Power Consumption Forecasting with AI and IOT
subject: Data fusion; Distributed energy resources; Grid resilience; Load forecasting; Machine learning algorithms; Optimization algorithms; Renewable energy integration; Time series forecasting
description: Electricity plays a fundamental and indispensable role in modern society, driving progress, development, and the overall quality of life. Electricity is profoundly ingrained in daily life. It powers homes, providing lighting, heating, cooling, and appliances that support, comfort, and convenience. From cooking meals to powering electronic devices and entertainment systems, electricity is vital for modern living, enhancing our quality of life and enabling various activities. Power forecasting is critical to the effective management and optimization of power generation, consumption, and distribution. Power consumption forecasting has evolved significantly with the introduction of advanced technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT). AI techniques, such as machine learning and deep learning, make use of the massive amounts of data produced by IoT devices like smart meters and energy monitoring devices. These devices continuously gather real-time data on power consumption, weather conditions, grid performance, and other relevant factors. AI algorithms can find patterns and correlations and provide accurate forecasts and important insights for power forecasting by processing and analyzing data. Machine learning algorithms, such as regression models, neural networks, and ensemble approaches, are trained using historical power consumption data and the features that have been chosen. The models discover the underlying patterns and correlations between input features and power consumption. These forecasts can be used for short-term load balancing, energy procurement planning, demand response management, and optimizing energy distribution. AI and IoT power usage projections give valuable data for decision-making and energy optimization techniques. These projections can be used by energy suppliers, grid operators, building managers, and consumers to plan energy usage, distribute resources efficiently, optimize demand response programs, an…
creator: Murugesan, G.; Radha, B.; Nithya, A.S.; Gunavathi, R.
source: Power Systems;Volume;Part F914;pp.57-78
publisher: Springer Science and Business Media Deutschland GmbH
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISSN: 16121287;
language: English
type: Book chapter
coverage: Murugesan G., Department of Artificial Intelligence and Machine Learning, Sree Saraswathi Thyagaraja College, Tamil Nadu, Pollachi, India; Radha B., Department of Computer Technology and Data Science, Sri Krishna Arts and Science College, Tamil Nadu, Coimbatore, India; Nithya A.S., Department of Artificial Intelligence and Machine Learning, Sree Saraswathi Thyagaraja College, Tamil Nadu, Pollachi, India; Gunavathi R., Data Science Department, Christ (Deemed to be University), Maharashtra, Pune, India

Navigating resource scarcity in a changing climate: AI-powered perspectives on mental health
description: In the backdrop of the extensive global impact of the COVID-19 pandemic, environmental crises have, to a certain degree, taken a back seat. The pandemic-induced scarcity mindset, emphasizing immediate short-term needs over long-term considerations, has played a role in this shift in priorities. This scarcity mindset, prevalent during the pandemic, poses a risk to pro-environmental behavior and may contribute to environmental degradation, thereby heightening the likelihood of future pandemics. This chapter advocates for a reevaluation of pro-environmental actions, emphasizing their role in addressing various human needs, especially during periods of scarcity. AI-driven chatbots possess the capability to significantly enhance accessibility to affordable and efficient mental health services by complementing the efforts of clinicians. To safeguard pro-environmental behavior, we propose a reconceptualization that positions these actions not merely as value-laden or effortful but as pragmatic measures essential for resource conservation, particularly in times of scarcity. The study explores, the intricate dynamics of resource scarcity, climate change, and mental health, employing AI-powered perspectives to navigate this complex interplay. 2024, IGI Global. All rights reserved.
creator: Musa A.I.A.; Priya T.M.; Sivaprakasam S.A.; Devi M.R.; Rajendran R.K.
source: The Climate Change Crisis and Its Impact on Mental Health, pp. 12-23.
publisher: IGI Global
date: 2024-01-01
rights: Restricted Access
relation: ISBN: 979-836933273-3; 979-836933272-6
format: Online
language: English
type: Book chapter
coverage: Musa A.I.A., Qassim University, Saudi Arabia; Priya T.M., Christ University, India; Sivaprakasam S.A., Rajalakshmi Engineering College, India; Devi M.R., Presidency University, India; Rajendran R.K., Christ University, India

Efficient multipath model based cross layer routing techniques for Gauss Markov movable node management in MANET
description: This research unveils an innovative cross-layer routing methodology tailored for managing Gauss Markov mobile nodes within MANETs. The primary focus deceits cutting-edge inspiring network performance through the efficient utilization of resources and the steadfast maintenance of mobile node connectivity. Central to this model is the implementation of joint optimization, which takes into account both node mobility patterns and resource allocation dynamics to pinpoint the most favorable data transmission pathway. Incorporating multipath routing, the methodology enables the simultaneous exploration of multiple transmission routes, thereby fortifying the network against potential link failures and disruptions. By embracing a cross-layer approach, it seamlessly integrates functionalities across network, and steering layers, thereby amplifying the complete system efficacy. Comprehensive simulations conducted reveal the superior performance of this approach compared to existing techniques, particularly in terms of network throughput, latency reduction, and augmentation of packet delivery ratios. Such findings underscore the immense potential of this methodology across a spectrum of MANET applications that demand streamlined and dependable data transmission mechanisms. 2024 Author(s).
creator: Musa A.I.A.; Sivakumar V.; Chandrasekharan N.; Priya T.M.; Kanna R.R.
source: AIP Conference Proceedings, Vol-3161, No. 1
publisher: American Institute of Physics
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 0094243X
format: Online
language: English
type: Conference paper
coverage: Musa A.I.A., Department of Computer Science, College of Computer, Qassim University, Riyadh, Saudi Arabia; Sivakumar V., School of Computing, Faculty of Computing Engineering and Technology, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia; Chandrasekharan N., School of Computing, Faculty of Computing Engineering and Technology, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia; Priya T.M., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India; Kanna R.R., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India

