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A kernelization algorithm for d-Hitting Set
Published 2010“…For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k2+k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. …”
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Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements
Published 2023“…<p dir="ltr">This work proposes an original preconditioner that couples the Constrained Pressure Residual (CPR) method with block preconditioning for the efficient solution of the linearized systems of equations arising from fully implicit multiphase flow models. …”
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A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation
Published 2024“…ML algorithms could play a pivotal role in dynamically allocating resources, devising efficient routes, and predicting demand patterns. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
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Application of Data Mining to Predict and Diagnose Diabetic Retinopathy
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Mining airline data for CRM strategies. (c2006)
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Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review
Published 2023“…Deep learning models were the most prominent branch of AI used for pancreatic cancer diagnosis in the studies, and the convolutional neural network was the most used algorithm (18/30, 60%). …”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn...
Published 2020“…Machine Learning (ML) saw a great increase in general and domain specific research. …”
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What are artificial intelligence literacy and competency? A comprehensive framework to support them
Published 2024“…We also identify five effective learning experiences to foster abilities and confidences, and suggest five future research directions: prompt engineering, data literacy, algorithmic literacy, self-reflective mindset, and empirical research.…”
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Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas
Published 2024“…In this context, we formulate the problem as a non-linear programming (NLP) optimization problem aimed at maximizing the total EH IoT devices and determining the optimal trajectory paths for UAVs while adhering to the constraints related to the maximum time duration, the UAVs’ maximum energy consumption, and the minimum data rate to achieve a reliable transmission. Due to the complexity of the problem, the combinatorial nature of the formulated problem, and the difficulty of obtaining the optimal solution using conventional optimization problems, we propose a lightweight meta-RL solution capable of solving the problem by learning the system dynamics. …”
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Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE
Published 2020“…The industry is yet to fully benefit from these big data by applying Machine Learning (ML) and Artificial Intelligence (AI). …”
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Using genetic algorithms to optimize software quality estimation models
Published 2004“…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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masterThesis