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Uzzal Kumar Acharjee

Researcher at Jagannath University

Publications -  26
Citations -  167

Uzzal Kumar Acharjee is an academic researcher from Jagannath University. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 3, co-authored 18 publications receiving 34 citations. Previous affiliations of Uzzal Kumar Acharjee include University of Dhaka.

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Journal ArticleDOI

Blockchain-SDN based Energy-Aware and Distributed Secure Architecture for IoTs in Smart Cities

TL;DR: The authors present a distributed and decentralized blockchain-software-defined networking (SDN)-based energy-aware architecture for IoT in smart cities that provides higher throughput, lower response time, and lower gas consumption than existing works for smart cities.
Proceedings ArticleDOI

Cyberbullying Detection on Social Networks Using Machine Learning Approaches

TL;DR: In this article, the authors designed and developed an effective technique to detect online abusive and bullying messages by merging natural language processing and machine learning, using bag-of-words and term frequency-inverse text frequency (TFIDF).
Book ChapterDOI

An SDN Based Distributed IoT Network with NFV Implementation for Smart Cities

TL;DR: The authors have proposed an SDN based distributed IoT network with NFV implementation for smart cities to improve load balancing, scalability, availability, integrity, and security of the whole network.
Journal ArticleDOI

An efficient hybrid system for anomaly detection in social networks

TL;DR: In this article, a hybrid anomaly detection method named DT-SVMNB was developed that cascades several machine learning algorithms including decision tree (C5.0), Support Vector Machine (SVM) and Naive Bayesian classifier (NBC) for classifying normal and abnormal users in social networks.
Journal ArticleDOI

Deep viewing for the identification of Covid-19 infection status from chest X-Ray image using CNN based architecture

TL;DR: In this article , a CNN based deep learning system was proposed to diagnose Covid-19 from chest X-ray images, which is a critical task for human being and it could be overlooked as both the disease have almost similar pixel features on X-Ray.