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A hybrid level shifted carrier-based PWM technique for modular multilevel converters
This paper presents a hybrid level shifted carrier-based pulse width modulation (HLSC-PWM) technique for modular multilevel converters (MMCs). The concept of the proposed HLSC-PWM method is developed by combining the principles of phase disposition PWM (PD-PWM), phase opposition disposition PWM (POD-PWM), and alternate phase opposition disposition PWM (APOD-PWM) methods. The main aim of the proposed HLSC-PWM method is to generate an output voltage with half-wave and quarter-wave symmetries. The generated symmetrical PWM output voltage based on the proposed HLSC-PWM method provides less total harmonic distortion (THD) and enhances the DC-Link voltage utilization (DCLVU). A generalized mathematical model is formulated to develop a single HLSC for MMC with an N number of submodules (SMs) per arm. Theoretical analysis of DCLVU for the proposed method is described. The functionality and performance of the HLSC-PWM method are carried out on a three-phase five-level MMC in MATLAB/Simulink. A hardware prototype of a single-phase five-level MMC is designed for experimental validation. The proposed HLSC-PWM method is implemented on an Altera/Cyclone I series (EP1C12Q240C8N) field-programmable gate array (FPGA), simulation and experimental results are presented. 2021 The Authors. IET Power Electronics published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology -
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Non-linear convection in chemically reacting fluid with an induced magnetic field across a vertical porous plate in the presence of heat source/sink
An investigation is carried out to observe the impacts of non-linear convection and induced magnetic field in the flow of viscous fluid over a porous plate under the influence of chemical reaction and heat source/sink. The plate is subjected to a regular free stream velocity as well as a suction velocity. The subjected non-linear problem is non-dimensionalized and analytic solutions are presented via perturbation method. The graphs are plotted to analyze the effect of relevant parameters on velocity, induced magnetic field, heat and mass transfer fields as well as friction factor, current density, Nusselt and Sherwood numbers. It is established that nonlinear convection aspect is destructive for thermal field and its layer thickness. The magnetic field effect enhances the thermal field while it reduces the velocity field. Also, the nonlinear effect subsides heat transfer rate significantly. 2018 Trans Tech Publications, Switzerland. -
FOPID controller tuning: A comparative study of optimization techniques for an automatic voltage regulator
This study evaluated a fractional order proportional-integral-derivative (FOPID) controller optimization with a fractional filter for an automated voltage regulator (AVR) system. For the suggested controller, a variety of different parameters can be changed. For the purpose of creating the optimum PID controller for an automated voltage regulator system, comparative analysis using multiple optimization methodologies is carried out. The Salp Swarm Algorithm (SSA), Ant Lion Optimization (ALO), and Particle Swarm Optimization algorithm (PSO) are the techniques that are being examined in this study. The settling time, rising time, and overshoot performance indices is being used. The transient responsiveness of the AVR system was increased by each of the recommended optimization techniques in a different way, and early results were optimistic. The comparison with the most ideally tuned FOPID controllers for the AVR system also serves to support the superiority of the suggested controller. 2023 Author(s). -
IRIS Data Classification using Genetic Algorithm Tuned Random Forest Classification
Optimising hyper-parameters in Random Forest is a time-consuming undertaking for several academics as well as professionals. To acquire greater performance hyper-parameters, specialists should explicitly customize a series of hyper-parameter settings. The best outcomes from this manual setting are then modelled and implemented in a random forest algorithm. Several datasets, on the other side, need various prototypes or hyper-parameter combinations, which may be time-consuming. To solve this, we offered various machine learning models and classifiers for correctly optimising hyper-parameters. Both genetic algorithm-based random forest and randomised CV random forest were assessed on performance measures such as sensitivity, accuracy, specificity, and F1-score. Finally, when compared to randomised CV random forest, our suggested model genetic algorithm-based random forest delivers more incredible accuracy. 2022 IEEE. -
LegalMind System and the LLM-based Legal Judgment Query System
LegalMind-GPT represents a notable advancement in legal technology, specifically tailored for the finance sector. This research paper introduces LegalMind-GPT, a system that integrates Large Language Models (LLMs) to develop a Legal Judgment Query System for financial legal contexts. The study focuses on the application of LLMs, particularly LLAMA-2, Claude AI, and FLAN-T5-Base, for interpreting and analysing complex legal documents in finance. The aim is to evaluate the system's effectiveness in providing accurate legal judgments and insights. The comparative analysis of these LLMs shows that LegalMind-GPT, powered by these models, significantly improves the accuracy and efficiency of legal analysis in the finance domain. 2024 IEEE. -
A comparative study on e-waste management systems in developed and developing countries: Legislative compliances and initiatives
