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Naimul Islam

Researcher at Sylhet Agricultural University

Publications -  11
Citations -  142

Naimul Islam is an academic researcher from Sylhet Agricultural University. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 4, co-authored 6 publications receiving 62 citations. Previous affiliations of Naimul Islam include Rajshahi University of Engineering & Technology.

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Fishers’ perceptions of the performance of hilsa shad (Tenualosa ilisha) sanctuaries in Bangladesh

TL;DR: In this article, the authors investigated the perceptions of fishers towards sanctuaries that were established in the rivers of Meghna and Padma and in inshore waters of Bangladesh since 2005 to protect the declining hilsa ( Tenualosa ilisha ) populations.
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Energy Sustainability–Survey on Technology and Control of Microgrid, Smart Grid and Virtual Power Plant

TL;DR: In this article, the authors focus on the role of control strategies applied to the microgrid, smart grid, and virtual power plant towards future energy generation, distribution, management, and security.
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A Comparative Analysis on Suicidal Ideation Detection Using NLP, Machine, and Deep Learning

TL;DR: A comparative analysis of multiple machine learning and deep learning models to identify suicidal thoughts from the social media platform Twitter reveals that the RF model can achieve the highest classification score among machine learning algorithms, but training the deep learning classifiers with word embedding increases the performance of ML models.
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Climate Change Impacts on a Tropical Fishery Ecosystem: Implications and Societal Responses

TL;DR: In this paper, the authors aimed to map out the current threats and anticipated impacts of climate change on the most important hilsa shad fishery and the associated fishing communities based on fieldwork in six coastal fishing communities.
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Cost effective aquaponics for food security and income of farming households in coastal Bangladesh

TL;DR: Considering the low capital cost, good return on investment and reduced vulnerability of this culture system to tidal surges and flood, this technology has the potential to increase resilience of the farming households with ponds towards climate change in the coastal region.