DNA Base-Calling Techniques by Odeh, Fadi

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DNA Base-Calling by Mohammed, Omniyah Gul

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Learning Based Spectrum Sensing in OFDM Cognitive Radios by Muzaffar, Muhammad Umair

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Feature modeling using polynomial classifiers and stepwise regression by Shanableh, Tamer

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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

EOG-Based Reading Detection in the Wild Using Spectrograms and Nested Classification Approach by Sriman Bidhan Baray (15302398)

Robust Polynomial Classifier Using L1-norm minimization by Assaleh, Khaled

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Behavior-Based Machine Learning Approaches to Identify State-Sponsored Trolls on Twitter by Saleh Alhazbi (16869960)

Android mobile app for real-time bilateral Arabic sign language translation using leap motion controller by Eqab, Abdulla

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Hypospadias Reconstruction Training: Development of an Ex-Vivo Model for Objective Evaluation of Surgical Skills by Abbas, Tariq

“…The study focused on 4 skills as follows: urethral mobilization, dorsal inlay graft harvest/implantation, meatal-based flap urethroplasty, and dorsal plication. Machine learning techniques analyzed muscle activation patterns and attributes for assessing surgical precision. …”
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Hypospadias Reconstruction Training: Development of an Ex-Vivo Model for Objective Evaluation of Surgical Skills by Tariq Abbas (368053)

“…The study focused on 4 skills as follows: urethral mobilization, dorsal inlay graft harvest/implantation, meatal-based flap urethroplasty, and dorsal plication. Machine learning techniques analyzed muscle activation patterns and attributes for assessing surgical precision. …”

Target Detection Using Learning Methods by Sahnoon, Mohammad Moufeed

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How effective is phonological awareness training for preschoolers with speech and language difficulties? Exploring the perspectives of teachers working in preschool settings in Dub... by O’NEILL, LEAH MARIE

“…Thematic analysis was applied and involved a process of manual coding to construct and interpret themes based on patterns that emerged from the data reflecting preschool teachers' perspectives. …”
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GDLL: A Scalable and Share Nothing Architecture Based Distributed Graph Neural Networks Framework by Duong Thi Thu Van (19499206)

“…<p dir="ltr">Deep learning has recently been shown to be effective in uncovering hidden patterns in non-Euclidean space, where data is represented as graphs with complex object relationships and interdependencies. …”

A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by Md Ferdous Wahid (13485799)

“…<p dir="ltr">Accurate prediction of the pressure gradient (PG) for the oil-water flow requires identification of the flow pattern (FP), which is usually achieved by using either an expensive measurement system or time-consuming manual observations. …”

Clinical patterns and outcomes of hospitalized patients with grinder-related neurovascular injuries: A decade of experience from a Level I Trauma center by Hassan Al-Thani (440106)

“…We aimed to outline the frequency, patterns of <u>injury,</u> and clinical characteristics of patients injured by high-rotation cutting tools (grinders) and to pinpoint the neurovascular (nerves and blood vessels) injuries. …”

Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…A total of eleven hundred experimental data points for nine FPs (two stratified and seven dispersed patterns) in horizontal wellbores are used to develop the MLs. …”

Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

“…In this paper, a pattern recognition technique was adopted to minimize the inaccuracy in DNA base-calling. …”
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Learning-Based Space-Time Adaptive Processing by El Khatib, Alaa

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Knowledge-based Deep Learning for Modeling Chaotic Systems by Elabid, Zakaria

“…Our proposed KDL can learn the complex patterns governing chaotic systems by jointly training on real and simulated data directly from the dynamics and their differential equations. …”
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