Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions حسب Alaa Abd-alrazaq (17058018)

"…However, we also critically examine the challenges that such integration might pose by addressing issues of algorithmic bias, overreliance, plagiarism, misinformation, inequity, privacy, and copyright concerns in medical education. …"

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

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Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings حسب Ahmad Yaser Alhaddad (7017434)

"…Additionally, we evaluate the performance of the best developed model with children. Machine learning algorithms experiments showed that XGBoost achieved the best performance across all metrics (e.g., accuracy of 90%) and provided fast predictions (i.e., 0.004 s) for the test samples. …"

Uplink Noma in UAV-Assisted IoT Networks حسب Mrad, Ali

"…The first part of the thesis considers the problem of data collection from time-constrained IoT devices through deploying a UAV with uplink NOMA. …"
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Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network حسب Fares Almomani (12585685)

"…<p dir="ltr">The present study evaluates the effect of co-digestion of agricultural solid wastes (ASWs), cow manure (CM), and the application of chemical pre-treatment with NaHCO₃ on the performance of anaerobic digestion (AD) process. An Artificial neural network (ANN) algorithm was developed to model and optimize the cumulative methane production (CMP) from ASWs, CM, and their mixture under mesophilic and thermophilic conditions. …"

Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR) حسب Elaine Beller (44602)

"…Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. …"

Building power consumption datasets: Survey, taxonomy and future directions حسب Yassine Himeur (14158821)

"…Accordingly, a novel visualization strategy based on using power consumption micro-moments has been presented along with an example of deploying machine learning algorithms to classify the micro-moment classes and identify anomalous power usage.…"

MoveSchedule حسب Zouein, Pierette

"…MoveSchedule is validated using realistic project data and its solution is qualitatively assessed by an experienced engineer on that project.…"
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Framework for rapid design and optimisation of immersive battery cooling system حسب Ali Almshahy (23544823)

"…A conjugate heat transfer model for a 3S2P pouch cell module (20 Ah LiFePO₄) is developed and validated against experimental data (< 2% error). The CFD model of a battery module is developed to train an ultra-fast metamodel for battery geometry optimisation. …"

Adaptive Video Streaming Over Cognitive Radio Networks حسب Mohamed, Ala Eldin Omer

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Current trends and future orientation in diagnosing lung pathologies: A systematic survey حسب Noorizadeh, Mohammad

"…The CV processing method involves the application of advanced imaging techniques and machine learning algorithms to scrutinize and diagnose lung pathologies and ventilator-associated pneumonia (VAP). …"
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Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases حسب Muhammad Ali Muzammil (17910611)

"…Biases based on age, gender, and race result from unbalanced datasets. A model's performance is impacted when diverse demographics are inadequately represented. …"

AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients حسب Azar, Danielle

"…The performance of the three algorithms is evaluated on a data set found in the public UCMI repository.…"
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A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications حسب Sharafeddine, Sanaa

"…The proposed scheme monitors the signal strength level during the file transfer process and compresses data blocks on-the-fly only whenever energy reduction gain is expected. …"
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Exploring new horizons in neuroscience disease detection through innovative visual signal analysis حسب Nisreen Said Amer (17984077)

"…To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. …"

Barriers of Adopting Artificial Intelligence Tools in Engineering Construction Projects حسب ALKAABI, ABDULLA

"…The situation may cause concern and trepidation about integrating AI technologies and lack understanding of their optimal deployment and operation. Construction data management and integration are difficult. AI algorithms depend on data for training and analysis. …"
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Growing hierarchical self-organizing map for filtering intrusion detection alarms حسب Mansour, Nashat

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Capillary trapping in mixed-wet porous media: Implications for subsurface carbon dioxide sequestration حسب Saideep Pavuluri (21792941)

"…The study also highlights shortcomings of analyzing multiphase flows in mono-wet systems. Insights from this study can be used for improving pore network models and training machine learning algorithms.…"

Dynamic single node failure recovery in distributed storage systems حسب Itani, M.

"…We selected fractional repetition coding due to its simple repair mechanism that minimizes the repair and disk access bandwidths together with the property of un-coded repair process. To minimize the system repair cost, we formulate our problem using incidence matrices and solve it heuristically using genetic algorithms for all possible cases of single node failures. …"
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Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition حسب Abboud, Ralph

"…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …"
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