Dr. K Gopalakrishna
@jyothyit.ac.in
Principal,
Jyothy Institute of Technology, Bangalore
Gopalakrishna K holds a Master’s in mechanical engineering, having specialized in production engineering from the University of Mysore, and a Ph.D. in polymer tribology from NAL-VTU. He has an experience of more than 30 years in academics and research. In addition to tribology, his research and teaching interests include pneumatics and hydraulics, thermal engineering and engineering drawing. He is certified by industry major FESTO in the domain of mechatronics and has executed projects that have resulted in five patent filings. With significant research publications in reputed Scopus / Thomson Reuter indexed journals and a monograph to his credit, he has been active in developing autonomous systems for surveillance funded by Naval Research Board-DRDO, coating systems for RP Components by ISRO-DOS, and others.
EDUCATION
Ph.D. in Polymer Tribology from NAL-VTU.
RESEARCH INTERESTS
Mechanical Engineering, Bio-composites,Polymer tribology,
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Kazi Md Sadat, M. Khalid Hossain, M. Shihab Uddin, P. Prabhu, Ankita Aggarwal, K. Gopalakrishna, P. Sasi Kiran, Alok Kumar Mishra, Sanjeev Kumar Shah, Sahjahan Islam,et al.
Springer Science and Business Media LLC
Abstract Recently, lead-free Cs4CuSb2Cl12 has garnered attention as an excellent material to be used as an absorber of perovskite solar cells (PSCs). In this work, Cs4CuSb2Cl12 absorber-based PSCs were studied and the conditions to get high performance for PSCs were investigated. Here, six different materials for electron transport layers (ETLs) and 10 different materials for hole transport layers (HTLs) were studied. A numerical approach was followed by using SCAPS-1D simulator. During the work, various device parameters of PSC were investigated such as thickness variation of the absorber and ETL layers, acceptor density variation of the absorber and HTL layers, variation of the donor density of the ETL layer, and effect of total defect density of absorber. Also, other parameters such as the impact of resistance, temperature, J-V graph, Q-E graph, and carrier generation rate at different positions of the PSCs were assessed. Among the studied 10 HTL materials, MWCNTs outperformed other studied materials, hence it was selected for further investigations. Then the structures were optimized based on the device parameters outcome, and the structure having MZO and STO ETLs both showed the maximum power conversion efficiency (PCE) of 28.23%. (Al/FTO/MZO/Cs4CuSb2Cl12/MWCNTs/Au) the structure showed an open-circuit voltage (Voc) of 1.249 V, short-circuit current density (Jsc) of 25.11 mA/cm2 and a fill factor (FF) of 90.1%. The performance was also evaluated with respect to key electrical parameters. Optimum performance was achieved at a series resistance of 1 Ω·cm² and a shunt resistance of 1000 Ω·cm², beyond which performance gains saturated. The other best-performing STO ETL-based (Al/FTO/STO/Cs4CuSb2Cl12/MWCNTs/Au) structure had Voc of 1.25 V, Jsc of 25.11 mA/cm2, and FF of 90.01% Under the optimized condition other structure with CdS, PC61BM, SnS2 and ZnSe ETLs showed PCE of 27.68%, 27.8%, 25.67% and 28.22%. This work gives good insights into several Cs4CuSb2Cl12 based PSC structures and shows in the future they have great potential to be developed practically for highly efficient performances.
Chiranth Ramesh and K. Gopalakrishna
Engineering, Technology & Applied Science Research
Underwater Wireless Sensor Networks (UWSNs) play a significant role in marine applications, including environmental monitoring, ocean floor mapping, and disaster response. However, the energy constraints of sensor nodes and Autonomous Underwater Vehicles (AUVs), as well as the high cost of underwater acoustic communication, present major design challenges. This paper introduces Energy-Conscious Optimization of AUVs (ECO-AUV), a new framework that uses energy-aware K-Means clustering and the A* heuristic search algorithm to improve underwater data collection. ECO-AUV is specially designed to minimize total energy expenditure by improving intra-cluster communication procedures and AUV navigation paths. The framework provides reliable data collection and transfer through dynamic route planning that accounts for environmental conditions such as ocean currents and seafloor anomalies. Extensive simulations were carried out to compare ECO-AUV with two recent hybrid methods: Particle Swarm Optimization (PSO) with Genetic Algorithms (GAs), and Artificial Bee Colony (ABC) with Ant Colony Optimization (ACO). Results demonstrate that ECO-AUV is significantly more energy-efficient, creates more optimized traversal patterns, offering a high Packet Delivery Ratio (PDR) of 98.5%. Additionally, the framework exhibits low computational complexity, enabling its application in real-time applications. These results establish ECO-AUV as a scalable, energy-efficient solution for strong underwater sensing and communication.
