Multimodal Learning Using Heterogeneous Data
Multimodal Learning Using Heterogeneous Data is a comprehensive guide to the emerging field of multimodal learning, which focuses on integrating diverse data types such as text, images, and audio within a unified framework. The book delves into the challenges and opportunities presented by multimodal data and offers insights into the foundations, techniques, and applications of this interdisciplinary approach. It is intended for researchers and practitioners interested in learning more about multimodal learning and is a valuable resource for those working on projects involving data analysis from multiple modalities. The book begins with a comprehensive introduction, focusing on multimodal learning's foundational principles and the intricacies of heterogeneous data. It then delves into feature extraction, fusion techniques, and deep learning architectures tailored for multimodal data. It also covers transfer learning, pre-processing challenges, and cross-modal information retrieval. The book highlights the application of multimodal learning in specialized contexts such as sentiment analysis, data generation, medical imaging, and ethical considerations. Real-world case studies are woven into the narrative, illuminating the applications of multimodal learning in diverse domains such as natural language processing, multimedia content analysis, autonomous systems, and cognitive computing. The book concludes with an insightful exploration of multimodal data analytics across social media, surveillance, user behavior, and a forward-looking examination of future trends and practical implementations. As a collective resource, Multimodal Learning Using Heterogeneous Data illuminates the powerful utility of multimodal learning to elevate machine learning tasks while also highlighting the need for innovative solutions and methodologies. The book acknowledges the challenges associated with deep learning and the growing importance of ethical considerations in the collection and analysis of multimodal data. Overall, Multimodal Learning Using Heterogeneous Data provides an expansive panorama of this rapidly evolving field, its potential for future research and application, and its vital role in shaping machine learning's evolution. 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Eslamian, Saeid; Nanjundan, Preethi; George, Jossy; Eslamian, Faezeh
Multimodal Learning Using Heterogeneous Data;pp.1-290
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1016/C2024-0-01863-2 https://www.scopus.com/pages/publications/105032925564?origin=resultslist
Eslamian S., Department of Water Science and Engineering, College of Agriculture, Isfahan University of Technology, Isfahan, Iran; Nanjundan P., Department of Data Science, CHRIST University, Lavasa Campus, Maharashtra, Pune, India; George J., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India; Eslamian F., GHD, QC, Canada
Augmented intelligent water drops optimisation model for virtual machine placement in cloud environment
Virtual machine placement in cloud computing is to allocate the virtual machines (VMs) (user request) to suitable physical machines (PMs) so that the wastage of resources is reduced. Allocation of appropriate VMs to suitable and effective PMs will lead the service provider to be a better competitor with more available resources for affording a greater number of VMs simultaneously which in turn reflects with the growth in the economy. In this research work, an augmented intelligent water drop (IWD) algorithm is used for effectively placing VMs. The preliminary goal of this proposed work is to reduce the overall resource utilisation by packing the VMs to appropriate PMs effectively. The proposed IWD model is tested under the standard simulation process as it is given in the literature. Performance of IWD is compared with the existing techniques first fit decreasing, least loaded and ant colony optimisation algorithm. Performance analysis shows the significance of the proposed method over existing techniques. The Institution of Engineering and Technology 2020.
Eswaran S.; Dominic D.; Natarajan J.; Honnavalli P.B.
IET Networks, Vol-9, No. 5, pp. 215-222.
Institution of Engineering and Technology
https://doi.org/10.1049/iet-net.2019.0165 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092355213&doi=10.1049%2fiet-net.2019.0165&partnerID=40&md5=5ad27ee66c68f40f0aceea32f8afcc23
Eswaran S., Department of Computer Science and Engineering, PES University, 100 Feet Ring Road, Bangalore, India; Dominic D., Department of Computer Science and Engineering, Christ University, Mysore Road, Bangalore, India; Natarajan J., Department of Computer Science and Engineering, Christ University, Mysore Road, Bangalore, India; Honnavalli P.B., Department of Computer Science and Engineering, PES University, 100 Feet Ring Road, Bangalore, India
An enhanced network intrusion detection system for malicious crawler detection and security event correlations in ubiquitous banking infrastructure
Bayesian network; Intrusion detection system (IDS); Malicious crawlers; Security correlations; Support vector machine
Purpose: In the recent era, banking infrastructure constructs various remotely handled platforms for users. However, the security risk toward the banking sector has also elevated, as it is visible from the rising number of reported attacks against these security systems. Intelligence shows that cyberattacks of the crawlers are increasing. Malicious crawlers can crawl the Web pages, crack the passwords and reap the private data of the users. Besides, intrusion detection systems in a dynamic environment provide more false positives. The purpose of this research paper is to propose an efficient methodology to sense the attacks for creating low levels of false positives. Design/methodology/approach: In this research, the authors have developed an efficient approach for malicious crawler detection and correlated the security alerts. The behavioral features of the crawlers are examined for the recognition of the malicious crawlers, and a novel methodology is proposed to improvise the bank user portal security. The authors have compared various machine learning strategies including Bayesian network, support sector machine (SVM) and decision tree. Findings: This proposed work stretches in various aspects. Initially, the outcomes are stated for the mixture of different kinds of log files. Then, distinct sites of various log files are selected for the construction of the acceptable data sets. Session identification, attribute extraction, session labeling and classification were held. Moreover, this approach clustered the meta-alerts into higher level meta-alerts for fusing multistages of attacks and the various types of attacks. Originality/value: This methodology used incremental clustering techniques and analyzed the probability of existing topologies in SVM classifiers for more deterministic classification. It also enhanced the taxonomy for various domains. 2021, Emerald Publishing Limited.
