Reputation-based cooperative detection model of selfish nodes in cluster-based QoS-OLSR protocol. (c2014) by Moati, Nadia

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Guidance, Control and Trajectory Tracking of Small Fixed Wing Unmanned Aerial Vehicles (UAV's) by Al-Radaideh, Amer

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

“…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. …”

Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers by Yousef, Hibba

“…In this study, we developed an interpretable machine learning model leveraging baseline levels of biomarkers of oxidative stress (OS), inflammation, and mitochondrial dysfunction (MD) for identifying individuals at risk of developing T2DM. …”
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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. …”

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)

“…The novelty of this work is, a recently developed DRF optimization methodology incorporated with the machine learning algorithm is utilized for maximizing the security level of IoT systems. …”

Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques by Kais Abdulmawjood (17947784)

Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…The performance level improvements are practically summarized in both the transmission and reception entities with the help of the proposed hybrid network architecture and the associated Dual Deep Network algorithm. …”

Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

“…This basically follows either a feature-level or decision-level strategy. In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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Energy-Efficient Computation Offloading in Vehicular Edge Cloud Computing by Xin Li (51274)

“…In this article, we study an adaptive wireless resource allocation strategy of computation offloading service under a three-layered vehicular edge cloud computing framework. We model the computation offloading process at the minimum assignable wireless resource block level, which can better adapt to vehicular computation offloading scenarios and can also rapidly evolve to the 5G network. …”

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma by Rawan AlSaad (14159019)

“…</p><h3>Results</h3><p dir="ltr">Our experimental evaluation demonstrate that whenever a clear visit-level pattern exists, the models learn that pattern and the contextual decomposition can appropriately attribute the prediction to the correct pattern. …”

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... by Tarik Elhadd (5480393)

“…Interestingly, the blood glucose level prediction by our model was influenced by use of SGLT2i.…”

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

On the Provisioning of Ultra-Reliable Low-Latency Services in IoT Networks with Multipath Diversity by Sweidan, Zahraa

“…Simulation results are presented for both parts of the thesis to illustrate the effectiveness of the proposed solutions and algorithms in comparison with optimal solutions and baseline algorithms.…”
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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series by Lasfer, Assia

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

“…The main purpose is to bridge the gap between EDM and International Assessments in the Arab world by applying EDM to predict Grade-4 student levels in TIMSS assessments in the UAE. We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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Peak Loads Shaving in a Team of Cooperating Smart Buildings Powered Solar PV-Based Microgrids by Ahmed Ouammi (14151039)

“…The developed predictive model is implemented as a smart energy management based high-level control of the TCM to reduce/shave the peak loads and satisfy the EVs power demands through a coordination of the power exchanges between the microgrids. …”

Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation by Zakaria Shams Siam (22048001)

“…Efforts are underway to develop algorithms that can generate 7T MRI from 3T MRI to achieve better image quality without the need for 7T MRI machines. …”

Corona power loss computation in bundled bipolar conductors by Al-Hamouz, Z.M.

“…In this paper, a finite element (FE) based algorithm devoted for the computation of the corona current and hence the corona power loss associated with bundled bipolar high voltage direct current (HVDC) conductors is presented. …”
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Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants by Shafiq, M.

“…The U-model is utilized to design an adaptive inverse controller by using a simple root-solving algorithm of Newton-Raphson. The synergy of U-model with AIC structure has provided an effective and straight forward method for adaptive tracking of nonlinear plants. …”
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