Abstract: The aim of this paper is to study the potential use of an intelligent/automatic classification system for Parkinson's Disease (PD), using magnetic resonance images (MRI). For feature extraction of MRI Discrete Wavelet Transform has been used, followed by minimum Redundancy Maximum Relevance critrium (mRMR) for feature selection and Principal Component Analysis (PCA) for feature reduction. We then applied Support Vector Machine (SVM) for classification and Genetic Algorithms (GA) for optimization. To discover which slices and regions of the MRI are the most relevant in the brain for identification of Parkinson's Disease region, optimization was carried out using a multi-objetive genetic algorithm. The slices obtained in this optimization process were consistent with those recommended by medical experts. The methodology presented outperformed most of the research available in the bibliography, achieving accuracies of 95% in classification of subjects. This suggests that the proposed work

• Publication Date: 08-Dec-2019
• DOI: 10.15224/978-1-63248-180-1-04
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Abstract: This study aims to investigate the interrelationship among brand engagement in self-concept, brand schematicity, situational brand engagement, and customer advocacy of air asia in Thailand. The survey questionnaires were used as a tool to collect the data from 400 customers. The data was analyzed through Structural Equation Modeling (SEM). The study reveals that brand engagement in self-concept has no influence on situational brand engagement which different from brand schematicity. And brand engagement in self-concept, brand Schematicity and situational brand engagement are all have direct influence on customer advocacy. The result of this study showing 81% explains with situational brand engagement and 72% explains with customer advocacy.

• Publication Date: 15-Sep-2019
• DOI: 10.15224/978-1-63248-179-5-01
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