Carboxymethyl Cellulose-Modified Strontium Oxide Nanoparticles: a Multifunctional Nanoplatform for C6 Glioma Therapy and Antimicrobial Applications
subject: Bioevaluation; Characterization; CMC-SrO nanoparticles; Synthesis; Zebrafish
description: Glioma, a very aggressive brain tumor, poses major therapeutic challenges. The present research investigates the synthesis, characterization, and bioevaluation of carboxymethyl cellulose (CMC)-functionalized strontium oxide (SrO) nanoparticles (SrCMC) as anticancer and biocompatibility probes. SrO nanoparticles were synthesized using co-precipitation and functionalized with CMC for better dispersion and stability. Characterization by XRD, FTIR, UVVis, PL, SEM, TEM, and EDAX proved structural and optical enhancements. SrCMC showed enhanced photoluminescence with a blue shift and increased emission intensity, indicating modified surface defects. UVVis analysis revealed a slight band gap increase from 4.07eV to 4.12eV due to CMC capping. FTIR and EDAX confirmed successful functionalization, while XRD showed reduced crystallite size (32nm to 26nm) and maintained tetragonal structure. SEM and HRTEM revealed improved dispersion and decreased lattice spacing in SrCMC, reflecting surface stabilization by CMC. For in vitro tests on C6 glioma cells, the cytotoxicity was found to be time- and dose-dependent with IC?? values of 22.1, 17.6, and 14.8g/mL for SrO and 20.3, 15.8, and 12.6g/mL for SrCMC after 24, 48, and 72h respectively. In vivo biocompatibility was assessed using zebrafish embryos exposed to SrCMC nanoparticles at 0.5mg/mL and 1mg/mL across various time intervals. The agar well diffusion method was employed to assess the antimicrobial activity against the following pathogens including Gram-positive (S. pneumoniae, B. subtilis), Gram-negative (K. pneumoniae, S. dysenteriae), and fungal (C. albicans) strains. The results revealed SrCMC exhibited significant inhibitory effects against all tested organisms and comparable to streptomycin. This work shows SrCMCs potential for biomedical applications, subject to careful control of toxicity. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
creator: Mushtaq, Zahi; Sharma, Vijay; Mukherjee, Jonaki; Wunnava, Aneesh; Thangavelu, Indumathi; Tadepalli, Srinivas; Bhran, Ahmed A.
source: Journal of Inorganic and Organometallic Polymers and Materials;Volume;35;Issue;12;pp.10290-10305
publisher: Springer
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISSN: 15741443;
format: online
language: English
type: Article
coverage: Mushtaq Z., Department of Mechanical Engineering, Presidency University, Karnataka, Bengaluru, India; Sharma V., Department of Pharmaceutics, SGT College of Pharmacy, SGT University, Haryana, Gurugram, India; Mukherjee J., Department of Electrical & Electronics, ARKA JAIN University, Jharkhand, Jamshedpur, India; Wunnava A., Electronics and Communication Engineering Department, Siksha O Anusandhan (Deemed to be University, Odisha, Bhubaneswar, 751030, India; Thangavelu I., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Tadepalli S., Department of Chemical Engineering, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Bhran A.A., Department of Chemical Engineering, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia

Pixelated Pasts: Deepfakes as Instruments of Counter-memory in India
description: A new era of digital memory invites society to confront the silences of the archive and rethink the politics of collective remembrance. 2025, Economic and Political Weekly. All rights reserved.
creator: Muskaan
source: Economic and Political Weekly;Volume;60;Issue;46;pp.72-73
publisher: Economic and Political Weekly
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISSN: 129976;
language: English
type: Notes
coverage: Muskaan, CHRIST University, Bengaluru, India

Comparative analysis on containers based on kubernetes, Docker swarm, open shift and Mesos
subject: Cloud computing; Container orchestrators; Dockswarm; Kubernetes; Openshift and Mesos
description: Cloud Computing has become increasingly common to use cloud computing solutions for Big Data processing because of their vast variety of computer resources and ability to extend over multiple cloud platforms. The rapid growth of the Internet of Things (IoT) concept has sparked this development. A traditional approach of cloud organisation is virtualization, which uses virtual computers and containers. It is impossible to overestimate the importance of lightweight cloud infrastructure for microservices. Many academics have proposed container-based virtualized computing services as a result of this. Container technology has risen in prominence as a viable alternative to traditional virtual machines in recent years. There is need to exploit high-level services such as orchestration. In this paper, we compare performance of various container orchestrators like Kubernetes, Dockswarm, Openshift and Mesos. 2025 IEEE.
creator: Muthakshi, S.; Rajalakshmi, K.; Helen Josephine, V.L.
source: Proceedings of the 2025 11th International Conference on Communication and Signal Processing, ICCSP 2025;pp.1398-1402
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-166545736-1;
language: English
type: Conference paper
coverage: Muthakshi S., M.O.P Vaishnav College for Women (Autonomous), Department of Computer Science and Information Technology, Chennai, India; Rajalakshmi K., C.M.R. Institute of Technology, Department of M.C.A., Bangalore, India; Helen Josephine V.L., Christ University, School of Business and Management, Bangalore, India

