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Performance investigation of modular multilevel inverter topologies for photovoltaic applications with minimal switches
Introduction. In recent years, a growing variety of technical applications have necessitated the employment of more powerful equipment. Power electronics and megawatt power levels are required in far too many medium voltage motor drives and utility applications. It is challenging to incorporate a medium voltage grid with only one power semiconductor that has been extensively modified. As a result, in high power and medium voltage settings, multiple power converter structure has been offered as a solution. A multilevel converter has high power ratings while also allowing for the utilization of renewable energy sources. Renewable energy sources such as photovoltaic, wind, and fuel cells may be readily connected to a multilevel inverter topology for enhanced outcomes. The novelty of the proposed work consists of a novel modular inverter structure for solar applications that uses fewer switches. Purpose. The proposed architecture is to decrease the number of switches and Total Harmonic Distortions. There is no need for passive filters, and the proposed design enhances power quality by creating distortion-free sinusoidal output voltage as the level count grows while also lowering power losses. Methods. The proposed topology is implemented with MATLAB / Simulink, using gating pulses and various pulse width modulation methodologies. Moreover, the proposed model also has been validated and compared to the hardware system. Results. Total harmonic distortion, number of power switches, output voltage and number of DC sources are compared with conventional topologies. Practical value. The proposed topology has been very supportive for implementing photovoltaic based multilevel inverter, which is connected to large demand in grid. References 12, table 5, figures 23. E. Parimalasundar, N.M.G. Kumar, P. Geetha, K. Suresh. -
Performance investigations of five-level reduced switches count ?-bridge multilevel inverter
Introduction. This research paper describes a simple five-level single-phase pulse-width modulated inverter topology for photovoltaic grid applications. Multilevel inverters, as opposed to conventional two-level inverters, include more than two levels of voltage while using multiple power switches and lower-level DC voltage levels as input to produce high power, easier, and less modified oscillating voltage. The H-bridge multilevel inverter seems to have a relatively simple circuit design, needs minimal power switching elements, and provides higher efficiency among various types of topologies for multi-level inverters that are presently accessible. Nevertheless, using more than one DC source for more than three voltage levels and switching and conduction losses, which primarily arise in major power switches, continue to be a barrier. The novelty of the proposed work consists of compact modular inverter configuration to connect a photovoltaic system to the grid with fewer switches. Purpose. The proposed system aims to decrease the number of switches, overall harmonic distortions, and power loss. By producing distortion-free sinusoidal output voltage as the level count rises while lowering power losses, the constituted optimizes power quality without the need for passive filters. Methods. The proposed topology is implemented in MATLAB/Simulink with gating pulses and various pulse width modulation technique. Results. With conventional topology, total harmonic distortion, power switches, output voltage, current, power losses, and the number of DC sources are investigated. Practical value. The proposed topology has proven to be extremely useful for deploying photovoltaic-based stand-alone multilevel inverters in grid applications. References 18, table 2, figures 15. 2023, National Technical University "Kharkiv Polytechnic Institute". All rights reserved. -
Fault diagnosis in a five-level multilevel inverter using an artificial neural network approach
Introduction. Cascaded H-bridge multilevel inverters (CHB-MLI) are becoming increasingly used in applications such as distribution systems, electrical traction systems, high voltage direct conversion systems, and many others. Despite the fact that multilevel inverters contain a large number of control switches, detecting a malfunction takes a significant amount of time. In the fault switch configurations diode included for freewheeling operation during open-fault condition. During short circuit fault conditions are carried out by the fuse, which can reveal the freewheeling current direction. The fault category can be identified independently and also failure of power switches harmed by the functioning and reliability of CHB-MLI. This paper investigates the effects and performance of open and short switching faults of multilevel inverters. Output voltage characteristics of 5 level MLI are frequently determined from distinctive switch faults with modulation index value of 0.85 is used during simulation analysis. In the simulation experiment for the modulation index value of 0.85, one second open and short circuit faults are created for the place of faulty switch. Fault is identified automatically by means of artificial neural network (ANN) technique using sinusoidal pulse width modulation based on distorted total harmonic distortion (THD) and managed by its own. The novelty of the proposed work consists of a fast Fourier transform (FFT) and ANN to identify faulty switch. Purpose. The proposed architecture is to identify faulty switch during open and short failures, which has to be reduced THD and make the system in reliable operation. Methods. The proposed topology is to be design and evaluate using MATLAB/Simulink platform. Results. Using the FFT and ANN approaches, the normal and faulty conditions of the MLI are explored, and the faulty switch is detected based on voltage changing patterns in the output. Practical value. The proposed topology has been very supportive for implementing non-conventional energy sources based multilevel inverter, which is connected to large demand in grid. References 22, tables 2, figures 17. E. Parimalasundar, R. Senthil Kumar, V.S. Chandrika, K. Suresh. -
