Nalini, V. Balaji, Vinitha Kumar, R. Priya, A. Ulaganayaki, and S. Siva Priya
IEEE
Diabetes develops in our body when our blood glucose levels are too high or low. Out of control of blood glucose levels may lead to serious disease. Blood glucose levels may be brought back to its normal level by injecting a sufficient amount of the blood glucose concentration has to be stabilized within the physiological range of 70-120 mg/dl. Blood glucose regulation system uses the sensor and the controller. The sensor detects the blood glucose level in the body and the controller takes the control action to decide the amount of insulin has to be injected. This project deals with the controller part with diabetes type 1 as a nonlinear model, which has been simulated in MATLAB SIMULINK environment by using the Model Predictive Controller.
Tesfaye Alamirew, V. Balaji, and Nigus Gabbeye
IAES Indonesia Section
This research paper is about developing a better type of controller, known as MPC (Model Predictive Control) for pasteurization process plant. MPC is an advanced control strategy that uses the internal dynamic model of the process and a history of past control moves and a combination of many different technologies to predict the future plant output.. The dynamics of the pasteurization process was estimated by using system identification from the experimental data. The quality of model structures like ARX, ARMAX, BJ and CT model structures was checked based on best fit with validation data, residual analysis and stability analysis. Auto-regressive with exogenous input (ARX322) model was chosen as a model structure of the pasteurization process dynamics and fits about 79.75% with validation data. Finally MPC control strategies were designed using ARX322 model structure.
V. Saravanan, M. Aravindan, V. Balaji, and M. Arumugam
Institute of Advanced Engineering and Science
Need for alternative energy sources to satisfy the rising demand in energy consumption elicited the research in the area of power converters/inverters. An increasing interest of using Z source inverter/converter in power generation involving renewable energy sources like wind and solar energy for both off grid and grid tied schemes were originated from 2003. This paper surveys the literature of Z source inverters/converter topologies that were developed over the years.
Tesfaye Alamirew, V. Balaji, and Nigus Gabbeye
Institute of Advanced Engineering and Science
Proportional–Integral–Derivative (PID) controllers are used in many of the Industries for various process control applications. PID controller yields a long settling time and overshoot which is not good for the process control applications. PID is not suitable for many of the complex process control applications. This research paper is about developing a better type of controller, known as MPC (Model Predictive Control). The aim of the paper is to design MPC and PID for a pasteurization process. In this manuscript comparison of PID controller with MPC is made and the responses are presented. MPC is an advanced control strategy that uses the internal dynamic model of the process and a history of past control moves and a combination of many different technologies to predict the future plant output. The dynamics of the pasteurization process was estimated by using system identification from the experimental data. The quality of different model structures was checked using best fit with data validation, residual and stability analysis. Auto-regressive with exogenous input (ARX322) model was chosen as a model structure of the pasteurization process and fits about 80.37% with datavalidation. MPC and PID control strategies were designed using ARX322 model structure. The controller performance was compared based on settling time, percent of overshoot and stability analysis and the results are presented.