Prediction of transportation index for urban patterns in small and medium-sized Indian cities using hybrid RidgeGAN model by Thottolil, Rahisha

“…A hybrid framework based on Kernel Ridge Regression (KRR) and the CityGAN model is introduced to predict network density using spatial indicators of human settlements. …”
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Optimizing pre-copy live virtual machine migration in cloud computing using machine learning-based prediction model by Raseena M. Haris (17773470)

Advanced Techniques for Predicting the Future Progression of Type 2 Diabetes by Md. Shafiqul Islam (8988548)

“…The proposed methods have been evaluated using data from a longitudinal clinical study, known as the San Antonio Heart Study. Our proposed model managed to achieve 95.94% accuracy in predicting whether a person will develop type 2 diabetes within the next 7-8 years or not.…”

Predictive factors for giftedness among Syrian refugee students: A focus on academic achievement, gender, and school context by Ali M. Alodat (22508036)

“…Middle school students were less likely to be identified compared to secondary students, while gender differences were not significant. Predictive modeling results should be interpreted with caution, as gifted identification was derived directly from the HOPE total score; models incorporating HOPE items closely mirrored the HOPE-based classification, whereas models using only demographic variables had limited discriminatory power. …”

Deep random vector functional link transformer network with multiple output layers for significant wave height forecasting by Aryan Bhambu (18767731)

“…The computational results demonstrate the superiority of the proposed models through a comparative analysis against state-of-the-art approaches across fifteen significant wave height time series, validated by three error metrics and a statistical test.…”

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. …”

A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by Md Ferdous Wahid (13485799)

“…This study proposes a hybrid scheme where two machine-learning (ML) models are coupled in a series to predict the PG value without any conclusive FP information. …”

Temporal self-attention for risk prediction from electronic health records using non-stationary kernel approximation by Rawan AlSaad (14159019)

“…Our experimental evaluation involved nine prediction models, categorized into three distinct groups. …”

Performance Prediction Using Classification by MOOLIYIL, GITA

“…Interestingly the variance in the performance measure values are not very significant for some of the models and it can be concluded that early risk prediction can happen earlier in the semester when intervention and associated benefits of improving student performance is more probable.…”
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The significance of general skills training for early career graduates: relationships with perceived organizational support, job satisfaction and turnover intention by Pinnington, Ashly

“…This study also found significant evidence for serial mediation by POS on PGST and its relationship with turnover intention. …”
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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)

“…<p dir="ltr">This study introduces comprehensive research on the prediction of the carbon dioxide (CO₂) uptake from the biomass-waste derived-porous carbons (BWDPCs), by using scientometrics and model agnostic multi-layered explainable artificial intelligence (XAI) techniques. …”

Exploiting the Spatio-Temporal Patterns in IoT Data to Establish a Dynamic Ensemble of Distributed Learners by Mehdi Mohammadi (5024105)

“…<p dir="ltr">Internet of Things applications can greatly benefit from accurate prediction models. The performance of prediction models is highly dependent on the quantity and quality of their training data. …”

Robust and novel attention guided MultiResUnet model for 3D ground reaction force and moment prediction from foot kinematics by Md. Ahasan Atick Faisal (15302410)

“…The framework has achieved an average correlation coefficient of 0.96 for 3D ground reaction force prediction and 0.86 for 3D ground reaction momentum prediction in cross-dataset validation. …”

Evolutionary algorithm for protein structure prediction by Mansour, Nashat

“…The protein structure prediction problem has real-world significance where several diseases are associated with the wrong folding of proteins. …”
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Forecasting Emerging Stock Market Crashes via Machine Learning by Khan, Mohammad Osama

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A Study into the Adoption of Internet of Things – IoT Technologies within Contractors in Dubai, United Arab Emirates by Al-Amleh, Khalel

“…Regression analysis was used to test the research hypotheses and Multiple linear regression was utilized to develop a prediction model. Findings – According to respondents, when asked on the types of IoT technologies utilized by their organizations BIM, smartphones, and cloud storage systems were the contractors' leading types of IoT technologies adopted. …”
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Prediction of Soil Loss in a Reservoir Watershed Using an Erosion Model and Modern Technological Tools: A Case Study of Marathon Lake, Attica in Greece by Pavlopoulos, Kosmas

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Prediction of in-hospital mortality in patients with post traumatic brain injury using National Trauma Registry and Machine Learning Approach by Ahmad Abujaber (9100064)

“…<h3>Background</h3><p dir="ltr">The use of machine learning techniques to predict diseases outcomes has grown significantly in the last decade. …”

Artificial Intelligence and Machine Learning Applications in Sudden Cardiac Arrest Prediction and Management: A Comprehensive Review by Sarah Aqel (17787809)

“…<h3>Purpose of Review</h3><p dir="ltr">This literature review aims to provide a comprehensive overview of the recent advances in prediction models and the deployment of AI and ML in the prediction of cardiopulmonary resuscitation (CPR) success. …”

ECP: Error-Aware, Cost-Effective and Proactive Network Slicing Framework by Amr E. Aboeleneen (19237135)