E-waste is an ongoing issue that still lacks a suitable solution, particularly in developing nations. The environment and human health have suffered dramatically as a result of poor recycling practices of waste of electrical and electronic equipment (WEEE), transboundary movement, improper management of e-waste, the lack of environmentally sound management (ESM) programs, and the ineffective EPR (extended producer responsibility) schemes. Although developed nations have implemented efficient legislative frameworks and regulations, emerging nations suffer due to their plans. E-waste management systems differ in developed and developing countries; thus, this study evaluates the differences between the management systems and outlines the areas where the developing nations lack effective e-waste management and the advantages developed countries enjoy. Therefore, the current study results are crucial for comprehending the severe hazard posed by improper management of e-waste and the viability of future research into creating strategies to address these problems of developing nations. 2023, IGI Global. -
Anti-inflammatory activity of Sabicea brevipes Wernharm (Rubiaceae)
Over the years, medicinal plants have been employed in the treatment of inflammation and related ailments. This study evaluated the anti-inflammatory potential of the aerial parts of S. brevipes. The extracts and fractions were further evaluated for anti-inflammatory activity in carrageenan-induced rat model at varying doses (200 and 400 mg/kg doses, orally) for 5 h of treatment. The result of the phytochemical screening showed the presence of alkaloids, terpenoids, glycosides, flavonoids and tannins in the aerial parts of the plant. The in vivo anti-inflammatory study exhibited inhibition of 42% and 44%, 47% and 36%, 33% and 31%, and 43% and 42% for methanol extract n-hexane fraction, ethyl acetate fraction, and methanol fraction, at 200 and 400 mg/kg doses, respectively. The positive control (diclofenac sodium) showed an inhibition value of 51% at 5 mg/kg dose. Finally, it is concluded that S. brevipes possesses anti-inflammatory potential which validates the enthnomedicinal claim of the plant. 2022. Attah EI et al. All Rights Reserved. -
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Research article toxicological evaluation of ethanolic leaf and fruit extracts of phaseolus vulgaris l. Treated with wastewater in danio rerio hamilton (zebrafish)
Background and Objective: The cultivation of Vegetables in the world is facing a shortage of water so that the farmers are forced to use sewage wastewater for cultivation in underdeveloped countries. Therefore, the present study was an attempt to examine the toxicity level of accumulated heavy metals in the vegetables irrigated with sewage water and treated sewage water. The concentration-dependent changes in toxicity of ethanolic leaf and fruit extracts of Phaseolus vulgaris treated with wastewater in Zebrafish were analysed in this study. Materials and Methods: For the experiment, finely ground powders of leaves and fruits of Phaseolus vulgaris were extracted with ethanol. Using different concentrations of these extracts, a toxicity test was done with Danio rerio as per the OECD guidelines 203. Results: Using AAS, heavy metals like lead and manganese were found in higher concentrations in untreated wastewater than in distilled water and treated wastewater. The results indicated that ethanolic leaf extracts of treated wastewater irrigated Phaseolus vulgaris does not induce toxicity when used at a dose below 400 mg LG1. Leaf extracts of Phaseolus vulgaris grown with wastewater showed the lowest and highest mortality at 100 and 400 mg LG1, respectively, when compared to other plant extracts. Histopathological variations were also observed in the fishes exposed to the lethal concentrations of plant extracts. Statistical evaluation of the correlation between concentration and mortality percentage was carried out using SPSS. Conclusion: The present study revealed that the leaf and fruit extracts of Phaseolus vulgaris grown with untreated wastewater were more toxic to Danio rerio than other extracts used in the experiment. 2022 Aleesa Augustine and Jobi Xavier. -
Public debt - economic growth nexus in emerging and developing economies: Exploring nonlinearity
This paper explores the nonlinear dynamics between public debt and economic growth by estimating the threshold level of debt for thirty-nine emerging and developing economies. The study found a considerable variation amongst the debt thresholds in these countries, ranging between 24 and 132 per cent. We observed the evidence for an inverted U-shape relationship either partially or fully only in six countries. On the contrary, our study found that expanding debt even beyond the threshold promotes economic growth in some countries, while debt hinders growth even at low debt levels in a few countries. 2022 Elsevier Inc. -
Leveraging Big Data Analytics and Hadoop in Developing India's Healthcare Services
International Journal of Computer Applications, Vol-89 (16), pp. 44-50. ISSN-0975-8887 -
Insights into the performance of farmer producer companies: An exploratory analysis in kerala, india
India faces challenges in farmers well-being due to small land holdings and the absence of an organized agricultural market system, prompting the introduc-tion of initiatives such as the promotion of Farmer Producer Organizations (FPOs) to fortify the agricultural market. However, ambiguity remains over the functioning of such initiatives. This study aims to tackle the aforementioned issue by collecting and analyzing data on the operations of 400 registered Farmer Producer Companies (FPCs) in the state of Kerala, India. The analysis focuses on key indicators such as the age of the FPC, paid-up capital, and activity status (whether active or struck-off). A primary survey has also been conducted, both telephonic and face-to-face inter-views, based on convenience, using a semi-structured questionnaire. Both farmers and representatives from FPCs are interviewed. The issues discussed are marketing assistance, input sales, type of services offered, managerial capacities, etc. The study finds that not all registered FPCs effectively improve the welfare of farmers. The most common service FPCs provide is marketing, which helps increase product sales through collective bargaining power and access to higher-paying markets. FPCs that engage in contract farming, sell through supermarkets, or explore inter-state or inter-national markets are more successful in increasing farmers revenues than those that only use traditional market chains. However, it is important to note that FPCs face several challenges, including a lack of infrastructure and support, limited access to credit, and a lack of skilled and trained staff. These essential factors must be addressed for FPCs to achieve their full potential. The Author(s). -
