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... by Elmahdy, Samy

“…The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. …”
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A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

“…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. In this paper, we proposed a novel technique in steganography within the digital images such is RGB, Gray Scale, Texture, Aerial images to achieve higher security, imperceptibility, capacity, and robustness as compared with existing methods. …”

A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

“…To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. A Newton-based algorithm is also adopted for solving the nonlinear systems resulting from the considered monolithic approach. …”
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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System by Abougharib, Arwa

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Modelling of pollutant transport in compound open channels by Chatila, Jean Georges

“…The numerical computation of open-channel flows requires preparing and processing larger volumes of boundary and bathymetry data for computer inputs and the development of numerical algorithms for treating complex boundary condition, channel properties, and free surface effects. …”
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Evolutionary support vector regression for monitoring Poisson profiles by Ali Yeganeh (16624998)

“…This paper aims to monitor Poisson profile monitoring problem in Phase II and develops a new robust control chart using support vector regression by incorporating some novel input features and evolutionary training algorithm. …”

Metallic coating thickness assessment over nonmagnetic metals using eddy current technology by Ansari, Zain Ali

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MoveSchedule by 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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An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication by Syed Muhammad Amrr (16855557)

“…The control law is developed using a state-dependent single feedback vector, which further assists in obeying the constrained network. …”

Advancing Data Center Networks: A Focus on Energy and Cost Efficiency by Zina Chkirbene (16869987)

“…These topologies must incorporate fault-tolerant and efficient routing algorithms. Consequently, the data center network topology must dynamically adapt to ever-changing application requirements. …”

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

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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”

Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…Considering the high cost and time-consuming experimental investigations, computational methods, particularly machine learning algorithms, can be the appropriate approach for efficiently screening the metal alloys as the electrocatalysts. …”

Defining quantitative rules for identifying influential researchers: Insights from mathematics domain by Ghulam Mustafa (458105)

“…To perform the experiment, we focused on the field of mathematics and used a dataset containing 525 individuals who received awards and 525 individuals who did not receive awards. The rules were developed for each parameter category using the Decision Tree Algorithm, which achieved an average accuracy of 70 to 75 percent for identifying awardees in mathematics domains. …”

Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting by Abdelkader Baggag (16864140)

“…The learned factors, with a graph-based temporal dependency, are then used in an autoregressive algorithm to predict the future state of the road network with a large horizon. …”

Real-Time Implementation of GPS Aided Low Cost Strapdown Inertial Navigation System by Sahawneh, Laith Rasmi

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A comparative analysis to forecast carbon dioxide emissions by Md. Omer Faruque (17545671)

“…This leads to the second step, which involves formulating the multivariate time series CO₂ emissions forecasting challenges considering its influential factors. 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). …”

Systems biology analysis reveals NFAT5 as a novel biomarker and master regulator of inflammatory breast cancer by Andrea Remo (447375)

“…The NFAT5 transcription factor might be developed into routine clinical practice as a putative biomarker of IBC phenotype.…”

Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by 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. …”