Anniah Pratima, K. Gopalakrishna, and Sarappadi Narasimha Prasad
Engineering, Technology & Applied Science Research
The precise identification of cardiac arrhythmias facilitates accurate diagnosis and proper treatment, but the characterization process remains complex due to disturbances in ECG data signals along with skewed class frequencies and individual patient-specific variations. This study developed a deep learning framework, known as Penalty Regression Function-enhanced Deep Convolutional Neural Network (PRF-DCNN), as a comprehensive solution to cope with signal noise along with class imbalance and variations in patient data. The system starts by applying Correlation Factor-Based Extended Kalman Filtering (CF-EKF) for ECG signal denoising before allowing Ensemble Empirical Mode Decomposition (EEMD) to extract nonstationary features. The feature selection process along with the reduction of redundant characteristics uses the Frechet Fitness Rank Distribution-Anas Platyrhynchos Optimization (FFRD-APO method. The dataset is balanced by a Balanced Zero Noise GAN (BZNGAN) before Age-Weighted Average-Based Farthest First Clustering (AWA-FFC) refines the clustering process. The St. Petersburg INCART 12-lead ECG dataset was used to test the model, which obtained 99.53% accuracy, 99.10% sensitivity, and 99.67% specificity. The proposed system outperforms current models, showing its capacity for dependable time-critical arrhythmia detection in medical environments.
Gireeshkumar Basavaraj Chavati, Sharath Kumar Basavaraju, Arthoba Nayaka Yanjerappa, Malashri Boraiah Sannaobaiah, Handanahally Basavarajaiah Muralidhara, Krishna Venkatesh, and Keshavanarayana Gopalakrishna
Wiley
ABSTRACTThe recycling of widely available polyethylene terephthalate (PET) into activated carbon–carbon sphere composites represents a sustainable approach for developing advanced energy storage materials. In this study, a novel carbon sphere@polyethylene terephthalate (CS/PET) active material was synthesized using a cost‐effective hydrothermal process, integrating dextrose‐derived oxygen‐rich carbon spheres and PET‐derived activated carbon. This eco‐friendly composite was utilized to modify 132 cm2 graphite felt electrodes for vanadium redox flow batteries (VRFBs) and served as an active material in supercapacitors. As a positive electrode electrocatalyst in VRFBs, the CS/PET‐modified electrode achieved a coulombic efficiency (CE) of 88.43%, a voltage efficiency (VE) of 59.79%, and an energy efficiency (EE) of 51.92%, with excellent stability over 100 cycles. For supercapacitor applications, the CS/PET composite exhibited an impressive specific capacitance of 193 F/g at 2 A/g, delivering 100% coulombic efficiency and 92% retention over 2500 cycles. These results highlight the potential of CS/PET composites as cost‐effective, clean, and high‐performance materials for sustainable energy storage systems, demonstrating significant promise for meeting future energy demands while addressing global environmental challenges.
Gireeshkumar Basavaraj Chavati, Sharath Kumar Basavaraju, Arthoba Nayaka Yanjerappa, Malashri Boraiah Sannaobaiah, Handanahally Basavarajaiah Muralidhara, Krishna Venkatesh, and Keshavanarayana Gopalakrishna
Royal Society of Chemistry (RSC)
Recent studies on redox flow batteries and supercapacitors have focused on grid-scale and micro-scale energy-storage systems, typically utilizing carbon composite materials as cost-effective electrocatalysts.