Eswaran S.; Rani V.; Daniel D.; Ramakrishnan J.; Selvakumar S.
International Journal of Pervasive Computing and Communications, Vol-18, No. 1, pp. 59-78.
https://doi.org/10.1108/IJPCC-04-2021-0102 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114252266&doi=10.1108%2fIJPCC-04-2021-0102&partnerID=40&md5=83ba9256c6868ea550688b412c8096aa
Eswaran S., Computer Science and Engineering, PES University, Bangalore, India; Rani V., Computer Applications, CMR Institute of Technology, Bangalore, India; Daniel D., Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Ramakrishnan J., Department of Information Technology and Security, Jazan University, Jazan, Saudi Arabia; Selvakumar S., Computer Science and Engineering, KalaignarKarunanidhi Institute of Technology, Coimbatore, India
Quantum-enhanced neuro-fusion framework for intelligent decision-making in smart home IoT surveillance
Adversarial resilience; AI-driven IoT systems; Anomaly detection; Deep neuro-fusion; Edge computing; Internet of things; Multi-modal data fusion; Quantum-inspired optimization; Real-time surveillance; Smart home security
Smart-home surveillance systems increasingly rely on heterogeneous IoT data streams, requiring efficient fusion, scalability, and robustness under noisy sensing conditions. This paper proposes a Quantum-Inspired Deep Neuro-Fusion Architecture (QDNFA) for anomaly detection in edgecloud IoT environments. The framework integrates modular encoders, temporal alignment, and a quantum-inspired optimisation mechanism to support multi-modal data processing while maintaining real-time performance. Experimental evaluation is conducted on the CASAS Smart Home dataset to validate sensor-centric anomaly detection, scalability across multiple devices, and edgecloud inference efficiency. While the architecture is designed to support audio and video modalities, the present study focuses on low-dimensional sensor data, and large-scale benchmarking on audiovisual surveillance datasets is identified as future work. Results demonstrate improved detection accuracy and reduced latency compared to baseline methods in sensor-driven smart-home scenarios. 2026 The Author(s).
Eugine Prince, M.; Rathi Devi, T.; Anu Disney, D.; Kannan, K.; Ramesh, K.; Sujatha Therese, P.
Franklin Open;Volume;15;Issue;;Article No.;100561;
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.1016/j.fraope.2026.100561 https://www.scopus.com/pages/publications/105032190667?origin=resultslist
Eugine Prince M., Department of Physics, S. T. Hindu College, Tamil Nadu, Nagercoil, India; Rathi Devi T., Department of Computer Science and Engineering, Christ University, Karnataka, Bengaluru, India; Anu Disney D., Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Tamil Nadu, Chennai, India; Kannan K., Department of Electronics and Communication Engineering, R. M. K. College of Engineering and Technology, Tamil Nadu, Thiruvallur, India; Ramesh K., Department of Electronics and Communication Engineering, Dhanalakshmi Srinivasan College of Engineering and Technology, Tamil Nadu, Chennai, India; Sujatha Therese P., Department of Electrical and Electronics Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India
Comparative Analysis of Machine Learning Models and Interpolation Techniques for Seasonal Rainfall Prediction in Tamil Nadu
Climate Dynamics; Geospatial Analysis; Gradient Boosting; Machine Learning; Predictive Modelling; QGIS; Rainfall Patterns; Random Forest; Tamil Nadu
This paper explains the rainfall patterns in the state of Tamil Nadu in October 2024, which is the monsoon season, with respect to the differences between the actual rainfall and what is experienced normally over districts. This study uses machine learning techniques from regression models of Random Forest and Gradient Boosting to anticipate future trends about rainfall based on the precedent data. Evaluation using Performance Metrics. The Proposed models are very well tested in terms of performance metrics like RMSE and R-squared, which gives insight about how accurate the forecasts of their results are. This research shows the applicability of QGIS to achieve geospatial analysis for visualizations of the rain distribution as well as anomalies across districts. The current work depicts the integration of data science methodology with geospatial analysis into the knowledge about climate dynamics in the state of Tamil Nadu. Research will help in deepening the understanding of regional climate impacts by bridging predictive analytics with spatial visualization, lending support to informed decision-making in the environment management context. 2025 IEEE.
