• Fashion & Textile Research Journal
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• v.21 no.6
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• pp.697-707
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• 2019

This review paper deals with materials, classification, and a current article investigation on smart textile sensors for wearable vital signs monitoring (WVSM). Smart textile sensors can lose electrical conductivity during vital signs monitoring when applying them to clothing. Because they should have to endure severe conditions (bending, folding, and distortion) when wearing. Imparting electrical conductivity for application is a critical consideration when manufacturing smart textile sensors. Smart textile sensors fabricate by utilizing electro-conductive materials such as metals, allotrope of carbon, and intrinsically conductive polymers (ICPs). It classifies as performance level, fabric structure, intrinsic/extrinsic modification, and sensing mechanism. The classification of smart textile sensors by sensing mechanism includes pressure/force sensors, strain sensors, electrodes, optical sensors, biosensors, and temperature/humidity sensors. In the previous study, pressure/force sensors perform well despite the small capacitance changes of 1-2 pF. Strain sensors work reliably at 1 ㏀/cm or lower. Electrodes require an electrical resistance of less than 10 Ω/cm. Optical sensors using plastic optical fibers (POF) coupled with light sources need light in-coupling efficiency values that are over 40%. Biosensors can quantify by wicking rate and/or colorimetry as the reactivity between the bioreceptor and transducer. Temperature/humidity sensors require actuating triggers that show the flap opening of shape memory polymer or with a color-changing time of thermochromic pigment lower than 17 seconds.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.37-53
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• 2021

The purpose of this study is to analyze the types of latent profiles depending on the job satisfaction of youth entrepreneurs in South Korea and examine the influence of related variables. Latent profile analysis (LPA) was conducted using data from the 12th year of the Youth Panel Study. Results of the study revealed that there were five latent profiles based on job satisfaction among young entrepreneurs: lowest job satisfaction, mid-low job satisfaction, middle job satisfaction, mid-high job satisfaction, and highest job satisfaction. By applying multinomial logistic analysis, the influencing factors for each latent profiles have been derived. Gender, marital status, subjective health, self-esteem, entrepreneurial motivation, difficulty in start-up, person-job fit, intrinsic or extrinsic job values, business scale, income, work hour, education or training, and labor insurance were significant predictors of youth entrepreneurs' job satisfaction. Based on these results, the article discusses practical implications that can enhance the job satisfaction of young entrepreneurs.