• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.224-239
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• 2022

Despite an impressive growth of online sales, the bricks-and-mortar bandwagon still remain high-profile in the realm of consumer channel switching behavior. Different from the existing research exploring the consumer switching behavior from the offline to the online retailer, this study is an effort to investigate why and when do consumers switch from the online to the offline channel by applying the push-pull-mooring framework. Thus, structural equation modeling and SPSS were used to test the established hypotheses. The results, as expected, show that both push factors (i.e., perceived risk and dissatisfaction) and pull factors (alternative attractiveness and perceived ownership) are positively related to a consumer's intention to switch from the online to the offline channel. Moreover, all of expected interactions between push factors and mooring factors (i.e., switching costs, variety seeking, and subjective norms), and between pull factors and mooring factors are supported, except for the interactions between push factors and switching costs as well as between pull factors and subjective norms. Finally, implications and limitations are discussed.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.401-409
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• 2021

This study aimed to estimate the photosynthetic capacity of tomato plants grown in a semi-closed greenhouse using temperature response models of plant photosynthesis by calculating the ribulose 1,5-bisphosphate carboxylase/oxygenase maximum carboxylation rate (V_cmax), maximum electron transport rate (J_max), thermal breakdown (high-temperature inhibition), and leaf respiration to predict the optimal conditions of the CO₂-controlled greenhouse, for maximizing the photosynthetic rate. Gas exchange measurements for the A-C_i curve response to CO₂ level with different light intensities {PAR (Photosynthetically Active Radiation) 200µmol·m^-2·s^-1 to 1500µmol·m^-2·s^-1} and leaf temperatures (20℃ to 35℃) were conducted with a portable infrared gas analyzer system. Arrhenius function, net CO₂ assimilation (A_n), thermal breakdown, and daylight leaf respiration (R_d) were also calculated using the modeling equation. Estimated J_max, A_n, Arrhenius function value, and thermal breakdown decreased in response to increased leaf temperature (> 30℃), and the optimum leaf temperature for the estimated J_max was 30℃. The CO₂ saturation point of the fifth leaf from the apical region was reached at 600ppm for 200 and 400µmol·m^-2·s^-1 of PAR, at 800ppm for 600 and 800µmol·m^-2·s^-1 of PAR, at 1000ppm for 1000µmol of PAR, and at 1500ppm for 1200 and 1500µmol·m^-2·s^-1 of PAR levels. The results suggest that the optimal conditions of CO₂ concentration can be determined, using the photosynthetic model equation, to improve the photosynthetic rates of fruit vegetables grown in greenhouses.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.69-70
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• 2021

본 논문은 PPM으로 관리되고 있는 자동차 부품 제조 공정에서 검사자의 육안검사 방법을 대체하기 위해 머신비전 및 CNN 기반 불량 검출 시스템으로 제안되었던 방식들의 단점을 개선하기 위하여 기존 머신 비전 기술에 합성곱 오토인코더 모델을 적용하여 단점을 해결하였다. 본 논문에서 제시한 오토인코더를 이용하는 방법은 정상 생산품의 이미지만으로 학습을 진행하고, 학습된 모델은 불량 부위가 포함된 이미지를 입력받아 정상 이미지로 출력한다. 이 방법을 사용하여 불량의 부위와 크기를 알 수 있었으며 불량 여부의 판단은 임계치에 의한 불량 부위의 화소 수 계산으로 판단하였다.

• Journal of Food Hygiene and Safety
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• v.34 no.4
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• pp.374-379
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• 2019

This study developed predictive growth models of Salmonella enterica Serovar Typhimurium on lettuce washed with chlorine (100~300 ppm) and ultrasound (US, 37 kHz, 380 W) treatment and stored at different temperatures ($10{\sim}25^{\circ}C$) using a polynomial equation. The primary model of specific growth rate (SGR) and lag time (LT) showed a good fit ($R^2{\geq}0.92$) with a Gompertz equation. A secondary model was obtained using a quadratic polynomial equation. The appropriateness of the secondary SGR and LT model was verified by coefficient of determination ($R^2=0.98{\sim}0.99$ for internal validation, 0.97~0.98 for external validation), mean square error (MSE=-0.0071~0.0057 for internal validation, -0.0118~0.0176 for external validation), bias factor ($B_f=0.9918{\sim}1.0066$ for internal validation, 0.9865~1.0205 for external validation), and accuracy factor ($A_f=0.9935{\sim}1.0082$ for internal validation, 0.9799~1.0137 for external validation). The newly developed models for S. Typhimurium could be incorporated into a tertiary modeling program to predict the growth of S. Typhimurium as a function of combined chlorine and US during the storage. These new models may also be useful to predict potential S. Typhimurium growth on lettuce, which is important for food safety purposes during the overall supply chain of lettuce from farm to table. Finally, the models may offer reliable and useful information of growth kinetics for the quantification microbial risk assessment of S. Typhimurium on washed lettuce.

