Publications by authors named "M I Zakariah"

Federated learning (FL) is a popular method where edge devices work together to train machine learning models. This study introduces an efficient network for analyzing healthcare records. It uses VPN technology and applies a federated learning approach over a wireless backhaul network.

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Brain tumors are one of the leading causes of cancer death; screening early is the best strategy to diagnose and treat brain tumors. Magnetic Resonance Imaging (MRI) is extensively utilized for brain tumor diagnosis; nevertheless, achieving improved accuracy and performance, a critical challenge in most of the previously reported automated medical diagnostics, is a complex problem. The study introduces the Dual Vision Transformer-DSUNET model, which incorporates feature fusion techniques to provide precise and efficient differentiation between brain tumors and other brain regions by leveraging multi-modal MRI data.

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Spermatogenesis is a complex process. It is the modification of progenitor spermatogonia into mature spermatozoa. The stages are similar in all-male vertebrates, as well as avian species.

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Detecting plant leaf diseases accurately and promptly is essential for reducing economic consequences and maximizing crop yield. However, farmers' dependence on conventional manual techniques presents a difficulty in accurately pinpointing particular diseases. This research investigates the utilization of the YOLOv4 algorithm for detecting and identifying plant leaf diseases.

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This study evaluated the histopathological changes in the gill, liver and kidney of African catfish () intoxicated with a sub-lethal dose of leaves extract (MCLE) for 96 h. The acute toxicity test has been determined previously with a value of 96-h LC = 127 mg/L, hence the selection of sub-lethal ranges from 60 mg/L to 160 mg/L of MCLE. Degenerative alterations were prominent in all tested organs, particularly after exposure to a high concentration of MCLE.

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