Evangilin, K.; Ryan Powell, L.; Suganthi, J.; Deepa, S.; Siddalingappa, Rashmi
Proceedings of 2025 International Conference on Emerging Trends in Industry 4.0 Technologies, ICETI4T 2025;
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICETI4T63625.2025.11131696 https://www.scopus.com/pages/publications/105016417680?origin=resultslist
Evangilin K., Christ (Deemed to be University), Department of Data Science and Statistics, Bangalore, India; Ryan Powell L., Christ (Deemed to be University), Department of Data Science and Statistics, Bangalore, India; Suganthi J., Christ (Deemed to be University), Department of Data Science and Statistics, Bangalore, India; Deepa S., Christ (Deemed to be University), Department of Data Science and Statistics, Bangalore, India; Siddalingappa R., Christ (Deemed to be University), Department of Science and Statistics, Bangalore, India
Serendipitous detection of an intense X-ray flare in the weak-line T Tauri star KM Ori with SRG/eROSITA
stars: activity; stars: flare; stars: individual (KM Ori); stars: pre-main sequence; stars: variables: T Tauri; X-rays: stars
Weak-line T Tauri stars (WTTS) exhibit X-ray flares, likely resulting from magnetic reconnection that heats the stellar plasma to very high temperatures. These flares are difficult to identify through targeted observations. Here, we report the serendipitous detection of the brightest X-ray flaring state of the WTTS KM Ori in the eROSITA DR1 survey. Observations from SRG/eROSITA, Chandra X-ray Observatory, and XMM-Newton are analysed to assess the X-ray properties of KM Ori, thereby establishing its flaring state at the eROSITA epoch. The long-term (1999-2020) X-ray light curve generated for the Chandra observations confirmed that eROSITA captured the source at its highest X-ray flaring state recorded to date. Multi-instrument observations support the X-ray flaring state of the source, with time-averaged X-ray luminosity reaching at the eROSITA epoch, marking it the brightest and possibly the longest flare observed so far. Such intense X-ray flares have been detected only in a few WTTS. The X-ray spectral analysis unveils the presence of multiple thermal plasma components at all epochs. The notably high luminosity , energy (erg), and the elevated emission measures of the thermal components in the eROSITA epoch indicate a superflare/megaflare state of KM Ori. Additionally, the H line equivalent width of from our optical spectral analysis, combined with the lack of infrared excess in the spectral energy distribution, were used to re-confirm the WTTS (thin disc/disc-less) classification of the source. The long-duration flare of KM Ori observed by eROSITA indicates the possibility of a slow-rise top-flat flare. The detection demonstrates the potential of eROSITA to uncover such rare, transient events, thereby providing new insights into the X-ray activity of WTTS. The Author(s), 2025. Published by Cambridge University Press on behalf of Astronomical Society of Australia.
Ezhikode S.H.; Anilkumar H.; Arun R.; Mathew B.; Jithesh V.; Bhattacharyya S.; Nedhath S.; Cysil T.B.; Muneer S.; Kartha S.S.; Kumar S.P.
Publications of the Astronomical Society of Australia, Vol-42
https://doi.org/10.1017/pasa.2024.98 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215675608&doi=10.1017%2fpasa.2024.98&partnerID=40&md5=a826f08b1a166d28ce15e66ff3ee400f
Ezhikode S.H., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India, St. Francis de Sales College (Autonomous), Electronics City, Bengaluru, India; Anilkumar H., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Arun R., Indian Institute of Astrophysics, Koramangala, Bangalore, India; Mathew B., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Jithesh V., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Bhattacharyya S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India, European Organisation for Astronomical Research in the Southern Hemisphere (ESO), Casilla 19001, Santiago, Chile; Nedhath S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India, Indian Institute of Astrophysics, Koramangala, Bangalore, India; Cysil T.B., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Muneer S., Indian Institute of Astrophysics, Koramangala, Bangalore, India; Kartha S.S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Kumar S.P., Indian Institute of Astrophysics, Koramangala, Bangalore, India
Long-term Optical and ?-Ray Variability of the Blazar PKS 1222+216
The ?-ray emission from flat-spectrum radio quasars (FSRQs) is thought to be dominated by the inverse Compton scattering of the external sources of photon fields, e.g., accretion disk, broad-line region (BLR), and torus. FSRQs show strong optical emission lines and hence can be a useful probe of the variability in BLR output, which is the reprocessed disk emission. We study the connection between the optical continuum, H? line, and ?-ray emissions from the FSRQ PKS 1222+216, using long-term (?2011-2018) optical spectroscopic data from Steward Observatory and ?-ray observations from Fermi Large Area Telescope (LAT). We measured the continuum (F C,opt) and H? (F H? ) fluxes by performing a systematic analysis of the 6029-6452 optical spectra. We observed stronger variability in F C,opt than F H? , an inverse correlation between the H? equivalent width and F C,opt, and a redder-when-brighter trend. Using discrete cross-correlation analysis, we found a positive correlation (DCF ? 0.5) between the F ??ray>100 MeV and F C,opt (6024-6092 light curves with a time lag consistent with zero at the 2? level. We found no correlation between the F ??ray>100 MeV and F H? light curves, probably dismissing the disk contribution to the optical and ?-ray variability. The observed strong variability in the Fermi-LAT flux and F ??ray>100 MeV ? F C,opt correlation could be due to the changes in the particle acceleration at various epochs. We derived the optical-to-?-ray spectral energy distributions during the ?-ray flaring and quiescent epochs that show a dominant disk component with no variability. Our study suggests that the ?-ray emission zone is likely located at the edge of the BLR or in the radiation field of the torus. 2022. The Author(s). Published by the American Astronomical Society.
