Neural network-based method for diagnosis and severity assessment of Graves' orbitopathy using orbital computed tomography.

Computed tomography (CT) has been widely used to diagnose Graves' orbitopathy, and the utility is gradually increasing. To develop a neural network (NN)-based method for diagnosis and severity assessment of Graves' orbitopathy (GO) using orbital CT, a specific type of NN optimized for diagnosing GO was developed and trained using 288 orbital CT scans obtained from patients with mild and moderate-to-severe GO and normal controls. The developed NN was compared with three conventional NNs [GoogleNet Inception v1 (GoogLeNet), 50-layer Deep Residual Learning (ResNet-50), and 16-layer Very Deep Convolutional Network from Visual Geometry group (VGG-16)].

Multi-Population Genetic Algorithm for Multilabel Feature Selection Based on Label Complementary Communication.

Multilabel feature selection is an effective preprocessing step for improving multilabel classification accuracy, because it highlights discriminative features for multiple labels. Recently, multi-population genetic algorithms have gained significant attention with regard to feature selection studies. This is owing to their enhanced search capability when compared to that of traditional genetic algorithms that are based on communication among multiple populations.

Competitive Particle Swarm Optimization for Multi-Category Text Feature Selection.

Multi-label feature selection is an important task for text categorization. This is because it enables learning algorithms to focus on essential features that foreshadow relevant categories, thereby improving the accuracy of text categorization. Recent studies have considered the hybridization of evolutionary feature wrappers and filters to enhance the evolutionary search process.

Evaluation of seismic performance and effectiveness of multiple slim-type damper system for seismic response control of building structures.

This paper presents the evaluation of seismic performance and cost-effectiveness of a multiple slim-type damper system developed for the vibration control of earthquake excited buildings. The multiple slim-type damper (MSD) that consists of several small slim-type dampers and linkage units can control damping capacity easily by changing the number of small dampers. To evaluate the performance of the MSD, dynamic loading tests are performed with three slim-type dampers manufactured at a real scale.