• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.6
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• pp.884-892
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• 2014

The purpose of this study was to investigate the drying characteristics and drying models of Ainsliaea acerifolia Sch. Bip. using far-infrared thin layer drying. Far-infrared thin layer drying test on Ainsliaea acerifolia Sch. Bip. was conducted at two air velocities of 0.6 and 0.8 m/sec, as well as three drying temperatures of 40, 45, and $50^{\circ}C$ respectively. The drying models were estimated using coefficient of determination and root mean square error. Drying characteristics were analyzed based on factors such as drying rate, leaf color changes, antioxidant activity, and contents of polyphenolics and flavonoids. The results revealed that increases in drying temperature and air velocity caused a reduction in drying time. The Thompson model was considered suitable for thin layer drying using far-infrared radiation for Ainsliaea accerifolia Sch. Bip. Greenness and yellowness values decreased and lightness values increased after far-infrared thin layer drying, and the color difference (${\Delta}E$) values at $40^{\circ}C$ were higher than those at $45^{\circ}C$ and $50^{\circ}C$. The antioxidant properties of Ainsliaea acerifolia Sch. Bip. decreased under all far-infrared thin layer drying conditions, and the highest polyphenolic content (37.9 mg/g), flavonoid content (22.7 mg/g), DPPH radical scavenging activity (32.5), and ABTS radical scavenging activity (31.1) were observed at a drying temperature of $40^{\circ}C$ with an air velocity of 0.8 m/sec.

• The Korean Journal of Air & Space Law and Policy
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• v.26 no.2
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• pp.149-179
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• 2011

Statistics of aviation accident in Korea show that safety level of training flights is high. However, more than 80% of aviation accidents happen owing to human factors. And because most reasons of them are concerned with pilot error, it is very important for student pilots who will transport a lot of passengers to develop the knowledge of safety and abilities of risk management for preventing accidents. In this study, in order to investigate the Human Factors which affect safety in training student pilots for flight, verified the correlationbetween experiences of accident, the differences according to the experience level of training flight and the differences between college student pilots and ordinary student pilots on the basis of human factors that composes the SHELL models. For the study, Using SPSS 17.0, conducted Correlation Analysis, Analysis of Variance(ANOVA) and t-test. To sum up the result of this study, student pilot's ability and equipment in the cockpit are the important factors for safety when pilots are training flight. Also the analysis of the differences between human factors according to the characters of student pilots' groups shows that college student pilots are affected by immanent factors and organizational cultures. So far, there haven't been any accidents which is related with human casualties when training at the ATO(Approved Training Organization). But accidents can occur at any time and anywhere. Especially the human factors which comprises most of aviation accident have a wide reach and are impossible to be eliminated, therefore, it is best to minimize them. Because ATO is the starting point to lead the aviation industry of Korea, we will have to be aware of problems and improve education/training of human factors.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Asia Marketing Journal
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• v.14 no.1
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• pp.25-51
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• 2012