Ezhikode S.H.; Shukla A.; Dewangan G.C.; Pawar P.K.; Agarwal S.; Mathew B.; Akhil Krishna R.
Ezhikode S.H., Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune, 411007, India, Department of Physics and Electronics, CHRIST (Deemed to be University, Hosur Road, Bengaluru, 560029, India; Shukla A., Department of Astronomy, Astrophysics and Space Engineering, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore, 453552, India; Dewangan G.C., Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune, 411007, India; Pawar P.K., Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune, 411007, India; Agarwal S., Department of Astronomy, Astrophysics and Space Engineering, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore, 453552, India; Mathew B., Department of Physics and Electronics, CHRIST (Deemed to be University, Hosur Road, Bengaluru, 560029, India; Akhil Krishna R., Department of Physics and Electronics, CHRIST (Deemed to be University, Hosur Road, Bengaluru, 560029, India
Soft excess in AGN with relativistic X-ray reflection
galaxies:active; galaxies:Seyfert; X-rays:galaxies
The soft X-ray excess, emission below (Formula presented.) 2keV over the X-ray power-law, is a marked spectral component in the X-ray spectra of many Seyfert1 galaxies. We investigate if the observed soft X-ray excess in a sample of Seyfert1s is in accordance with the prediction of the relativistic reflection model by analyzing the XMM-Newton and NuSTAR spectra. The fractional difference in the soft excess (SE) obtained from the blurred reflection emission predicted (from NuSTAR) and the observed (from XMM-Newton) luminosities show that the reflection model underestimates the SE emission in our sample. The results point to alternative models (for example, warm Comptonization) to explain the soft X-ray excess in AGN. 2023 Wiley-VCH GmbH.
Ezhikode S.H.; Shyam Prakash V. P.; Dewangan G.C.; Mathew B.
Astronomische Nachrichten, Vol-344, No. 4
https://doi.org/10.1002/asna.20230042 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150789080&doi=10.1002%2fasna.20230042&partnerID=40&md5=0c9ebd52f9e5954a1a79292386f34110
Ezhikode S.H., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Shyam Prakash V. P., Space Astronomy Group, ISRO Satellite Centre, ISITE Campus, Bengaluru, 560037, India; Dewangan G.C., Inter-University Centre for Astronomy and Astrophysics, Pune, 411007, India; Mathew B., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, 560029, India
Ezhikode, Savithri H.; Anilkumar, Hema; Arun, R.; Mathew, Blesson; Jithesh, V.; Bhattacharyya, Suman; Nedhath, Sneha; Cysil, T.B.; Muneer, S.; Kartha, Sreeja S.; Kumar, S. Pramod
Publications of the Astronomical Society of Australia;Volume;42;Issue;;Article No.;e009;
All Open Access; Hybrid Gold Open Access
https://doi.org/10.1017/pasa.2024.98 https://www.scopus.com/pages/publications/85215675608?origin=resultslist
Analysis of the Performance of a 5-Level Modular Multilevel Inverter for a Solar Grid-Connected System
five-level; matlab-simulink; multilevel inverter; photovoltaic; total harmonic distortion
The main purpose of a multilevel inverter is to combine numerous levels of DC voltage to create a nearly sinusoidal voltage. The synthesized output waveform has more stages as the number of levels rises, creating a staircase ripple which resembles the preferred waveform. As the number of voltage levels rises, the output waves harmonic distortion diminishes and eventually approaches zero. In particular, the performance analysis of a five-level inverter with variable loads is highlighted in this paper. This topology has fewer devices than traditional multilevel inverters for the same five output levels, which makes it more affordable due to lesser driver circuits. The proposed modular five level topology is simulated using both high frequencies switching pulse width modulation and basic frequency switching modulation techniques. The output voltage, current waveform, and total harmonic distortion are examined and compared using simulink to confirm the viability of the modular multilevel inverter topology. 2024, TUBITAK. All rights reserved.
