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101
Deep transfer learning strategy in intelligent fault diagnosis of gas turbines based on the Koopman operator
Published 2024“…A <u>deep neural network</u>-based transfer learning framework is proposed for realizing a precise adaptive linear model called the deep transfer linear (DTL) model enabling reliable prediction of the system’s behavior in various situations and designing structured fault residuals. …”
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Reduced neural network based ensemble approach for fault detection and diagnosis of wind energy converter systems
Published 2022“…EL is a technique that creates and combines multiple machine learning models in order to produce one optimal predictive model which gives improved results. The goal of this paper is to develop and validate effective neural networks based ensemble approach. …”
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103
DiaNet v2 deep learning based method for diabetes diagnosis using retinal images
Published 2024“…<p dir="ltr">Diabetes mellitus (DM) is a prevalent chronic metabolic disorder linked to increased morbidity and mortality. With a significant portion of cases remaining undiagnosed, particularly in the Middle East North Africa (MENA) region, more accurate and accessible diagnostic methods are essential. …”
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104
Deep learning-based beat-to-beat arterial blood pressure estimation using distant radar signals
Published 2025“…While traditional cuff-based approaches are non-invasive, they have limitations in providing continuous blood pressure monitoring. …”
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The Prevalence and Genetic Spectrum of Familial Hypercholesterolemia in Qatar Based on Whole Genome Sequencing of 14,000 Subjects
Published 2022“…This pioneering study provides a reliable estimate of FH prevalence in Qatar based on a significantly large population-based cohort, whilst uncovering the spectrum of genetic variants associated with FH.…”
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107
Enhancing Liquefied Natural Gas supply chain robustness through digital twin-driven machine learning models: A special case of cryogenic heat exchanger
Published 2025“…Next, this data is processed through Aspen HYSYS-based and ML-driven DT to assess the system performance and predict potential failures, respectively. …”
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108
Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects
Published 2021“…Motivated by the outstanding success of DL-based prediction methods, this article attempts to provide a thorough review from a broad perspective on the state-of-the-art advances of DL in SG systems. …”
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109
Non-Linear Programming-Based Energy Management for a Wind Farm Coupled with Pumped Hydro Storage System
Published 2022“…The forecasting module is responsible for predicting the wind power generation and load demand. …”
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FlashDetR: A deep learning pipeline for early detection and time estimation of flashover in high-voltage insulators using infrared videos
Published 2025“…In this work, we propose a pipeline named Flashover Detector and Time Estimator, which integrates a transformer-based model to accurately predict flashover occurrences, while a Three Dimensional Convolutional Neural Network-based model estimates the time to flashover. …”
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112
Mathematical Model-Based Optimization of Continuous Flow Photobioreactor Operating at Steady State Using MATLAB Optimization Function
Published 2024“…The <i>fmincon</i> optimization results agree well with the literature that used different optimization methods. The model-based optimization predicts the best performance of PBR without conducting experiments. …”
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Prostate-based biofluids for the detection of prostate cancer: A comparative study of the diagnostic performance of cell-sourced RNA biomarkers
Published 2016“…The aim of this study was to investigate if PEUW contained prostate-based material, evidenced by the presence of prostate specific antigen (PSA), and to evaluate the diagnostic performance of PEUW-based biomarkers. …”
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The impact of nozzle diameter and printing speed on geopolymer-based 3D-Printed concrete structures: Numerical modeling and experimental validation
Published 2024“…The numerical model successfully captures these buildability trends, though with an error ranging from 32 % to 45 % in predicting failure in 3D-printed structures. Nevertheless, the overall performance of the numerical model remains reliable in predicting the influence of printing parameters on buildability.…”
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Deep learning-based marine big data fusion for ocean environment monitoring: Towards shape optimization and salient objects detection
Published 2023“…This research study presents a data fusion-based method for underwater salient object detection and ocean environment monitoring by utilizing a deep model.…”
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Computational identification of genetic subnetwork modules associated with maize defense response to Fusarium verticillioides
Published 2015“…The other two predicted modules were indirectly involved in the defense response, where the most significant GO terms associated with these modules were GO:0046914 (transition metal ion binding) and GO:0046686 (response to cadmium ion). …”
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120
A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
Published 2025“…Three different publicly available datasets have been used based on the age group to create the best predicting model for each case. …”