Three approaches to modelling heating and evaporation of monocomponent droplets by Dmitrii V. Antonov (21225041)

“…It is shown that the algorithm for the third approach predicts values which are close to the experimental data.…”

SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data by Tekli, Joe

“…This paper describes SemIndex+, a semantic-aware indexing and querying framework that allows semantic search, result selection, and result ranking of structured (relational DB-style), unstructured (IR-style), and partly structured (NoSQL) data. Various weighting functions and a parallelized search algorithm have been developed for that purpose and are presented here. …”
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Brain Source Localization in the Presence of Leadfield Perturbations by Momin, Rabiya Nakhat

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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter by Syed Rahman (569240)

“…In this paper, closed loop control of nine - level three - phase qZSI system is implemented using single FPGA control board thereby eliminating above said problems. …”

Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by 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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KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…The proposed method is compared with the ten top performing contemporary oversamplers by testing the accuracy of classifiers trained on augmented data provided by each oversampler. The experimental results on several common imbalanced datasets show that our method ranks first more consistently than the other state-of-art oversamplers. …”

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm by Abraham Marquez Alcaide (18582451)

“…<p dir="ltr">Hand-in-hand with the smart-grid paradigm development, power converters used in high-power applications are facing important challenges related to efficiency and power quality. …”

Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm by Mostafa Jabari (21841727)

“…The study evaluates the BDGOA by applying it to identify unknown parameters of five solar modules. The algorithm's effectiveness is demonstrated through the extraction of parameters for RTC France, PWP201, SM55, KC200GT, and SW255 models, validated against experimental data under diverse conditions. …”

A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) by Wehbe, Gioia Wahib

“…These discriminative motifs can be further studied to understand their role both at the evolutionary and disease levels.…”
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A Parallel Genetic Algorithm for the Geometrically Constrained Site Layout Problem with Unequal-Size Facilities by Zouein, Pierrette P.

“…Parallel genetic algorithms techniques have been used in a variety of computer engineering and science areas. …”
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Public health utility of cause of death data: applying empirical algorithms to improve data quality by Sarah Charlotte Johnson (9715415)

A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study by Masurkar, Faeez

“…Finally, a 3D Finite Element simulation was conducted to validate the findings and each observation resulting from the experiments. …”
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Integrated economic and environmental models for a multi stage cold supply chain under carbon tax regulation by Hariga, Moncer

“…The elevated level of public and organizations awareness concerning sustainability has necessitated the adoption of environmentally conscious practices in the management of supply chains. …”
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…A total of eleven hundred experimental data points for nine FPs (two stratified and seven dispersed patterns) in horizontal wellbores are used to develop the MLs. …”

Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

“…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain by Jun Zhu (84054)

“…The “MODIS-like” VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the “dark-target” algorithm that is applied to MODIS. …”

Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars by Abathar Al-Hamrani (16494884)

“…However, FRP-reinforced concrete (RC) structures exhibit less ductile response compared to steel RC structures. Recently, the use of basalt fiber reinforced concrete (BFRC) reinforced with BFRP bars was investigated to achieve a reasonable level of ductility in BFRC-BFRP one-way slabs. …”

Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”