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Mrs. Sarika Nyaramneni

VNR Vignana Jyothi Institute of Engineering and Technology, Jayamukhi Institute of Technological Sciences, Vaagdevi College of Engineering

ORCID iD 0000-0002-4948-4507

About

Sarika Nyaramneni
Assistant Professor
VNR VJIET
Hyderabad -500090

Employment

  • VNR Vignana Jyothi Institute of Engineering and Technology Assistant Professor
    2015 - Present
  • Jayamukhi Institute of Technological Sciences Assistant Professor
    2010 - 2015

Education

  • Jayamukhi Institute of Technological Sciences M.Tech
    2008 - 2011
  • Vaagdevi College of Engineering B.Tech
    2004 - 2008

Projects & Funding

Projects & funding information is unavailable.

Publications (21)

  • Traffic Signal Coordination And Accident Detection
    2025 International Conference on Sustainability, Innovation & Technology (ICSIT) 2026
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  • Collision and Congestion Avoidance in Microscopic Traffic Modeling Using Cellular Automata
    2025 International Conference on Sustainability, Innovation & Technology (ICSIT) 2026
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  • SDN Traffic Prediction using Empirical Mode Decomposition
    Journal of Information Systems Engineering and Management 2025 DOI: 10.52783/jisem.v10i24s.3874
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  • XeroDrop: A system for secure document printing and delivery
    2025
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  • Decentralized DDoS Detection and Blocking System Using ML Models
    2nd International Conference on Computing and Data Science (ICCDS-2025) 2025
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  • Lane Merging Model Using Priority Based Queuing Theory and Cellular Automata
    International Conference on Computer Vision and Robotics 2025
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  • A Survey on Cryptography
    15th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2024 2024
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  • ANALYSIS OF V-D BASED FEATURES FOR DISTRACTED DRIVER MONITORING SYSTEM USING DEEP LEARNING
    Futuristic Trends in Artificial Intelligence 2024
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  • Patient Obligation Perceiving System Using Eye Gestures
    International Conference on Micro-Electronics and Telecommunication Engineering 2024
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  • Advanced Ensemble Machine Learning Models to Predict SDN Traffic
    Procedia Computer Science 2023 DOI: 10.1016/j.procs.2023.12.097
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