• Safety and Health at Work
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• v.13 no.2
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• pp.170-179
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• 2022

Background: The vulnerability of international migrant workers is on the rise, affecting the frequency of occupational accidents at workplaces worldwide. If migrant workers are managed in the same way as native workers, the consequences on safety assurance and risk management will be significant. This study aimed to develop the vulnerability factor model for migrant workers in seafood processing industries because of significant risk-laden labor of Thailand, which could be a solution to control the risk effectively. Methods: A total of 569 migrant workers were surveyed (432 Burmese and 137 Cambodian), beginning with 40 initial vulnerability factors identified in the questionnaire established from experts. The data were analyzed through descriptive analysis; exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to ascertain the model. Results: The result of content validity >0.67 and the Cronbach's alpha of 0.957 specified the high reliability of 40 factors. The EFA indicated a total variance of 65.49%. The final CFA validated the model and had an empirical fitting; chi-square = 85.34, Adjust Goodness-of-Fit Index = 0.96, and root mean square error of approximation = 0.016. The structure concluded with three dimensions and 18 factors. Dimension 1 of the structure, "multicultural safety operation," contained 12 factors; Dimension 2, "wellbeing," contained four factors; and Dimension 3, "communication technology," contained two factors. Conclusion: The vulnerability factor structure developed in this study included three dimensions and 18 factors that were significantly empirical. The knowledge enhanced safety management in the context of vulnerability factor structure for migrant workers at the workplace.

• Journal of Electrochemical Science and Technology
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• v.13 no.4
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• pp.462-471
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• 2022

In this study, the electrochemical impedance characteristics of CO₂/H₂O co-reduction to produce CO/H₂ syngas were investigated in a low-temperature single cell. The effect of the operating conditions on the single-cell performance was evaluated at different feed concentrations and cell voltages, and the corresponding electrochemical impedance spectroscopy (EIS) data were collected and analyzed. The Nyquist plots exhibited two semicircles with separated characteristic frequencies of approximately 1 kHz and tens of Hz. The high-frequency semicircles, which depend only on the catholyte concentration, could be correlated to the charge transfer processes in competitive CO₂ reduction and hydrogen evolution reactions at the cathodes. The EIS characteristics of the CO₂/H₂O co-reduction single cell could be explained by the equivalent circuit suggested in this study. In this circuit, the cathodic mass transfer and anodic charge transfer processes are collectively represented by a parallel combination of resistance and a constant phase element to show low-frequency semicircles. Through nonlinear fitting using the equivalent circuit, the parameters for each electrochemical element, such as polarization resistances for high- and low-frequency processes, could be quantified as functions of feed concentration and cell voltage.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.433-439
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• 2022

Muscle fatigue models to predict maximum endurance time (MET) are broadly classified as either 'empirical' or 'theoretical'. Empirical models are based on fitting experimental data and theoretical models on mathematical representations of physiological process. This paper examines the effectiveness of dynamic muscle fatigue model as theoretical model to predict maximum endurance time during forearm isometric contraction. Forty volunteers (20 females, 20 males) are participated in this study. Empirical models (exponential model and power model) and theoretical model (dynamic muscle fatigue model) are used to compare. Mean absolute deviation (MAD), correlation coefficient (r) and intraclass correlation (ICC) are calculated between theoretical model and empirical models. MAD are below 3.5%p, r and ICC are above 0.93 and 0.87, respectively. This results demonstrate that dynamic muscle fatigue model as theoretical model is valid to predict MET.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.5
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• pp.760-771
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• 2022

This study sought to develop clothing for a companion animal that can provide stable ECG measurements. A pattern for the smart clothing of a companion dog was manufactured using the replica method to select a location and method that best suited the stable measurement of ECG and improved the clothing's fitness. The smart clothing was developed as the following three types: strap type, top type, and combined top and vest type with a detachable wireless ECG monitor. The detection abilities of these were observed using the PQRST rate taken after ECG measurements while the three companion dogs were tested while resting and moving. The results revealed that apart from using an electrode, applying a gel pad is the most effective way to achieve stable ECG measurements, and the central chest region is more reliable than the left armpit for providing steady readings. The combined top and vest type showed the highest average ECG PQRST detection number, meaning that the ECG signal measurement was steady. These results may contribute to the measurement of ECG in smartwear for U-Healthcare to measure other biometric data of a companion dog.

• Tribology and Lubricants
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• v.38 no.3
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• pp.84-92
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• 2022

In Part I, developed was a method to obtain the stress field due to an edge dislocation that locates in an elastic half plane beneath the contact edge of an elastically similar square wedge. Essential result was the corrective functions which incorporate a traction free condition of the free surfaces. In the sequel to Part I, features of the corrective functions, F_kij,(k = x, y;i,j = x,y) are investigated in this Part II at first. It is found that F_xxx(ŷ) = F_xyx(ŷ) where ŷ = y/η and η being the location of an edge dislocation on the y axis. When compared with the corrective functions derived for the case of an edge dislocation at x = ξ, analogy is found when the indices of y and x are exchanged with each other as can be readily expected. The corrective functions are curve fitted by using the scatter data generated using a numerical technique. The algebraic form for the curve fitting is designed as F_kij(ŷ) = $\frac{1}{\hat{y}^{1-{\lambda}}I+yp}$$\sum_{q=0}^{m}{\left}$$\left[A_q\left(\frac{\hat{y}}{1+\hat{y}} \right)^q \right]$ where λ_I=0.5445, the eigenvalue of the adhesive complete contact problem introduced in Part I. To investigate the exponent of F_kij, i.e.(1 - λ_I) and p, Log|F_kij|(ŷ)-Log|(ŷ)| is plotted and investigated. All the coefficients and powers in the algebraic form of the corrective functions are obtained using Mathematica. Method of analyzing a surface perpendicular crack emanated from the complete contact edge is explained as an application of the curve-fitted corrective functions.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.455-464
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• 2022