Quantifying the Impact: Assessing FPO Penetration in Indian Agriculture Through the Lens of the 2019 Situation Assessment Survey
In India, Farmer Producer Organisations (FPOs) are garnering significant attention as a potential solution to address the challenges faced by small-scale farmers. This research paper focuses on the engagement of farmers with more than 33,000 registered FPOs in India. It analyzes data from the Situation Assessment of Agricultural Households 2019 and the FPO dataset by the Tata Cornell Institute. The paper sheds light on how farmers are involved with FPOs to meet their agricultural needs, such as acquiring inputs, managing the sale of farm produce, and receiving technical support for farming activities. Despite the anticipated benefits for farmers through their engagement with FPOs, the actual achievements have not met initial expectations. The impact of FPOs on farmers remains minimal, with fewer than 1% of farmers in India utilizing FPO services. This emphasizes the crucial need for reassessment and targeted interventions to enhance the effectiveness of these organizations. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
The industry use cases for the Digital Twin idea
Digital Twin Technology has taken the place in top 10 strategic technology trends in 2017 termed by Gartner Inc. Digital Twin concept brings out the virtual depiction or the digital representation of the real world equipment, device or system whereas the real world and the virtual world gets the highest synchronization. The digital representation of the complete life cycle of a product from its design phase to the maintenance phase will give the prophetic analysis of the problems to the business. This greatest advantage of foreseeing problems in the development of a device will give early warnings, foil downtime, cultivate novel prospects and inventing enhanced devices or gadgets for the later use at the lesser expense by means of digital representations. Indeed, these will devise a larger influence on conveying superior consumer feeling also in the enterprise. The emerging trends such as Artificial Intelligence, Machine Learning, Deep Learning, Internet of Things and Big Data used in Industry 4.0 play a vital role in Digital Twin and they are mostly adopted in the world of manufacturing, Industrial Internet of Things, and automobile business world. The penetration, wide coverage and the advancement of the Internet of Things in real-world have elevated the power of Digital Twins more economical and reachable for the world of various businesses. 1. Manufacturing: Digital Twin has brought out the change in the existing manner of the manufacturing segment. Digital Twins have a substantial influence on the design of products and their manufacturing and maintenance. Because of its influence the manufacturing more competent and augmented while dropping throughput times. 2. Industrial IoT: Integrating digital twin with industrial firms will facilitate the activities such as monitoring, tracking and controlling industrial systems in digital means. We can potentially experience the power of digital twin since it captures environmental data such as locality, settings of the devices, financial frameworks, etc., other than the operational data, which benefits in foreseeing the forthcoming operations and incongruities. 3. Healthcare: Since the healthcare sector demands higher accuracy in diagnosis and treatment, with the important data from IoT, digital twins can play a vital role by reducing the expense for the patient, precautionary alerts to avoid health deterioration and giving tailored health support system. This will be great support especially in developing countries like India. 4. Smart cities: Digital Twin coupled with IoT data can augment the efficient planning of the smart city and execution of its building by supplementing financial progress, effectual administration of resources, lessening of environmental impression and escalate the complete worth of a resident's life. The digital twin prototypical can aid city organizers and legislators in the smart city planning by retrieving the visions from numerous sensor networks and smart systems. The information received from the digital twins supports them in reaching well-versed choices concerning the future as well. 5. Automobile: Automobile industry can get voluminous benefits out of Digital Twins for producing the simulated framework of a coupled vehicle. It retrieves the behavioral and functional information of the vehicle and services in examining the inclusive performance efficiency of the vehicle as well as the features connected along with it. Digital Twin also supports in supplying a justly enhance support and service for the consumers. 6. Retail: Alluring client satisfaction is a fundamental factor in the merchandising world. Digital twin employment can play a key role in supplementing the retail customer experience by forming virtual twins for customers and modeling fashions for them on it. Digital Twins also supports enhanced planning of stock maintenance, safekeeping procedures, and human resource administration in an augmented means. 2020 Elsevier Inc. -
Road Accident Prediction using Machine Learning Approaches