AI-Driven Stacking Ensemble for Predicting Total Power Output of Wave Energy Converters: A Data-Driven Approach to Renewable Energy Processes
subject: AI-driven energy forecasting; machine learning; renewable energy; sustainable energy systems; wave energy converters
description: This study develops and evaluates an AI-driven stacked hybrid machine learning model for predicting the total power output of wave energy converters (WECs) across four Australian coastal locations: Adelaide, Perth, Sydney, and Tasmania. This research enhances prediction accuracy through advanced ensemble learning techniques while addressing spatial variability in wave energy processes. The dataset comprises spatial coordinates and power output readings from 16 fully submerged WECs per location, capturing the variability of wave energy across different coastal regions. Data preprocessing included missing value imputation, duplicate removal, and spatial feature transformation via Euclidean distance calculation. Principal component analysis (PCA) was employed to reduce dimensionality while preserving critical features influencing power generation. To develop an accurate prediction model, we employed a stacking ensemble approach using XGBoost, LightGBM, and CatBoost as base learners, optimized via Optuna hyperparameter tuning with 10-fold cross-validation. A Ridge regression meta-learner combined the outputs of these models, leveraging their complementary strengths to enhance predictive performance. Experimental results demonstrate that the hybrid model consistently outperforms individual models, enhancing predictive accuracy across all locations. Sydney exhibited the highest accuracy (RMSE = 9089.58 W, R2 = 0.8576), while Tasmania posed the greatest challenge (RMSE = 45,032.37 W, R2 = 0.8378). The ensemble approach mitigated overfitting and improved generalization by leveraging the complementary strengths of XGBoost, LightGBM, and CatBoost. By leveraging AI-driven ensemble learning, this study provides a scalable and reliable framework for wave energy forecasting, facilitating more efficient grid integration and resource planning in renewable energy systems. 2025 by the authors.
creator: Muthamizhan, T.; Karthick, K.; Aruna, S.K.; Velmurugan, P.
source: Processes;Volume;13;Issue;4;Article No.;961;
publisher: Multidisciplinary Digital Publishing Institute (MDPI)
date: 01-01-2025
rights: All Open Access; Gold Open Access
relation: ISSN: 22279717;
format: online
language: English
type: Article
coverage: Muthamizhan T., Department of Electrical and Electronics Engineering, Sri Sai Ram Institute of Technology, Tamil Nadu, Chennai, 600044, India; Karthick K., Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam Andhra Pradesh, 532127, India; Aruna S.K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST University, Karnataka, Bangalore, 560074, India; Velmurugan P., Department of Electrical and Electronics Engineering, St. Josephs College of Engineering, Tamil Nadu, Chennai, 600119, India

Attenuation properties of epoxy-Ta2O5 and epoxy-Ta2O5-Bi2O3 composites at ?-ray energies 59.54 and 662 keV
subject: composites; films; mechanical properties; thermogravimetric analysis (TGA)
description: Epoxy resin filled with suitable high Z elements can be a potential shield for X-rays and ?-rays. In this work, we present the ?-ray attenuation properties of epoxy composites filled with (030 wt%) Tantalum pentoxide (Ta2O5) and Ta2O5-Bi2O3, which were prepared by open mold cast technique. X-ray diffraction patterns showed crystalline peaks of Ta2O5 and bismuth oxide (Bi2O3) in the prepared epoxy-Ta2O5 and epoxy-Ta2O5-Bi2O3 composites. Homogeneity of the samples at higher filler wt% was revealed by SEM images. Mechanical characterization showed the enhanced mechanical strength of epoxy-Ta2O5-Bi2O3 composites compared to epoxy-Ta2O5. Higher storage modulus and glass transition temperature of the epoxy-Ta2O5-Bi2O3 composites showed enhanced stiffness and thermal stability when compared to neat and epoxy-Ta2O5. Decrease in the value of tan(?) at higher content of filler loadings indicated the good adhesion between filler and matrix. Mass attenuation coefficients of epoxy-Ta2O5 (30 wt%) composites at ?-ray energies 59.54 and 662 keV were found to be 0.876 cm2 g1 and 0.084 cm2 g1, while that of epoxy-Ta2O5-Bi2O3 (30 wt% Bi2O3) composite were 1.271 cm2 g1 and 0.088 cm2 g1, respectively. The epoxy-5% Ta2O5-30% Bi2O3 composites with higher ?/? value and tensile strength may be a potential ?-ray shield in various radiation environments. 2020 Wiley Periodicals, Inc.
creator: Muthamma M.V.; Bubbly S.G.; Gudennavar S.B.
source: Journal of Applied Polymer Science, Vol-137, No. 44
publisher: John Wiley and Sons Inc.
date: 2020-01-01
rights: Restricted Access
relation: ISSN: 218995; CODEN: JAPNA
format: Online
language: English
type: Article
coverage: Muthamma M.V., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, India; Bubbly S.G., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, India; Gudennavar S.B., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, India