Fault Analysis and Compensation in a Five Level Multilevel DC-AC Converter
Existing Neutral clamped active (NCA) inverters have the property of high frequency common mode voltage, which can reduce the severity with less voltage gain. A newly designed five level (5L) NCA inverter can capable have achieved voltage step-up with a one stage inversion process. The proposed circuit common ground enhances DC link voltage usage while also mitigating common mode voltage with high frequency. The proposed topology is more compact and has less voltage stress than the conventional two stage topology. The proposed circuit contains merely seven power switches and two capacitors, whereas the conventional topology has ten switches and three capacitors, resulting in a more efficient layout. The proposed topology is developed in the simulink platform, and the simulation results are validated in a proto-type model with a power rating of 2000 W to validate its feasibility and performance with fault clearance capabilities. 2023, TUBITAK. All rights reserved. -
A Performance Investigations of Modular Multilevel Inverter with Reduced Switch Count
A multilevel inverter is a special variant of converter for dc-Ac conversion in medium and high voltage and power requirements. In this paper, a novel configuration with fewer switches needed has been developed for the staircase output voltage levels. Two direct current voltage sources and eight transistors are required to synthesize five levels across the load using the conventional topology. The modular topology has two dc voltage sources, and six switches with a five-level output. Using the optimum multi-carrier pulse width modulation approach, the voltage quality is enhanced and total harmonic distortion is reduced. Furthermore, the viability of the proposed topology in contrast to the conventional cascaded H-bridged multilevel inverter with five levels is established by presenting comparable results showing reduced power losses with varied modulation indexes and increased efficiency. The simulation analysis has been carried out using the MATLAB/SIMULINK tool. 2022 IEEE. -
Flat Unglazed Transpired Solar Collector: Performance Probability Prediction Approach Using Monte Carlo Simulation Technique
Engineering applications including food processing, wastewater treatment, home heating, commercial heating, and institutional heating successfully use unglazed transpired solar collectors (UTCs). Trapping of solar energy is the prime goal of developing an unglazed transpired solar collector. The UTC is usually developed in and around the walls of the building and absorbs the solar energy to heat the air. One of the key challenges faced by the UTC designer is the prediction of performance and its warranty under uncertain operating conditions of flow variables. Some of the flow features are the velocity distribution, plate temperature, exit temperature and perforation location. The objective of the present study was to establish correlations among these flow features and demonstrate a method of predicting the performance of the UTC. Hence, a correlation matrix was generated from the dataset prepared after solving the airflow over a perforated flat UTC. Further, both strong and weak correlations of flow features were captured through Pearsons correlation coefficient. A comparison between the outcomes from a linear regression model and that of computational simulation was showcased. The performance probability for the UTC was interlinked with correlation matrix data. The Monte Carlo simulation was used to predict the performance from random values of the flow parameters. The study showed that the difference between the free stream value of temperature and the value of temperature inside the UTCs chamber varied between 15 and 20 C. The probability of achieving system efficiency greater than 35% was 55.2%. This has raised the hope of recommending the UTC for drying and heating where the required temperature differential is within 20 C. 2022 by the authors. -
On building up a closer psychic distance as a fundamental ground of relationship between India and Korea: Focusing on Jeonlanam-Do in Korea
The Uppsala model (Johanson and Wiedersheim-Paul, 1975) identifies cultural differences, market attractiveness, and core competence of nations or firms as the key factors affecting international market selection. Among these three factors, psychic distance caused by cultural differences is regarded as the most important factor. However, the psychic distance between India and Korea is not very close. The main objective of this paper is to examine the ways to boost economic relationships between India and Korea by building up a closer relationship of psychic distance. We suggest Jeonlanam-Do including Gwangju Metropolitan City (JDGC) in Korea as a stepping stone to make both countries' psychic distance closer as JD has several common grounds of intangible assets with India which includes its adherence to democracy, human rights and peace; the diverse food culture; and the religious zeal to Buddhism. We propose these common interests as a way to enhance the awareness of national brand 'India' in Korea which will attribute to a strategically developed economic relationship between Korea and India. 2022 Inderscience Enterprises Ltd.. All rights reserved. -
Comparison of the inter-item correlations of the Big Five Inventory-10 (BFI-10) between Western and non-Western contexts