Road accidents create a significant number of serious injuries reported per year and are a chief concern of the world, mostly in underdeveloped countries. Many people have lost their near and dear ones due to these road accidents. Hence a system that can potentially save lives is required. The system detects essential contributing elements for an accident or creates a link among accidents and various factors for the occurrence of accidents. This research proposes an Accident Prediction system that can help to analyze the potential safety issues and predict whether an accident will occur or not. A comparative study of various Machine Learning Algorithms was conducted to check which model can help predict accidents more accurately. The dataset used for this paper is the government record accidents that occurred in a district in India. Logistic Regression, Random Forest, Decision Tree, K-Nearest Neighbor, XGBoost, and Support Vector Machine are among the Machine Learning models used in this paper to predict accidents. The Random Forest algorithm gave the highest accuracy of 80.78% when the accuracies of the Machine Learning models were compared. 2022 IEEE. -
Performance evaluation of parallel genetic algorithm for brain MRI segmentation in hadoop and spark /
Indian Journal of Science and Technology, Vol.8, Issue 48, pp.1-7, ISSN: 0974-6846 (Print), 0974-5645 (Online). -
Tribal population and skill development programme: A study of Idukki district in Kerala
India is a country which has people of different cultures, religions, traditions, languages, castes and creed. In the democratic country of India, tribal people are one of the groups keeping their own culture and tradition that needs to be emphasized. The significant characteristics of the tribes are primitive traits, geographic isolation, distinct culture, shyness of contact and economically backwardness. By and large, tribes are living in different geo-climatic and ecological conditions covering from forest and plains to hills and the area lack accessibility. Though they are considered as the marginalized or most vulnerable population in India, their way of life and tradition, culture is to be preserved and they should be brought into the mainstream of society. In order to uplift the tribal community to be a part of the mainstream of society, the development of their skills is very essential. Skill development is the driving force for the transformation and development of an economy. The Government of India has taken several steps and launched many skill development schemes along with other welfare schemes for the betterment of the mainstream as well as the tribal communities in India. -
Tribal population and skill development programme : A study of idukki district in kerala
India is a country which has people of different cultures, religions, traditions, newlinelanguages, castes and creed. In the democratic country of India, tribal people are one of the groups keeping their own culture and tradition that needs to be emphasized. The significant characteristics of the tribes are primitive traits, geographic isolation, distinct culture, shyness of contact and economically backwardness. By and large, tribes are living in different geo-climatic and ecological conditions covering from forest and plains to hills and the area lack accessibility. Though they are considered as the marginalized or most vulnerable population in India, their way of life and tradition, culture is to be preserved and they should be brought into the mainstream of society. In order to uplift the tribal community to be a part of the mainstream of society, the development of their skills is very essential. Skill development is the driving force for the transformation and development of an economy. The Government of India has taken several steps and launched many skill development newlineschemes along with other welfare schemes for the betterment of the mainstream as well as the tribal communities in India. .Keeping this objective in mind, in the 12thfive-year plan, the government of India gave the highest priority to skill development. The National Policy on Skill Development was announced by the cabinet of India (2009) to make a workforce with the strong skills knowledge and accepted qualification framework which will help to enhance the competitiveness of India and to get a decent job in the global market(IBEF, 2013). But many factors prevent the scheduled tribes from becoming beneficiaries of various skill development programs provided by the government. In the above context, this study is an attempt to know the nature and effectiveness of various skill development programs offered to the tribal community. -
Theoretical framework of the relationship between emotional intelligence and effective leadership to ensure sustainability
There is little argument about the need for sustainability. Organizations around the world have now understood their role in contributing to the broader goals of, environmental and social sustainability. While financial sustainability of the organization has always been the key purpose. In order to identify, implement and promote sustainable practices, the leadership support is critical. This not only includes the current set of leaders but the future leaders of the organization as well. Thus, there arises a need to identify the key competencies and skills that contribute to effective leadership and to ensure that the training of future leaders focuses on the same. The current paper reviews theories in the area of Leadership and their evolution. Based on the proposition by key theorists in the area of leadership, the proposed theoretical framework links the dimensions of effective leadership to the dimensions of emotional intelligence. The purpose of the study was to establish a theoretical relationship between Emotional Intelligence, Effective leadership and sustainability. The proposed model is based on existing theories in the respective areas and the researchers hope that future research would work to provide empirical evidence for the same. This would ensure that the leadership pipeline is designed to promote the skills required to create and run a sustainable organization. 2020 IJSTR.