Poly(vinyl alcohol)bismuth oxide composites for X-ray and ?-ray shielding applications
subject: applications; irradiation; mechanical properties; optical properties; thermogravimetric analysis (TGA)
description: Polymer composites, which are light in weight, cost effective, and less toxic, have potential applications in X-ray and ?-ray shielding and protection. In this work, we have explored the efficacy of poly(vinyl alcohol)bismuth oxide composites as radiation shielding materials. Poly(vinyl alcohol) composites with different wt % (050) of bismuth were prepared by a simple solution casting technique. Structural and thermal characterization of these samples was carried out using Fourier transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). TGA revealed the enhanced thermal stability of these composites. AC conductivity measurements and optical spectroscopy were used to analyze their electrical behavior. The composites showed low conductivity, and the energy gap obtained also showed their tendency to be insulators. The radiation attenuation properties were investigated using X-ray (5.895 and 6.490 keV) and ?-ray (59.54 and 662 keV) transmission measurements. The shielding efficiency of the composites increased with filler wt %. The 40 wt % composites exhibited mass attenuation coefficients of 122.68 and 93.02 cm2/g at photon energies of 5.895 and 6.490 keV, respectively, while the 50 wt % composites showed 1.57 and 0.092 cm2/g at photon energies of 59.54 and 662 keV, respectively. The effective atomic number quantifies the probability of interaction of radiation with matter. The effective atomic number of the composites calculated by the direct method was in good agreement with the theoretical value obtained from Auto-Zeff software. 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 47949. 2019 Wiley Periodicals, Inc.
creator: Muthamma M.V.; Bubbly S.G.; Gudennavar S.B.; Narendranath K.C.S.
source: Journal of Applied Polymer Science, Vol-136, No. 37
publisher: John Wiley and Sons Inc.
date: 2019-01-01
rights: Restricted Access
relation: ISSN: 218995; CODEN: JAPNA
format: Online
language: English
type: Article
coverage: Muthamma M.V., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, -560 029, India; Bubbly S.G., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, -560 029, India; Gudennavar S.B., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, -560 029, India; Narendranath K.C.S., Space Science Division, Space Astronomy Group, ISITE Campus, ISRO, Bengaluru, -560 037, India

Attenuation parameters of polyvinyl alcohol-tungsten oxide composites at the photon energies 5.895, 6.490, 59.54 and 662 keV
subject: mass attenuation coefficient; radiation shielding; tungsten filled polyvinyl alcohol composite
description: The growing demand for lightweight, non-toxic and effective X-A nd ?-ray shielding materials in various fields has led to the exploration of various polymer composites for shielding applications. In this study, tungsten filled polyvinyl alcohol (PVA) composites of varying WO3 concentrations (0-50 wt%) were prepared by solution cast technique. The structural, morphological, and thermal properties of the prepared composite films were studied using X-ray diffraction technique (XRD), Scanning electron microscopy (SEM) and Thermogravimetric analysis (TGA). The AC conductivity studies showed the low conductivity property of the composites. The X-ray (5.895 and 6.490 keV) and ?-ray (59.54 and 662 keV) attenuation studies performed using CdTe and NaI(Tl) detector spectrometers revealed a noticeable increase in shielding efficiency with increase in filler wt%. The effective atomic number (Zeff) calculated by the direct method agreed with the values obtained using Auto-Zeff software. The % heaviness showed that tungsten filled polyvinyl alcohol composites are lighter than traditional shielding materials. 2020 M V Muthamma et al., published by Sciendo 2020.
creator: Muthamma M.V.; Gudennavar B.S.; Gudennavar S.B.
source: Polish Journal of Medical Physics and Engineering, Vol-26, No. 2, pp. 77-85.
publisher: Sciendo
date: 2020-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 14254689
format: Online
language: English
type: Article
coverage: Muthamma M.V., Department of Physics and Electronics, Christ, Deemed to Be University, Bangalore Central Campus, Karnataka, Bengaluru, 560029, India; Gudennavar B.S., Department of Physics and Electronics, Christ, Deemed to Be University, Bangalore Central Campus, Karnataka, Bengaluru, 560029, India; Gudennavar S.B., Department of Physics and Electronics, Christ, Deemed to Be University, Bangalore Central Campus, Karnataka, Bengaluru, 560029, India