The Big Five Inventory-10 (BFI-10; Rammstedt & John, 2007) is one of many short versions of personality inventories that measure the Big Five trait dimensions. Short versions of scales often present methodological challenges as a trade-off for their convenience. Based on samples from 28 countries (N = 10,560), the current study investigated inter-item correlations estimated using Omega coefficients within each of the five personality characteristics measured by the BFI-10. Results showed that inter-item correlations were significantly lower, in the sample data from non-Western countries compared with the Western countries, for three of the five personality traits, specifically Conscientiousness, Extraversion, and Emotional Stability. Our findings indicate that the psychometric challenges exist across different cultures and traits. We offer recommendations when using short-item scales such as BFI-10 in survey research. 2022 Elsevier Ltd -
Real- coded genetic algorithm for optimal ordering and pricing in segmented market with freshness and price- dependent demand, advance payment, and trade credit
We study the inventory model of a product having demand affected by its freshness and selling price in the context of supply chains, freshness, and price-dependent demand, where the supplier is dominated, as is usually the case with producers of agri-based products. The product when received exhibits heterogeneous quality. The retailer subdivides the product into quality-dependent segments, which he sells simultaneously during the selling season at prices commensurate with the quality. The sizes of the segments are random variables. The supplier can get a partial advance payment from the dominant retailer by providing a discount on the partial advance with the proportion of partial payment as well as the epoch of partial payment chosen by the supplier. The retailer can, at times, choose the advance proportion to be paid, and the discounted price which we call the endogenous case but takes a loan for the advance payment from a financer, whom he repays with interest when a delayed payment period permitted by the supplier gets over. The retailer in turn gets some time before he can pay his remaining dues and pays the supplier a fraction of the cost price commensurate with the quality of the product. Lost sales shortages are considered for fresh items. The model is aimed at obtaining optimal values of ordering amount, selling price, and discounted selling prices for the various segments. It is also aimed to obtain advance proportion and the discount on advance payment for the endogenous case. Real-coded genetic algorithm (RCGA) and Hybrid RCGA have been used to obtain the optimal solutions for numerical examples and the results are compared. Finally, sensitivity analysis to evaluate the effects of changes in some parameter values has also been presented. 2025 selection and editorial matter, Sulabh Bansal, Aprna Tripathi, Shilpa Srivastava and Prem Prakash Vuppuluri; individual chapters, the contributors. -
OTT Regulation, Platform Governance, and the Politics of Digital Misinformation in India
The rapid growth of Over-the-Top (OTT) platforms in India has significantly reshaped the entertainment industry. Audiences increasingly prefer streaming films and series over traditional cinema and television due to accessibility, affordability, flexibility, and on-demand viewing, even in rural and small-town regions. This shift reflects the empowerment of Indias digital media ecosystem. This paper analyses Netflix and Amazon Prime Video as case studies to support the research. However, the expansion of OTT platforms has also raised serious concerns regarding freedom of expression and content regulation. While creative autonomy promotes diverse storytelling and social commentary, it may also lead to the circulation of sensitive, offensive, or harmful content. Recently, the Indian government banned 25 OTT platforms for hosting obscene material without effective age-verification mechanisms exposing minors to such content. The Tandav controversy further illustrates the tension between artistic freedom and Indias cultural and religious sensitivities. Copyright 2026, IGI Global Scientific Publishing. Copying or distributing in print or electronic forms without written permission of IGI Global Scientific Publishing is prohibited. Use of this chapter to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development. -
Leveraging artificial intelligence for predictive financial risk management in emerging markets
This chapter examines how AI is changing the management of financial risk in emerging markets. It discusses how AI is applied, what challenges it encounters, and what the future may hold. Fast changes in global financial markets and the growing complexity of economies in developing countries require better ways of managing risks than the old methods offer. This chapter focuses on how AI technologies change risk assessment and management practices. They offer new capabilities in analyzing data, patterns, and even predicting. The discussion begins by explaining why the old ways of managing risk are not effective in new markets. It then zooms in on how AI-powered solutions can rectify these issues. The chapter explores various uses of AI in managing financial risk, including the assessment of credit risk, detection of fraud, analysis of market risk, and optimization of portfolios. It takes a view of what technical infrastructure is required to implement AI successfully and the steps to do so. It focuses on the challenges of updating old systems in new market financial institutions. 2025 by IGI Global Scientific Publishing. -
Mangrove area classification in Pichavaram using Hyperspectral Imaging and Optimized Channel-Level Residual CNN framework
