D John Aravindhar
Biographic Data
| ID | 7987940 |
|---|---|
| NAME | D John Aravindhar |
| GIVEN NAMES | D John |
| FAMILY NAME | Aravindhar |
| SIGNATURE | ARAVINDHAR D J |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Enhancing Online Teaching and Learning Through Machine Learning and Learning Analytics
Online learning environments are gaining popularity as an alternative to traditional learning environments during times of global pandemic. The traditional classroom setting has given way to online learning in recent educational developments. To employ it as a classifier in online education, the goal of this work is to construct a real-time face emotion detection system that recognizes and categorizes emotions of a human. It uses machine learning…
Detection and Mitigation of DDOS Attack in SDN Environment Using Hybrid CNN-LSTM
DDoS attacks, powered by botnets to flood network resources, pose a significant threat to traditional network setups. Software-Defined Networking (SDN) boosts network adaptability and programmability by separating the control and data planes. However, the centralized control in SDN can be a vulnerability, allowing attackers to exploit security flaws and launch DDoS attacks. These attacks overwhelm network controllers and switches, consuming bandw…
No prominent works on this page.
Enhancing Online Teaching and Learning Through Machine Learning and Learning Analytics
Online learning environments are gaining popularity as an alternative to traditional learning environments during times of global pandemic. The traditional classroom setting has given way to online learning in recent educational developments. To employ it as a classifier in online education, the goal of this work is to construct a real-time face emotion detection system that recognizes and categorizes emotions of a human. It uses machine learning…
Detection and Mitigation of DDOS Attack in SDN Environment Using Hybrid CNN-LSTM
DDoS attacks, powered by botnets to flood network resources, pose a significant threat to traditional network setups. Software-Defined Networking (SDN) boosts network adaptability and programmability by separating the control and data planes. However, the centralized control in SDN can be a vulnerability, allowing attackers to exploit security flaws and launch DDoS attacks. These attacks overwhelm network controllers and switches, consuming bandw…
Artificial Intelligence (2 works) · Computer Science (2 works) · Advanced Malware Detection Techniques (1 work) · Affective Computing (1 work) · Application layer DDoS attack (1 work) · Botnet (1 work) · Classifier (UML (1 work) · CLIPS (1 work) · Computer network (1 work) · Computer security (1 work)