Micro and nano Bi2O3 filled epoxy composites: Thermal, mechanical and ?-ray attenuation properties
subject: Bismuth oxide; Epoxy; Micro/nano composites; ?-Ray attenuation studies
description: Polymer composites have attracted considerable attention as potential light-weight and cost-effective materials for radiation shielding and protection. In view of this, the present work focusses on development of lead-free composites of diglycidyl ether of bisphenol A (DGEBA) epoxy resin with micro (~ 10 ?m) and nano (~ 20 nm) bismuth (III) oxide (Bi2O3) fillers, using solution casting technique. Thermal, mechanical and ?-ray attenuation properties of the composites were studied by varying the filler loading. Inclusion of the fillers into epoxy matrix was confirmed both structurally and morphologically by XRD and SEM, respectively. Thermogravimetric analysis (TGA) showed the thermal stability of composites to be as high as 400 C. The nanocomposites exhibited relatively higher thermal stability than their micro counterparts. Among the composites, 14 wt% nano-Bi2O3/epoxy composites showed highest tensile strength of 326 MPa, which is about 38% higher than 30 wt% micro Bi2O3/epoxy composites. Mass attenuation coefficients (?/?) of the composites were evaluated at ?-ray energies ranging from 0.356 to 1.332 MeV. Nanocomposites showed better ?-ray shielding at all energies (0.356, 0.511, 0.662, 1.173, 1.280 and 1.332 MeV) than micro composites with same filler loading. These studies revealed the significance of nano-sized fillers in enhancing overall performance of the composites. 2021 Elsevier Ltd
creator: Muthamma M.V.; Prabhu S.; Bubbly S.G.; Gudennavar S.B.
source: Applied Radiation and Isotopes, Vol-174
publisher: Elsevier Ltd
date: 2021-01-01
rights: Restricted Access
relation: ISSN: 9698043; PubMed ID: 34052516; CODEN: ARISE
format: Online
language: English
type: Article
coverage: Muthamma M.V., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore Central Campus, Bengaluru, 560029, Karnataka, India; Prabhu S., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore Central Campus, Bengaluru, 560029, Karnataka, India; Bubbly S.G., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore Central Campus, Bengaluru, 560029, Karnataka, India; Gudennavar S.B., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore Central Campus, Bengaluru, 560029, Karnataka, India

A reconfigurable integrated level shifted carrier based PWM method for modular multilevel converters
subject: carrier based sinusoidal pulse width modulation; harmonic distortion; modular multilevel converters; pulse width modulation
description: This article presents a reconfigurable integrated level shifted carrier-based pulse width modulation (ILSC-PWM) method for modular multilevel converters (MMCs). The principles of basic level shifted carrier-based PWM (LSC-PWM) methods such as phase disposition PWM (PD-PWM), phase opposition disposition PWM (POD-PWM) and alternate phase opposition disposition PWM (APOD-PWM) methods are combined to develop the concept of reconfigurable ILSC-PWM method. The main objectives of the proposed reconfigurable ILSC-PWM method is to develop the pulse width modulated output voltage with both half-wave and quarter-wave symmetries and to reduce the total harmonic distortion (THD). A simplified mathematical approach is developed to formulate reconfigurable single ILSC wave for MMC with N number of submodules (SMs) per arm. The functionality and performance of the reconfigurable ILSC-PWM method are carried out on three-phase five-level MMC in MATLAB/Simulink. A hardware prototype of single-phase five-level MMC is designed for experimental validation. The proposed ILSC-PWM method is implemented on an Altera/Cyclone I series (EP1C12Q240C8N) field programmable gate array (FPGA). Computer Simulations and laboratory experimental results are presented. 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
creator: Muthavarapu A.K.; Anjana K.G.; Biswas J.; Barai M.
source: IEEJ Transactions on Electrical and Electronic Engineering, Vol-17, No. 8, pp. 1148-1159.
publisher: John Wiley and Sons Inc
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 19314973
format: Online
language: English
type: Article
coverage: Muthavarapu A.K., Electrical and Electronics Engineering, Aditya Engineering College (A), Andhra Pradesh, Surampalem, 533437, India; Anjana K.G., Electrical Engineering, National Institute of Technology, Kerala, Calicut, 673601, India; Biswas J., Department of Computer Science, Christ University, Karnataka, Bengaluru, 560029, India; Barai M., Electrical Engineering, National Institute of Technology, Kerala, Calicut, 673601, India

An Efficient Sorting Algorithm for Capacitor Voltage Balance of Modular Multilevel Converter With Space Vector Pulsewidth Modulation
subject: Analogue sorting; capacitor voltage balancing; modular multilevel converters (MMCs); space vector pulsewidth modulation (SVPWM)
description: Thisarticle presents an efficient analogue sorting algorithm for balancing the submodule (SM) capacitor voltages of modular multilevel converter (MMC). The proposed analogue sorting algorithm offers the advantage of fast convergence rate without any need of recursive loops for the implementation on embedded devices. It can be easily implemented with combinational logic operations on field programmable gate array (FPGA) and provides less hardware and computational overhead. The functionality and performance of the proposed analogue sorting algorithm is evaluated with the simulation model of three phase five-level MMC in MATLAB/Simulink environment. The real time implementation of the proposed sorting algorithm with the SM capacitor voltage balancing strategy is implemented on Altera/Cylone - I (EP1C12Q240C8N) FPGA. A five-level continuous space vector pulsewidth modulation (CSVPWM) is realized on a PIC microcontroller (PIC18F452). A down-scaled model of single-phase five-level MMC is designed and constructed to investigate the reliable and stable operation of MMC with the proposed analogue sorting algorithm and SVPWM method. Simulation and experimental results are presented for validation. 1986-2012 IEEE.
creator: Muthavarapu A.K.; Biswas J.; Barai M.
source: IEEE Transactions on Power Electronics, Vol-37, No. 8, pp. 9254-9265.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 8858993; CODEN: ITPEE
format: Online
language: English
type: Article
coverage: Muthavarapu A.K., Aditya Engineering College (A), Electrical and Electronics Engineering Department, Surampalem, 533437, India; Biswas J., Christ University, Department of Computer Science, Bengaluru, 560029, India; Barai M., National Institute of Technology, Department of Electrical Engineering, Kozhikode, Calicut, 673601, India

