Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…This strategy </p><p dir="ltr">not only improves detection efficiency and accuracy but also supports early diagnosis and treatment planning, </p><p dir="ltr">leading to better patient outcomes. By leveraging the binary GWO algorithm to optimize the feature selection </p><p dir="ltr">process and CNNs for image classification, the proposed approach reduces computational costs while increasing </p><p dir="ltr">classification accuracy. …”

Datasets and their properties. by Olaide N. Oyelade (14047002)

“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”

Parameter settings. by Olaide N. Oyelade (14047002)

“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”

Hyperparameters of the LSTM Model. by Ahmed M. Elshewey (21463867)

“…This effectively balances exploration and exploitation, and addresses the early convergence problem of the original algorithms. To choose the most crucial characteristics of the dataset, the feature selection method employs the binary format of AD-PSO-Guided WOA. …”

The AD-PSO-Guided WOA LSTM framework. by Ahmed M. Elshewey (21463867)

“…This effectively balances exploration and exploitation, and addresses the early convergence problem of the original algorithms. To choose the most crucial characteristics of the dataset, the feature selection method employs the binary format of AD-PSO-Guided WOA. …”

Prediction results of individual models. by Ahmed M. Elshewey (21463867)

“…This effectively balances exploration and exploitation, and addresses the early convergence problem of the original algorithms. To choose the most crucial characteristics of the dataset, the feature selection method employs the binary format of AD-PSO-Guided WOA. …”

Iteration curve of the optimization process. by Meijun Shang (22806461)

“…The load-bearing mechanism of the proposed steel platform was analyzed theoretically, and finite element analysis (FEA) was employed to evaluate the stresses and deflections of key members. A particle swarm optimization (PSO) algorithm was integrated with the FEA model to optimize the cross-sectional dimensions of the primary beams, secondary beams, and foundation boxes, achieving a balance between load-bearing capacity and cost efficiency. …”

Data_Sheet_1_Early detection of sepsis using machine learning algorithms: a systematic review and network meta-analysis.pdf by Mikhail Ya Yadgarov (18543769)

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by D. Andrew Brown (6584837)

Data_Sheet_1_Determination of phage load and administration time in simulated occurrences of antibacterial treatments.docx by Steffen Plunder (14022498)

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

“…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …”

Data_Sheet_1_Adaptive restraint design for a diverse population through machine learning.pdf by Wenbo Sun (531308)

Optimal Timings Codebook.xlsx by Emma Spillane (11249121)

Data_Sheet_1_A Bayesian Model to Analyze the Association of Rheumatoid Arthritis With Risk Factors and Their Interactions.PDF by Leon Lufkin (11276856)

datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf by Jan Tönshoff (10192709)

Optimal Time Intervals of Breech Births Dataset by Emma Spillane (11249121)

A portfolio selection model based on the knapsack problem under uncertainty by Fereshteh Vaezi (6655028)

“…The resulted model is converted into a parametric linear programming model in which the decision maker is able to determine the optimism threshold. Finally, a discrete firefly algorithm is designed to find the near optional solutions in large dimensions. …”

Malware detection workflow in compressed archives by Paul A. Gagniuc (1818325)

Heavy-load transfer steel platform. by Meijun Shang (22806461)

“…The load-bearing mechanism of the proposed steel platform was analyzed theoretically, and finite element analysis (FEA) was employed to evaluate the stresses and deflections of key members. A particle swarm optimization (PSO) algorithm was integrated with the FEA model to optimize the cross-sectional dimensions of the primary beams, secondary beams, and foundation boxes, achieving a balance between load-bearing capacity and cost efficiency. …”

Traditional scaffolding reinforcement system. by Meijun Shang (22806461)

“…The load-bearing mechanism of the proposed steel platform was analyzed theoretically, and finite element analysis (FEA) was employed to evaluate the stresses and deflections of key members. A particle swarm optimization (PSO) algorithm was integrated with the FEA model to optimize the cross-sectional dimensions of the primary beams, secondary beams, and foundation boxes, achieving a balance between load-bearing capacity and cost efficiency. …”