Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr... by Elmahdy, Samy

“…The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. …”
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Current trends and future orientation in diagnosing lung pathologies: A systematic survey by Noorizadeh, Mohammad

“…The CV processing method involves the application of advanced imaging techniques and machine learning algorithms to scrutinize and diagnose lung pathologies and ventilator-associated pneumonia (VAP). …”
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Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases by Muhammad Ali Muzammil (17910611)

“…The effective implementation of AI-powered ECG analysis is limited by issues such as systematic bias. Biases based on age, gender, and race result from unbalanced datasets. …”

Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants by Shafiq, M.

“…The U-model is utilized to design an adaptive inverse controller by using a simple root-solving algorithm of Newton-Raphson. The synergy of U-model with AIC structure has provided an effective and straight forward method for adaptive tracking of nonlinear plants. …”
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Dynamic adaptation for video streaming over mobile devices. (c2013) by Jalloul, Rayan A.

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A Full-System Approach of the Elastohydrodynamic Line/Point Contact Problem by Habchi, Wassim

“…The use of the finite element method allows the use of variable unstructured meshing and different types of elements within the same model which leads to a reduced size of the problem. …”
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User-centric strategies for resource management in heterogeneous wireless networks with QoS considerations by Abbas, Nadine Fawaz

“…Due to the complexity of the problem, we design sub-optimal hierarchical tree-based algorithms for real-time operation taking into account realistic constraints. …”
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A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study by Masurkar, Faeez

“…Further, As the quality of received signals differs at different sensing points as a result of the surface conditions of the specimen, the Self Adaptive Smart Algorithm (SASA) method was adopted to filter out the noise and accurately pinpoint the defect reflected wave packet which ultimately aids in better detection and localization. …”
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Simulations of the penetration of 6061-T6511 aluminum targets by spherical-nosed VAR 4340 steel projectiles by Warren, Thomas

“…In the context of an analysis code, this approximation eliminates the need for discretizing the target as well as the need for a contact algorithm. Thus, this method substantially reduces the computer time and memory requirements. …”
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An intelligent approach to predicting the effect of nanoparticle mixture ratio, concentration and temperature on thermal conductivity of hybrid nanofluids by Ifeoluwa Wole-Osho (14151315)

“…A polynomial correlation model, the adaptive neuro-fuzzy inference system model and an artificial neural network model optimised with three different learning algorithms. The adaptive neuro-fuzzy inference system model was most accurate in forecasting the thermal conductivity of the Al₂O₃–ZnO hybrid nanofluid with an R² value of 0.9946.…”

Query acceleration in distributed database systems by Haraty, Ramzi A.

“…Query optimization strategies aim to minimize the cost of transferring data across networks. Many techniques and algorithms have been proposed to optimize queries. …”
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Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review by Hiba Alzoubi (18001609)

“…</p><h3>Conclusion</h3><p dir="ltr">AI algorithms show promise in detecting and subtyping medulloblastomas, but the findings are limited by overreliance on one dataset, small sample sizes, limited study numbers, and lack of meta-analysis Future research should develop larger, more diverse datasets and explore advanced approaches like deep learning and foundation models. …”

Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

“…The string is rigidly connected to the fixed end of the beam and through a spring and damper to a second point on the beam. The finite element method is used to model the system and a reduced order model is obtained through modal reduction performed on both the string and the beam. …”
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A fuzzy basis function network for generator excitation control by Abido, M.A.

“…The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on generator loading conditions. The orthogonal least squares learning algorithm is developed for designing an adequate and parsimonious FBFN model. …”
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An Alternating Projection Framework for Elementwise Masked Nonlinear Matrix Decomposition by Kulathil, Muhammed Noshin Poovan

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The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review by Uzair Shah (15740699)

“…The most common signal normalization and feature extractions in the included studies were the bandpass filter and wavelet-based feature extraction. We categorized the studies based on AI techniques, such as machine learning and deep learning. …”

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications by Abdallah Falah Mohammad Aldwekat (22457821)

“…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …”

Mining airline data for CRM strategies. (c2006) by Maalouf, Lena

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A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems by Abido, M.A.

“…The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on machine loading conditions. The orthogonal least squares (OLS) learning algorithm is developed for designing an adequate and parsimonious FBFN model. …”
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Automation of the Arabic sign language recognition by Mohandes, M.

“…This paper introduces a system to recognize the Arabic sign language using an instrumented glove and a machine learning method. Interfaces in sign language systems can be categorized as direct-device or vision-based. …”
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