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

“…<h3>Introduction</h3><p dir="ltr">Diabetes Mellitus (DM) is characterized by impaired ability to metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia). …”

Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective by Zhitao Xu (2426023)

“…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …”

Conceptual Design and Analysis of Concentrated Photovoltaic Thermal (CPVT) Solar Collectors with Different Configurations by Sharaf, Omar Z.

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

Systems biology analysis reveals NFAT5 as a novel biomarker and master regulator of inflammatory breast cancer by Andrea Remo (447375)

“…</p><h3>Methods</h3><p dir="ltr">In-silico modeling and Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) on IBC/non-IBC (nIBC) gene expression data (n = 197) was employed to identify novel master regulators connected to the IBC phenotype. …”

Multi-Agent Variational Approach for Robotics: A Bio-Inspired Perspective by Mir, Imran

“…Stochastic factors are integrated into the Aquila Optimizer to enhance the algorithm's efficiency. The architecture, called the Multi-Agent Exploration - Parameterized Aquila Optimizer (MAE-PAO), starts by using deterministic MAE to assess the cost and utility values of nearby cells encircling the agents. …”
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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)

“…Hamad International Training Center not only offers formal resuscitation training like Advanced Life Support Obstetrics and Neonatal Resuscitation Program courses but also ensures the frontline care providers’ readiness for managing cardiac arrest events in Hamad Medical Corporation facilities through regular mock drills and monitoring the relevant Key Performance Indicators (KPIs). The study aimed to explore the impact of a multidisciplinary maternal resuscitation training program and the introduction of the maternal resuscitation algorithm pathway (Figure 1) on the relevant seven KPIs.…”

Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review by Asma Alamgir (18288895)

“…Data extracted from the included studies were synthesized narratively.…”

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Then, the Conjugate Self-Organizing Migration (CSOM) optimization algorithm is deployed to select the most relevant features to train the classifier, which also supports increased detection accuracy. …”

An Ontology-based Semantic Web for Arabic Question Answering: The Case of E-Government Services by ALBARGHOTHI, ALI BAHA’EDDIN

“…Further, 414 automatic questions are tested on the QA algorithm using two methods, semantics-based and keyword-based. …”
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HPTS: heterogeneous parallel tabu search for VLSI placement by Al-Yamani, A.

“…Two parallelization strategies, i.e., functional decomposition and multi-search thread strategies are integrated. The proposed algorithm is tested on the VLSI standard cell placement problem, however, the same algorithm can be used on any combinatorial optimization problem. …”
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Multi-UAV-Enabled Mobile Edge Computing IoT Systems: Joint Association and Resource Allocation Framework by Abu Farha, Yazan Mahmoud

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A multi-pretraining U-Net architecture for semantic segmentation by Cagla Copurkaya (22502042)

“…The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. For the validation of the proposed model, we used data from 21,000 cell nuclei at a resolution of 1000 by 1000 pixels. …”

Control of cardiac alternans by mechanical and electrical feedback by Yapari, Felicia

“…Complimentary to these studies, a three variable Nash-Panfilov model is used to investigate alternans annihilation via mechanical (or stretch) perturbations. …”
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Performance Prediction Using Classification by MOOLIYIL, GITA

“…Principal component analysis and feature selection by weights using information gain ratio, Gini index, correlation and PCA is used to determine the relevant predictors of the datasets used. This study also addresses gaps in the current available literature on performance prediction, such as data imbalance and the use of Ensemble models. …”
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Tailoring motivational health messages for smoking cessation using an mHealth recommender system integrated with an electronic health record: a study protocol by Santiago Hors-Fraile (5950823)

“…Health recommender systems are information-filtering algorithms that can choose the most relevant health-related items—for instance, motivational messages aimed at smoking cessation—for each user based on his or her profile. …”

Impact of birth weight to placental weight ratio and other perinatal risk factors on left ventricular dimensions in newborns: a prospective cohort analysis by Ashraf Gad (17040114)

“…Missing data were imputed with principal component analysis. …”

Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe

“…In the past decade, there has been an increasing need for semantic-aware data search and indexing in textual (structured and NoSQL) databases, as full-text search systems became available to non-experts where users have no knowledge about the data being searched and often formulate query keywords which are different from those used by the authors in indexing relevant documents, thus producing noisy and sometimes irrelevant results. …”
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A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis by Alaa Abd-Alrazaq (17430900)

“…Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.…”

Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…Hence, detecting any act of cyberbullying in an automated manner will be helpful for stakeholders to prevent any unfortunate results from the victim’s perspective. Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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