• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.295-308
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• 2021

In recent years, as many people post their interests on social media or store documents in digital form due to the development of the internet and computer technologies, the amount of text data generated has exploded. Accordingly, the demand for technology to create valuable information from numerous document data is also increasing. In this study, through statistical techniques, we investigate how the meanings of Korean words change over time by using the presidential speech records and newspaper articles public data. Using this, we present a strategy that can be utilized in the study of the synchronic change of Hangeul. The purpose of this study is to deviate from the study of the theoretical language phenomenon of Hangeul, which was studied by the intuition of existing linguists or native speakers, to derive numerical values through public documents that can be used by anyone, and to explain the phenomenon of changes in the meaning of words.

• Anxiety and mood
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• v.19 no.1
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• pp.10-18
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• 2023

Objective : The 18-item Obsessive-Compulsive Inventory-Revised (OCI-R) is widely employed to assess symptoms of obsessive-compulsive disorder (OCD). However, this instrument's factor structure does not align with contemporary dimensional models of OCD. Therefore, the objective of this study was to examine psychometric properties of the 12-item Korean OCI (OCI-12) on four obsessive-compulsive symptom dimensions, in patients with OCD. Methods : A total of 157 patients with OCD and 51 healthy controls completed psychological measures, including the OCI-R, Dimensional Obsessive-Compulsive Scale (DOCS), and scales evaluating anxiety and depressive symptoms. Pychometric characteristics of the OCI-12 with three neutralizing and three hoarding items eliminated from the OCI-R, were analyzed. Results : All OCI-12 items registered excellent internal consistency at 0.83. Confirmatory factor analysis revealed strong association between individual items and their proposed latent factors (i.e., subscales). Convergent validity was appropriate. A high correlation was particularly observed for the DOCS score (r=0.71, p<0 .001). Moreover, the OCI-12 was as sensitive as the OCI-R for determining effects of empirically supported treatment for OCD. Conclusion : The OCI-12 is a 12-item measure that adheres to the prevailing 4-factor model of OCD dimensions. Like OCI-R, it possesses good to excellent psychometric properties, including reliability, validity, and sensitivity to treatment.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.53.4-54
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• 2021

Although the era of very large telescopes has come, small telescopes still have advantages for fast follow-up and long-term monitoring observation. Intensive monitoring survey of nearby galaxies (IMSNG) aims to understand the nature of the supernovae (SNe) by catching the early light curve from them with the network of small telescopes from 0.4-m to 1.0-m all around the world. To achieve the scientific goals with heterogeneous facilities, three factors are important. First, automatic processes as soon as data is uploaded will increase efficiency and shorten the time. Second, searching for transients is necessary to deal with newly emerged transients for fast follow-up observation. Finally, the Integrated process for different telescopes gives a homogeneous output, which will eventually make connections with the database easy. Here, we introduce the integrated pipeline, 'gppy' based on Python, for more than 10 facilities having various configurations and its performance. Processes consist of image pre-process, photometry, image align, image combine, photometry, and transient search. In the connected database, homogeneous output is summarized and analyzed additionally to filter transient candidates with light curves. This talk will suggest the future work to improve the performance and usability on the other projects, gravitational wave electromagnetic wave counterpart in Korea Observatory (GECKO), and small telescope network of Korea (SOMANGNET).

• Journal of Distribution Science
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• v.21 no.10
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• pp.21-29
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• 2023

Purpose: The current study focused on developing Klong Kone Shrimp Paste (Mesopodopsis) products and packaging, aiming to enhance the capabilities of entrepreneurs with cultural capital in post-pandemic Samut Songkhram Province. Research design, data and methodology: This study sought to analyze product and packaging issues and examine packaging expectations for Klong Kone shrimp paste. A combination of quantitative and qualitative methods was used, including a questionnaire administered to a sample of 400 individuals who purchased community enterprise products. Descriptive analysis, involving percentage, mean, and S.D., along with qualitative analysis through phenomenological methods, such as in-depth interviews and focus groups, were conducted with community enterprise entrepreneurs, experts, and customers. Results: The findings indicate that addressing product conditions and packaging issues with Klong Kone shrimp paste can be achieved by incorporating an attached label on the community product packaging. Conclusion: This approach is necessary due to the lack of community identity reflection and unattractive design, which currently deter customers from considering the products as souvenirs. Additionally, diversifying product offerings is recommended to better align with consumer needs. In terms of packaging expectations, a majority of respondents expressed a strong preference for an attractive appearance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.851-863
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• 2023

The mandatory use of BIM(Building Information Model) in larger Korean public construction projects necessitates participants to have a comprehensive understanding of the relevant procedures and technologies, especially during the bidding stage. However, most small and medium-sized construction and engineering companies possess limited BIM proficiency and understanding. This hampers their ability to recognize bidding requirements and make informed decisions. To address this challenge, our study introduces a method to gauge the complexity of BIM requirements in bidding documents. This is achieved by integrating a morphological analyzer, which encompasses BIM bidding terminology, with a deep learning model. We investigated the effects of the parameters in our proposed deep learning model and examined its predictive validity. The results revealed an F1-score of 0.83 for the test data, indicating that the model's predictions align closely with the actual BIM performance challenges.