Ramya G Franklin, Savinder Kaur, Binita Kumari, Mohit Gupta, Gopalakrishna K, and Trapty Agarwal Maharishi
IEEE
Brute pressure attacks are a not unusual approach utilized by malicious actors to gain unauthorized rights of entry to touchy records on mobile devices. Those assaults involve trying out multiple combinations of usernames and passwords until the precise one is located. This poses a huge risk to mobile security, as those devices often incorporate a tremendous quantity of personal and private information. The proposed solution is to detect and save brute force attacks on cellular gadgets by enforcing superior encryption techniques. Those techniques contain complex algorithms and methods to protect touchy records from being accessed by way of unauthorized events. This may make it easier for attackers to decipher the encrypted documents, even though they're capable of getting entry to them. The device will constantly display the get entry to attempts and locate any unusual styles or suspicious pastimes. If a brute pressure assault is detected, the device will robotically block further entry attempts and cause an alert to the consumer. It'll additionally encrypt the information in the tool to save it from being compromised. This answer will appreciably increase the security of cell gadgets because it will make it almost impossible for hackers to benefit from unauthorized admission to sensitive data. It's going to supply user's peace of thoughts, understanding that their statistics are covered, and offer an extra layer of security to cell gadgets.
Abhinav Mishra, Gopalakrishna K, Biswa Mohan Acharya, P. N. Ramesh, Siddharth Sriram, and Kalanandhini G
IEEE
Ayaan Faiz, K Gopalakrishna, Ankita Agarwal, R Suchithra, Pavas Saini, and Ishan Ayus
IEEE
The LSTM-CNN ensemble method performs well in predicting malignant brain tumors. The model above combines the best of LSTM and CNN to enhance accuracy and consistency in forecasts. An LSTM model is an RNN architecture that allows the collecting and processing of repeatable data, e.g., time series or language text. It is one of the best tools for medical data analysis, such as brain tumor image scans. It will allow the LSTM model to learn patterns and correlations in your data regarding precision when predicting future observations. Meanwhile, the CNN model is best for interpreting high-dimensional data and then amalgamating them to make predictions. It renders it a beneficial tool for analyzing brain tumor imaging scans and predicting features indicative of a malignant nature. It unites the best of abilities in both models and helps to make up for their shortcomings, respectively. It leads to a more reliable and precise prognosis of brain cancers, both for early detection as well as treatment planning. Additionally, employing deep learning methods such as LSTM-CNN ensemble may greatly help enhance brain tumor diagnosis and therapy efficiency.
Sharath Kumar Basavaraju, Gireeshkumar Basavaraj Chavati, Malashri Boraiah Sannaobaiah, Handanahally Basavarajaiah Muralidhara, Arthoba Nayaka Yanjerappa, Krishna Venkatesh, and Keshavanarayana Gopalakrishna
American Chemical Society (ACS)
T. N. Nithin, M. Narendra Kumar, Dinesh Nolakha, K. Gopalakrishna, and Krishna Venkatesh
Springer Science and Business Media LLC
Mohit Kumar Sharma, Gopalakrishna K, and Aarsi Kumari
IEEE
Latest advances in records generation have enabled virtual signatures for use in a variety of net-primarily based and network-primarily based applications. Digital signatures are used to authenticate the identity of a user, as well as to affirm the integrity and facts confidentiality of the transmitted information. However, virtual signatures are a challenge to numerous safety and overall performance problems, some of which may be exploited by malicious attackers. This paper seeks to study the performance of digital signature algorithms in a diffusion of records protection fashions implemented in networking programs. The paper will, in particular survey, present digital signature algorithms used for authentication and encryption of statistics in networking applications, as well as contemporary studies associated with enhancing their security and overall performance. Furthermore, the paper will identify the top-of-the-line algorithms and fashions encouraged for use in specific eventualities and applications. Moreover, the paper will analyze the usability of these fashions in phrases of their complexity, scalability, and user requirements. Eventually, the paper will gift future research directions and guidelines for similarly enhancing the safety and performance of digital signatures in the context of networking programs.
K Gopalakrishna, Urvashi Thakur, and Vishvendra Singh
IEEE
The electromagnetic subject (EMF) publicity related to network connections remains a vital protection difficulty in nowadays notably related global. This paper offers a way to quantify EMF publicity stages for one-of-a-kind networking. The developed approach takes into consideration diverse environmental factors, including the kind of materials present inside the surroundings, the gap among additives, and the power of the relationship. Effects display that the EMF ranges rely strongly upon the particular setup, highlighting the want for similar investigation and attention to environmental elements while deploying community connections. The methodology provides a basis for future researchers to expand greater state-of-the-art models and improve the accuracy of EMF exposure assessments.
