@article{choo_kim_2023, title={A study on the evaluation of tokenizer performance in natural language processing}, volume={37}, ISSN={["1087-6545"]}, DOI={10.1080/08839514.2023.2175112}, abstractNote={Formulae display:?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom.}, number={1}, journal={APPLIED ARTIFICIAL INTELLIGENCE}, author={Choo, Sanghyun and Kim, Wonjoon}, year={2023}, month={Dec} }
 @article{kim_kim_lyons_nam_2020, title={Factors affecting trust in high-vulnerability human-robot interaction contexts: A structural equation modelling approach}, volume={85}, ISSN={["1872-9126"]}, DOI={10.1016/j.apergo.2020.103056}, abstractNote={The current research proposed and tested a structural equation model (SEM) that describes hypothesized relationships among factors affecting trust in human-robot interaction (HRI) such as trustworthiness, human-likeness, intelligence, perfect automation schema (PAS), and affect. A video stimulus depicting an autonomous guard robot interacting with humans was employed as a stimulus via Amazon's Mechanical Turk to recruit 233 participants. Human-related and robot-related metrics were found to affect trustworthiness that subsequently affected trust. In particular, ability (as a trustworthiness facet) was a dominant factor affecting trust in HRI. Integrity was found to mediate the relationships between robot- and human-related metrics and trustworthiness. This study also showed a correlation between intelligence and trustworthiness, as well as between PAS and trustworthiness. The findings of the present study have significant implications for both theory and practice on factors and levels that affect trust in HRI.}, journal={APPLIED ERGONOMICS}, author={Kim, Wonjoon and Kim, Nayoung and Lyons, Joseph B. and Nam, Chang S.}, year={2020}, month={May} }
 @article{moon_park_park_kim_yun_park_2019, title={A Study on Affective Dimensions to Engine Acceleration Sound Quality Using Acoustic Parameters}, volume={9}, ISSN={["2076-3417"]}, DOI={10.3390/app9030604}, abstractNote={The technical performance of recent automobiles is highly progressed and standardized across different manufacturers. This study seeks to derive a semantic space of engine acceleration sound quality for end users and identify the relation with sound characteristics. For this study, two affective attributes: ‘refined’ and ‘powerful’, and eight acoustic parameters considering revolutions per minute were used to determine the correlation coefficient for those affective attributes. In the experiment, a total of 35 automobiles were selected. Each of the 3rd gear wide open throttle sounds was recorded and evaluated by 42 adult subjects with normal hearing ability and driving license. Their subjective evaluations were analyzed using factor analysis, independent t-test, correlation analysis, and regression analysis. The prediction models for the affective dimensions show distinct differences for the revolutions per minute. From the experiment, it was confirmed that the customers’ affective response can be predicted through the acoustic parameters. In addition, it was found that the initial revolutions per minute in the accelerated condition had the greatest influence on the affective response. This study can be a useful guideline to design engine acceleration sounds that satisfy customers’ affective experience.}, number={3}, journal={APPLIED SCIENCES-BASEL}, author={Moon, Soyoun and Park, Sunghwan and Park, Donggun and Kim, Wonjoon and Yun, Myung Hwan and Park, Dongchul}, year={2019}, month={Feb} }
 @article{kim_2019, title={A comparative study on the statistical modelling for the estimation of stature in Korean adults using hand measurements}, volume={76}, ISSN={["0003-5548"]}, DOI={10.1127/anthranz/2019/0903}, abstractNote={In forensic research, stature is an important indicator in the identification of humans. There are numerous methods for estimating stature, and their goal is to determine the optimal variables for delivering the most accurate predictions. The purpose of this study is to compare the predictive algorithms for stature based on various hand dimensions. The selected hand variables can be separated into four categories-length, breadth, wrist, and thickness-and 18 variables were eventually selected in this research. The hand dimension data were analyzed by descriptive statistics. In the Korean population, there were significant differences found within genders in terms of hands and stature. Two predictive algorithms, regression and artificial neural network, were compared on the basis of their coefficient of determination (R2) and root mean square error (RMSE). In the single linear regression, hand length (R2 = .386) and palm length (R2 = .349) were found to be the most relevant variables in stature prediction for males. For females, hand length (R2 = .286) and inner grip circumference (R2 = .261) scored the highest R2. In the multiple linear regression, an R2 of .659 was obtained for both males and females, with an RMSE of 5.38 cm. In the artificial neural network, the value of R2 was .05, along with an RMSE of 5.17 cm. Overall, this study proposes the artificial neural networks as an improved predictive algorithm for stature, and hand length and inner grip circumference were found to be the most relevant variables to predict stature.}, number={1}, journal={ANTHROPOLOGISCHER ANZEIGER}, author={Kim, Wonjoon}, year={2019}, pages={57–67} }
 @article{kim_jin_choo_nam_yun_2019, title={Designing of smart chair for monitoring of sitting posture using convolutional neural networks}, volume={53}, ISSN={["2514-9318"]}, DOI={10.1108/DTA-03-2018-0021}, abstractNote={
Purpose
Sitting in a chair is a typical act of modern people. Prolonged sitting and sitting with improper postures can lead to musculoskeletal disorders. Thus, there is a need for a sitting posture classification monitoring system that can predict a sitting posture. The purpose of this paper is to develop a system for classifying children’s sitting postures for the formation of correct postural habits.
}, number={2}, journal={DATA TECHNOLOGIES AND APPLICATIONS}, author={Kim, Wonjoon and Jin, Byungki and Choo, Sanghyun and Nam, Chang S. and Yun, Myung Hwan}, year={2019}, month={Apr}, pages={142–155} }