VADIVUKKARASI S

@atce.in

PROFESSOR IN DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING
ANNAI TERESA TERESA COLLEGE OF ENGINEERING, THIRUNAVALUR

VADIVUKKARASI S


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https://researchid.co/vadivu2024

EDUCATION

B.E. ELECTRONICS & COMMUNICATION ENGINEERING
M.E. APPLIED ELECTRONICS
Ph.D ELECTRONICS & INSTRUMENTATION ENGINEERING / COGNITIVE RADIO

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Artificial Intelligence, Decision Sciences, Computer Networks and Communications
3

Scopus Publications

3

Scholar Citations

1

Scholar h-index

Scopus Publications

  • Experimental Evaluation of Artificial Intelligence Enabled Hate Speech Recognition over Social Network Platform using Enhanced Learning Approach
    S.Vadivukkarasi, Sameer Sharma, Kotteeswaran R, Ipsita Das, R.Krishnamoorthy, R.Thiagarajan
    Proceedings 2024 4th International Conference on Soft Computing for Security Applications Icscsa 2024, 2024
    In recent years, social network platforms such as Twitter, Facebook, and Reddit have become central to digital communication. While these platforms provide a space for individuals to share ideas and opinions, they also serve as a breeding ground for hate speech (HS). HS, characterized by discriminatory and offensive language targeting individuals or groups based on characteristics such as race, ethnicity, religion, or gender, has become a critical issue, particularly as it spreads rapidly through online platforms. This paper presents an Enhanced Learning Approach (ELA) that integrates a Hybrid CNN-GRU Model with Attention Mechanism to detect HS in user-generated content. By leveraging the strengths of CNN in feature extraction and GRU in handling sequential data, combined with an Attention Mechanism, the proposed model significantly improves detection accuracy. The dataset was collected from popular platforms like Twitter, Reddit, and Facebook and was processed using advanced text preprocessing techniques. The proposed model achieved a remarkable accuracy of 97.54%, significantly outperforming traditional and deep learning (DL) models. The effectiveness of this approach was evaluated using various metrics such as accuracy, precision, recall, F1-score, and AUC, demonstrating superior performance in HS detection. This study offers a promising solution for real-time and scalable HS recognition across diverse social network platforms..
  • A novel hybrid learning based Ada Boost (HLBAB) classifier for channel state estimation in cognitive networks
    S. Vadivukkarasi, S. Santhi
    International Journal of Dynamics and Control, 2021
  • A novel adaptive fuzzy-based sliding mode control for channel state estimation in cognitive radio for reduction of interference
    S. Vadivukkarasi, S. Santhi
    International Journal of Networking and Virtual Organisations, 2020
    Research in spectrum availability and its effective utilisation is becoming an epicentre of research in recent times with the increasing scarcity of radio spectrum. An effective solution is in the form of cognitive radios (CRs) which are quite intelligent to effectively utilise the scarcely available spectrum in an efficient and economic manner. Apart from being intelligent, they represent reconfigurable wireless communication systems, which are self-aware of their environment and learn to adapt it for dynamic changes. They are characteristic of efficient spectrum utilisation. This research paper defines the objective of determining the channel state information through sliding model control-based intelligent adaptive fuzzy algorithm. The CR has ability to operate in a particular radio configuration based on device status and environmental aspects including interference noise. The proposed adaptive fuzzy SMC-based channel state estimation has been compared against conventional and recent techniques and outputs established in terms of bit error rate and mean squared error. The proposed sliding rule method is quite an ideal choice for the proposed scenario characterised by dynamically changing input conditions to the sensing components of the CR network.

RECENT SCHOLAR PUBLICATIONS

  • Experimental Evaluation of Artificial Intelligence Enabled Hate Speech Recognition over Social Network Platform using Enhanced Learning Approach
    S Vadivukkarasi, S Sharma, I Das, R Krishnamoorthy, R Thiagarajan
    2024 4th International Conference on Soft Computing for Security … , 2024
    2024
  • A novel hybrid learning based Ada Boost (HLBAB) classifier for channel state estimation in cognitive networks: S. Vadivukkarasi, S. Santhi
    S Vadivukkarasi, S Santhi
    International Journal of Dynamics and Control 9 (1), 299-307 , 2021
    2021
    Citations: 3
  • A Meta Heuristic Inverse Ant Colony Optimization Based ADA Boost Classifier (Io-HLBAB) For Cognitive Networks To Aid In Channel State Estimation
    DSS S.Vadivukkarasi
    International Journal of Advanced Science and Technology 29 (5), 10240-10255 , 2020
    2020
  • An optimal spectrum allocation in Cognitive Radio Networks using Ant Colony Optimization model
    DSS S.Vadivukkarasi
    International Conference on Automation Science and Engineering(ICASE-20), 57-60 , 2020
    2020
  • A novel adaptive fuzzy-based sliding mode control for channel state estimation in cognitive radio for reduction of interference
    S Vadivukkarasi, S Santhi
    International Journal of Networking and Virtual Organisations 23 (4), 358-372 , 2020
    2020

MOST CITED SCHOLAR PUBLICATIONS

  • A novel hybrid learning based Ada Boost (HLBAB) classifier for channel state estimation in cognitive networks: S. Vadivukkarasi, S. Santhi
    S Vadivukkarasi, S Santhi
    International Journal of Dynamics and Control 9 (1), 299-307 , 2021
    2021
    Citations: 3
  • Experimental Evaluation of Artificial Intelligence Enabled Hate Speech Recognition over Social Network Platform using Enhanced Learning Approach
    S Vadivukkarasi, S Sharma, I Das, R Krishnamoorthy, R Thiagarajan
    2024 4th International Conference on Soft Computing for Security … , 2024
    2024
  • A Meta Heuristic Inverse Ant Colony Optimization Based ADA Boost Classifier (Io-HLBAB) For Cognitive Networks To Aid In Channel State Estimation
    DSS S.Vadivukkarasi
    International Journal of Advanced Science and Technology 29 (5), 10240-10255 , 2020
    2020
  • An optimal spectrum allocation in Cognitive Radio Networks using Ant Colony Optimization model
    DSS S.Vadivukkarasi
    International Conference on Automation Science and Engineering(ICASE-20), 57-60 , 2020
    2020
  • A novel adaptive fuzzy-based sliding mode control for channel state estimation in cognitive radio for reduction of interference
    S Vadivukkarasi, S Santhi
    International Journal of Networking and Virtual Organisations 23 (4), 358-372 , 2020
    2020