Mukul Pandey, Shiv Shankar Shankar, and K Gopalakrishna
IEEE
Self-sustaining routing algorithms for Unmanned Aerial Vehicle (UAVs) enabled telecommunications structures can offer a low-cost and strength-efficient answer for community controllers. However, these algorithms ought to be evaluated so as to discover their weaknesses and strengths and to understand their viability to be used in such networks. This paper provides an assessment of numerous autonomous routing algorithms with admiration for their overall performance measures associated with the hyperlink pleasant, latency, and packet transport ratio. The authors investigated and compared the performance of numerous routing algorithms, inclusive of the Dynamic supply Routing (DSR), the Ado On-demand Distance Vector (AODV), the Optimized link state Routing (OLSR), and the area Routing Protocol (ZRP) for UAV-enabled telecommunications networks. To assess these algorithms, the authors hired actual-world datasets of UAV trajectories obtained from the NRMA visitor’s Telematics Dataset in combination with the COMSNET simulator. The effects of the have look showed that the DSR executed better than the AODV and the OLSR in phrases of latency and packet shipping ratio, at the same time as the ZRP executed first-rate in phrases of hyperlink best measurements. However, further evaluation discovered that the AODV and the OLSR had superior overall performance beneath varying mobility styles. In addition, the authors discovered that the wide variety of nodes and the terrain analysis of the community affected the performance of the algorithms differently.
K Gopalakrishna, Laxman Sahoo, R. Arunadevi, Namrata N. Wasatkar, Girija Shankar Sahoo, and Dhiraj Singh
IEEE
Mobile device protection has emerged as an increasingly important difficulty as more and more customers depend upon wireless networks for everyday conversation and other duties. Wi-Fi networks offer convenience and versatility for users; however, they also come with safety worries. This paper presents an overview of the safety-demanding situations related to Wi -Fi networks, discusses safety issues related to cellular devices, and offers more than a few answers for creating cozy cell surroundings. It focuses on defensive person identification, privacy, statistics, and defending against possible malicious activities. Primarily, the paper explores security solutions, encryption, authentication, community access control, and tool control. Moreover, it appears on the role of service carriers in cell tool protection and shows an aggregate of quality practices and generation to sell secure usage. Finally, the paper recommends persevering with studies to identify new threats and answers to decorate mobile safety similarly.
N. V. Balaji, Madhur Grover, T Vignesh, Kanika Seth, K Gopalakrishna, and Vikas K. Kolekar
IEEE
The motive of this technical summary is to have a look at the performance of interference-conscious routing protocols for wireless Mesh Networks (WMNs). Interferenceconscious routing models help to lessen interference among WMN nodes associated with transmissions at the identical frequency channel. This type of interference can degrade the throughput of a network and reduce communication performance. The efficacy of a routing protocol is typically measured via parameters consisting of packet transport ratio, throughput, and end-to-stop delay. This AC will compare and assess unique algorithms for interference-conscious routing and evaluate their overall performance in terms of these parameters. Initial simulations will be carried out on diverse topologies of WMNs to determine the effect of interference-aware routing protocols on packet delivery ratio, throughput, and stop-to-stop put-off. The outcomes may be used to put together an assessment among exceptional algorithms and determine the most effective technique. In addition, the abstract will discover approaches to optimize the layout of interference-conscious routing protocols to attain the most green conversation overall performance. Subsequently, the paper will finish with a dialogue of capability demanding situations and important future studies guidelines in this area.
