Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier حسب Yassine Himeur (14158821)

"…Specifically, short local histograms are drawn to represent individual appliance consumption signatures and robustly extract appliance-level data from the aggregated power signal. Furthermore, an improved k-nearest neighbors (IKNN) algorithm is presented to reduce the learning computation time and improve the classification performance. …"

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models حسب 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. …"

Tailoring motivational health messages for smoking cessation using an mHealth recommender system integrated with an electronic health record: a study protocol حسب Santiago Hors-Fraile (5950823)

"…Patients’ feedback on the messages and their interactions with the app will be analyzed and evaluated following an observational prospective methodology to a) assess the perceived quality of the mobile-based health recommender system and the messages, using the precision and time-to-read metrics and an 18-item questionnaire delivered to all patients who complete the program, and b) measure patient engagement with the mobile-based health recommender system using aggregated data analytic metrics like session frequency and, to determine the individual-level engagement, the rate of read messages for each user. …"

Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model حسب 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. …"

Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition حسب Dabeeruddin Syed (16864260)

"…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …"

Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams حسب Eduardo Feo-Flushing (23276023)

"…Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. …"

Establishing Autonomous AUS-Quadrotor حسب Al Younes, Younes

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A novel few shot learning derived architecture for long-term HbA1c prediction حسب Marwa Qaraqe (10135172)

"…Despite the impact of such prediction capabilities, no work in the literature or industry has investigated the futuristic prediction of HbA1c using current blood glucose (BG) measurements. For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. …"

A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai حسب ALGHANEM, HANI SUBHI MOHD

"…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …"
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Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review حسب Loay A. Salman (14150322)

"…</p><h3>Conclusion</h3><p dir="ltr">This study demonstrated the potential of AI as a valuable complement for planning TKA, exhibiting a satisfactory level of reliability in predicting TKA implant sizes. …"

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

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Comparative Study of Control Strategies for Under Actuated Manipulator حسب Abed, Joudeh Yasin

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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... حسب Tarik Elhadd (5480393)

"…The optimal XGBoost model prioritized age, gender, BMI and HbA1c followed by glucose levels and physical activity. Interestingly, the blood glucose level prediction by our model was influenced by use of SGLT2i.…"

Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP حسب Abdelhafez, Nada

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Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes حسب Muhammad Mohsin Khan (22150360)

"…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …"

Optimizing clopidogrel dose response حسب Saab, Yolande B.

"…The aim of the study is to investigate the cumulative effect of CYP2C19 gene polymorphisms and drug interactions that affects clopidogrel dosing, and apply it into a new clinical-pharmacogenetic algorithm that can be used by clinicians in optimizing clopidogrel-based treatment. …"
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Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace حسب Shahid, Saif Mohammad

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Multi-Model Investigation and Adaptive Estimation of the Acoustic Release of a Model Drug From Liposomes حسب Wadi, Ali

"…Then, the algorithm was used to process the five experimental datasets. …"
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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information حسب 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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MoveSchedule حسب Zouein, Pierette

"…The layout construction algorithm that underlies MoveSchedule uses Constraint Satisfaction to find the set of all positions that meet the constraints on resources' positions and Linear Programming to find the optimal positions that minimize resource transportation and relocation costs. …"
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