Researches about the relationship between SST(Self Service Technology) and TRI(Technology Readiness Index) have been carried out after TRI was developed by Parasuraman and his colleagues(2000). We hypothesize Consumer Readiness can also influence consumer's motivation, attitude, and intent to use SST. Currently, there has been no research on this subject. In this study, we investigated the relationship between TR, Consumer Readiness and SST Core Attitudinal Model which Dabholkar & Bagozzi(1994) proposed. The researchers also investigated moderating effects of consumer traits and situational factors to verify the acceptance of such forms of service delivery by all kinds of consumers and under different situational contexts. Self consciousness, the need for interaction with an employee, and the technology anxiety were used as consumer trait variables. Perceived waiting time and perceived crowding were used as situational variables. 380 questionnaires were distributed to a sample group of people in their 20's and 30's, and the data were analyzed with structural equation model using AMOS 18.0 program. All of Cronbach's alpha values representing reliabilities were satisfactory. The values of Composite Reliability(CR) and Average Variance Extracted(AVE) also showed the above criteria, thus providing evidence of convergent validity. To confirm discriminant validity among the constructs, confirmatory factor analysis and correlations among all the variables were examined. The results were satisfactory. The results of this study are summarized as follows. 1. Optimism and innovativeness of TR partially influenced the motivation to use SST. People who tend to be optimistic use SST because of ease of use and fun. The innovative however, usually use SST due to its performance. However, consumer readiness of role clarity, ability and self-efficacy influence all the components of motivation to use SST, ease of use, performance and fun. The relative effect of consumer readiness on the motivation to use SST was much stronger and more significant than that of TR. No other previous studies have examined the effects of Consumer Readiness on SST usage motivation, attitude and intention. It is academically meaningful that the researchers verified that Consumer Readiness is the important precedent construct influencing the self service technology core Attitudinal Model. Our findings suggest that marketers should consider fun and ease of use attributes to promote the use of self service technology. In addition, the SST usage frequency will rise rapidly when role clarity, ability, and self-efficacy which anybody can easily handle SST is assured. If the SST usage rate is increased, waiting times for customers could be decreased. Shorter waiting time could lead to higher customer satisfaction. It may also result in making a long-term profit owing to the reduced number of employees. Thus, presentation of using SST by employees or videos showing how to use it will promote the usage attitude and intent. 2. In SST core attitudinal model, performance and fun factors among SST usage motivation affected attitudes of using SST. The attitude of using SST highly influenced intent to use SST. This result is consistent with previous researches that dealt with the relationship between motivation, attitude and intention. Expectation of using SST could result in good performance just like the effect of ordering menu to service employees and to have fun since fun during its use could promote more SST usage rate. 3. In the relationship among motivation, attitude and intent in SST core attitudinal model, the moderating effect of consumer traits(self-consciousness, need for interaction with service employees and technology anxiety) and situational factors(perceived crowding and perceived waiting time) were tested. The results also supported the hypothesized moderating effects except perceived crowding. The highly self-conscious tended to form attitudes to use SST because of its fun compared to those who were less self-conscious because of its performance. People who had a high need for interaction with service employees tended to use SST for its performance. This result indicates that if ordering results are assured, SST is easily accessible to even consumers who have a high need for interaction with a service employee. When SST is easy to use, attitudes strengthen intent among people who had a high level of anxiety of technology. People who had low technology anxiety formed attitudes to use SST because of its performance. Service firms must ensure their self service technology is designed to be easy to use for those who have a high level of technology anxiety. Shorter perceived waiting times strengthened the attitude to use self service technology because of its fun. If the fun aspect is assured, people willing to use self service technology even perceive waiting time to be shorter than it actually is. Greater perceived waiting times form higher level of intent to use self service technology than those of shorter perceived waiting times. This implies that people view self service technology as a faster alternative to ordering service employees. The fun aspect of self service technology will attract a higher rate of usage for self service technology. 4. It has been proven that ease of use, performance and fun aspects are very important factors in motivation to form attitudes and intent to use self service technology regardless of the amount of perceived waiting time, self-consciousness, need for interaction with service employees, and technology anxiety. Service firms must consider these motivation aspects(ease of use, performance and fun)strongly in their promotion to use self service technology. Ease of use, assuring absolute performance compared to interaction with service employees', and adding a fun aspect will positively strengthen consumers' attitudes and intent to use self service technology. Summarizing the moderating effects, fun is the most valuable factor triggering SST usage attitude and intention. Therefore, designing self service technology to be fun will be the key to its success. This study focused on the touch screen self service technology in fast food restaurant. Although it has its limits due to the fact that it is hard to generalize the results to any other self service technology, the conceptual framework of this study can be applied to future research of any other service site.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1367-1375
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• 2015

The purpose of this paper is to suggest 10 mm aggregate specification for thin layer asphalt pavement using steel slag. Aggregate gradations of conventional dense-graded asphalt mixtures were made by fuller's model, whereas 10 mm dense-graded asphalt mixture was obtained tender mix due to close to the maximum density line. The proposed aggregate gradation specification was made to have enough VMA and well-interlocking refer to foreign standards. The correlation between the proposed aggregate gradation and the properties of mixtures were analyzed using Gradation Ratio (GR) and Compacted Aggregate Density (CAD). The CAD index has a high $R^2$ of 0.86-0.99 because the CAD index is able to reflect various aggregate properties. As the results of evaluation by CAD index the proposed aggregate gradation provides more reliable stability and VMA. The percent passing (%) of aggregate size smaller than 0.3 mm was limited 10% or more for improving crack resistance. This limitation increased for 15% of the asphalt mixture's toughness.

