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Implementation of Scalar Control Technique in SVPWM Switched Three–Level Inverter Fed Induction Motor Using DSP Controller Vinoth Kumar; S. Suresh Kumar; Kishore Reddy
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 1, No 2: December 2011
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (365.967 KB)

Abstract

The main objective of the paper is to control the speed of an induction machine with scalar control technique. The scalar control technique (V/F) is used because of simplicity of control algorithm implementation and the response is better and accurate with closed loop slip compensation. An IGBT based three level diode clamped inverter (DCI) topology has been used instead of conventional two level inverter in order to reduce the harmonic content and to increase the device capability to handle the double the voltage of its rating.DOI: http://dx.doi.org/10.11591/ijpeds.v1i2.98
Applying K-Means Clustering to Group Jobs Based on Location and Experience Level: Analysis of the Job Recommendation Kumar, Vinoth; S, Priya
International Journal for Applied Information Management Vol. 4 No. 3 (2024): Regular Issue: September 2024
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijaim.v4i3.89

Abstract

Labor market analysis plays a crucial role in helping job seekers identify employment opportunities that align with their qualifications, location, and experience level. This study uses the K-Means clustering algorithm to group jobs based on these critical factors. By analyzing job market data, the research identifies the most sought-after skills across various industries and highlights the geographic and experience-level disparities in job availability. Key findings include the high demand for foundational skills such as customer service, sales, and production planning, as well as more specialized skills like Medical Research in certain sectors. The study provides actionable insights for job seekers and policymakers, suggesting that targeted skill development and training programs are essential for improving job match quality. However, the study also acknowledges its limitations, such as the lack of consideration for broader economic and social factors that influence labor market trends. Future research is recommended to address these gaps, using more comprehensive datasets and advanced analytical techniques.
Harnessing Sentiment Analysis with VADER for Gaming Insights: Analyzing User Reviews of Call of Duty Mobile through Data Mining Batumalay, Malathy; S, Priya; Kumar, Vinoth
International Journal Research on Metaverse Vol. 2 No. 2 (2025): Regular Issue June 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijrm.v2i2.27

Abstract

This study investigates the application of sentiment analysis to understand user feedback for Call of Duty Mobile, a highly popular mobile game, by analyzing 50,000 reviews sourced from the Google Play Store. The research aimed to extract actionable insights from user sentiments, which could guide future game development and improvement. To achieve this, the sentiment of each review was analyzed using VADER (Valence Aware Dictionary and sEntiment Reasoner), a robust tool for classifying sentiment in textual data. The study categorizes reviews into three sentiment groups—positive, negative, and neutral—to identify and analyze prevailing user emotions. The findings revealed that the majority of reviews were positive, with users primarily praising the gameplay, graphics, and overall mobile experience. These aspects were considered crucial in driving user satisfaction and contributed to a majority of the positive feedback. Conversely, negative reviews were often focused on issues such as network connectivity problems, long loading times, and performance errors, indicating areas where users experienced frustration. These results highlight the importance of technical performance and network stability as key factors influencing player satisfaction. The study also delved deeper into keyword analysis to uncover common themes in the reviews, such as in-app purchases and concerns related to technical performance, which were frequently mentioned by users in both positive and negative feedback. These insights provide developers with a clearer understanding of what players value most in the game and where improvements are necessary. The study concludes that sentiment analysis can serve as a powerful tool for understanding user feedback, offering developers a data-driven approach to enhance game features and address user concerns. Moving forward, future research could benefit from the application of additional machine learning models to refine sentiment classification accuracy, as well as the integration of cross-platform reviews to gain a more comprehensive understanding of player sentiment across different user groups and devices. Such approaches would provide a richer, more nuanced view of user experiences, enabling game developers to create even more engaging and satisfying gaming experiences.