Effects of Euphorbia thymifolia and Euphorbia hirta leaf extracts on membrane-bound, mitochondrial enzymes and lipid profile of carbon tetrachloride-induced hepatotoxicity in rats
subject: Hepatoprotective activity; lipid profifiles; membrane-bound; mitochondrial enzymes
description: The present investigation was aimed to identify the potentiality of Euphorbia thymifolia Linn. and Euphorbia hirta Linn. leaf extract on the toxin-induced (carbon tetrachloride- CCl4) Albino Wistar rats. The animals were grouped into 7 categories including control (basal diet, G1), CCl4-induced (1.5 mL/kg, b.w., i.p.) (G2), G1 administrated with 300 mg/kg b.w., extract of E. thymifolia (G3) and E. hirta (G4), G2 administrated with 300 mg/kg b.w., extract of E. thymifolia (G5), E. hirta (G6), and standard drug (silymarin 25 mg/kg b.w.; G7) for 21- days trial period with each group contains 6 rats. The samples were collected and the following parameters including mitochondrial enzymes, different ATPase and lipid profiles were analyzed. The membrane-bound enzymes, the mitochondrial enzymes levels and the lipid profiles were reduced in the toxin-induced rats but the levels of enzymes were restored, significantly increased and lipid profiles are returned to the normal in the treatment of both extracts. 2022 Visagaa Publishing House.
creator: Muthu Mani G.D.; Balamuralikrishnan B.; Manikandan R.; Sampathkumar P.; Arun M.; Lakshminarayanan R.R.; Liu W.-C.; Anand A.V.
source: Natural Resources for Human Health, Vol-2, No. 4, pp. 443-449.
publisher: Visagaa Publishing House
date: 2022-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 25831194
format: Online
language: English
type: Article
coverage: Muthu Mani G.D., Department of Biochemistry, SRM Arts and Science College, Tamil Nadu, Chennai, India; Balamuralikrishnan B., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, South Korea; Manikandan R., Department of Biochemistry, Shrimati Indira Gandhi College, Tamil Nadu, Trichy, India; Sampathkumar P., Department of Chemistry and Biosciences, SASTRA University, Tamil Nadu, Kumbakonam, India; Arun M., Department of Life Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560076, India; Lakshminarayanan R.R., Department of Animal Sciences, Bharathiadasan University, Tamil Nadu, Tiruchirappalli, India; Liu W.-C., Department of Animal Science, College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, 524088, China; Anand A.V., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, India

Unveiling the Emotions: A Sentiment Analysis of Amazon Customer Feedback
subject: Amazon customer feedback; Confusion matrix; Machine learning; Sentiment analysis; Word cloud
description: This study explores sentiment analysis in the context of diverse regions and contemporary customer feedback, aiming to address research questions related to consolidation based on polarity scores and sentiments. The research utilizes multinomial regression for a comprehensive analysis of customer feedback worldwide. The investigation incorporates confusion matrices, statistics, and class-specific metrics to evaluate the models performance. Results indicate a highly accurate model with perfect sensitivity, specificity, and overall accuracy. The analysis further includes a breakdown of key metrics such as accuracy, confidence intervals, no information rate, p-value, kappa, and prevalence, emphasizing the models robustness. In conclusion, the multinomial logistic regression model demonstrates exceptional performance in predicting sentiment across diverse classes, highlighting its effectiveness in sentiment analysis on a global scale. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
creator: Muthu Ruben V.; VijayaKumar R.; Sateesh Kumar T.K.
source: Studies in Systems, Decision and Control, Vol-536, pp. 403-410.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 21984182
format: Online
language: English
type: Book chapter
coverage: Muthu Ruben V., School of Law, Christ University, Bangalore, India; VijayaKumar R., Kristu Jayanti College (Autonomous), Bangalore, India; Sateesh Kumar T.K., Kristu Jayanti College (Autonomous), Bangalore, India

DFT electronic structure calculations, spectroscopic studies, and normal coordinate analysis of 2-[(5-nitro-1,3-thiazol-2-yl)carbamoyl]phenyl acetate
subject: DFT; FTIR and FT-Raman spectra; HOMO-LUMO; NBO; NCA
description: The solid phase FTIR and FT-Raman spectra of 2-[(5-nitro-1,3-thiazol-2-yl)carbamoyl]phenyl acetate (25N2LCPA) have been recorded 450-4000 cm-1 and 100-4000 cm-1 respectively. The normal coordinate analysis was carried out to confirm the precision of the assignments. DFT calculations have been performed giving energies, optimized structures, harmonic vibrational frequencies and IR intensities. The structure of the molecule was optimized and the structural characteristics were determined by density functional theory (DFT) using B3LYP method with 6-31+G(d,p) basis set. The detailed interpretation of the vibrational spectra has been carried out with aid of normal coordinate analysis (NCA) following the scaled quantum mechanical force field methodology. The Vibrational frequencies are calculated in the above method and are compared with experimental frequencies which yield good agreement between observed and calculated frequencies. Stability of the molecule arising from hyper conjugative interactions, charge delocalization has been analyzed using natural bond orbital (NBO) analysis. In addition, Frontiers molecular orbital and molecular electrostatic potential were computed by using Density Functional Theory (DFT) B3LYP/6-31+G(d,p) basis set. The calculated HOMO and LUMO energies show that charge transfer occurs in the molecule. 2014 Elsevier B.V. All rights reserved.
creator: Muthu S.; Elamuruguporchelvi E.; Varghese A.
source: Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy, Vol-138, pp. 743-752.
publisher: Elsevier
date: 2015-01-01
rights: Restricted Access
relation: ISSN: 13861425; PubMed ID: 25544190; CODEN: SAMCA
format: Online
language: English
type: Article
coverage: Muthu S., Department of Physics, Sri Venkateswara College of Engg, Sriperumbudur, Tamil Nadu, 602105, India; Elamuruguporchelvi E., Department of Physics, Kanchi Pallavan Engineering College, Kanchipuram, Tamil Nadu, 631502, India; Varghese A., Department of Chemistry, Christ University, Bangalore, 560029, India

