Temporal fusion transformer-based prediction in aquaponics by Ahmet Metin (12832543)

Predicting Mobile Game Success Using Data Analytics by ALOMARI, KHALED MOHAMMAD

“…A model of mobile game app success prediction based upon the game features values that are created proposed.…”
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A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity by Wesam S. Ahmed (10170053)

“…Here, we combined molecular dynamics (MD) simulation and mutational analysis to show that the R162A mutation results in a decreased but stable <u>bioluminescence </u>activity of NLuc in living cells and in vitro. …”

A Novel Centrality-Based Approach for Link Prediction by El Khoury, Elissa Lichaa

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PredictPTB: an interpretable preterm birth prediction model using attention-based recurrent neural networks by Rawan AlSaad (14159019)

Forecasting model to predict project success based on the contractors’ characteristics by AlSuwaidi, Khalid Waleed Rashid Deemas

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Detection of statistically significant network changes in complex biological networks by Raghvendra Mall (581171)

“…The proposed procedure exploits a more effective model selection criteria to generate <i>p</i>-values for statistical significance and is more efficient in terms of computational time and prediction accuracy than literature methods. …”

Addition of sphingosine-1-phosphate to human oocyte culture medium decreases embryo fragmentation by Zreik, Tony

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Traffic Transformer: Transformer-based framework for temporal traffic accident prediction by Mansoor G. Al-Thani (19237204)

“…To address the inherent shortcomings of current traffic prediction models, we propose the Traffic Transformer for multidimensional, multi-step traffic accident prediction. …”

The Anti-Tumor Agent Sodium Selenate Decreases Methylated PP2A, Increases GSK3βY216 Phosphorylation, Including Tau Disease Epitopes and Reduces Neuronal Excitability in SHSY-5Y Neu... by Wesal Habbab (17346961)

“…Somewhat surprisingly, the catalytically active form, methylated PP2A (mePP2A) was significantly decreased. In close correlation to these data, the phosphorylation state of two substrate proteins, sensitive to PP2A activity, GSK3β and Tau were found to be increased. …”

Optimizing malicious website prediction: An advanced XGBoost-based machine learning model by Sumaira Hussain (19259669)

Deep learning based multimodal urban air quality prediction and traffic analytics by Saad Hameed (6488738)

“…The proposed system tackles the challenge of predicting air quality at locations having no sensors or experiencing sensor failures by training a joint model on the data obtained from nearby stations/sensors using a Particle Swarm Optimization (PSO)-based merit fusion of the sensor data. …”

AI-based remaining useful life prediction and modelling of seawater desalination membranes by Al Ali, Fajer

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ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks by Muhammad Asif Khan (7367468)

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

NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY by JINESH, PADIKKAPPARAMBIL

“…Therefore, this thesis proposed a Novel Stacking Classification and Prediction (NSCP) algorithm based on AAL for the older people with Multi-strategy Combination based Feature Selection (MCFS) and Novel Clustering Aggregation (NCA) algorithms. …”
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Both decreasing interstructural space size and increasing total cover increase shrimp abundance on artificial structures deployed in a UAE seagrass bed by Bartholomew, Aaron

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

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

“…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)

“…<h3>Aims</h3><p dir="ltr">To develop a prediction model for diabetes using metabolomics data and to evaluate various machine learning approaches and identify the most effective framework for disease prediction.…”