A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48 by Al-Manaseer, Hitham

“…The performance of the algorithms for accuracy was evaluated using the Healthcare (heart attack possibility) dataset, freely available on kagle. …”
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QU-GM: An IoT Based Glucose Monitoring System From Photoplethysmography, Blood Pressure, and Demographic Data Using Machine Learning by Md Nazmul Islam Shuzan (21842426)

“…We collected PPG signals, demographic information, and blood pressure data from 139 diabetic (49.65%) and non-diabetic (50.35%) subjects. …”

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

“…</p><h3>Methods</h3><p dir="ltr">Using historical data (2008-2020), an accurate prediction model using machine learning methods was developed and incorporated into a mobile app. …”

A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems by Faria Nawshin (21841598)

“…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL in these devices exposes them to adversarial attacks that can compromise user data and device security. …”

Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…LR with the reduced feature set using the intersection between CS and RFE proved to be the best model among the tested algorithms. …”
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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. …”

Stochastic Search Algorithms for Exam Scheduling by Mansour, Nashat

“…Then, we empirically compare the three proposed algorithms and FESP using realistic data. Our experimental results show that SA and GA produce good exam schedules that are better than those of FESP heuristic procedure. …”
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Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

“…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
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Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

“…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
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Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

“…They then present a numerical controller design algorithm based on the derived bounds.Examples are used for demonstration.…”
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Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”

Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence by Atiq Ur Rehman (8843024)

“…Keeping in view the need of an optimization algorithm with fast convergence speed, suitable for high dimensional data space, this article proposes a novel concept of Multi-Cluster Jumping PSO. …”

Data Redundancy Management in Connected Environments by Mansour, Elio

“…., building) equipped with sensors that produce and exchange raw data. Although the sensed data is considered to contain useful and valuable information, yet it might include various inconsistencies such as data redundancies, anomalies, and missing values. …”
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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. …”

Process Mining over Unordered Event Streams by Awad, Ahmed

“…This requires online algorithms that, instead of keeping the whole history of event data, work incrementally and update analysis results upon the arrival of new events. …”
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Android Malware Detection Using Machine Learning by Al Ali, Shaikha

“…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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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)

“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”

Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by Zakaria Tolba (16904718)

“…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …”

Image-CNN Based Process Control of Profile by Zeinab, Zeinab Jihad

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