THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar by M. Walid Qoronfleh (14153088)

Applying urban parametric design optimisation processes to a hot climate: Case study of the UAE by Taleb, Hanan

“…Parametric and algorithmic design is considered a current trend in architectural design processes. …”
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Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

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Impact of AI and Dynamic Ensemble Techniques in Enhancing Healthcare Services: Opportunities and Ethical Challenges by Haseeb Javed (18576340)

Optimizing microgrid efficiency: Coordinating commercial and residential demand patterns with shared battery energy storage by Mohammadreza Gholami (17032317)

“…Utilizing a Firefly Algorithm (FA) for optimization, the study determines the optimized BESS capacity for minimum total cost. …”

Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study by Muhammad Atif Butt (10849980)

“…Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. …”

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

Tensile Test Optimization Using the Design of Experiment and Soft Computing by Mehdi Moayyedian (14880358)

“…The marginal error of only 0.72% in the hybrid approach showcases its high precision and reliability in determining the optimal levels of machining parameters. These findings underscore the potential of the Taguchi optimization method, ANFIS, and GA in achieving superior results in the tensile testing of materials, particularly in cases where multiple parameters are involved. …”

Performance Modeling of Rooftop PV Systems in Arid Climate, a Case Study for Qatar: Impact of Soiling Losses and Albedo Using PVsyst and SAM by Sachin Jain (19161721)

Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV by Zulkifli, Muhammad

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Teachers' Perceptions of the Role of Artificial Intelligence in Facilitating Inclusive Practices for Students with Special Educational Needs and Disabilities: A Case Study in a Pri... by BACHIR, HIBAH AHMAD

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Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach by Haitham Osman (11737057)

The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions by Abdulmalik Alwarafy (17984104)

“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”

Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods by Sivakavi Naga Venkata Bramareswara Rao (15944992)

“…In addition, three distinct optimization techniques are used to find the optimum ANN training algorithm: Levenberg–Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. …”

Identifying Regional Trends in Avatar Customization by Peter Mawhorter (18602944)

Learning-Based Spectrum Sensing and Access for Cognitive Radio Systems by Shehabeldin, Menatalla Diaaeldin

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Multidimensional Gains for Stochastic Approximation by Saab, Samer S.

“…Two algorithms are proposed: one for the case where M≥ N and the second one for the antithesis. …”
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Competitive learning/reflected residual vector quantization for coding angiogram images by Mourn, W.A.H.

“…Medical images need to be compressed for the purpose of storage/transmission of a large volume of medical data. Reflected residual vector quantization (RRVQ) has emerged recently as one of the computationally cheap compression algorithms. …”
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Design and analysis of entropy-constrained reflected residual vector quantization by Mousa, W.A.H.

“…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. …”
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A hybrid Harris Hawks optimizer for economic load dispatch problems by Al-Betar, Mohammed Azmi

“…Furthermore, the proposed algorithm is evaluated on two ELD real-world cases which are 6 units-1263 MW and 15units-2630 MW. …”
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