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Recent advancements in technology and methodologies have significantly bettered the quality and effectiveness of systems in machine paraphrase, speech processing, healthcare, and wireless dispatches. This check examines innovative approaches, including deep knowledge models for paraphrase quality discovery, optimization fabrics for speech- centric processing, and queuing systems for managing case and staff satisfaction in healthcare. pivotal methodologies explored include intermittent neural networks for paraphrase quality estimation, common optimization ways for automatic speech recognition (ASR), and queuing proposition operations to anatomize staying times and service quality.These methodologies offer benefits analogous as
advanced real- time evaluation, robustness against crimes, and a comprehensive view of user satisfaction. still, challenges like resource intensity, performance complexity, and reliance on accurate data models are also mooted. also, the integration of virtual ranges in space- ground networks and line-alive resource operation in wireless dispatches highlights the severity of these systems to dynamic environments. This check emphasizes the significance of empirical evidence and user acceptance, furnishing perceptivity into the evolution of intelligent systems and their implicit to attack complex challenges across various fields. future disquisition directions are
suggested to explore limitations and expand the connection of these innovative approaches.
Keywords:
Machine Translation, Speech Processing, Healthcare, Queuing Theory, Deep Learning, User Satisfaction
Cite Article:
"A Survey On Queue Management Systems", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 1, page no.a186-a192, January-2025, Available :http://www.ijrti.org/papers/IJRTI2501027.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator