R
Rourab Paul
Researcher at Siksha O Anusandhan University
Publications - 51
Citations - 243
Rourab Paul is an academic researcher from Siksha O Anusandhan University. The author has contributed to research in topics: Field-programmable gate array & Encryption. The author has an hindex of 6, co-authored 43 publications receiving 155 citations. Previous affiliations of Rourab Paul include Indian Institute of Technology Kanpur & Information Technology University.
Papers
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Journal ArticleDOI
Common Readout Unit (CRU) - A new readout architecture for the ALICE experiment
TL;DR: An overview ofCRU architecture in ALICE is given, the different interfaces are discussed, along with the firmware design and implementation of CRU on the LHCb PCIe40 board.
Proceedings ArticleDOI
Outlier Detection in Sensor Data Using Machine Learning Techniques for IoT Framework and Wireless Sensor Networks: A Brief Study
TL;DR: In this work, some machine learning approaches have been discussed which have proved their mettle in outlier detection and their importance in Internet of Things framework and Wireless Sensor Networks.
Journal ArticleDOI
Fault Matters: Sensor data fusion for detection of faults using Dempster–Shafer theory of evidence in IoT-based applications
TL;DR: This work has adopted Dempster-Shafer Theory of Evidence which is a popular learning method to collate the information from sensors to come up with a decision regarding the faulty status of a sensor node to verify the validity of the proposed method.
Proceedings ArticleDOI
IoT Based Secure Smart City Architecture Using Blockchain
TL;DR: An IoT based smart city architecture which adopted the blockchain technology preserving all the cryptographic security issues is proposed and comparison of all security parameters with existing literature shows that the architecture is reasonably efficient in terms of security.
Posted Content
NIST Statistical Test Suite
TL;DR: The principal strategy of the NIST Statistical Test Suite is to judge statistical randomness property of random bit generating algorithms.