Predicting Plasma Vitamin C Using Machine Learning حسب Daniel Kirk (17302798)

"…The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …"

L₂min^2/2s: Efficient Linear Reconstruction Filter for Incremental Delta-Sigma ADCs حسب Bo Wang (86769)

Target Detection Using Learning Methods حسب Sahnoon, Mohammad Moufeed

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Simultaneous analysis of frequency and voltage control of the interconnected hybrid power system in presence of FACTS devices and demand response scheme حسب Sudhanshu Ranjan (17151115)

"…System responses have been critically analyzed under Mine Blast Algorithm (MBA) based proportional–integral–derivative (PID) controllers</p><h2>Other Information</h2><p dir="ltr">Published in: Energy Reports<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.egyr.2021.10.100" target="_blank">https://dx.doi.org/10.1016/j.egyr.2021.10.100</a></p>…"

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study حسب Ayman Hassan (14426412)

"…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.…"

Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques حسب Ameema Zainab (16864263)

"…A spamicity score was awarded to each of the IoT devices by the algorithm, based on the feature importance and the root mean square error score of the machine learning models to determine the trustworthiness of the device in the home network. …"

Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data حسب Arfan Ahmed (17541309)

"…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …"

Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review حسب Avneet Kaur (712349)

"…It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. …"

Adaptive Federated Learning Architecture To Mitigate Non-IID Through Multi-Objective GA-Based Efficient Client Selection حسب Ajaj, Mohamad

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

"…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …"

Active distribution network type identification method of high proportion new energy power system based on source-load matching حسب Qinlin, Shi

"…Here, we report an active distribution network type identification method based on source-load matching. Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …"
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QU-GM: An IoT Based Glucose Monitoring System From Photoplethysmography, Blood Pressure, and Demographic Data Using Machine Learning حسب Md Nazmul Islam Shuzan (21842426)

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

"…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…"

Energy-Efficient Computation Offloading in Vehicular Edge Cloud Computing حسب Xin Li (51274)

"…Finally, we propose a low-complexity heuristic resource allocation algorithm based on this novel theoretical discovery. …"

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security حسب S. Shitharth (12017480)

"…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …"

Effective solutions for the capacitated vehicle routing problem and for the split delivery vehicle routing problem with time windows. (c2013) حسب Hilal, Nathalie

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Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling حسب Majed Hadid (17148364)

"…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …"

A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition حسب Hanif Heidari (22467148)

"…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …"

Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr... حسب Elmahdy, Samy

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Could Petrol Stations Play a Key Role in Transportation Electrification? A GIS-Based Coverage Maximization of Fast EV Chargers in Urban Environment حسب Safak Bayram (16925975)

"…More specifically, the location problem is modelled as a maximum coverage location problem (MCLP) and solved using a geographic information system (GIS) based platform. …"