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coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
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181
A cluster-based model for QoS-OLSR protocol
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conferenceObject -
182
Copy number variations in the genome of the Qatari population
Published 2015“…CNVs were detected in 97 unrelated Qatari individuals by running two calling algorithms on each of two primary datasets: high-resolution genotyping (Illumina Omni 2.5M) and high depth whole-genome sequencing (Illumina PE 100bp). …”
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184
Enhanced Inverse Model Predictive Control for EV Chargers: Solution for Rectifier-Side
Published 2024“…Then, an adaptive estimation strategy employing a recursive least square algorithm is proposed for online dynamic model estimation, which is then used by the IMPC for optimal switching states prediction. …”
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185
Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review
Published 2022“…Wearable devices (WDs) make use of sensors historically reserved for hospital settings. …”
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186
Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection
Published 2022“…We also review methods that use machine learning algorithms to predict blood glucose trends, especially for high risk events such as hypoglycemia. …”
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187
Communication-Based Adaptive Overcurrent Protection for Distribution Systems with DistributedGenerators
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doctoralThesis -
188
Depthwise Separable Convolutions and Variational Dropout within the context of YOLOv3
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conferenceObject -
189
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190
Thermodynamic Analysis and Optimization of Densely-Packed Receiver Assembly Components in High-Concentration CPVT Solar Collectors
Published 2016“…However, accurate design models and clear simulation algorithms on the component-level are critical for the proper system-level engineering and evaluation of CPVT collectors. …”
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191
The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…</p><h3>Objective</h3><p dir="ltr">This review aims to explore the machine learning algorithms used for the detection and diagnosis of bipolar disorder and its subtypes.…”
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192
Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
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doctoralThesis -
193
A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation
Published 2023“…Conventional methods, which are used to solve state estimation on the transmission level, require the grid to be observable. …”
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masterThesis -
194
AGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics
Published 2022“…AGEomics biomarkers have been used in diagnostic algorithms using machine learning methods. …”
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195
Dynamic multiple node failure recovery in distributed storage systems
Published 2018“…In this work, we address the problem of multiple failure recovery with dynamic scenarios using the fractional repetition code as a redundancy scheme. …”
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196
Software defect prediction. (c2019)
Published 2019“…One that focuses on predicting defect in software modules using a hybrid heuristic - a combination of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
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masterThesis -
197
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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Modelling of pollutant transport in compound open channels
Published 1998“…Longitudinal and transverse mixing coefficients were calculated using the method of moments and by estimation using empirical relationships. …”
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masterThesis -
200
A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks
Published 2022“…This paper introduces a new solution to detect energy consumption anomalies based on extracting micro-moment features using a rule-based model. The latter is used to draw out load characteristics using daily intent-driven moments of user consumption actions. …”