• Journal of the Korean Society of Food Culture
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• v.24 no.6
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• pp.805-812
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• 2009

The consumer acceptance of food is not only affected by the sensory characteristics of food but also by the non-food factors, including food experience, consumption frequency, and food attitudes. Therefore, food attitude scales such as the food neophobic scale, VARSEEK scale, Dutch restrained eating scale, health taste attitude scale, etc. have been developed and effectively used to predict consumer liking and behaviors. Since the globalization of Korean food is currently one of the hottest topics in the Korean food industry, the aim of this study was to identify the tastes and flavors that may represent Korean cuisine. Additionally, an attitudinal scale for Korean taste and flavors was developed, which can then be utilized to predict a consumer's liking of Korean food. In the first stage of the experiment, the representative taste and flavors of Korean cuisine was surveyed by a Korean culinary expert group (n=23) and general consumers (n=62). As a result of these surveys, 4 types of flavors, hot pepper flavor, 'goso' flavor, garlic flavor, and fermented flavor were shown to be the most representative flavors of Korean cuisine. Based on these results, the second stage of the experiment was carried out to develop an attitudinal scale for Korean style flavors. Eleven to 17 questionnaires were developed for each of the 4 types of flavors. The survey consisted of a total of 53 questionnaires and 154 female consumers and 158 male consumers participated in the survey. The data was analyzed by factor analysis. For each type of flavor, the final attitudinal questionnaires were selected based on the following criteria: 1. high absolute factor loading value, 2. carrying clear meaning of the corresponding flavor attitude, and 3. delivering the meaning sufficiently when translated into other language. The final Korean style flavor attitude scale consisted of 7 hot pepper flavor, 6 'goso' flavor, 6 garlic flavor, and 7 fermented flavor questionnaires. In the next step of this study, experiments will be carried out to validate the Korean style flavor attitude scale.

• Journal of Korea Water Resources Association
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• v.56 no.7
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• pp.439-449
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• 2023

Recent advancements in data measuring technology have facilitated the installation of various sensors, such as pressure meters and flow meters, to effectively assess the real-time conditions of water distribution systems (WDSs). However, as cities expand extensively, the factors that impact the reliability of measurements have become increasingly diverse. In particular, demand data, one of the most significant hydraulic variable in WDS, is challenging to be measured directly and is prone to missing values, making the development of accurate data generation models more important. Therefore, this paper proposes an adversarially trained autoencoder (ATAE) model based on generative deep learning techniques to accurately estimate demand data in WDSs. The proposed model utilizes two neural networks: a generative network and a discriminative network. The generative network generates demand data using the information provided from the measured pressure data, while the discriminative network evaluates the generated demand outputs and provides feedback to the generator to learn the distinctive features of the data. To validate its performance, the ATAE model is applied to a real distribution system in Austin, Texas, USA. The study analyzes the impact of data uncertainty by calculating the accuracy of ATAE's prediction results for varying levels of uncertainty in the demand and the pressure time series data. Additionally, the model's performance is evaluated by comparing the results for different data collection periods (low, average, and high demand hours) to assess its ability to generate demand data based on water consumption levels.

• Journal of Korea Water Resources Association
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• v.56 no.7
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• pp.461-470
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• 2023

The purpose of this research is to derive the optimal temperature, location, and heating control system for a tipping bucket rain gauge heating system used for observing snowfall during winter. We conducted indoor and outdoor experiments by manufacturing a tipping bucket rain gauge that can be variably controlled for heating at the funnel, exterior, and interior, and indoor and outdoor. The indoor experiments involved using a temperature and humidity chamber to compare the performance and derive the appropriate temperature of the precipitation gauge heating system. Subsequently, the outdoor experiments were carried out at the Cloud Physics Observation Center located in Daeguallyeong, heavy snowfall region, to validate the findings. The analysis result was derived that the heating temperature of the funnel should be set at the 10 to 30℃, while the internal heating temperature should be 70℃. Furthermore, the optimal locations for the heating devices, which aim to minimize measurement delay, were identified as the exterior of the rain gauge, the rim of the funnel, and the vertical surface of the funnel. Our result shows that used as the basis for the operating conditions of precipitation gauge heating systems for solid precipitation measurement in winter.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.117-125
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• 2023

