A data-driven approach of load monitoring on laminated composite plates using support vector machine

2018 ◽  
Author(s):  
Hadi Fekrmandi ◽  
Yun Seok Gwon
Keyword(s):  
Support Vector Machine ◽  
Laminated Composite ◽  
Composite Plates ◽  
Data Driven ◽  
Support Vector ◽  
Laminated Composite Plates ◽  
Load Monitoring ◽  
Data Driven Approach

scholarly journals Articulatory Distinctiveness of Vowels and Consonants: A Data-Driven Approach

2013 ◽  
Vol 56 (5) ◽  
pp. 1539-1551 ◽  
Author(s):  
Jun Wang ◽  
Jordan R. Green ◽  
Ashok Samal ◽  
Yana Yunusova
Keyword(s):  
Support Vector Machine ◽  
Time Series Data ◽  
Movement Time ◽  
Objective Measure ◽  
Procrustes Analysis ◽  
Data Driven ◽  
Series Data ◽  
Support Vector ◽  
Vowel Space ◽  
Data Driven Approach

Purpose To quantify the articulatory distinctiveness of 8 major English vowels and 11 English consonants based on tongue and lip movement time series data using a data-driven approach. Method Tongue and lip movements of 8 vowels and 11 consonants from 10 healthy talkers were collected. First, classification accuracies were obtained using 2 complementary approaches: (a) Procrustes analysis and (b) a support vector machine. Procrustes distance was then used to measure the articulatory distinctiveness among vowels and consonants. Finally, the distance (distinctiveness) matrices of different vowel pairs and consonant pairs were used to derive articulatory vowel and consonant spaces using multidimensional scaling. Results Vowel classification accuracies of 91.67% and 89.05% and consonant classification accuracies of 91.37% and 88.94% were obtained using Procrustes analysis and a support vector machine, respectively. Articulatory vowel and consonant spaces were derived based on the pairwise Procrustes distances. Conclusions The articulatory vowel space derived in this study resembled the long-standing descriptive articulatory vowel space defined by tongue height and advancement. The articulatory consonant space was consistent with feature-based classification of English consonants. The derived articulatory vowel and consonant spaces may have clinical implications, including serving as an objective measure of the severity of articulatory impairment.

Data-Driven Thermal Comfort Prediction With Support Vector Machine

2017 ◽  
Author(s):  
Bo Peng ◽  
Sheng-Jen Hsieh
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Thermal Comfort ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Support Vector ◽  
Climate Control ◽  
Data Driven Approach ◽  
Ubiquitous Sensor Networks ◽  
Model Training

Personal thermal comfort is a crucial yet often over-simplified factor in building climate control. Traditional comfort models lack the adaptability to fit individuals’ demand. Recent advances of machine learning and ubiquitous sensor networks enable the data-driven approach of thermal comfort. In this paper, we built a platform that can simulate occupants with different thermal sensations and used it to examine the performance of support vector machine (SVM) and compared with several other popular machine learning algorithms on thermal comfort prediction. We also proposed a hybrid SVM-LDA thermal comfort classifier that can improve the efficiency of model training.

Ballistic performance of composite structure configurations with high elongation calendered rubber layer laminated to AA5083-H112 aluminum alloy

2021 ◽  
pp. 146442072110145
Author(s):  
Hasan Kasım
Keyword(s):  
Adhesion Strength ◽  
Laminated Composite ◽  
Composite Plates ◽  
Front Face ◽  
Laminated Composite Plates ◽  
Ballistic Performance ◽  
Rubber Layer ◽  
Interface Interaction ◽  
Metal Rubber ◽  
High Elongation

This study aims to determine the ballistic performances of laminated composite plates produced with AA5083-H112 series aluminum and rubber material with high elongation capacity under impact loading. To investigate the effect of rubber compounds, two types of rubber with calendered and damping were prepared. Thanks to the surface treatment applied to the aluminum plates, the rubber–metal adhesion strength was adjusted, and four different laminated composite plate samples were prepared. Calendered rubber was used on the bullet impact surface of all samples, and damping rubber was used on the back. It has been observed that the pressure barrier created by the calendered rubber bullet on the front face provides high performance to absorb energy. A detailed study was carried out on the total thickness of laminated composite plates, the interface adhesion strength between rubber and aluminum layers, and the ballistic performance of aluminum-rubber combinations. It was concluded that the laminated composite plate’s energy absorption would increase, especially by increasing the thickness of the dumping rubber layer on the back of the aluminum sheets. In the strong metal-rubber interface interaction between the rubber and aluminum layer, the bullet is stopped before the pressure barrier is formed. The penetration depth and bulging height increase, and most of the energy are transmitted through the aluminum plate. In the weak metal-rubber interface interaction, a significant portion of the energy is absorbed by the rubber and air thanks to the pressure barrier.

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