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Rajest, S. Suman
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Neuroscience

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Journal : IJHCS

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A Review on Using Machine Learning to Conduct Facial Analysis in Real Time for Real-Time Profiling T, Shynu; Rajest, S. Suman; Regin, R.; R, Steffi.
International Journal on Human-Computing Studies Vol. 5 No. 2 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i2.4032

Abstract

The micro facial expressions and eye blinks of the liar are analyzed by the lie detection system, which makes use of the Facial Landmark Detection System that is included in the OpenCV Tool Kit. While the suspect responds to a series of questions, the system will observe the motions of the facial muscles and the rate at which their eyes blink. The Eye-Opening Ratio is used to determine the eye-opening in each frame. An approach that makes use of human behaviors to identify deception has been proposed here. In order to assess whether a candidate is being dishonest during an interrogation and come up with a conclusion about them, the system will do face detection and an eye blink calculation. During an interrogation session, the interrogator can use this result to assist them in doing an analysis of the blink threshold value and locating the lie. In the future, developments could include thermal monitoring, which would involve collecting video of the suspect while they are answering questions during interrogation. This video would then be used in conjunction with face detection and eye blink rate to provide a more in-depth analysis of the suspect's dishonest behavior.
Utilizing Deep Learning Classification Method for the Detection of Potholes T, Shynu; Rajest, S. Suman; Regin, R.; Raj, Steffi
International Journal on Human-Computing Studies Vol. 6 No. 1 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i1.5230

Abstract

The existence of potholes on the roadways is one of the primary factors that contribute to the occurrence of crashes involving automobiles. In order to find a solution to this issue, a number of different strategies have been explored. Among these methods are the employment of vibration-based sensors, manual reporting to authorities, and laser imaging for the reconstruction of three-dimensional space. The high cost of installation, potential danger during detection, and lack of night vision are just a few of the drawbacks of some of these systems. Researching the feasibility and accuracy of using thermal imaging to the problem of pothole detection is, hence, the goal of this effort. We have collected enough data with pictures of potholes in different weather conditions and used augmentation techniques to it. After this, a novel technique to this problem area that utilises thermal imaging the convolutional neural networks (CNN) method of deep learning was implemented. Also included is a comparison of the researcher's own convolutional neural model to pretrained models. Positive outcomes will follow from this investigation, and it will aid in directing future studies into this novel use of thermal imaging for pothole detection.
A Dual-Protocol File Transfer Application: Balancing Speed and Reliability in Peer-to-Peer Networks Rajasekaran, G; Rajest, S. Suman; Regin , R; Sameer Ali , M. Mohamed; Kumar, S. Ramesh
International Journal on Human-Computing Studies Vol. 7 No. 1 (2025): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v7i1.5467

Abstract

In today’s digital era, secure and efficient file transfer mechanisms are crucial as digital communication becomes increasingly prevalent. This paper presents a File Transfer Application that enables collaborative file sharing among multiple users over a network. The application uses a client-server architecture, integrating UDP for fast communication and TCP for secure and reliable file transfers. The server manages client registrations, maintains a dynamic table of active users, and broadcasts file availability updates, fostering real-time collaboration. Clients register with the server by sending their details and receive a list of online peers. Users can share files or request them directly from others, promoting peer-to-peer interaction. A simple command-line interface allows easy navigation, making the application accessible to users with varying technical backgrounds. File transfers utilize TCP to ensure data integrity, while UDP handles lightweight communication, minimizing latency. The system allows clients to disconnect gracefully, updating the server and other users accordingly. Tested in various environments, including simulations on a single machine, the application demonstrates its robustness in handling concurrent users effectively. This paper not only highlights key networking and socket programming concepts but also lays the groundwork for future enhancements like encryption and authentication, ensuring secure, scalable digital file sharing.
Co-Authors Kumar, S. Ramesh R, Steffi. Raj, Steffi Rajasekaran, G Regin , R Regin, R. Sameer Ali , M. Mohamed T, Shynu