El-Cezeri Journal of Science and Engineering, Vol-11, No. 1, pp. 103-108.
https://doi.org/10.31202/ecjse.1240222 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189566281&doi=10.31202%2fecjse.1240222&partnerID=40&md5=633400437683b18fbfea3397cf4f0e3d
Ezhilvannan P., Department of EEE, Sree Vidyanikethan Engineering College, Tirupati, India; Krishnan S., Department of EEE, Christ deemed to be University, Bengaluru, India
Development of effective charging station for EVs using multiport converter and photovoltaic cell integration
Boost converter; Grid; Inverter; MPPT; State of charge
The adoption of electric vehicles (EVs) is increasing rapidly as a response to the urgent need to reduce greenhouse gas emissions and dependence on fossil fuels. However, the deployment of a reliable and cost-effective EV charging infrastructure remains a challenge. To address this challenge, this paper proposes the development of an effective charging station using multiport converter and photovoltaic cell integration. A promising approach in the transportation sector is an efficient charging station with multiport converter and photovoltaic cell integration. A multiport converter, photovoltaic cells, a battery energy storage system, and an electric vehicle charging port constitute the proposed charging station. The power flow between the photovoltaic cells, the battery energy storage system, and the electric vehicle charging port is controlled by the multiport converter. The excess energy generated by the photovoltaic cells is stored in the battery energy storage system. The proposed charging station is designed and analysed using MATLAB/Simulink. The simulation results show that the proposed charging station is capable of providing an electric vehicle a reliable and consistent power supply. In contrast to conventional charging stations, the proposed charging station is also capable of offering a faster charging rate. 2024 Nova Science Publishers, Inc. All rights reserved.
Ezhilvannan P.; Krishnan S.; Cheepati K.R.; Kumar B.H.
The Future of Hybrid-Electric Vehicles, pp. 289-318.
Ezhilvannan P., Department of Electrical and Electronics Engineering, Mohan Babu University (Erst while Sree Vidyanikethan Engineering College), Tirupati, Andhrapradesh, India; Krishnan S., Department of Electrical and Electronics Engineering, Christ University, Bangalore, Karnataka, India; Cheepati K.R., Department of Electrical and Electronics Engineering, K. S. R. M. College of Engineering, Kadapa, Andhrapradesh, India; Kumar B.H., Department of Electrical and Electronics Engineering, Mohan Babu University (Erst while Sree Vidyanikethan Engineering College), Tirupati, Andhrapradesh, India
Analysis of the Effectiveness of a Two-Stage Three-Phase Grid-Connected Inverter for Photovoltaic Applications
Boost voltage; DC-AC converter; distortion; Maximum power; Solar cell; Total harmonic
This paper proposes a two-stage three-phase grid-connected inverter for photovoltaic applications. The proposed inverter topology consists of a DC-DC boost converter and a three-phase grid-connected inverter. The DC-DC boost converter is used to boost the low voltage DC output of the PV array to a high voltage DC level that is suitable for feeding into the grid-connected inverter. The three-phase grid-connected inverter is used to convert the high voltage DC output of the boost converter into a three-phase AC output that is synchronized with the grid voltage. The proposed inverter topology offers several advantages over traditional single-stage inverters. Firstly, the DC-DC boost converter allows for the use of a smaller, more efficient inverter in the second stage, reducing the overall cost of the system. Secondly, the use of a boost converter allows for the maximum power point tracking of the PV array, which can increase the overall efficiency of the system. The proposed inverter topology offers improved control of the grid current, reducing the impact of the PV system on the grid. The proposed topology has been simulated using MATLAB/Simulink and the results show that the system is capable of delivering a high-quality three-phase AC output with low harmonic distortion. The Author(s). Publisher: University of Tehran Press.
Ezhilvannan P.; Krishnan S.; Kumar B.H.; Janardhan K.; Ramachandran S.
Journal of Solar Energy Research, Vol-8, No. 2, pp. 1471-1483.
