• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.651-662
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• 2022

The electrochemical impedance spectroscopy(EIS) method was used to evaluate the concrete deterioration process related to chloride-induced steel corrosion with various corrosion levels(initiation, rust propagation and acceleration periods). The impressed current technique, with four total current levels of 0C, 13C, 65C and 130C, was used to accelerate steel corrosion in concrete cylinder samples with w/c ratio of 0.4, 0.5, and 0.6, immersed in a 0.5M NaCl solution. A series of EIS measurements was performed to monitor concrete deterioration during the accelerated corrosion test in this study. Some critical parameters of the equivalent circuit were obtained through the EIS analysis. It was observed that the charge transfer resistance(R_c) dropped sharply as the impressed current increased from 0C to 13C, indicating a value of approximately 10kΩcm². However, the sensitivity of R_c significantly decreased when the impressed current was further increased from 13C to 130C after corrosion of steel had been initiated. Meanwhile, the double-layer capacitance value(C_dl) linearly increased from 50×10^-6μF/cm² to 250×10^-6μF/cm² as the impressed current in creased from 0C to 130C. The results in this study showed that monitoring C_dl is an effective measurement parameter for evaluating the progress of internal concrete damages(de-bonding between steel and concrete, micro-cracks, and surface-breaking cracks) induced by steel corrosion. The findings of this study provide a fundamental basis for developing an embedded sensor and signal interpretation method for monitoring concrete deterioration due to steel corrosion at various corrosion levels.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.

• Tuberculosis and Respiratory Diseases
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• v.42 no.4
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• pp.569-583
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• 1995

Background: The expression of the adhesion molecules on the cell surface is important in the movement of cells and the modulation of immune response. DILD starts as an alveolitis and progresses to pulmonary fibrosis. So adhesion molecules in these patients is expected to be increased. There are several reports about adhesion molecules in DILD in terms of the percentage of positive cells in immuno-stain, in which the interpretation is subjective and the data were variable. Methods: So we measured the relative median fluorescence intensity(RMFI) which is the ratio of the FI emitted by bound primary monoclonal antibody to FI emitted by isotypic control antibody of the cells in BALF of 28 patients with DILD(IPF:10, collagen disease:7, sarcoidosis:9, hypersensitivity pneumonitis:2) and 9 healthy control. Results: RMFI of the ICAM-1 on AM($3.30{\pm}1.16$) and lymphocyte($5.39{\pm}.70$) of DILD were increased significantly than normal control($0.93{\pm}0.18$, $1.06{\pm}0.21$, respectively, p=0.001, P=0.003). RMFI of the CD18 on lymphocyte was also higher($24.9{\pm}14.9$) than normal($4.59{\pm}3.77$, p=0.0023). And there was a correlation between RMFI of ICAM on AM and the % of AM(r=-0.66, p=0.0001) and lymphocyte(r=0.447, p=0.0116) in BALF. Also RMFI of ICAM on lymphocyte had a significant (r=0.593, p=0.075) correlation with the % of IL-2R(+) lymphocyte in BALF. The soluble ICAM(sICAM) in serum was also significantly elevated in DILD($499.7{\pm}222.2\;ng/ml$) compred to normal($199.0{\pm}38.9$) (p=0.00097) and sICAM in BAL fluid was also significantly higher than normal control group($41.8{\pm}23.0\;ng/ml$ vs $20.1{\pm}13.6\;ng/ml$). There was a Significant correlation between sICAM level in serum and the expression of ICAM-l on AM(r=0.554, p=0.0259).Conclusion: These data suggest that in DILD the expression of adhesion molecules is increased in the AM and BAL lymphocytes with elevated serum sICAM, and these parameter may be useful in determining disease activity.