QU-GM: An IoT Based Glucose Monitoring System From Photoplethysmography, Blood Pressure, and Demographic Data Using Machine Learning by Md Nazmul Islam Shuzan (21842426)

“…Furthermore, the proposed models were deployed in Amazon Web Server. The wristband is connected to an Android mobile application to collect real-time data and update the estimated glucose and diabetic severity every 10-seconds, which will allow the users to gain better control of their diabetic health.…”

A Survey of Data Clustering Techniques by Sobeh, Salma

“…Clustering, an unsupervised learning technique, aims to identify a specific number of clusters to effectively categorize the data through data grouping. Hence, clustering is related to many fields and is used in various applications that deal with large datasets. …”
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Smart transportation solutions for faster emergency medical services response using an enhanced whale optimization algorithm by Hina Gupta (21842246)

A comparison of data mapping algorithms for parallel iterative PDE solvers by Mansour, Nashat

“…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
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Stacking-based ensemble learning for remaining useful life estimation by Begum Ay Ture (17773170)

An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

“…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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Cortical EEG Source Localization of Focal Epilepsy by Siyam, Wisal Elfatih Mohamed

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The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

“…Five critical applications, such as network intrusion detection and malware detection, were identified, and several tasks used in these applications were observed. Most of the studies used supervised learning algorithms, and there were very limited studies that focused on other types of machine learning. …”

Information reconciliation through agent controlled graph model. (c2018) by Saba, Rita

“…Multiple models have been proposed and different techniques and data structures were used. …”
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Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks by Javed Butt , Usman

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Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

“…The most important question when using multimodal data is how to fuse them—a field of growing interest among researchers. …”

Data Endowment as a Digital Waqf: An Islamic Ethical Framework for AI Development by Abdulqadir J. Nashwan (11659453)

“…<p dir="ltr">In the era of artificial intelligence (AI), data is often called the new oil—an essential asset for training algorithms and fueling intelligent systems. …”

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. …”

Predicting Plasma Vitamin C Using Machine Learning by Daniel Kirk (17302798)

“…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”

A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm by Amirsajjad Rahmani (17541453)

“…The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”

A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System by Ameema Zainab (16864263)

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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)

Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem by El Khoury, John

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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption by Azadeh, Ali

“…To show the applicability of the proposed approach, Iran’s bitumen consumption data in the period of 1991-2006 are used as a case study. …”
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