• Journal of the Korean Institute of Gas
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• v.22 no.4
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• pp.32-38
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• 2018

The purpose of this study is to assess quantitatively the amount of leaks and the extent of dispersion in case of a leak at a hydrogen fluoride tank container unloading station, and to suggest a safety improvement plan to prevent recurrence of similar accidents. In 2012, Company H leaks 8 tonnes of tank containers with a maximum storage capacity of 18 Ton, causing it to become a social issue. As a result of calculation using Gaussian plume model, the concentration was estimated to be more than 20ppm from the leak point to 1,321 m radius. The leakage of hydrogen fluoride from the company R in 2014 was estimated to be 11.02 kg, of which 2.9 kg was treated by the scrubber. As a result of calculation using Gaussian plum model, the damage range with a concentration of 20ppm or more from the leak source was estimated to be 69 m in radius. As a result of comparing the above two accidents, it was found that the leakage amount was about 987 times different and the damaged site was more than 19 times different. Therefore, it was concluded that it was necessary to control the wearing of the protective equipment, the enclosure of the unloading site, the installation of the scrubber, and the emergency training to avoid the accidental leakage of a hydrogen fluoride from the unloading site.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.105-115
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• 2023

This study seeks to find a way to induce users to expand their direct participation in sports through the acceptance of digital technology. From July 1 to August 30, 2022, a survey was conducted targeting home training users who applied the Internet of Things (IoT). 129 people participated in the survey through non-face-to-face self-administration method. For data processing, frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis, and 3-step mediation regression analysis were conducted using IBM's SPSS 21.0 program. The results of the study are as follows. First, in the relationship between the home training PPM model and direct participation in sports, ease appeared to have a mediating effect. In the factors of push, simple functionality showed a complete mediating effect, and inefficiency showed a partial mediating effect. Among pull factors, enjoyment and possibility of experience showed a complete mediating effect. In the mooring factors, individual innovativeness showed a complete mediating effect. Second, in the relationship between home training PPM model and direct participation in sports, usefulness showed a mediating effect. In the factors of push, simple functionality showed a complete mediating effect, and inefficiency showed a partial mediating effect. Among pull factors, enjoyment and possibility of experience showed a complete mediating effect. Among the mooring factors, individual innovativeness showed a partial mediating effect. Through this research, it is expected that the sports industry will contribute to the expansion of consumption expenditure and economic growth through the expansion of digital technologies such as NFT, Metaverse, and virtual/augmented reality.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.11-25
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• 2022

In this study, we want to verify the factors that affect the intention to switch to a supply chain management information system applied with blockchain. To this end, variable selection and research model were constructed through the review of previous studies, and empirical analysis was conducted using the TOE framework and PPM model. The effects of Push and Pull factors on the intention to switch to the block chain system and the moderating effect through the switching cost which is a Mooring factor, were verified. The hypothesis was verified using a structural equation model using a sample of 320 response data by conducting a questionnaire survey on small and medium-sized enterprises located in Korea. As a result of the study, social influence, which is a push factor, and management's will to innovate, which is a Pull factor, had a significant effect on switching intention. And the moderating effect between the groups with high and low switching cost recognition was confirmed. This study is significant in that it presents the concept and research direction of SCBM (supply chain & blockchain management) that can enhance the competitiveness of a company through the implementation of a blockchain-based supply chain management information system.

• Journal of Sensor Science and Technology
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• v.5 no.4
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• pp.17-24
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• 1996

Planar multi-junction thermal converters were fabricated for precise measurements of the ac voltage and current by an ac-dc transfer method. A heater and a thermocouple array were fabricated onto a sandwiched membrane, $Si_{3}N_{4}$ (200 nm) / $SiO_{2}$ (400 nm) / $Si_{3}N_{4}$ (200 nm), a thickness of $0.8\;{\mu}m$ and a size of $2{\times}4\;mm^{2}$, which is supported by a surrounding frame. The NiCr heater is located at the center of the membrane vertically. Hot junctions of $48{\sim}156$ pairs of thermocouples (Cu-CuNi44) are located near or onto the heater, and cold junctions are located onto the silicon frame. Output of the thermal converters for 10 mA dc input was $76\;mV{\sim}382\;mV$ dependent on a model, and short term stability of the outputs was ${\pm}5{\sim}15\;ppm$/ 10 min with 5 mA dc input. Responsivity in air was in the range of $3.9{\sim}14.5V/W$. Responsivity of the model BF48 in air which has 48 thermocouples was 2 times or greater than that of 3 dimensional multi-junction thermal converter in vacuum which has 56 thermocouples. AC-DC transfer differences with an input of 10 mA or less were less than ${\pm}1\;ppm$ in the frequency range from 5 Hz to 2 kHz, and about $2{\sim}3\;ppm$ at 5 kHz and 10 kHz.

• The Korean Journal of Pesticide Science
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• v.14 no.3
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• pp.191-198
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• 2010

To predict and design of new potent insecticidal compounds, the two dimensional quantitative structure-activity relationships (2D-QSARs) and molecular hologram quantitative structure-activity relationships (HQSARs) between the various physicochemical parameters as descripters of N'-phenyl-N-methylformamidine analogues (1-22) and their insecticidal activity against the two spotted spider mite (Tetranychus urticae) were discussed quantitatively. From 2D-QSAR models (1 & 3), the width ($B_2$) of $R_3$-group as sterically factor and optimal total dipole moment (TDM=2.025D) of $R_4$-group were mainly influenced to increase the activity. Therefore, the activities were depend upon the $R_3$- and $R_4$-groups. Particularly, it is predicted that the activity of newly designed potent compound (PI; $EC_{50}$=0.516 ppm) by 2D-QSAR models (3) and HQSAR model F2 was about 34.3 fold higher than that of the commercialized insecticide, Amitraz ($EC_{50}$=17.7 ppm).

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.74-99
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• 2022

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.