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24 articles for “real-world scenarios”
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Study of Finite State Machines as Language Recognizer
Abstract: Finite State Machines (FSMs) play a fundamental role in computer science and linguistics as language recognizers. This study presents an exploration of the principles and applications of FSMs as efficient tools for recognizing formal languages. The study delves into the theoretical foundations of FSMs and their practical implementation in various language recognition tasks. The fundamental ideas of FSMs, including as states, transitions, and input symbols, are introduced in this study. …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 18–24 Read article
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Antibiotics – Challenges in our Post-COVID Era
Abstract: Accidental discovery of the antibiotic properties of penicillin marked a watershed moment in healthcare, transforming the landscape of medicine and saving countless lives of injured and infected. Further research and awareness on the advantages of this “miracle drug” resulted in its bulk production in the 1940s, and played a crucial role in saving lives of thousands during World War II. Subsequent discoveries especially broad-spectrum antibiotics paved the way for further …
Published in International Journal of Antibiotics · Vol. 1, Issue 2, 2024 · pp. 1–5 Read article
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Ecomotion Cityglide Commuter E-Bike
Abstract: The transition from conventional gasoline motorcycles to electric bikes represents a pivotal step in addressing the increasing demand for sustainable transportation solutions in urban environments. This paper meticulously explores the multifaceted aspects of this transition, focusing on the technological advancements, design innovations, and societal implications associated with the adoption of electric bikes. Electric bikes, powered by Brushless DC (BLDC) motors and rechargeable battery packs, offer a suite of benefits over …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 43–49 Read article
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The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments
Abstract: The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 9–24 Read article