ML in drug delivery-current scenario and future trends
description: Machine learning (ML) has enabled transformative applications and emerged as a domain-agnostic decision-making tool as a virtue of its rapid democratization. The authors believe that a systematic assortment of important publications on this issue is indispensable in this context. In terms of data ingestion, data curation, data preprocessing, data handling, and model cross-validation, this review gathers together several studies that have demonstrated a minimum ML framework approach. In general, ML models are described as black-box models, with limited information supplied about their transparency. The authors propose techniques based on the US Food and Drug Administration (FDA)'s current good ML practice (GMLP) in order to improve the ML framework and minimize the aforementioned gap, especially for data. Considering this, the conversation around a model's logic and interpretability are additionally provided. Explicitly, the authors explore the challenges and constraints that ML execution confronts throughout the development of pharmaceuticals. In this context, a structural approach in statistics is presented to allow the scientist to assess the quality of data and incorporate important ideas and techniques that would be implemented in modern ML. The data analytics tetrahedron proposed here can be applied to data of any size. To further contextualize, selected case studies capturing good practices are highlighted to provide pharmaceutical scientists, pharmaceutical ML enthusiasts, readers, reviewers, and regulatory authorities an exposure to fundamental and cuttingedge techniques of ML and data science with respect to chemistry, manufacture, and control (CMC) of drug products. In addition, the authors believe that leveraging ML within CMC procedures can assist in improving decision-making, increasing quality, and enhancing the speed of pharmaceutical product development. IOP Publishing Ltd 2023. All rights reserved.
creator: Muthudoss P.; Ali H.; Ramasamy G.; Allada R.; Fink E.; Kalaiselvan V.; Jayakrishnan B.; Shahane S.; Ramalingam M.; Kanakaraj L.; Kaliappan I.; Paudel A.
source: Advances in Drug Delivery Systems for Healthcare: From concept to clinic, pp. 9-.
publisher: Institute of Physics Publishing
date: 2024-01-01
rights: Restricted Access
relation: ISBN: 978-075035615-2; 978-075035611-4
format: Online
language: English
type: Book chapter
coverage: Muthudoss P., A2Z4.0 Research and Analytics Private Limited, Chennai, 600062, India; Ali H., Christ University, Bangalore, 560029, India; Ramasamy G., Christ University, Bangalore, 560029, India; Allada R., Novugen Pharma (Malaysia) Sdn Bhd, Hicomglenmarie Industrial Park, 3, Jalan Jururancang U1/21, Selangor, 40150, Malaysia; Fink E., Research Center Pharmaceutical Engineering GmbH (RCPE), Inffeldgasse 13, Graz, 8010, Austria; Kalaiselvan V., Indian Pharmacopoeia, Commission, Ministry of Health and Family Welfare, Government of India, Sector 23, Rajnagar, 201002, India; Jayakrishnan B., Business School, Vellore Institute of Technology (VIT), Chennai Campus, Kekottaiyur, 600127, India; Shahane S., The Machine Learning Company, Maharashtra, India; Ramalingam M., Chettinad School of Pharmaceutical Sciences, Chettinad Academy of Research and Education, Chettinad Health City, Chennai, 603103, India; Kanakaraj L., Chettinad School of Pharmaceutical Sciences, Chettinad Academy of Research and Education, Chettinad Health City, Chennai, 603103, India; Kaliappan I., SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, India; Paudel A., Graz University of Technology, Institute of Process and Particle Engineering, Inffeldgasse 13/3, Graz, 8010, Austria