https://doi.org/10.22059/jser.2023.357025.1285 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159462796&doi=10.22059%2fjser.2023.357025.1285&partnerID=40&md5=bca8d0c97ec5c5f472bcc5043b4bac27
Ezhilvannan P., Department of Electrical and Electronics Engineering, Mohan Babu University (Erst while Sree Vidyanikethan Engineering College), Tirupati, India; Krishnan S., Department of Electrical and Electronics Engineering, Christ University, Bangalore, India; Kumar B.H., Department of Electrical and Electronics Engineering, Mohan Babu University (Erst while Sree Vidyanikethan Engineering College), Tirupati, India; Janardhan K., Department of Electrical and Electronics Engineering, Mohan Babu University (Erst while Sree Vidyanikethan Engineering College), Tirupati, India; Ramachandran S., Department of Electrical and Electronics Engineering, Mohan Babu University (Erst while Sree Vidyanikethan Engineering College), Tirupati, India
Enhancing power conversion efficiency in five-level multilevel inverters using reduced switch topology
Efficiency; Inverter; Pulse width modulation; Reduced switch count; Total harmonic distortion
This paper presents extensive research on improving the power conversion efficiency of five-level multilevel inverters (MLIs) by utilizing a reduced switch topology. MLIs have received an abundance of focus because of their ability to generate high-quality output waveforms and have better harmonic outcomes than traditional two-level inverters. The high number of switches in MLIs, on the other hand, can result in increased power losses and lower overall efficiency. In this paper, a novel reduced switch topology for five-level MLIs, which is having five switches is proposed with the aim of minimizing power losses while preserving superior performance due to lesser number of switches. To achieve efficient power conversion, the proposed topology employs advanced pulse width modulation control strategies and optimized switching patterns. The simulation results show that the minimized switch topology improves the power conversion efficiency of the five-level MLI, resulting in lower losses and better overall system performance. The total harmonic distortion (THD) value of the output current has been reduced to 7.12% and the efficiency has been achieved to 96.92%. The findings of this investigation help to advance MLI technology, allowing for more efficient and reliable power conversion in a variety of applications such as renewable energy systems, electric vehicles, and industrial drives. 2024, Institute of Advanced Engineering and Science. All rights reserved.
Ezhilvannan P.; Ramasamy D.; Subramanian S.K.; Krishnan S.
Bulletin of Electrical Engineering and Informatics, Vol-13, No. 3, pp. 1495-1503.
Institute of Advanced Engineering and Science
https://doi.org/10.11591/eei.v13i3.6884 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196480092&doi=10.11591%2feei.v13i3.6884&partnerID=40&md5=b1e3a4b1437bc4cafa34c8584d2df5b1
Ezhilvannan P., Department of Electrical and Electronics Engineering, Mohan Babu University (Erst while Sree Vidyanikethan Engineering College), Tirupati, India; Ramasamy D., Department of Electrical and Electronics Engineering, Panimalar Engineering College, Chennai, India; Subramanian S.K., Department of Electrical and Electronics Engineering, S.A. Engineering College, Chennai, India; Krishnan S., Department of Electrical and Electronics Engineering, Christ Deemed to be University, Bangalore, India
Digital Competencies in the Structure of Training of Advertising and Public Relations Specialists
Digitalization; Educational Program; Gamification; Higher Education; Media Communications; Neural network; Project-based learning
The article examines the problem of the formation of digital competencies in the training of specialists in the field of media communications. An extensive review of the literature on the issue under study is given. The article examines the trends in the transformation of the profession of a communicator in the context of the intensive development of the latest technologies in the field of big data, gamification, artificial intelligence, etc. The article presents the research results on the basis of which an innovative educational program for training specialists in the field of advertising and public relations has been developed. The program includes modules related to general digital literacy, artificial intelligence resources, management in the digital environment, Internet marketing, technologies for working on various media platforms, as well as project activities using digital technologies. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Ezhova, Elena; Kushchenko, Alisa; Mary Anita, E.A.; Semikovennova, Elena
Lecture Notes in Networks and Systems;Volume;1616 LNNS;pp.112-120
Springer Science and Business Media Deutschland GmbH
https://doi.org/10.1007/978-3-032-04365-8_10 https://www.scopus.com/pages/publications/105019504782?origin=resultslist
Ezhova E., North Caucasus Federal University, Stavropol, Russian Federation; Kushchenko A., North Caucasus Federal University, Stavropol, Russian Federation; Mary Anita E.A., CHRIST (Deemed to be University), Bangalore, India; Semikovennova E., North Caucasus Federal University, Stavropol, Russian Federation
Investigation on window opening behavior in naturally ventilated hostels of warm and humid climate
Logistic regression model; Natural ventilation; Occupant behavior; Warm and Humid climate; Window opening behavior
A window is an inevitable element of a naturally ventilated building, and its usage improves indoor environmental conditions. Various research has presented window opening behavior models, stating that it may vary with region, climate, season, building type and many more environmental and non-environmental factors. Major studies in India relied on survey data and were not focused on continuous monitoring. Limited occupants behavior studies have been reported in warm and humid climatic zones, specifically in hostel buildings. Also, a realistic description of occupants window opening behavior is require for more accurate evaluation of building performance using energy simulation. Therefore, there is a need to study the window opening behavior to predict the indoor environment more accurately by using energy simulation tools. In this context, a one-year field research involving questionnaire survey, physical observation, and monitoring was conducted in different hostel buildings in Tiruchirappalli, India. Logistic models were developed to predict the window state in hostel buildings in warm and humid region based on physical observational and long-term monitoring data. It is found that window use is influenced by season, time of the day, weekdays, floor level, buildings orientation, user type, and gender. Results also showed that insects and animal menace (snakes, squirrels, lizards, mosquitoes etc.) impede window opening behavior. The study also presented a logistic model for window opening behavior based on outdoor environment conditions for simulation modeling. 2022 Elsevier B.V.
