Journal Articles
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Item A novel single source multilevel inverter with hybrid switching technique(John Wiley and Sons Ltd, 2022) Nageswar Rao, B.; Yellasiri, Y.; Shiva Naik, B.; Venkataramanaiah, J.; Aditya, K.; Panda, A.A novel multilevel inverter (MLI) configuration with the hybrid switching technique is presented in this paper. The proposed MLI consists of the H-bridge combination with unidirectional switches, half-bridges, and transformers. The suggested MLI with the additional cascaded connection increases to higher voltage levels. The number of employed components in this topology is drastically minimized. Therefore, the complexity, cost, and volume of the proposed topology are also reduced. The operation of the suggested topology is tested through the improved novel switching technique. This modulation method reduces the total harmonic distortion (THD) and produces high root mean square (RMS) voltage. Further, a comprehensive comparison with the recent MLI topologies is performed to validate the merits of the suggested inverter. Simulation and experimental results verify the suggested topology performance using the new modulation technique at different loading conditions and modulation indices. © 2021 John Wiley & Sons, Ltd.Item Hindi fake news detection using transformer ensembles(Elsevier Ltd, 2023) Praseed, A.; Rodrigues, J.; Santhi Thilagam, P.S.In the past few decades, due to the growth of social networking sites such as Whatsapp and Facebook, information distribution has been at a level never seen before. Knowing the integrity of information has been a long-standing problem, even more so for the regional languages. Regional languages, such as Hindi, raise challenging problems for fake news detection as they tend to be resource constrained. This limits the amount of data available to efficiently train models for these languages. Most of the existing techniques to detect fake news is targeted towards the English language or involves the manual translation of the language to the English language and then proceeding with Deep Learning methods. Pre-trained transformer based models such as BERT are fine-tuned for the task of fake news detection and are commonly employed for detecting fake news. Other pre-trained transformer models, such as ELECTRA and RoBERTa have also been shown to be able to detect fake news in multiple languages after suitable fine-tuning. In this work, we propose a method for detecting fake news in resource constrained languages such as Hindi more efficiently by using an ensemble of pre-trained transformer models, all of which are individually fine-tuned for the task of fake news detection. We demonstrate that the use of such a transformer ensemble consisting of XLM-RoBERTa, mBERT and ELECTRA is able to improve the efficiency of fake news detection in Hindi by overcoming the drawbacks of individual transformer models. © 2022 Elsevier LtdItem A novel nine-level inverter with reduced component count using common leg configuration(Springer Science and Business Media Deutschland GmbH, 2023) Nageswar Rao, B.; Yellasiri, Y.; Shiva Naik, B.S.; Aditya, K.This article proposes a nine-level (9 L) inverter with a common leg configuration employing transformers and a single dc source. The suggested inverter uses eight switches and two transformers to produce 9 L output voltage. The suggested circuit minimizes the switches and transformers compared with existing transformer-based multilevel inverters (TMLI). Therefore, the proposed circuit cost, volume and complexity are also reduced. Additionally, a thorough comparison with the various 9 L inverter circuits is conducted to ensure the benefits of the suggested TMLI. A basic logic gate-based pulse width modulation (PWM) is implemented for the suggested 9 L inverter. Simulation and hardware studies verifying the feasibility and proficiency of the suggested inverter are performed. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Item A new single-phase multilevel inverter with improved modulation technique(John Wiley and Sons Ltd, 2023) Nageswar Rao, B.; Yellasiri, Y.; Shiva Naik, B.; Aditya, K.; K Panda, A.This article proposes a seventeen-level (17L) inverter with a common leg configuration and an improved modulation technique. The proposed inverter uses only 10 switches, one toroidal core transformer, and one dc source. Therefore, the proposed design offers less control complexity with reduced cost and volume. Additionally, the suggested modulation technique improves the load voltage quality by minimizing the harmonic content. Simulation and laboratory studies are performed to confirm the proficiency of the suggested inverter with a new modulation technique. Further, a thorough comparison with recent