There are two unique characteristics of the datasets from a manufacturing process. They are the severe class imbalance and lots of Out-of-Distribution samples. Some good strategies such as the oversampling over the minority class, and the down-sampling over the majority class, are well known to handle the class imbalance. In addition, SMOTE has been chosen to address the issue recently. But, Out-of-Distribution samples have been studied just with neural networks. It seems to be hardly shown that Out-of-Distribution detection is applied to the predictive model using conventional machine learning algorithms such as SVM, Random Forest and KNN. It is known that conventional machine learning algorithms are much better than neural networks in prediction performance, because neural networks are vulnerable to over-fitting and requires much bigger dataset than conventional machine learning algorithms does. So, we suggests a new approach to utilize Out-of-Distribution detection based on SVM algorithm. In addition to that, bagging technique will be adopted to improve the precision of the model.

• The Research Journal of the Costume Culture
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• v.31 no.2
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• pp.173-192
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• 2023

This study conducted in-depth interviews with experts to implement Hanbok shows on metaverse, which can contribute to the succession and development of Hanbok design and to establish a platform that fits the reality of the Hanbok industry and consumers. In-depth interviews were conducted to collect opinions from experts, and the derived contents were divided and analyzed using an affinity diagram. Experts were positive about the use of the metaverse platform of the Hanbok show in terms of impact, accessibility, exposure, virtual fitting, issuance of NFTs, and promotion of Hanbok brands. As a result of verifying the validity of the four components of metaverse, experts highly evaluated the possibility of using Hanbok shows in the order of virtual reality, augmented reality, mirror world, and lifelogging. Visuality, influence, marketing efficiency in virtual reality, immersion in augmented reality, fantasy and artistic elements, expression, diversity, and abundant experiences were expected. The platform's requirements emphasized realistic implementation equipment and technology, collaboration between Hanbok designers and producers, in addition to government support. Results of this study showed that appropriate target was analyzed to be in the 10-30s, and the appropriate price range was found to be able to sell at a discount of 40-80% compared to offline. This study provides useful implications for the service development of metaverse content, which will also be actively used in the Hanbok field, and can be used as basic data for reviving the Korean Hanbok industry and strengthening international competitiveness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.2-5
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• 2022

With the advent of deep learning and the rapid development of ICT (Information and Communication Technology), research using artificial intelligence is being actively conducted in various fields of society such as politics, economy, and culture and so on. Deep learning-based artificial intelligence technology is subdivided into various domains such as natural language processing, image processing, speech processing, and recommendation system. In particular, as the industry is advanced, the need for a recommendation system that analyzes market trends and individual characteristics and recommends them to consumers is increasingly required. In line with these technological developments, this paper extracts and classifies attribute information from structured or unstructured text and image big data through deep learning-based technology development of 'language processing intelligence' and 'image processing intelligence', and We propose an artificial intelligence-based 'customized fashion advisor' service integration system that analyzes trends and new materials, discovers 'market-consumer' insights through consumer taste analysis, and can recommend style, virtual fitting, and design support.

• Journal of Practical Agriculture & Fisheries Research
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• v.6 no.1
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• pp.143-154
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• 2004

The value of daily heating degree hour(described as DH hereafter) is essential for calculating the heating load of a greenhouse during the winter months. Many researchers have so for proposed different models for estimating DH value. Models for estimating DH have been investigated DH(unit, ℃·h·year^-1) in this paper. The comparisons of standard and existed DH values were made to know the estimation error of each model proposed so far. The standard DH values and other proposed DH values have were obtained for the inside setpoint temperatures of 9, 13, 16 and 20℃ in greenhouse, estimated based on meterological data from 1961 to 2000 according to locals, and standard DH values were independent and existed DH values were dependent. Among the various model, the one developed theoretically by Mihara modified to author was the best fitting for standard DH values. The DH values were obtained for the inside setpoint temperature of 9, 13, 16 and 20℃ by Modified Mihara's model. A new DH contour line graph was proposed using Modified Mihara's model. Using the DH contour line graph, the DH values can be obtained easily for any setpoint according to local.

• Journal of the Korean Geotechnical Society
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• v.22 no.2
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• pp.41-53
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• 2006

The brittle materials like rocks show complicated strain-softening behavior after the peak which is hard to model using the classical constitutive models based on the relation between strain and stress tensors. A kinematically constrained three-dimensional microplane constitutive model is developed for granite. The model is verified by fitting the experimented data of Westerly granite and Bonnet granite. The triaxial behavior of granite is well reproduced by the model as well as the uniaxial behavior. We studied the development of the fracture zone in granite during blasting impact using the model with the standard finite element method. All the results obtained from the microplane model developed are compared to those from the linear elasticity model which is commonly used in many researches and practices. It is found that the nonlinearity of rocks sigificantly affects the results of analysis.