In the development of clothing design through virtual simulation, it is essential to minimize the differences between the virtual and the real world as much as possible. The most critical task to enhance the similarity between virtual and real garments is to find simulation parameters that can closely emulate the physical properties of the actual fabric in use. The simulation parameter optimization process requires manual tuning by experts, demanding high expertise and a significant amount of time. Especially, considerable time is consumed in repeatedly running simulations to check the results of applying the tuned simulation parameters. Recently, to tackle this issue, artificial neural network learning models have been proposed that swiftly estimate the results of drape test simulations, which are predominantly used for parameter tuning. In these earlier studies, relatively simple linear stiffness models were used, and instead of estimating the entirety of the drape mesh, they estimated only a portion of the mesh and interpolated the rest. However, there is still a scarcity of research on non-linear stiffness models, which are commonly used in actual garment design. In this paper, we propose a learning model for estimating the results of drape simulations for non-linear stiffness models. Our learning model estimates the full high-resolution mesh model of drape. To validate the performance of the proposed method, experiments were conducted using three different drape test methods, demonstrating high accuracy in estimation.

• Korean Journal of Construction Engineering and Management
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• v.24 no.1
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• pp.31-39
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• 2023

To reduce facility management costs and safety concerns due to aging of facilities, it is important to estimate the future facilities' condition based on facility management data and utilize predictive information for management decision making. To this end, this study proposed a methodology to estimate facility elements' condition using XGBoost. To validate the proposed methodology, this study constructed sample data for road bridges and developed a model to estimate condition grades of major elements expected in the next inspection. As a result, the developed model showed satisfactory performance in estimating the condition grades of deck, girder, and abutment/pier (average F1 score 0.869). In addition, a testbed was established that provides data management function and element condition estimation function to demonstrate the practical applicability of the proposed methodology. It was confirmed that the facility management data and predictive information in this study could help managers in making facility management decisions.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.3-12
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• 2022

In general construction project planning ratio of manpower and quantity of outputs produced, such as the construction estimate standard, is used as the criterion for labor productivity. This method is highly effective in construction projects with repetitive work, however, there is a limit to apply in large-scale projects with high complexity. This is because the influence of non-work time caused by various work interruption factors that act complexly on the productivity of the project is greater than the average labor productivity derived from the performance data of the project. Therefore, this study proposes a productivity measurement method that can evaluate the characteristics of construction works and the cause of non-working time. To this end, first, detailed work processes and their non-work factors for each work type are defined, and the Adv-FMR technique is developed for quantitatively measuring them. Next, based on the concept of obtainable productivity, methods for comparative productivity analysis by work type, evaluating non-work factors, and deriving productivity improvement methods are proposed. Finally, a case study is conducted to validate that the analysis results based on Adv-FMR data can support the decision-making of construction managers on productivity management.

• Journal of the Korean GEO-environmental Society
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• v.24 no.8
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• pp.5-11
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• 2023

Due to frequent occurrences of concentrated heavy rainfall caused by abnormal climate conditions in recent years, collapses of steep slopes have been occurring frequently due to surface erosion and increased pore water pressure. Various methods are being applied to prevent slope collapses, such as increasing the resistance to movement and reducing pore water pressure. Research on these methods has been consistently conducted as they provide an efficient response to slope collapses by satisfying both the conditions of resistance to movement and pore water pressure simultaneously. Therefore, in this study, we propose an upward slope reinforcement method by burying drainage materials with an upward slope inclination, instead of the conventional horizontal application. This approach aims to satisfy both slope reinforcement and drainage functions effectively, offering a comprehensive solution for slope stabilization. Furthermore, to determine the optimal burial angle that exhibits the most effective reinforcement and drainage effects of the proposed method, we investigated the reinforcement and drainage effects under conditions where the horizontal drainage materials were set at angles ranging from 0° to 60° in increments of 10° on a representative cross-section. Additionally, indoor model experiments were conducted under the conditions of 40°, which showed the most outstanding drainage effect, and 20°, which exhibited the highest safety factor, to validate the numerical analysis results. The results showed that the burial angle of 40° exhibits a relatively higher drainage effect as with the numerical analysis results, while the angle of 20° results in inadequate drainage and observed slope collapse.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.345-354
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• 2006

