When geoscience meets generative AI and large language models: Foundations, trends, and future challenges حسب Hadid, Abdenour

"…This survey discusses several GAI models that have been used in geoscience comprising generative adversarial networks (GANs), physics‐informed neural networks (PINNs), and generative pre‐trained transformer (GPT)‐based structures. …"
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Probabilistic AutoRegressive Neural Networks for Accurate Long-Range Forecasting حسب Panja, Madhurima

"…While numerous statistical and machine learning methods have been proposed, real-life prediction problems often require hybrid solutions that bridge classical forecasting approaches and modern neural network models. …"
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Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning حسب Mohamed Massaoudi (16888710)

"…This article provides an updated review of the cutting-edge machine learning and data-driven techniques used for PGP in networked PSs. …"

COVID-19 infection localization and severity grading from chest X-ray images حسب Anas M. Tahir (16870077)

"…An extensive set of experiments was performed using the state-of-the-art segmentation networks, U-Net, U-Net++, and Feature Pyramid Networks (FPN). …"

Hydrogen Sulfide (H₂S) Sensor: A Concept of Physical Versus Virtual Sensing حسب Ahmed Alsarraj (16876014)

"…The merits of the proposed system are as follows: 1) a virtual sensing concept is combined with a physical sensing platform to enhance the proposed model’s estimation power in quantifying H₂S in air samples; 2) a new feature extraction method based on fractional derivatives is proposed to further enhance the model’s learning capabilities; 3) an array of four gas sensors is fabricated in the in-house foundry to record and analyze the signature of H₂S at various concentration levels; 4) a shallow neural network (NN) model is trained and tested on the recorded data, and based on the NN’s input–output relation, a mathematical model is presented for the quantification of H₂S; and 5) the proposed model is a highly sensitive and reliable H₂S gas sensing scheme with the ability to detect the gas instantaneously. …"

An Overview on XML Semantic Disambiguation from Unstructured Text to Semi-Structured Data: Background, Applications, and Ongoing Challenges حسب Tekli, Joe

"…Third, we describe current and potential application scenarios that can benefit from XML semantic analysis, including: data clustering and semantic-aware indexing, data integration and selective dissemination, semantic-aware and temporal querying, web and mobile services matching and composition, blog and social semantic network analysis, and ontology learning. Fourth, we describe and discuss ongoing challenges and future directions, including: the quantification of semantic ambiguity, expanding XML disambiguation context, combining structure and content, using collaborative/social information sources, integrating explicit and implicit semantic analysis, emphasizing user involvement, and reducing computational complexity.…"
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