Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation by Raveendra Pilli (21633287)

“…Effective and reliable assessment methods are required to accurately classify and estimate brain age. In this study, a brain age classification and estimation framework is proposed using structural magnetic resonance imaging (sMRI) scans, a 3-D convolutional neural network (3-D-CNN), and a kernel ridge regression-based random vector functional link (KRR-RVFL) network. …”

Regression estimation for continuous-time functional data processes with missing at random response by Mohamed Chaouch (17983846)

Automatic Video Summarization Using HEVC and CNN Features by Issa, Obada

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Voltage stability estimation and prediction using neural network by Belhadj, C.A.

“…This paper proposes a neural network-based method for on-line voltage stability estimation, prediction and monitoring at each power system load bus. …”
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COUSCOus: improved protein contact prediction using an empirical Bayes covariance estimator by Reda Rawi (391865)

“…Finally, we showed that when using a simple random forest meta-classifier, by combining contact detecting techniques and sequence derived features, PSICOV predictions should be replaced by the more accurate COUSCOus predictions.…”

Source Localization in Random Acoustic Waveguides by Issa, Leila

“…We also show how it can be used to estimate the correlation function of the random fluctuations of the wave speed.…”
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Convergence Speed of Bermudan, Randomized Bermudan, and Canadian Options by Leduc, Guillaume

“…American options have long received considerable attention in the literature, with numerous publications dedicated to their pricing. Bermudan and randomized Bermudan options are broadly used to estimate their prices efficiently. …”
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Accurate multiple network alignment through context-sensitive random walk by Hyundoo Jeong (3840013)

“…It has been shown that network alignment methods can be used to detect pathways or network modules that are conserved across different networks. …”

Estimating Dust Accumulation on Photovoltaic Modules in the UAE by AlArif, Amal AbdulAziz

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Data extraction error in pharmaceutical versus non-pharmaceutical interventions for evidence synthesis: Study protocol for a crossover trial by Yi, Zhu

“…A generalized linear mixed effects model (based on the above three levels) will be used to estimate the potential differences in the error rates, with a log link function for binomial data. …”
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Incorporating Uncertainty into the Estimation of the Passing Sight Distance Requirements by El Khoury, John

“…The main objective of the article is to derive a PSD distribution that accounts for the variations in the contributing random variables. Two models are devised, a Monte-Carlo simulation model used to obtain the PSD distribution and a closed form analytical estimation model used for verification purposes. …”
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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…Specifically, this study exhibits people’s predilection toward the COVID-19 vaccine and its results based on the reviews. Five models, e.g., random forest (RF), a support vector machine (SVM), decision tree (DT), K-nearest neighbor (KNN), and an artificial neural network (ANN), were used for forecasting the overall predilection toward the COVID-19 vaccine. …”

Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks by Elmahdi Bentafat (16896405)

“…Each Bloom filter represents the set of vehicle IDs that contacted the RSU but may also be used to estimate the traffic flow between any number of RSUs. …”

Fuzzy Divergence Weighted Ensemble Clustering With Spectral Learning Based on Random Projections for Big Data by Ali, Tarig

“…Then it used to evaluate the weight of each cluster. Finally, we create regularized graphs from these membership matrices and use spectral matrices to estimate the affinity matrices of these graphs using fuzzy KL divergence anchor graphs. …”
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A New Data-Based Dust Estimation Unit for PV Panels by Shaaban, Mostafa

“…The UAE has low intensity rainfall and wind velocity; therefore solar panels must be cleaned manually or using automated cleaning methods. Estimating dust accumulation on solar panels will increase the output power and reduce maintenance costs by initiating cleaning actions only when required. …”
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Integrated Stochastic Approach for Risk and Service Estimation: Passing Sight Distance Application by El Khoury, John

“…As a result, a risk index can then be attached to every design value in the random distribution. Finally, level of service (LOS) measures can be estimated and a trade-off analysis between LOS and safety could be conducted. …”
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Resilience analytics: coverage and robustness in multi-modal transportation networks by Abdelkader Baggag (14153040)

“…Given a multi-modal transportation system of a city, we are interested in assessing its quality or efficiency by estimating the coverage i.e., a portion of the city that can be covered by a random walker who navigates through it within a given time budget, or steps. …”

Tranexamic Acid for Traumatic Injury in the Emergency Setting: A Systematic Review and Bias-Adjusted Meta-Analysis of Randomized Controlled Trials by Pieter Francsois, Fouche

“…MethodsA systematic review and bias-adjusted meta-analysis were performed to assess TXA’s effectiveness in emergency traumatic injury settings by pooling estimates from randomized controlled trials. Researchers searched Medline, Embase, and Cochrane Central for randomized controlled trials comparing TXA’s effects to a placebo in emergency trauma cases. …”
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Assessing the risk of angiotensin receptor blockers on major cardiovascular events: a systematic review and meta-analysis of randomized controlled trials by Yara Wanas (8744844)

Hybrid Tree-Based Machine Learning Models for State-of-Charge and Core Temperature Estimation in EV Batteries by Aya Haraz (22225036)

“…Among the combinations tested, the Extra Trees Regressor-Random Forest (ETR-RF) model delivered the highest estimation accuracy, while the Decision Tree-LightGBM (DT-LGBM) model exhibited the fastest training time. …”