The Pichavaram mangrove forest in Tamil Nadu is one of Indias most ecologically significant regions, supporting coastal health and local communities. However, effective mangrove area classification remains challenging due to field inaccessibility and inefficiency of traditional assessment methods, highlighting the demand for advanced solutions. As the existing remote sensing-based studies suffer from limited classification accuracy and high computational complexity, this study combined Hyperspectral Image (HSI) with an Optimized Channel Level Residual CNN (OC-LRCNN) model for improved results in mangrove-related research. The proposed model employs unsupervised feature extraction to capture essential patterns with minimal training data while channel-level residual connections enhance discriminative feature selection and reduce spectral redundancy. Utilizing the Pichavaram EO-1 Hyperion and AVIRIS-NG datasets, the proposed model is compared with traditional CNN, state-of-the-art deep learning architectures (VGG, ResNet, DenseNet) and machine learning methods like SVM and RF. The OC-LRCNN achieved classification accuracies of 98.2% and 99.0% for the Hyperion and AVIRIS-NG datasets with consistently high precision, recall, F1-score and kappa values. These findings demonstrate the models effectiveness in reliable mangrove classification and monitoring applications. The Author(s), under exclusive licence to Springer Nature B.V. 2026. -
Exploring the Patterns of Recreational Polysubstance Use and Executive Functions in Indian Young Adults: A Cross-Sectional Study
Background: Substance use is a serious public health concern and young adults in India often use multiple substances, often together. There is a dearth of research examining this and its neuropsychological consequences. Polysubstance use (PSU) usually indicates higher chances of dependence and negative outcomes. This study aims to describe the patterns of PSU and associated executive function profiles in a sample of young adults in India. Methods: Fifty-four participants aged 1825 years filled out a self-report questionnaire on PSU, for lifetime and current use of seven classes of substances. Thirty-four participants also performed four executive functions (Flexibility, Inhibition, Working Memory, and Planning). A descriptive analysis was used to identify patterns of PSU and one-way analysis of variance (ANOVA) was conducted to compare the executive functions between three groups of substance users with nonusers. Results: Three patterns of PSU were identified in our sample: simultaneous (16.3%), concurrent (37.2%), and mixed (46.5%) patterns of use. Simultaneous and concurrent users reported the most commonly used substance combinations (alcohol/nicotine/cannabis). Performance on executive function tasks was compared among the different groups of substance users and nonusers. Executive function assessments revealed deficits in simultaneous users for inhibition (most errors) and planning (most number of moves) compared to other groups. Concurrent users had the lowest accuracy for the two-back visual working memory. Conclusions: The findings of this small sample study suggest executive function deficits are more common in simultaneous users and underscore the need for more research to examine the synergistic effects of substances on cognition and executive functions. 2025 The Author(s). -
Fractional study of a novel hyper-chaotic model involving single non-linearity
The applications of hyperchaotic systems (HCSs) can be widely seen in diverse fields associated with engineering due to their complicated dynamics, randomness, and high delicacy and sensibility. In the present work, we aim to investigate a new hyper-chaotic system involving a single non-linearity under the fractional CaputoFabrizio (CF) derivative for the first time. In fact, there is no previous study using fractional derivatives in this system. A new mathematical system using a fractional-order operator will be designed with the novel operator. The CaputoFabrizio non-integer operator is aimed to be employed to capture complex nature. In order to solve the extracted dynamical system, a quadratic numerical scheme is applied. This study contains stability and convergence sections for the considered method. Moreover, numerical results of the problem under various values of fractional orders and different values of initial conditions (ICs) are provided to show the performance of the suggested scheme. Figures of solutions for each dependent variable can be observed. 2022 The Author(s) -
Performance optimization for extraction, transformation, loading and reporting of data
Enterprise Resource Planning has become the cornerstone for making data acquisition and related operations more efficient. Recent advances in hardware and software technologies have enabled us to think about performance optimization. Ninety percent of ERP projects spend more than their allocated budgets and have exceeded the time schedule for implementation. There are many factors that can be attributed to the low success rate of implementation but one main factor is the performance of the ERP package itself. In this paper, we have described the Business Intelligence tool and database which is related to Systems, Applications and Products. It is popularly known as SAP. Based on this, a new, mulch-dimensional performance metric is proposed for extracting, transforming, loading and reporting the data. 2015 IEEE. -
Photon, Electron, Proton and Alpha Particle Interaction Parameters of Different Clays
Modern life has made human beings and nature vulnerable to harmful radiations at different levels. This can be a great health hazard of our times. Since there is no probability of dodging the harmful influence, the practical way out is having protective shielding. Lead, the most efficient attenuator in current use has the drawbacks of being heavy, toxic and capable of producing secondary radiations. Other attenuators concrete, glass etc. have similar deficits in use. This is the context of the scientific world's quest for a perfect shielding material which can provide protection from harmful radiations effectively, economically and environment friendly. This work attempts a computational study on the radiation shielding efficiency of different types of clays, understanding of which would enable its applications for radiation shielding. The presence of high Z elements and the layered structure of clay along with its good thermal stability make it ideal filler for an effective radiation shield. In this work, we have performed a systematic study of the mass attenuation coefficients, effective atomic number and electron density of various clay samples. 2022 American Institute of Physics Inc.. All rights reserved. -
