Now showing items 1-5 of 5
The development of a reviewer selection method: a multi-level hesitant fuzzy VIKOR and TOPSIS approaches
This paper proposes a new approach for the selection of reviewers to evaluate research and development (R&D) projects using a new integrated hesitant fuzzy VIKOR and TOPSIS methodology. A reviewer selection model must have ...
Comparative Study for Tuberculosis Detection by Using Deep Learning
Tuberculosis (TB) is an infectious disease which becomes a significant health problem worldwide. Many people have been affected by this disease owing to deficiency of treatment and late or inaccuracy of diagnosis. Therefore, ...
Automated Tuberculosis Detection Using Pre-Trained CNN and SVM
Tuberculosis (TB) is a dreadfully contagious and life-threatening disease if left untreated. Therefore, early and accurate diagnosis is critical for treatment. Today, invasive, expensive, or time-consuming tests are performed ...
Obesity Level Estimation based on Machine Learning Methods and Artificial Neural Networks
Obesity is a growing societal and public health problem starting from 1980 that needs more attention. For this reason, new studies are emerging day by day, including those looking for obesity in children, especially the ...
A New Multi-Echelon Repair Network Model with Multiple Upstream Locations for Level of Repair Analysis Problem
Level of repair analysis (LORA) determines (1) the best decision during a malfunction of each product component; (2) the location in the repair network to perform the decision and (3) the quantity of required resources in ...