Faheem M.; Bhandari N.; Tadepalli S.; Abinaya J.
https://doi.org/10.1016/j.enbuild.2022.112184 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131442202&doi=10.1016%2fj.enbuild.2022.112184&partnerID=40&md5=becea978657e30f97908b53c49249a6c
Faheem M., Department of Architecture, National Institute of Technology, Tamil Nadu, Tiruchirappalli, 620015, India; Bhandari N., Department of Architecture, National Institute of Technology, Tamil Nadu, Tiruchirappalli, 620015, India; Tadepalli S., Department of Architecture, National Institute of Technology, Tamil Nadu, Tiruchirappalli, 620015, India; Abinaya J., Department of Architecture, National Institute of Technology, Tamil Nadu, Tiruchirappalli, 620015, India, School of Architecture, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India
Factors of self-congruity and personality traits in conjunction and its impact on buying behavior of Gen Z toward personal care beauty products
Sustainable Marketing and Customer Value, pp. 241-257.
Faheema K., Christ University, India; Suresh A.S.; Sharma V., Symbiosis Centre for Management and Human Resource Development, Symbiosis International University, Pune, India
Revolutionizing Road Transportation: The Role of Artificial Intelligence in Smart and Efficient Systems
AI-based traffic management systems; Artificial intelligence; Autonomous vehicles; Intelligent Traffic Management Systems (ITMS); Machine learning; Predictive maintenance; Road transport; Smart cities; Smart transportation systems; Traffic management
This chapter is about how AI is transforming road transportation by improving efficiency, safety, and comfort. By emphasising the importance of AI integration and moving on to main AI technologies such as machine learning (ML) for applications like traffic prediction and autonomous driving. Deep learning techniques, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), are essential for vehicle detection and traffic analysis. Also, natural language processing (NLP) enhances traffic planning and customer support by providing real-time information and virtual assistants. We can also know from the chapter that AI applications like self-driving cars that use AI for vision and control, intelligent traffic management systems that optimise signal timings, and predictive maintenance to avoid vehicle problems. It also discusses data privacy, technology, and ethics questions, as well as demonstrates effective real-world AI deployments and future trends. Overall, the chapter emphasises AIs disruptive impact on road transport and its potential for ongoing innovation and improvement in the pursuit of a smarter, more efficient transportation network. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Fahim, Md Forkan Hossain; Usman, Muhammad Mansur; Al Mahedi Hassan, Md; Sardar, Tanvir Habib; Bindu Madavi, K.P.; Venkatachalam, Nirmala
Springer Tracts on Transportation and Traffic;Volume;22;pp.87-107
https://doi.org/10.1007/978-3-031-87627-1_6 https://www.scopus.com/pages/publications/105006841073?origin=resultslist
Fahim M.F.H., IniAstra Tech, Chattogram, Bangladesh; Usman M.M., Department of CS, African University of Science and Technology, Abuja, Nigeria; Al Mahedi Hassan M., IniAstra Tech, Chattogram, Bangladesh; Sardar T.H., Department of CSE, Dayananda Sagar University, Bengaluru, India; Bindu Madavi K.P., Department of CSE, Christ University, Bengaluru, India; Venkatachalam N., Department of Artificial Intelligence and Data Science, Easwari Engineering College, Chennai, India
Bimetallic Cobalt-Vanadium Boride as a Bifunctional Electrocatalyst for Overall Water Splitting
Amorphous metal boride; Bifunctional electrocatalyst; Cobalt-Vanadium boride; Hydrogen evolution reaction; Oxygen evolution reaction
The transition to a hydrogen-based economy necessitates the development of sustainable and cost-effective electrocatalysts for green hydrogen production via water electrolysis. In this study, we report a novel cobalt-vanadium boride (CoVB) catalyst, which exhibits enhanced bifunctional activity for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline media. CoVB was synthesized using a facile one-step chemical reduction method with varying vanadium concentrations, optimizing performance at a 3% vanadium content. Electrochemical analyses demonstrated that CoVB significantly outperformed cobalt boride (CoB), achieving an HER and OER overpotential (?10) of 80mV and 320mV, respectively, comparable to noble metal benchmarks. Characterization results revealed that V plays a promoting role in inhibiting the growth of particles and agglomeration of particles, leading to an increase in surface area and producing unique mixed amorphous and crystalline structures in CoVB to enhance catalytic activity by increasing the number of active sites and conductivity across the interface. Furthermore, in two-electrode systems, the cell voltage of 1.66V was needed to achieve 10mA/cm2 of current density with superior stability and reusability. Overall, the CoVB catalyst, a new candidate from the metal boride family, presents a promising alternative to precious metals for efficient and sustainable water-splitting in alkaline electrolyzers. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
