Collaborative Caching for D2D Content Sharing in 5G by Abdelsalam, Ansam Elfadil Kamel

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Dynamic multiple node failure recovery in distributed storage systems by Itani, May

“…In this work, we address the problem of multiple failure recovery with dynamic scenarios using the fractional repetition code as a redundancy scheme. The fractional repetition (FR) code is a class of regenerating codes that concatenates a maximum distance separable code (MDS) with an inner fractional repetition code where data is split into several blocks then replicated and multiple replicas of each block are stored on various system nodes. …”
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Indoor Localization Schemes for Mobile Robots by Al-Jarrah, Islam Mohammad-Amin

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Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures by JUMA, MAZEN GHAZI

“…The technology stack of the proposed solution was also implemented with four algorithms and eight protocols. …”
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Detection of statistically significant network changes in complex biological networks by Raghvendra Mall (581171)

“…Moreover, the structure of the proposed algorithm allows for a faster parallelized implementation.…”

Video Streaming over D2D Networks by Ahmed, Ibtihal Mohamed Taha

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Combinatorial method for bandwidth selection in wind speed kernel density estimation by El Dakkak, Omar

“…This goal calls for devising probabilistic models with adaptive algorithms that accurately fit wind speed distributions. …”
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The architecture of a highly reconfigurable RISC dataflow array processor by Sait, Sadiq M.

“…This processor forms an element of a processor array which possess the features of both static and dynamic dataflow models. The array can be programmed to execute arbitrary algorithms in both static and dynamic manner. …”
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Cooperative Caching Policy in Fog Computing for Connected Vehicles by Ghazleh, Ali

“…Furthermore, the results showed the proposed model's effectiveness compared to traditional algorithms.…”
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Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

“…Traditional machine learning-based defect prediction models have been built since the early 2000s, and recently, deep learning-based models have been designed and implemented. …”

The Effects of Data Mining on Small Businesses in Dubai by AlMutawa, Rasha

“…While there are numerous studies on the best data mining models and their uses, even on certain industries, this study focuses on the applications more than the algorithms and models and their usefulness for small businesses specifically. …”
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Condenser capacity and hyperbolic perimeterImage 1 by Mohamed M.S., Nasser

“…We study the conformal capacity by using novel computational algorithms based on implementations of the fast multipole method, and analytic techniques. …”
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Four quadrant robust quick response optimally efficient inverterfed induction motor drive by Islam, S.M.

“…Simulation results with a 100-hp motor show that up to 80% savings in controllable losses are achievable at light load, and the motor can reach rated speed in just 750 ms. The control algorithms developed are readily implementable with present-day microprocessors…”
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Design and analysis of efficient and secure elliptic curve cryptoprocessors. by Al-Somani, Turki Faisal

“…The proposed architectures have been modeled using VHDL and implemented on FPGA platform.…”
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LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…The main aim was to predict the initial leukemia disease. Machine learning algorithms such as decision tree (DT), naive bayes (NB), random forest (RF), gradient boosting machine (GBM), linear regression (LinR), support vector machine (SVM), and novel approach based on the combination of Logistic Regression (LR), DT and SVM named as ensemble LDSVM model. …”

Prototype project management tool (PPMT) with cocomo calibration. (c1998) by Haddad, Ibrahim F.

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Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…However, limited datasets in affective computing and healthcare research can lead to inaccurate conclusions regarding the ML model performance. This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”

Using C++ to Calculate SO(10) Tensor Couplings by Bhagwagar, Azadan

“…Model building in SO(10), which is the leading grand unification framework, often involves large Higgs representations and their couplings. …”
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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…The practical results obtained by implementing machine learning and deep learning models, such as convolutional neural networks (CNN) and recurrent neural networks (RNN), show substantial enhancements in forecasting different performance metrics. …”

Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine by Majd A. AbuAlrob (22392505)

“…Ethical considerations, such as safeguarding patient privacy, ensuring data security, and mitigating algorithmic bias, underscore the importance of responsible AI integration. …”