Teacher Trainee's Acceptance of Interactive eBooks for Teaching: An Analysis Using the Modified Technology Acceptance Model (TAM)
subject: Interactive eBooks; quality education; teacher training; technology acceptance model (TAM); technology-integrated teaching
description: The current empirical study utilized the Technology Acceptance Model (TAM) to investigate teacher trainees' acceptance of interactive eBooks for teaching. The study investigated the relationships among variables such as attitude toward using interactive eBooks, perceived ease of use, perceived usefulness, enjoyment, perceived self-efficacy, and behavioural intention to use. A sample consisting of 89 teacher trainees studying in diploma and bachelors teacher training programs from two private and public universities in Malaysia participated in the study. The TAM model, which involves seven hypotheses, was tested using the Partial Least Square Structural Equation Modelling approach (PLS-SEM). The key findings of this empirical study confirmed that attitude influences both behaviour intention to use, and perceived self-efficacy of teacher trainees in teaching using interactive eBooks. Besides, the study confirmed a direct effect of ease of use on the level of enjoyment and a direct effect of perceived usefulness on the perception of ease of use. The study findings shed light on preparing teacher trainees for technology-integrated teaching. 2024, The Pacific Association for Computer Assisted Language Learning (PacCALL). All rights reserved.
creator: Muthukrishnan P.; Aravind B.R.; Salim E.J.H.; Balakrishnan S.V.; Kaur B.; Prakasha G.S.
source: CALL-EJ, Vol-25, No. 2, pp. 109-129.
publisher: The Pacific Association for Computer Assisted Language Learning (PacCALL)
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 21879036
format: Online
language: English
type: Article
coverage: Muthukrishnan P., Faculty of Education and Liberal Arts, INTI Intl University, Malaysia; Aravind B.R., Faculty of English, Kalasalingam Academy of Research and Education, India; Salim E.J.H., Department of Education, HELP University, Malaysia; Balakrishnan S.V., Institut Pendidikan Guru Malaysia Kampus Pendidikan Teknik, Nilai, Malaysia; Kaur B., Department of Education, HELP University, Malaysia; Prakasha G.S., School of Education, Christ University, Bangalore, India

A New Approach to Robust Weighted Support Vector Regression and Its Applications in Medical MRI Image Processing
subject: Image processing; Robust weight function; Support vector regression
description: In recent years, the field of machine learning has experienced significant growth, with the emergence of various advanced technologies leveraging its principles. Among these, Support Vector Regression (SVR) has established itself as a widely recognized and robust regression technique. This article introduces a novel approach, Robust Hampel Weight-Based Support Vector Regression (RH-SVR), designed to enhance the resilience and efficiency of traditional SVR. The study investigates and compares several regression methods, including the Robust Linear Model (RLM), SVR, RH-SVR, and Least Squares Regression (LS). An experimental analysis was conducted using MRI images of the human heart and brain, both in their original form and with added noise at varying levels (10, 20, and 30%). Performance metrics such as Mean Square Error (MSE), Median Absolute Error (MDAE), Relative Standard Error (RSE), and Peak Signal-to-Noise Ratio (PSNR) were evaluated. The results consistently demonstrate that the proposed RH-SVR method achieves lower error rates and higher PSNR values, showcasing superior accuracy and robustness, particularly when processing noisy images. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
creator: Muthukrishnan, R.; Kalaivani, S.
source: Lecture Notes in Networks and Systems;Volume;1355 LNNS;pp.347-356
publisher: Springer Science and Business Media Deutschland GmbH
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISSN: 23673370; ISBN: 978-981964882-5;
language: English
type: Conference paper
coverage: Muthukrishnan R., Bharathiar University, Tamil Nadu, Coimbatore, India; Kalaivani S., Christ University, Karnataka, Bangalore, India

Computer modelling of trace SO2 and NO2 removal from flue gases by utilizing Zn(ii) MOF catalysts
description: SO2 and NO2 capture and conversion have been investigated via density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations using a novel hydrogen-bonded 3D metal-organic framework (MOF) containing a Zn(ii) centre and a partially fluorinated (polar -CF3) long-chain dicarboxylate ligand with a melamine (basic -NH2) co-ligand. Initially, computational single-component isotherms have been determined for SO2 and NO2 gases. These simulations have shown exothermic adsorption enthalpies of ?36.4 and ?28.6 kJ mol?1 for SO2 and NO2, respectively. They have also indicated that SO2 has a high affinity for polar -CF3 and basic -NH2 binding sites of the ligand in the framework pore walls. The lower adsorption capacity of NO2 compared with SO2 is due to weaker electrostatic interactions with the framework. Furthermore, MOF adsorbent selectivity for removing trace amounts of SO2 and NO2 in flue gases has been estimated through the co-adsorption of ternary gas mixtures (SO2/CO2/N2 and NO2/CO2/N2). Together with DFT, the climbing image nudged elastic band (CI-NEB) method has been used for investigating the plausible mechanisms for HbMOF1 catalyzed cycloadditions of SO2 and NO2 with epoxides leading to the formation of cyclic sulphites and nitrates, respectively. 2023 The Royal Society of Chemistry.
creator: Muthukumar D.; Nagaraja C.M.; Badawi M.; Pillai R.S.
source: New Journal of Chemistry, Vol-47, No. 38, pp. 18086-18095.
publisher: Royal Society of Chemistry
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 11440546; CODEN: NJCHE
format: Online
language: English
type: Article
coverage: Muthukumar D., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India, Laboratoire de Physique et Chimie Thriques UMR CNRS 7019 Universitde Lorraine, Nancy, France; Nagaraja C.M., Department of Chemistry, Indian Institute of Technology, Ropar, Punjab, Rupnagar, 140001, India; Badawi M., Laboratoire de Physique et Chimie Thriques UMR CNRS 7019 Universitde Lorraine, Nancy, France; Pillai R.S., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India, Analytical and Spectroscopy Division, ASCG/PCM, Vikram Sarabhai Space Centre, Indian Space Research Organization, Kerala, Thiruvananthapuram - 695 022, India