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181
Applications of fast fourier transform in the integrity evaluation of deep foundations
Published 2016“…The method is developed and validated using experimental data, and is based on applying the fast Fourier transform mapping algorithm on data obtained from cross-hole sonic logging. …”
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182
Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation
Published 2023“…Five different scenarios are used to test and validate the created model, and in each case, the proposed method is found to be superior to the current methodology in terms of range, energy, density, time periods, and total metrics of operation.…”
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183
Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials
Published 1997“…Performance evaluation of the proposed methods and comparisons with existing methods are made by means of Monte-Carlo simulations, experimental data and analysis. The first scheme makes use of the complex cepstrum of the third-order cumulants (complex bicepstrum) of the ultrasonic signals. …”
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masterThesis -
184
Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations
Published 2025“…<p>Human behavior significantly impacts domestic energy consumption, making it essential to monitor and improve these consumption patterns. …”
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185
A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks
Published 2025“…Deep reinforcement learning (DRL) offers a data-driven alternative that couples perception with sequential decision-making. …”
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186
A novel few shot learning derived architecture for long-term HbA1c prediction
Published 2024“…For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. …”
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187
A multi-pretraining U-Net architecture for semantic segmentation
Published 2025“…The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. …”
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188
Oversampling techniques for imbalanced data in regression
Published 2024“…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …”
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189
Using machine learning to support students’ academic decisions
Published 2019“…This approach uses other students’ grades to make a prediction. This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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190
An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System
Published 2019“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. Experiment is performed using Azure Machine Learning (ML) platform to test and assess the most efficient model that would predict the failure of system elements and predict the abnormality of the operation. …”
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191
Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog...
Published 2023“…This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. The calibrated simulation model based on indoor and outdoor measured temperature for a school of interest is used to evaluate the optimization strategies. …”
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192
Identity and Aggregate Signature-Based Authentication Protocol for IoD Deployment Military Drone
Published 2021“…Both GPS and UAVN/FANET use open network channels for data broadcasting, which are exposed to several threats, thus making security risky and challenging. …”
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193
Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
Published 2021“…<p dir="ltr">Enormous amounts of data are being produced everyday by sub-meters and smart sensors installed in residential buildings. …”
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194
Legal and Ethical Considerations of Artificial Intelligence for Residents in Post-Acute and Long-Term Care
Published 2024“…Second, how discrimination and bias in algorithmic decision-making can undermine Medicare coverage for PA-LTC, causing doctors' recommendations to be ignored and denying residents the care they are entitled to. …”
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195
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196
Artificial intelligence models for predicting the mode of delivery in maternal care
Published 2025“…</p><h3>Objectives</h3><p dir="ltr">This study aims to evaluate and compare the predictive accuracy of AI algorithms in predicting the mode of delivery (vaginal or cesarean) using routinely collected antepartum data from electronic health records (EHRs). …”
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197
FoGMatch
Published 2019“…In this context, the notion of fog computing has been projected to furnish data analytics and decision-making closer to the IoT devices. …”
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masterThesis -
198
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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199
Using artificial bee colony to optimize software quality estimation models. (c2015)
Published 2016“…We validate our technique on data describing maintainability and reliability of classes in an Object-Oriented system. …”
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masterThesis -
200
Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects
Published 2021“…This ongoing transition undergoes rapid changes, requiring a plethora of advanced methodologies to process the big data generated by various units. In this context, SG stands tied very closely to Deep Learning (DL) as an emerging technology for creating a more decentralized and intelligent energy paradigm while integrating high intelligence in supervisory and operational decision-making. …”