Financial capability and financial wellbeing of women in community-based organizations: mediating role of decision-making ability
Purpose: Financial capability is considered to be an important concept that has drawn the attention of many world nations. While the literature suggests various studies on financial capability and financial wellbeing, focus on their combined significance has been limited. The purpose of this paper is to examine how financial capability affects the financial wellbeing of women in community-based organizations and how decision-making ability mediated this relationship. Design/methodology/approach: In total, 1,000 women who are associated with the community-based organization Kudumbashree in the state of Kerala, India participated in the survey-based study. Findings: The structural equation modelling results show that there exists a significant relationship between financial capability and the financial wellbeing of women in CBOs. Further, decision-making ability was identified as a significant mediator in this relationship thus establishing a partial mediation effect. Practical implications: The financial social workers can focus their activities on promoting financial capability and decision making aspects of women from middle/low income families to facilitate their financial wellbeing. The scope for financial socialisation and proper orientation is more for the women associated with the community based organisations. This opportunity can be made use by the government authorities and other practitioners to change their financial outlook and contribute towards the empowerment of these women from the grass root level. Originality/value: The studies related to financial literacy and financial inclusion are available in the Indian context, but the conceptualization of financial capability is still an under-researched area in India. Hence, this study is an attempt to explain the capability-wellbeing relationship from a financial point of view in the Indian context, and further establishes its connection with the individual's decision-making ability. To strengthen the research base, the study was conducted among the women in the community-based organization who belong to middle and low-income families. 2022, Emerald Publishing Limited. -
Driving Financial Inclusion: Technology as an Indicator of Financial Ecosystem Development During the COVID-19 Pandemic in India
This paper examines Indias level of digital access to financial services as compared to other Asian countries. The study also intends to analyse whether COVID-19 has influenced the usage trend of the selected digital payment indicators in India. Data has been collected from the World Bank Global Findex Database and RBI bulletins. Cross country descriptive analysis was used for studying Indias digital financial access against the other Asian countries. Event study methodology followed by trend analysis was employed to examine whether COVID-19 has impacted the digital payment indicators usage in India. The findings of the study indicated that Indias position in digital financial access needs to be improved. It was further identified that COVID-19 has increased the usage of digital modes for financial transactions in India. There has been a significant increase in the usage volume of mobile banking after the declaration of the pandemic. Govt. can frame its action plans to make use of the opportunity created through the pandemic to improve digital financial access in India. 2022 IGI Global. All rights reserved. -
The Women in CBOs: A Resource-based Approach for COVID-19 Management in Kerala
In the fight against COVID-19-the global health emergency-the community-based organisations were an effective tool for planning and implementation of relief measures. This article is an examination of the various ways in which the community-based organisations extended their support in the fight against the pandemic. 2022 Economic and Political Weekly. All rights reserved. -
Womens Financial Capability and Financial Wellbeing: A Study on Community Based Organisations for Sustainable Development
This book investigates the impact of financial capability and decision-making ability on the financial wellbeing of women associated with community based organisations (CBOs). In light of the evolving socio-economic landscape in South Asia and the growing gender disparity in poverty, there is an urgent need to address these issues at the grassroots level to achieve sustainable development. CBOs play a crucial role by providing a platform for women to discuss shared challenges, develop potential solutions and create livelihood opportunities. Drawing on data from Asia's largest women's community network, this book examines how Kudumbashree, as a successful model, can serve as a guiding framework for other community networks across South Asia. It also investigates how demographic factors such as age, marital status, education, income and family size influence women's financial capability. Furthermore, this book delves into the financial wellbeing of women and explores how addressing their needs can contribute to the attainment of the Sustainable Development Goals (SDGs). By examining global initiatives aimed at empowering women economically, this book offers valuable insights for policymakers, financial social workers, scholars and organisations dedicated to advancing financial wellbeing for women and promoting sustainable development. 2026 V. K. Parvathy and Jyothi Kumar.