K. Gopalakrishna, Bhirgu Raj Maurya, Rajeev Kumar, Sushila Arya, Himanshi Bhatia, and Ankur Gupta
Wiley
Gireeshkumar Basavaraj Chavati, Sharath Kumar Basavaraju, Arthoba Nayaka Yanjerappa, Handanahally Basavarajaiah Muralidhara, Krishna Venkatesh, and Keshavanarayana Gopalakrishna
American Chemical Society (ACS)
N. Thangarasu, Amritpal Sidhu, Shalini M, Romil Jain, Gopalakrishna K, and Suruchi Gaurav Dedgaonkar
IEEE
Internet of Things has emerged as a vital technology that connects a variety of devices to enable the seamless exchange and processing of data. Nevertheless, the extensive and diverse character of IoT environments presents substantial security challenges, requiring the implementation of security mechanisms that are both efficient and robust. This paper suggests a novel method for improving the security and performance of IoT by combining Hybrid Gravitational Search Algorithm Optimisation (HGSAO) with Fuzzy Logic-based Secure Cluster Formation. The three-tier architecture that has been developed for this purpose includes mutual authentication, secure cluster formation, and optimal path selection. The methodology guarantees an optimal equilibrium between security and performance by reducing computational complexity and energy consumption. The efficacy of the proposed system in the secure and efficient management of IoT networks is underscored by its superior packet delivery ratio and throughput in comparison to existing methods.
Manish Srivastava, K Gopalakrishna, A Mohamed Jaffar, C Santhosh Kumar, Jayashree V. Bagade, and Preeti Naval
IEEE
This technical abstract search for a court between synthetic Intelligence (AI) and statistics technology (DS). We analyze and survey the regions wherein the two fields overlap. We determine the current kingdom of both AI and DS from their respective historical sequences and discuss the capability possibilities among them. We look at how they complement each other and which new technologies can get up from the combination of both. We also look into the ethical implications of such technologies and how AI can help enhance DS studies. Subsequently, we speak of viable software situations in a selection of domain names.
Gopalakrishna K and Vinaykumar SB
AIP Publishing
A Pratima, K GopalaKrishna, and S N Prasad
IOP Publishing
Abstract Cardiac Arrhythmia (CA) is a disorder of heartbeat or rhythm, that happens when the electrical signals that synchronize the heartbeats do not function properly. The Electro Cardio Gram (ECG) is the electrical realization of the expanding and contracting action of the heart and can be registered easily with the electrodes placed near the chest. Hence, due to the complexity of analyzing the huge number of signals in ECG records, it has become one of the major challenges to cardiologists to make early and accurate diagnoses and prognoses. Therefore, there is an essential need for accurate automatic arrhythmia classification. According to the records of the World Health Organization (WHO), 4.5 million CA patients are reporting alone in the United States. Therefore, it is stated as one of the most common reasons for death worldwide and it is very essential to the early diagnosis and prevention of CA. Hence, this research article mainly focuses to analyse the various methods used for the classification, early diagnosis, and prevention of CA. This research presents the overview of a few research articles suggesting different methods based on various fields like IOT, Machine Learning (ML) approaches, Deep Learning (DL) approaches, and so on for the automatic detection of Cardiac Arrhythmia. The literature work mainly focuses on various early Detection, prediction, and classification techniques for CA. The research gaps were also analyzed from these papers and elaborated for further research work which can be helpful for society.
Aruna Dore, Gopalakrishna K, and Trapty Agrawal
IEEE
Fuzzy logic has become a widely used alternative in control systems because of its inherent advantages, such as robustness. Despite this, the Type-2 fuzzy reasoning approach has gained popularity lately, particularly in applications for processing of images. It enables for addressing the uncertainty of models. In order to investigate how Type-2 Fuzzy Logic Controls (FLCs) impact operator sales, this research compares Period Type-2 and Generalized Type-2 FLCs. Using several standard testing facilities, the study evaluates performance metrics like completion time, integral squared deviation, integrated absolute mistake, and integrated times-weighted actual mistake. The outcomes of the experiment are used to offer selection criteria for choosing amongst several fuzzy logic controls based on effectiveness and processing time demands.
Savita, Sowmya C S, and Gopalakrishna K
IEEE
Using software robots that communicate with systems via their user interfaces, robotic process automation (RPA) attempts to automate corporate operations while increasing efficiency and cutting costs. To prevent inefficiencies,choosing the appropriate procedures for RPA automation is essential. This study offers a method for examining RPA development in corporate settings. Design, methodology, and approach: To pinpoint the key ideas behind RPA, this research undertakes a thorough literature assessment. It suggests a model linking these ideas and assesses its viability using Design Science Research (DSR) analysis of previous RPA case studies. Findings- The study shows that several of the key RPA ideas outlined in the literature analysis are absent from a number of case studies.