Integrated whole transcriptome and small RNA analysis revealed multiple regulatory networks in colorectal cancer by Hibah Shaath (5599658)

“…Additionally, potential interaction between differentially expressed lncRNAs such as H19, SNHG5, and GATA2-AS1 with multiple miRNAs has been revealed. Taken together, our data provides thorough analysis of dysregulated protein-coding and non-coding RNAs in CRC highlighting numerous associations and regulatory networks thus providing better understanding of CRC.…”

R-CONV++: uncovering privacy vulnerabilities through analytical gradient inversion attacks by Tamer Ahmed Eltaras (22565414)

“…The first algorithm presents a novel data leakage method that efficiently exploits convolutional layer gradients, demonstrating that even with non-fully invertible activation functions, such as ReLU, training samples can be analytically reconstructed directly from gradients without the need to reconstruct intermediate layer outputs. …”

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

“…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …”

Left Ventricular Wall Motion Estimation by Active Polynomials for Acute Myocardial Infarction Detection by Serkan Kiranyaz (3762058)

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models by Osama Bassam J. Rabie (21323741)

“…It also supports increasing the training speed and reducing the error rate of the classifier. …”

Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

“…., Internet of Things devices) for the training of machine learning models. However, selecting the participants that would contribute to this collaborative training is highly challenging. …”
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A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation by Kfouri, Ronald

“…Due to the lack of public frameworks, we create a dataset that emulates real-life scenarios to train and test the neural network. Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …”
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Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review by Yazeed Yasin Ghadi (16667109)

“…These devices will have complete artificial intelligence capabilities, enabling them to understand their environment and respond. During the training phase, machine-learning systems may face challenges due to the large amount of data required and the complex nature of the training procedure. …”

Can AI Help in Screening Viral and COVID-19 Pneumonia? by Muhammad E. H. Chowdhury (14150526)

Video Streaming over D2D Networks by Ahmed, Ibtihal Mohamed Taha

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Wearable Real-Time Heart Attack Detection and Warning System to Reduce Road Accidents by Muhammad E. H. Chowdhury (14150526)

“…Linear classification and several machine algorithms were trained and tested for real-time application. …”

Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review by Francisco Monteiro-Guerra (16864122)

Deep and transfer learning for building occupancy detection: A review and comparative analysis by Aya Nabil Sayed (17317006)

“…Moreover, the paper conducted a comparative study of the readily available algorithms for occupancy detection to determine the optimal method in regards to training time and testing accuracy. …”

Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles by Zainab Akhtar (15192184)

“…Neural network-based methods tackle these problems by accurately approximating unknown nonlinearities through training on input-output data. This paper proposes an adaptive Multi-layer Neural Network (MLNN) Luenberger observer-based control for altitude and attitude tracking of a quadrotor UAV. …”

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

“…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.…”

An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System by Alkhatib, Osama

“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. …”
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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…In this paper, a Dual-Deep-Network technique is described for the extraction of statistical structures from a hybrid beam forming model based on mmWave logics, as well as training logic for the network map functions. The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”

Target Detection Using Learning Methods by Sahnoon, Mohammad Moufeed

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Using machine learning for disease detection. (c2013) by Jreij, Georges Antoun

“…Classification has three main components: the classification algorithm, the pre-classified data (training data) and the un-classified data (testing data). …”
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Computation of conformal invariants by Mohamed M.S., Nasser

“…In particular, we provide an algorithm for computing the conformal capacity of a condenser. …”
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