Tuning of a fuzzy logic power system stabilizer using geneticalgorithms by Abido, M.A.

“…It is shown that the performance of FLPSS can be improved significantly by incorporating a genetic based learning mechanism. The performance of the proposed HPSS under different disturbances and loading conditions is investigated. …”
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Decision-level Gait Fusion for Human Identification at a Distance by Al-Tayyan, Amer

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Building power consumption datasets: Survey, taxonomy and future directions by Yassine Himeur (14158821)

“…Accordingly, a novel visualization strategy based on using power consumption micro-moments has been presented along with an example of deploying machine learning algorithms to classify the micro-moment classes and identify anomalous power usage.…”

A family of minimum curvature variable-methods for unconstrained optimization. (c1998) by Obeid, Samir Y.

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An efficient cache replacement strategy for the hybrid cache consistency approach in a mobile environment. (c2008) by Zeitunlian, Aline Michel

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An efficient cache replacement strategy for the hybrid cache consistency approach by Haraty, Ramzi A.

“…Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. …”
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Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe

“…We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…Modern ML models are used for prediction, prioritization, and decision making. Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”

Predicting User Behavior over the Web by Al Safadi, Amal Adnan

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Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…This is achieved by predicting subsequent tokens, such as keywords, variable names, types, function names, operators, and more. Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”

Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

“…After completing their first year, this work predicts student’s GPA in different concentrations using grades of Year 1 courses. …”
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The Effects of Data Mining on Small Businesses in Dubai by AlMutawa, Rasha

“…The benefits of using data mining on such businesses was confirmed, a different criteria from the traditional kind for evaluating the available tools was used, and an existing cross industry standard for implementing data mining projects (CRISP-DM) was used to evaluate five selected tools for the business based on availability of models, price, platform, and popularity. …”
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MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network by Sakib Mahmud (15302404)

“…The performance of the deep learning models is measured using three well-known performance matrices viz. mean absolute error (MAE)-based construction error, the difference in the signal-to-noise ratio (ΔSNR), and percentage reduction in motion artifacts (<i>η</i>). …”

Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations by Ayman Al-Kababji (16870080)

“…Hence, in this paper, we survey the key studies that are published between 2014 and 2022, showcasing the different machine learning algorithms researchers have used to segment the liver, hepatic tumors, and hepatic-vasculature structures. …”

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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Arabic text recognition by Haraty, Ramzi

“…Thus, the need to attempt a research related to Arabic handwritten text recognition. Algorithms based on neural networks have proved to give better results than conventional methods when applied to problems where the decision rules of the classification problem are not clearly defined. …”
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Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

“…The main purpose is to bridge the gap between EDM and International Assessments in the Arab world by applying EDM to predict Grade-4 student levels in TIMSS assessments in the UAE. We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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Decision-level fusion for single-view gait recognition with various carrying and clothing conditions by Al-Tayyan, Amer

“…Gait samples are fed into the MPCA and MPCALDA algorithms using a novel tensor-based form of the gait images. …”
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The political economy of AI: a content analysis of ChatGPT outputs and anti-Palestinian media bias by King, Gretchen

“…Grounded in research-based teaching methods, and employing a mixed-method content and frequency analysis and comparison of ChatGPT outputs in English and Arabic, this article expands research on AI biases, algorithmic oppression and digital divides within the context of digital Orientalism and anti-Palestinianism. …”
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Using artificial intelligence to improve body iron quantification: A scoping review by Abdulqadir J. Nashwan (11659453)

“…The search revealed a wide range of machine learning algorithms used by different studies. Notably, most studies used a single data type. …”