transformer-based circuits is carried out to highlight the benefits of the proposed structure. © 2023 John Wiley & Sons Ltd.Item A Two-Stage Module Based Cell-to-Cell Active Balancing Circuit for Series Connected Lithium-Ion Battery Packs(Institute of Electrical and Electronics Engineers Inc., 2023) Manjunath, K.; Kalpana, R.; Singh, B.; Kiran, R.This article addresses a two-stage module based cell-to-cell active equalization topology based on a modified buck-boost converter for series connected Lithium-ion battery packs. In the proposed topology, initially module based equalizing currents are controlled. Subsequently, cell-based equalizers are controlled in parallel within each battery module. The proposed topology significantly reduces the balancing time by transferring higher balancing current from a strong cell to the weakest cell in a module directly. With the proposed topology's modularized design, reduces voltage stress on long strings of switches, resulting in improved performance with fewer components. The operating principle, control strategy and design constraints are analyzed in detail. The MATLAB/Simulink platform is utilized to demonstrate the feasibility of the proposed technique for balancing the energy in series connected battery cells. To reduce the complexity of the control approach, the digital control is implemented using an FPGA control board. Further, a laboratory prototype is developed to show the feasibility and operability of the proposed topology. © 1986-2012 IEEE.Item A modified T-type multilevel inverter for renewable energy applications(Elsevier Ltd, 2024) Nageswar Rao, B.; Yellasiri, Y.; Shiva Naik, B.S.; Aditya, K.; Panda, A.K.The primary challenge in integrating renewable resources into grids using multilevel inverters (MLI) is the need for many separate DC sources and switching device counts. Transformer-based multilevel inverters (TMIs) have emerged to address this issue, aiming to minimize system components and boost source voltage with a single DC source. This research article introduces a novel TMI topology that utilizes only a single DC source and incorporates ten switches to produce good-quality load voltage with high magnitude. The proposed TMI offers several structural advantages, including self-galvanic isolation, reduced switching devices and uniform voltage levels across all turn ratios. Additionally, the TMI operates a switching method called pulse width modulation, which provides the gating pulses to all the power semiconductor devices in the proposed TMI. An experimental model has been created in a laboratory environment, and simulations are performed using the MATLAB/Simulink platform to assess the effectiveness of the suggested TMI. Furthermore, a comparison between the suggested TMI circuit and other recent TMI designs with similar characteristics is performed. This comparison is carried out to assess and validate the superior features of the proposed TMI over the alternative designs. © 2024 Elsevier B.V.Item Implementation of novel toroidal transformer-based single-phase multilevel inverter(Springer Science and Business Media Deutschland GmbH, 2024) Nageswar Rao, B.; Yellasiri, Y.; Shiva Naik, B.; Aditya, K.Multilevel inverters (MLIs) have gained traction for their application in high-voltage AC systems and renewable energy. They use fewer DC sources and switches in transformer-based designs to attain the necessary output voltage magnitude. Creating an efficient, high-gain MLI with reduced sources and switches demands meticulous design and substantial effort. This paper introduces a new multilevel inverter design utilizing a toroidal transformer with a reduced number of components. The new topology incorporates ten transistors and a single toroidal transformer. These components are arranged as two H-bridge modules and a bidirectional switch with a transformer to generate nine voltage levels. Notably, the inclusion of three complementary switch pairs in the inverter circuit simplifies the control strategy of the proposed inverter. This configuration enables the inverter to achieve more voltage levels and higher voltage gain using fewer components. Comparison with other existing nine-level inverters highlights the effectiveness of the new design in minimizing the cost function value. The performance assessment of the proposed inverter employs a cost-effective solution. Simulation and experimental results are provided to showcase the practicality and efficiency of the proposed nine-level inverter. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.Item An Ensemble of Vision-Language Transformer-Based Captioning Model With Rotatory Positional Embeddings(Institute of Electrical and Electronics Engineers Inc., 2025) Sathyanarayana, K.B.; Naik, D.Image captioning is a dynamic and crucial research area focused on automatically generating image textual descriptions. Traditional models, primarily employing an encoder-decoder framework with Convolutional Neural Networks (CNNs), often struggle to capture the complex spatial and sequential relationships inherent in visual data. This gap in performance underscores the necessity for more sophisticated solutions. The proposed work introduces a groundbreaking ensemble model that integrates CNN, Graph Convolutional Network (GCN), Bidirectional Long Short-Term Memory (BiLSTM), and Transformer architectures. Our approach achieves an outstanding 97% increase in CIDEr scores on the Flickr30K dataset and a remarkable 28.6% improvement on the Flickr8K dataset, thanks to the innovative implementation of Rotary Positional Encoding (RoPE). By strategically incorporating GCN and BiLSTM layers, our model adeptly captures essential relationships within the data. This groundbreaking research effectively addresses the challenges of image captioning, leveraging a powerful combination of advanced architectures. As a result, our model significantly enhances the generation of accurate and contextually rich captions, positioning it as a game-changer for automated image-to-text applications. The proposed Ensemble model with RoPE, achieved impressive performance on the Flickr8k and Flickr30k datasets, with scores of 80.62 and 95.0 for BLEU-1, 72.01 and 90.51 for BLEU-2, 63.12 and 81.24 for BLEU-3, 48.32 and 68.8 for BLEU-4, 74.26 and 81.89 for METEOR, 80.24 and 84.29 for ROUGE-L, 118.94 and 155.77 for CIDEr, and 48.7 and 39.0 for SPICE, respectively. © 2013 IEEE.Item Design and implementation of novel multilevel inverter with full DC-utilization(Taylor and Francis Ltd., 2025) Nageswar Rao, B.; Yellasiri, Y.; Aditya, K.; Shiva Naik, B.S.; Karunakaran, E.This paper presents a novel single-source transformer-based nine-level (9 L) inverter configuration. The design incorporates a three-level neutral-point-clamped (3 L NPC) inverter, a 3-L full bridge, and a transformer to produce 9 L output voltage levels. In particular, one of the 2 L legs in the full bridge is common among the transformer and the load. The proposed structure minimises the components compared to existing transformer-based nine-level inverters. Thus, the suggested inverter volume, cost, and complexity are minimised. Furthermore, a pulse width modulation method has been developed to generate the necessary gating pulses for the proposed inverter. Additionally, a complete comparison study illustrates the enhanced performance of the suggested architecture. The validity of the suggested 9 L inverter is assessed by performing MATLAB simulations and using a scaled prototype. The results obtained from the simulations and experimental tests are then presented and analysed. A clear correlation was observed between the simulation and the hardware results. © 2024 Informa UK Limited, trading as Taylor & Francis Group.Item LeDoFAN: enhancing lengthy document fake news identification leveraging large language models and explainable window-based transformers with n-gram expulsion(Springer Science and Business Media Deutschland GmbH, 2025) LekshmiAmmal, H.R.; Anand Kumar, M.Nowadays, people use social media to gather everything around them and consider it their primary source of information. Moreover, people rely more on information disseminated through social media and news channels. The alarming concern is that as the amount of information increases, the amount of fake news or misinformation spread also increases through social media. Generally, fake news has few lines of data; when it comes to a document or an article, the amount of information or the size of the documents is high, and it needs to be appropriately trained to build a model. In this work, we have developed a model that identifies and classifies fake news, consisting of articles collected from social media websites and news pages trained using transformer-based architecture. We have introduced a novel window method for handling lengthy documents and an N-gram expulsion method for managing similar words for classifying the article as fake or real news. We achieved the state-of-the-art F1-score of 0.3492 on test data for the window-based N-gram expulsion method and got an F1-score improvement of 2.1% for long documents alone with this method. We also explored the large language models (LLMs), specifically TinyLlama, which could only achieve an F1-score of 0.2098, and with LLama for summarization of the document that achieved an F1-score of 0.3402 with N-gram expulsion. We have further explored the results using Explainable Artificial Intelligence (XAI) to know the reason behind the proposed model’s intuition. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.