Falake, Maheshwar B.; Bhabal, Rinkoo; Chunduri, Avani; Dhulia, Vinita; Patel, Rupali; Patel, Nainesh
https://doi.org/10.1007/s12678-025-00946-6 https://www.scopus.com/pages/publications/105001506035?origin=resultslist
Falake M.B., Department of Physics, NES Ratnam College of Arts, Science and Commerce, University of Mumbai, Bhandup (W), Mumbai, 400078, India, Department of Physics, SIES College of Arts, Science and Commerce, Sion (W), University of Mumbai, Mumbai, 400022, India; Bhabal R., Department of Physics and Electronics, Christ University, Bengaluru, 560029, India; Chunduri A., Department of Physics, University of Mumbai, Vidyanagari, Santacruz (E), Mumbai, 400098, India; Dhulia V., Department of Physics, NES Ratnam College of Arts, Science and Commerce, University of Mumbai, Bhandup (W), Mumbai, 400078, India; Patel R., Department of Physics and Electronics, Christ University, Bengaluru, 560029, India; Patel N., Department of Physics and Electronics, Christ University, Bengaluru, 560029, India
Fabrication of NiO nanoparticles modified with carboxymethyl cellulose and D-carvone for enhanced antimicrobial, antioxidant and anti-cancer activities
Antibacterial activity; Antioxidant activity; Carboxymethyl cellulose; Colon cancer; D-carvone; HCT-116 cells; NiO nanoparticles
Colon cancer is a deadly disease while pathogens such as Klebsiella pneumoniae (K. pneumoniae), Shigella dysenteriae (S. dysenteriae), Bacillus subtilis (B. subtilis), Staphylococcus aureus (S. aureus), and Candida albicans (C. albicans) are serious threat to the human health due to their persistent nature and resistant to conventional drugs. This study aims to develop NiO nanoparticles via single one pot chemical approach and to modifying them with natural molecules carboxymethyl cellulose and D-carvone to enhance antioxidant, anticancer and antibacterial activity. The NiO and NiO-CMC-Dcar exhibit fcc structure confirmed by XRD. The band gap values were found be 4.15 eV for NiO and 4.23 eV for NiO-CMC-Dcar nanocomposite. DLS study confirmed that the mean particles diameter of NiO and NiO-CMC-Dcar were 154.1 nm and 130.3 nm respectively. The TEM and SEM analysis confirmed that both NiO and NiO-CMC-Dcar samples were roughly spherical. PL emission spectra of NiO-CMC- Dcar nanoparticles at 426 nm and 506 nm indicate the electronic structural modification due to incorporation of CMC and Dcar molecules in to NiO materials. The green emission observed at 506 nm is due to oxygen vacancy that can be correlated to production of more reactive oxygen species (ROS) to kill microorganism. The experimental results show that the NiO-CMC- Dcar nanoparticles exhibit enhanced antimicrobial, anticancer and antioxidant activity when compared to NiO alone. 2024 Elsevier B.V.
Falemban A.H.; Abdel Aziz Ibrahim I.; Bamagous G.A.; Alzahrani A.R.; Shahid I.; Shahzad N.; Hasan Hussein-Al-Ali S.; Arulselvan P.; Thangavelu I.
Inorganic Chemistry Communications, Vol-171
https://doi.org/10.1016/j.inoche.2024.113517 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209637688&doi=10.1016%2fj.inoche.2024.113517&partnerID=40&md5=b82e768923e7cf4ce00fd19a54852578
Falemban A.H., Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al-Qura University, Al-Abidiyah, P.O.Box 13578, Makkah, 21955, Saudi Arabia; Abdel Aziz Ibrahim I., Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al-Qura University, Al-Abidiyah, P.O.Box 13578, Makkah, 21955, Saudi Arabia; Bamagous G.A., Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al-Qura University, Al-Abidiyah, P.O.Box 13578, Makkah, 21955, Saudi Arabia; Alzahrani A.R., Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al-Qura University, Al-Abidiyah, P.O.Box 13578, Makkah, 21955, Saudi Arabia; Shahid I., Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al-Qura University, Al-Abidiyah, P.O.Box 13578, Makkah, 21955, Saudi Arabia; Shahzad N., Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al-Qura University, Al-Abidiyah, P.O.Box 13578, Makkah, 21955, Saudi Arabia; Hasan Hussein-Al-Ali S., Department of Chemistry, Faculty of Sciences, Isra University, Amman, 11622, Jordan; Arulselvan P., Department of Chemistry, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, India; Thangavelu I., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India
Falemban, Alaa H.; Abdel Aziz Ibrahim, Ibrahim; Bamagous, Ghazi A.; Alzahrani, Abdullah R.; Shahid, Imran; Shahzad, Naiyer; Hasan Hussein-Al-Ali, Samer; Arulselvan, Palanisamy; Thangavelu, Indumathi
Inorganic Chemistry Communications;Volume;171;Issue;;Article No.;113517;
https://doi.org/10.1016/j.inoche.2024.113517 https://www.scopus.com/pages/publications/85209637688?origin=resultslist