Drought brings on long term damage in contrast to flood, on economic loss in the region, and on ecologic and environmental disruptions. Drought is one of major natural disasters and gives a painful hardship to human beings. So we have tried to quantify the droughts for reducing drought damage and developed the drought indices for drought monitoring and management. The Palmer's drought severity index (PDSI) is widely used for the drought monitoring but it has the disadvanges and limitations in that the PDSI is estimated by considering just climate conditions as pointed out by many researchers. Thus this study uses the SWAT model which can consider soil conditions like soil type and land use in addition to climate conditions. We estimate soil water (SW) and soil moisture index (SMI) by SWAT which is a long term runoff simulation model. We apply the SWAT model to Soyang dam watershed for SMI estimation and compare SMI with PDSI for drought analysis. Say, we calibrate and validate the SWAT model by daily inflows of Soyang dam site and we estimate long term daily soil water. The estimated soil water is used for the computation of SMI based on the soil moisture deficit and we compare SMI with PDSI. As the results, we obtained the determination coefficient of 0.651 which means the SWAT model is applicable for drought monitoring and we can monitor drought in more high resolution by using GIS. So, we suggest that SMI based on the soil moisture deficit can be used for the drought monitoring and management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6A
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• pp.543-560
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• 2010

Safety-related concrete structures in a nuclear power plant must be protected against the impact of flying objects, referred to in the profession as missiles. In practice, the structural verification is usually carried out by means of empirical formulas, which relate the velocity of the impinging missile to the wall thickness needed to prevent scabbing or perforation. The purpose of this study is to reevaluate the predictability of the local effect prediction formulas for the penetration and scabbing depths and perforation thickness. Therefore, available formulas for predicting the penetration depth, scabbing thickness, and perforation thickness of concrete structures impacted by solid missiles are summarized, reviewed, and compared. A series of impact analyses is performed to predict the local effects of the projectile at impact velocities varing from 95 to 215 m/s. The results obtained from the numerical simulations have been compared with tests that were carried out at Kojima to validate numerical modelling. The simulation results show reasonable agreement with the Kojima test results for the overall impact response of the RC slabs. From these results, it seems that the Degen equation give a very good estimate of perforation thickness against a tornado projectile for test data. Finally, the results obtained from the impact analysis have been compared with Degen formula to determine the perforation thickness of the RC slab.

• Korean Journal of Culture and Social Issue
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• v.24 no.3
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• pp.385-410
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• 2018

Materialistic values can be a important variable to understand Koreans' psychological well-being and mental health. This study aimed to validate the Korean version of the Material Values Scale (K-MVS)(Richins & Dawson, 1992). In study 1, we performed confirmatory factor analysis(CFA) to ascertain the three factor model of the original MVS using 417 Korean undergraduate student data(sample 1). The CFA confirmed the three-factor model of the MVS. Yet, three items that yielded low factor loadings in this study as well as in other MVS validation studies were excluded from the final model. In study 2, content, construct, and concurrent validity of the K-MVS were examined with 650 undergraduate student data(Sample 2). We also tested measurement invariance across two groups(i.e., college student group of Sample 2 and employee group of Sample 3). The result revealed that the three-factor model of the K-MVS hold true across the two groups. Lastly test-retest reliability was calculated with 408 female college student data(Sample 4) that filled out K-MVS twice within 6 months. These findings suggest that the K-MVS is a reliable and valid measure for assessing materialistic values in Korea.