Cortical EEG Source Localization of Focal Epilepsy by Siyam, Wisal Elfatih Mohamed

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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”

Scatter search for protein structure prediction. (c2008) by Kehyayan, Christine Houry

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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…Our experimental design included Data Collection, Feature Engineering, ML model selection/development, and reporting evaluation of metrics.…”

Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation by Hariprasath Manoharan (14157966)

“…Five different scenarios are used to test and validate the created model, and in each case, the proposed method is found to be superior to the current methodology in terms of range, energy, density, time periods, and total metrics of operation.…”

Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

“…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
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Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic by Hassan Farhat (9000509)

Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation by Fawaz Kserawi (16904859)

“…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”

Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”

Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

“…We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network by Nasru Minallah (9427338)

Scan Test Cost and Power Reduction Through Systematic Scan Reconfiguration by Al-Yamani, A.

“…Using SAS, this paper also presents systematic scan reconfiguration, a test data compression algorithm that is applied to achieve 10times to 40 times compression ratios without requiring any information from the automatic-test-pattern-generation tool about the unspecified bits. …”
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A kernelization algorithm for d-Hitting Set by Abu-Khzam, Faisal N.

“…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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NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM by Kamel, M.S.

“…The performance of the new algorithms is compared with the fuzzy c-means algorithm by testing them on four published data sets. …”
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems by Majdi Mansouri (16869885)

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Impact Of Multidisciplinary Maternal Resuscitation Training Program on Improving the Front-Line Care Provider’s Readiness to Manage Maternal Cardiac Arrest: A Pre-test/Post-test St... by Mohamed Elsayed Saad Aboudonya (18466385)

“…The sample size consisted of three groups of front-line multidisciplinary obstetric maternal resuscitation teams (physicians, midwives, and nurses) divided into a pre-test group (N=30) and post-test group (N=30). The multidisciplinary resuscitation teams were observed during the cardiac arrest mock drills both before and after conducting the multidisciplinary resuscitation simulation-based training program and the introduction of the maternal resuscitation algorithm pathway against seven KPIs. …”

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

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Fuzzy Logic Based Patients' Monitoring System by Al-Dmour, Jumana

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Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems by Tarek Berghout (16905132)