Proactive machine learning-based solution for advanced manageability of multi-persona mobile computing by Tout, Hanine

“…A dynamic programming algorithm is advocated to find the adequate strategies. …”
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Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation by Hariprasath Manoharan (14157966)

“…Therefore, the suggested approach finds the main hole in undersea systems and fills it using robotic automation. …”

Anomaly Detection Based Framework for Profile Monitoring by Al-Rahim, Nour Al-Huda Z. Al-Abed

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Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace by Shahid, Saif Mohammad

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The effects of data balancing approaches: A case study by Paul Mooijman (4453189)

“…In this research, classification algorithms, combined with resampling strategies and dimensionality reduction methods, were investigated to find a prediction model to correctly identify the samples of treated animals. …”

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)

“…The findings demonstrate that coupling data-driven soiling optimization with refined albedo representation modernizes the predictive capabilities of PVsyst and SAM, yielding more reliable performance forecasts. …”

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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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…This research highlights the ability of AI to develop adaptable, effective, and successful e-learning environments, promoting enhanced academic achievement and customized learning experiences. The findings demonstrate that CNN outperformed other deep learning and machine learning algorithms in terms of accuracy during the prediction phase, showcasing the advanced capabilities of AI in educational contexts. …”

Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling by Armin, Amindari

“…However, implementation of this approach is difficult using custom built codes and algorithms. In this paper, we present an FSI modeling methodology for aortic valve hemodynamics using a commercial modeling software, ANSYS. …”
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Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling by Amindari, Armin

“…However, implementation of this approach is difficult using custom built codes and algorithms. In this paper, we present an FSI modeling methodology for aortic valve hemodynamics using a commercial modeling software, ANSYS. …”
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Seasonal variations in feed-water chemistry and fouling dynamics of reverse-osmosis systems: A global climate lens by Nasser Zareei (22921226)

“…Through this review, three principal findings emerge. First, climate-specific seasonal fouling regimes are distinct and mechanistically predictable patterns: arid coasts (BWh) experience summer biofouling synergistically amplified by gypsum scaling; temperate systems (Cfa, Dwa) face winter organic fouling from recalcitrant humics despite reduced microbial activity; and tropical intakes (Aw, Am) endure monsoonal pulses that increase both colloidal fouling and dissolved organics by 5–100× relative to dry-season baselines. …”

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

“…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. …”

Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine by Naila, Rabbani

“…Development of diagnostic algorithms by artificial intelligence machine learning is enhancing the applications of glycation biomarkers. …”
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A comparative analysis to forecast carbon dioxide emissions by Md. Omer Faruque (17545671)

“…Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). …”

Machine Learning Model for a Sustainable Drilling Process by Alsaidi, Ola

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Iterative Methods for the Solution of a Steady State Biofilter Model by Salih, Mubarak Sahal

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Applications of artificial intelligence in emergency and critical care diagnostics: a systematic review and meta-analysis by Jithin Kalathikudiyil Sreedharan (18268894)

“…It uses various models and algorithms to detect patterns and specific findings to diagnose a disease with utmost accuracy. …”

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications by Abdallah Falah Mohammad Aldwekat (22457821)

“…By 2090, a 44.56 % (range: 33–57.9 %) across the models, increase in suitable habitat is predicted, accompanied by a 27.66 % (range: 22.4–31.7 %) loss of current habitats. …”

Assessment of network module identification across complex diseases by Sarvenaz Choobdar (18602821)

“…Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. …”

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

“…A comparative evaluation of three FL algorithms (FedAvg, FedProx, Mime-lite) identifies the most suitable aggregation strategy. …”