Hyperspectral-physiological based predictive model for transpiration in greenhouses under CO₂ enrichment by Ikhlas Ghiat (16932564)

“…Three machine learning models were investigated for transpiration modelling and prediction: deep neural networks (DNN), extreme gradient boosting (XGBoost), and support vector machine regression (SVR). …”

Serum Vitamin D Concentration ≥75 nmol/L Is Related to Decreased Cardiometabolic and Inflammatory Biomarkers, Metabolic Syndrome, and Diabetes; and Increased Cardiorespiratory Fitn... by Vijay Ganji (8710491)

Morphological changes in amblyopic eyes in choriocapillaris and Sattler’s layer in comparison to healthy eyes, and in retinal nerve fiber layer in comparison to fellow eyes through... by Masri, Oussama Samer

“…Results The method of measuring reflectivity is good to excellent reliability for all regions of interest except the fourth. The mean reflectivity of the choriocapillaris and Sattler’s layer in amblyopic eyes were significantly lower than in healthy eyes (p = 0.003 and p = 0.008 respectively). …”
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Nonlinear Control of Brushless Dual-Fed Induction Generator With a Flywheel Energy Storage System for Improved System Performance by Mohammed Hamidat (3722086)

“…After optimization, the SMC settling time was significantly reduced from 0.7 seconds to 19.97 milliseconds, achieving a 96.9% improvement in response speed, while its steady-state error decreased from 0.48 to 0.06, marking an 87.5% reduction in tracking error. …”

Nurses’ work environment and intent to leave in Lebanese hospitals by Dimassi, Hani

“…Regression analysis revealed that for every 1 point score decrease on career development there was a 93% increase in likelihood of reporting intent to leave country. …”
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Android Malware Detection Using Machine Learning by Al Ali, Shaikha

“…In this work, several machine learning algorithms were utilized, namely k-Nearest neighbor (KNN), Decision Trees (DT), Naive Bayes (NB), Support Vector Machine (SVM) and other ensemble classifiers including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM) and CatBoost. …”
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Sleeve Gastrectomy in Patients with Type 2 Diabetes: Anthropometric and Cardiometabolic Improvements at 1, 3, 5, 7, and 9 years—Are the Initial Benefits Sustained? by Wahiba Elhag (5245547)

“…Mean HbA1c significantly decreased from 8.1%preop to 6.77%_{year 9}. …”

Analysis of mode choice affects from the introduction of Doha Metro using machine learning and statistical analysis by Ammar, Abulibdeh

“…Two statistical models and one machine learning model were used to analyze the current and future mode choices: discrete choice binary logit (BL) and multinomial logit (MNL) models as well as extreme gradient boosting (XGBoost). Furthermore, the SHapley Additive exPlanations (SHAP) method was used to rank the input features based on their importance according to the mean SHAP value. …”
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Performance Prediction Using Classification by MOOLIYIL, GITA

“…Ensemble models using bagging, boosting and the vote operator in addition to Gradient Boosted trees and Random Forest were compared to the individual classifiers to measure model efficiency. …”
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Explainable machine learning model and reliability analysis for flexural capacity prediction of RC beams strengthened in flexure with FRCM by Tadesse G. Wakjira (14779165)

“…A total of seven machine learning (ML) models such as kernel ridge regression, K-nearest neighbors, support vector regression, classification and regression trees, random forest, gradient boosted trees, and extreme gradient boosting (xgBoost) are evaluated to propose the best predictive model for FRCM-strengthened beams. …”

Analysis of mode choice affects from the introduction of Doha Metro using machine learning and statistical analysis by Ammar Abulibdeh (15785928)

“…Two statistical models and one machine learning model were used to analyze the current and future mode choices: discrete choice binary logit (BL) and multinomial logit (MNL) models as well as extreme gradient boosting (XGBoost). Furthermore, the SHapley Additive exPlanations (SHAP) method was used to rank the input features based on their importance according to the mean SHAP value. …”

Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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Hyper-Hypo study: A Retrospective Observational Study of Neonatal Hypoglycemia Related to Maternal Hypertension by Thiruveni Ramkumar (17075051)

“…On the other hand, neonates of hypertensive mothers administered with methyldopa showed a significant decrease of initial blood glucose reading.…”

Rescue cerclage by Khoury, Alfred

“…Advanced dilation of 3 cm and/or prolapsed membranes (n = 18) did not decrease the likelihood of reaching 28 weeks. Mean gestational age at delivery for this subset of patients was 30.7 ± 7.2 weeks. …”
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Prediction of CO₂ uptake in bio-waste based porous carbons using model agnostic explainable artificial intelligence by Mohd Azfar Shaida (19756971)

“…For this study, through model evaluation parameters, and scatter plots, statistical analysis supports the fact that the Extreme Gradient Boosting (XGBoost) model is found to be the best performing model for CO₂ uptake prediction with low errors and high coefficient of correlation for both training (<i>MSE</i>: 0.157, <i>RMSE</i>: 0.397, <i>MAE</i>: 0.294, <i>MAPE</i>: 0.112, <i>R</i>^<em>2</em>: 0.931) and testing phases (<i>MSE</i>: 0.345, <i>RMSE</i>: 0.588, <i>MAE</i>: 0.461, <i>MAPE</i>: 0.121, <i>R</i>^<em>2</em>: 0.860). …”

Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches by Mohammad, Areej Osama

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A Novel Versatile Framework for Enabling Early Detection of Evolving Network-based Cyberattacks by THOMAS, RAJESH

“…For botnet attack detection, the byte-based feature learning techniques with Decision Trees (DT) and Extreme Gradient Boosting (XGB) performed optimally, achieving 99.9% accuracy with fast detection times ranging from 0.006 to 0.026 seconds. …”
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Food safety knowledge attitude and practices of oncology nurses, in Lebanese hospitals by Angy, Mallah

“…Knowledge scores were higher among nurses holding a graduate degree (mean = 85; p < 0.05), and those who attended a training course (mean = 79; p < 0.05). …”
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Identification of novel hypertension biomarkers using explainable AI and metabolomics by Karthik Sekaran (16845959)

“…Glycerophosphorylcholine (GPC), N-Stearoylsphingosine (d18:1/18:0)*, and glycine are critical metabolites for accurate hypertension prediction. The light gradient boosting model yielded superior results, underscoring the potential of our research in enhancing hypertension diagnosis and treatment. …”

Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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