Results for 'Abhiram Pajjuri'

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  1.  32
    Speech Emotion Recognition Using Machine Learning.Abhiram Pajjuri - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (5):1-15.
    . Speech Emotion Recognition (SER) is an interdisciplinary field that leverages signal processing and machine learning techniques to identify and classify emotions conveyed through speech. In recent years, SER has gained significant attention due to its potential applications in human-computer interaction, healthcare, education, and customer service. Emotions such as happiness, anger, sadness, fear, surprise, and disgust can be inferred from various acoustic features including pitch, intensity, speech rate, and spectral characteristics. However, accurately recognizing emotions from speech is challenging due to (...)
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  2.  30
    Online Personalized Learning Remediation/Tutoring Tool: A Teacher Recommendation System.D. J. Abhiram - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (5):1-16.
    Online education will be paired by developing intelligent systems that can provide personalization to the learner. To that extent ,this paper is proposing the design for an Online Personalized Learning Remediation/Tutoring Tool to help learners find the most suitable teachers for certain topics. The tool relies on a dataset of teacher profiles, comprising the subjects taught, video links, ratings, and experience, so that using machine learning techniques, it could recommend top educators. Applying feature extraction using CountVectorizer and recommendation based on (...)
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  3.  34
    Design of Cybersecurity Smart Controller For Grid Connected Microgrid.Soma Abhiram - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (5):1-15.
    The research introduces to the design and implementation of the Cybersecurity Enabled Smart Controller for the grid connected microgrid which uses the combination of the Web technologies and the authentication mechanism which enables real time monitoring with help of the Dashboards built using Chart.js which is a framework of JavaScript. Due to the role and connection of the Microgrids with the critical infrastructure they are vulnerable to the cyber threats. This project leverages the use of HTML, CSS, JavaScript and MongoDB (...)
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