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

Get full text

Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection by Atiq ur Rehman (3044409)

Machine Learning Based Photovoltaics (PV) Power Prediction Using Different Environmental Parameters of Qatar by Amith Khandakar (14151981)

“…Calibration of several sensors for an in-house built PV system was described. Several multiple regression models and artificial neural network (ANN)-based prediction models were trained and tested to forecast the hourly power output of the PV system. …”

Metabolomics-based prediction model for diabetes: A comprehensive analysis of biomarkers and machine learning approaches by Doaa Farid (22565300)

“…</p><h3>Conclusion</h3><p dir="ltr">Metabolomics data can effectively predict diabetes status, with logistic regression providing the optimal balance of performance and interpretability. …”

Decreased Analgesic Requirements in Super Morbidly Versus Morbidly Obese Patients Undergoing Laparoscopic Sleeve Gastrectomy by Hamed Elgendy (14148846)

Modeling of photovoltaic soiling loss as a function of environmental variables by Wasim Javed (6105866)

“…The ANN model performed significantly better in predicting daily ΔCIas well as cumulative CI than the linear model in term of R2 values and statistical error indexes. …”

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

“…Moreover, the proposed algorithm demonstrated excellent prediction accuracy with a mean absolute error (MAE) of <b>3.89</b> years, <b>3.64 </b>years, and <b>4.49</b> years for GM, WM, and CSF regions, confirming that changes in WM volume are significantly associated with normal brain aging. …”

Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis by Md Arifuzzaman (11471123)

“…The parameters that affect the behaviour of asphalt have been used to predict the results using the CART. The results obtained from CART analysis were also compared with those from the regression model. …”

L1-CAM knock-down radiosensitizes neuroblastoma IMR-32 cells by simultaneously decreasing MycN, but increasing PTEN protein expression by Rached, Johnny

Get full text
Get full text
Get full text
Get full text

Estimating hydrogen absorption energy on different metal hydrides using Gaussian process regression approach by Majedeh Gheytanzadeh (17541927)

“…A robust Gaussian process regression (GPR) approach with four kernel functions is proposed to predict the hydrogen absorption energy based on the inputs. …”

Deep learning-based modeling of land use/land cover changes impact on land surface temperature in Greater Amman Municipality, Jordan (1980–2030) by Khaled F. Alkaraki (22051967)

“…This study aimed to model past, present, and future LULCC on Land Surface Temperatures in the Greater Amman Municipality (GAM) in Jordan between 1980 and 2030. …”

Role of nutritional indices in predicting outcomes of vascular surgery by Jabbour, Jana

“…We aimed to assess the combined use of recent significant weight loss (>10% body mass) and serum albumin levels as a nutritional status index to predict outcomes. …”
Get full text
Get full text
Get full text
Get full text

Prediction of the Backwater Level Due to Bridge Constriction in Waterways by Assar, Kimia Haji Amou

Get full text

Comparison of four intensive care scores in prediction of outcome after Veno-Arterial ECMO: A single-center retrospective study by Suraj Sudarsanan (20090727)

“…APACHE-II > 27 (AUC of 0.66), calculated 24 h post-ICU admission after ECMO insertion, showed the greatest predictive ability for mortality. Multivariate logistic regression analysis of the four scores showed that APACHE-II > 27 and SOFA > 14, calculated 24 h post-ICU admission after ECMO insertion, were independently significantly predictive of mortality.…”

A Multi-Feature Based Approach Incorporating Variable Thresholds for Detecting Price Spikes in the National Electricity Market of Australia by Dao H. Vu (19570225)

Prediction of stroke-associated hospital-acquired pneumonia: Machine learning approach by Abujaber, Ahmad A.

“…BackgroundStroke-associated Hospital Acquired Pneumonia (HAP) significantly impacts patient outcomes. This study explores the utility of machine learning models in predicting HAP in stroke patients, leveraging national registry data and SHapley Additive exPlanations (SHAP) analysis to identify key predictive factors. …”
Get full text
Get full text
Get full text

Contrasting and Predicting Social Media’s Role in Addictive Use and Well-Being by Deniz Cemiloglu (17150980)

“…Competence in using social media significantly predicted both PSMU and SM-WB in the Arab sample. …”

Factors Determining SMEs Intention to Access Alternative Financing in Emerging Markets: Evidence from the UAE by SHAH, SHAZIA

“…The research findings strongly support the significance of innovation, credit terms of alternative finance, visibility of alternative finance, and SME owner/manager financial literacy within the TOE framework in predicting the intention of SME owners/managers to utilize alternative finance. …”
Get full text

Machine learning-based prediction of one-year mortality in ischemic stroke patients by Ahmad Abujaber (9100064)

“…</p><h3>Methods</h3><p dir="ltr">Five machine learning models were trained using data from a national stroke registry, with logistic regression demonstrating the highest performance. The SHapley Additive exPlanations (SHAP) analysis explained the model’s outcomes and defined the influential predictive factors. …”

Prediction of knowledge acquisition, knowledge sharing and knowledge utilization from locus control by Karkoulian, Silva

Get full text
Get full text
Get full text