Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

“…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …”

Can AI Help in Screening Viral and COVID-19 Pneumonia? by Muhammad E. H. Chowdhury (14150526)

Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective by Zhitao Xu (2426023)

“…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …”

Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems by Tarek Berghout (16905132)

Deep and transfer learning for building occupancy detection: A review and comparative analysis by Aya Nabil Sayed (17317006)

“…Typically, analyzing big occupancy data gathered by BIoT networks helps significantly identify the causes of wasted energy and recommend corrective actions. …”

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

“…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.…”

A new estimator and approach for estimating the subpopulation parameters by Mohammad Salehi M. (21259490)

“…<p dir="ltr">Based on some theoretical results, we recommend a new algorithm for estimating the total and mean of a subpopulation variable for the case of a known subpopulation size, which is different from the algorithm recommended by most of sampling books. …”

THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar by M. Walid Qoronfleh (14153088)

“…Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. …”

Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework by Tayyabah Hasan (18427887)

“…After selecting the most appropriate lattice map (32 × 32) in 750,000 iterations using SOMs, the data points below the dark blue region are mapped onto the data frame to get the videos. …”

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…<p dir="ltr">Nowadays, in contemporary building and energy management systems (BEMSs), the predominant approach involves rule-based methodologies, typically employing supervised or unsupervised learning, to deliver energy-saving recommendations to building occupants. However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”

Exploring Digital Competitiveness through Bayesian Belief Networks by Qazi, Abroon

“…Three states were assigned to variables—low, medium, and high performance—and the tree augmented naive Bayes (TAN) algorithm was applied to model interdependencies. …”
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Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…To account for limitations associated with small datasets, robust strategies were implemented based on methodological recommendations for ML with a limited dataset, including data segmentation, feature selection, and model evaluation. …”

Diagnosing failed distribution transformers using neural networks by Farag, A.S.

“…The ANN was trained utilizing backpropagation algorithm using a real (out of the field) data obtained from utilities distribution networks transformer's failures. …”
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A multi-pretraining U-Net architecture for semantic segmentation by Cagla Copurkaya (22502042)

“…The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. …”

Teachers' Perceptions of the Role of Artificial Intelligence in Facilitating Inclusive Practices for Students with Special Educational Needs and Disabilities: A Case Study in a Pri... by BACHIR, HIBAH AHMAD

“…Findings referred these barriers to limited teacher training, technological accessibility, and data privacy concerns, as well as ethical biases in AI algorithms. …”
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Legal and Ethical Considerations of Artificial Intelligence for Residents in Post-Acute and Long-Term Care by Barry Solaiman (19160614)

“…Second, how discrimination and bias in algorithmic decision-making can undermine Medicare coverage for PA-LTC, causing doctors' recommendations to be ignored and denying residents the care they are entitled to. …”

Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care by Regina Padmanabhan (14231606)

“…Other highlights are (1) a novel set of easily available features for the prediction of the aforementioned clinical complications and (2) the use of data augmentation methods and model-scoring-based hyperparameter tuning to address the problem of class disproportionality, a common challenge in medical datasets and often the reason behind poor event prediction rate of various predictive models reported so far. …”

Automatic White Blood Cell Differential Classification by Al-Muhairy, Juma A. Bin Darwish

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Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges by Muhammad Mohsin Khan (22303366)

“…Still, challenges in adversarial attacks, algorithmic bias, and variable regulatory frameworks remain strong. …”

Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System by Abougharib, Arwa

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