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Thompson Stephan

Researcher at Guru Gobind Singh Indraprastha University

Publications -  47
Citations -  722

Thompson Stephan is an academic researcher from Guru Gobind Singh Indraprastha University. The author has contributed to research in topics: Computer science & Routing protocol. The author has an hindex of 7, co-authored 29 publications receiving 164 citations. Previous affiliations of Thompson Stephan include Pondicherry University & Easwari Engineering College.

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I-AREOR: An energy-balanced clustering protocol for implementing green IoT in smart cities

TL;DR: An Improved-Adaptive Ranking based Energy-efficient Opportunistic Routing protocol (I-AREOR) is proposed, based on regional density, relative distance, and residual energy of the sensor nodes, for improving sensor based communication in future smart cities.
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FAJIT: a fuzzy-based data aggregation technique for energy efficiency in wireless sensor network

TL;DR: An algorithm named fuzzy attribute-based joint integrated scheduling and tree formation (FAJIT) technique for tree formation and parent node selection using fuzzy logic in a heterogeneous network is proposed and is compared with the distributed algorithm for Integrated tree Construction and data Aggregation (DICA).
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Forecasting major impacts of COVID-19 pandemic on country-driven sectors: challenges, lessons, and future roadmap.

TL;DR: The impact of this pandemic on country-driven sectors is evaluated and some strategies to lessen these impacts on a country’s economy are recommended.
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An automated breast cancer diagnosis using feature selection and parameter optimization in ANN

TL;DR: The IAIS-ABC-CDS with Momentum-based Gradient Descent Backpropagation (MBGD) that uses the advantages of Simulated Annealing (SA) for enhancing local search process is compared to the benchmark diagnosis schemes.
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Performance Analysis of Machine Learning Algorithms for Big Data Classification: ML and AI-Based Algorithms for Big Data Analysis

TL;DR: The authors collect the unstructured research data from a frequently used social media network by using a Twitter application program interface (API) stream and implement different machine classification algorithms like decision trees (DT), neural networks (NN), support vector machines (SVM), naive Bayes (NB), linear regression (LR), and k-nearest neighbor (K-NN) from the collected research data set.