Browsing by Author "Bhalekar, D."

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    A deep learning approach to detect drowsy drivers in real time
    (Institute of Electrical and Electronics Engineers Inc., 2019) Pinto, A.; Bhasi, M.; Bhalekar, D.; Hegde, P.; Koolagudi, S.G.
    Fatigue and microsleep are the reasons behind many severe road accidents. These can be avoided if the symptoms of fatigue are detected on time. This paper describes a real-time system for monitoring driver vigilance. Driver drowsiness detection algorithms in the past have proven to work in controlled environments but have not been implemented on a wide scale as of yet. Algorithms in the past suggest calculating a scalar value known as Eye Aspect Ratio (EAR) and detect drowsiness by comparing its instantaneous value with a previously configured value. We propose a generalised approach using Convolution Neural Networks (CNN) in this paper. Our algorithm tracks the driver's eyes and feeds it into a pre-trained that predicts the state of the eye. Once the prediction is obtained, we would be able to detect if the driver is drowsy or not. The main components of our system include a camera, for real time image acquisition, a processor for running algorithms to process the acquired image and an alarm system to warn the driver when the symptoms are detected in order to avoid potential accidents. © 2019 IEEE.
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    Linux-like Loss Detection Techniques for ns-3 TCP
    (Institute of Electrical and Electronics Engineers Inc., 2019) Bakshi, S.; Sahoo, A.P.; Keerthana, P.; Bhalekar, D.; Tahiliani, M.P.
    Recent Acknowledgment (RACK) is a new loss detection technique for TCP proposed by Google and described in an Internet Draft in TCP Maintenance Working Group (tcpm) of IETF. It is the default loss detection technique in Linux kernel. RACK internally uses Forward Acknowledgement (FACK) and Duplicate Selective Acknowledgement (DSACK) loss detection techniques, and leverages the benefits of Tail Loss Probe (TLP). This paper describes the implementation and evaluation of FACK, DSACK and TLP loss detection techniques for TCP model in ns-3. The goal is to provision prerequisite loss detection techniques in ns-3 for implementing RACK. The implementation of FACK, DSACK and TLP in Linux is used as a reference for this work. Our implementation of these techniques in ns-3 is verified by evaluating their performance in respective scenarios and ensuring that they exhibit their key characteristics. © 2019 IEEE.