• Journal of Energy Engineering
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• v.5 no.2
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• pp.160-169
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• 1996

Parametric studies are conducted for optimizing the integration design between gas turbine compressor and air separation unit (ASU) of integrated gasification combined cycle power plant. The present study adopts the ASU of double-distillation column process, from which integration conditions with compressor such as the heat exchanger condition between air and nitrogen, the amount and the pressure of extracted air are defined and mathematically formulated. The performance variations of the compressor integrated with ASU are analyzed by combining streamline curvature method and pressure loss models, and the predicted results are compared with the performance test results of actual compressors to verify the prediction accuracy. Using the present performance prediction method, the effects of pinch-point temperature difference (PTD) in the heat exchanger, the amount and the pressure of extracted air on compressor performances are quantitatively examined. As the extraction air amount or the PTD is increased, the pressure ratio and the power consumption of compressor are increased. The compressor efficiency deteriorates as the increase of the flow rate of air extracted at higher pressure level while improving at lower pressure air extraction. Furthermore, through the characteristic curve between generalized inlet condition and efficiency of compressor, optimal integration condition is presented to maximize the compressor efficiency.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.9
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• pp.925-932
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• 2014

If a rotor possesses a high gyroscopic coupling or the running speed is high, the dynamical changes in the rotor become prominent. When active magnetic bearings are used to support such rotors, it is necessary for the bearing controller to take these dynamical changes into consideration. Independent-axis controllers, which are the most commonly used, modulate the bearing force solely based on the sensor output of the same axis. However, this type of controller has difficulties in overcoming the dynamical changes. On the other hand, mixed-axis controllers transform the sensor output into components corresponding to the vibrational modes. A separate controller can then be designed for each vibrational mode. In this way, the controller can be designed based on the dynamics of the rotor. In this paper, we describe a design process for a mixed-axis controller that uses a detailed mathematical model of the system. The performance of the controller is evaluated based on the ISO sensitivity requirements and unbalance response, while considering the change in the system dynamics due to the running speed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.8
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• pp.640-647
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• 2014

Infrared signature of aircraft exhaust plume is the critical factor for aircraft survivability. To improve the military aircraft survivability, the accurate prediction of infrared signature for the propulsion system is needed. The numerical analysis of thermal fluid field for nozzle inflow, free stream flow, and plume region is conducted by using the in-house code. Weighted Sum of Gray Gases Model based on Narrow Band with regrouping is adopted to calculate the spectral infrared signature emitted from aircraft exhaust plume. The accuracy and reliability of the developed code are validated in the one-dimensional band model. It is found that the infrared radiant intensity is relatively more strong in the plume through the analysis, the results show the different characteristic of the spectral infrared signature along the temperature, the partial pressure, and the species distribution. The continuous spectral radiant intensity is shown near the nozzle exit due to the emission from the nozzle wall.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.434-441
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• 2016

Friction Stir Welding (FSW) is a solid-state joining process involving the frictional heat between the materials and tools. The amount of heat conducted into the workpiece determines the quality of the welded zone. Excessive heat input is the cause of oxides and porosity defects, and insufficient heat input can cause problems, such as tunnel defects. Therefore, analyzing the temperature history and distribution at the center of the Friction Stir Welded zone is very important. In this study, the temperature distribution of the friction stir welding region of an AZ61 magnesium alloy was investigated. To achieve this goal, the temperature and metal flow was predicted using the finite element method. In FE analysis, the welding tool was simplified and the friction condition was optimized. Moreover, the temperature measuring test at the center of the welding region was performed to verify the FE results. In this study, the tool rotation speed was a more dominant factor than the welding speed. In addition, the predicted temperature at the center of the welding region showed good agreement with the measurement results within the error range of 5.4% - 7.7%.