• Steel and Composite Structures
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• v.50 no.4
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• pp.383-401
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• 2024

The research comprehensively studies the axial compression performance of T-shaped concrete-filled thin-walled steel tubular (CTST) long columns after fire exposure. Initially, a series of tests investigate the effects of heating time, load eccentricity, and stiffeners on the column's performance. Furthermore, Finite Element (FE) analysis is employed to establish temperature and mechanical field models for the T-shaped CTST long column with stiffeners after fire exposure, using carefully determined key parameters such as thermal parameters, constitutive relations, and contact models. In addition, a parametric analysis based on the numerical models is conducted to explore the effects of heating time, section diameter, material strength, and steel ratio on the axial compressive bearing capacity, bending bearing capacity under normal temperature, as well as residual bearing capacity after fire exposure. The results reveal that the maximum lateral deformation occurs near the middle of the span, with bending increasing as heating time and eccentricity rise. Despite a decrease in axial compressive load and bending capacity after fire exposure, the columns still exhibit desirable bearing capacity and deformability. Moreover, the obtained FE results align closely with experimental findings, validating the reliability of the developed numerical models. Additionally, this study proposes a simplified design method to calculate these mechanical property parameters, satisfying the ISO-834 standard. The relative errors between the proposed simplified formulas and FE models remain within 10%, indicating their capability to provide a theoretical reference for practical engineering applications.

• Korean Journal of Community Nutrition
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• v.29 no.1
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• pp.16-33
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• 2024

Objectives: The purpose of this study was to examine mothers' knowledge levels on complementary foods and their perception of convenience complementary foods. Methods: An online survey was conducted with mothers aged 20-49 years who had purchased convenience complementary foods and had a preschool child aged 4 months or older. The respondents were categorized into 3 groups based on their knowledge scores: low- (0-50 points), mid- (55-65 points), and high- (70-100 points) knowledge groups. Results: The average score of mothers' knowledge on complementary foods was 58.8 out of 100 points. Working mothers were found to have lower levels of knowledge compared to mothers who were housewives. Only 1/4 of responding mothers had educational experience on complementary foods. Mothers expressed a desire for information on the types of complementary foods (72.2%) and the intake amounts (60.3%) corresponding to each phase of their child's development. Multivariate analysis of variance revealed significant differences in health (P = 0.002), variety (P = 0.039), and hygiene (P = 0.041) among the factors taken into consideration when purchasing convenience complementary foods according to the mothers' knowledge levels. Mothers in the high-knowledge group placed a greater importance on 'balanced nutrition' (P = 0.022) and 'hygienic cooking' (P = 0.010) compared to mothers in the low-knowledge group. The results of the modified importance-performance analysis, which compared the importance and performance of the factors taken into consideration when purchasing convenience complementary foods, highlighted the need for efforts in 'health,' 'hygiene,' and 'price,' while also indicating an excessive effort in 'convenience.' Conclusions: This study suggests expanding relevant education programs to enhance mothers' knowledge on complementary foods, especially for working mothers. In the industry, marketing strategies for complementary food products could be developed that align with the needs of mothers, focusing on health, hygiene, and price.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.363-373
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• 2023

Numerous studies have established a correlation between sociodemographic characteristics and water usage, identifying population as a primary independent variable in mid- to long-term demand forecasting. Recent dramatic sociodemographic changes, including urban concentration-rural depopulation, low birth rates-aging population, and the rise in single-person households, are expected to impact water demand and supply patterns. This underscores the necessity for operational and managerial changes in existing water supply systems. While sociodemographic characteristics are regularly surveyed, the conducted surveys use aggregate units that do not align with the actual system. Consequently, many water demand forecasts have been conducted at the administrative district level without adequately considering the water supply system. This study presents an upward water demand forecasting model that accurately reflects real water facilities and consumers. The model comprises three key steps. Firstly, Statistics Korea's SGIS (Statistical Geological Information System) data was reorganized at the DMA level. Secondly, DMAs were classified using the SOM (Self-Organizing Map) algorithm to consider differences in water facilities and consumer characteristics. Lastly, water demand forecasting employed the PCR (Principal Component Regression) method to address multicollinearity and overfitting issues. The performance evaluation of this model was conducted for DMAs classified as rural areas due to the insufficient number of DMAs. The estimation results indicate that the correlation coefficients exceeded 0.9, and the MAPE remained within approximately 10% for the test dataset. This method is expected to be useful for reorganization plans, such as the expansion and contraction of existing facilities.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.205-220
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• 2023

This study aimed to analyze the needs and interests of the public on endangered wildlife using complaint big data. We collected 1,203 complaints and their corresponding text data on endangered wildlife, pre-processed them, and constructed a document-term matrix for 1,739 text data. We performed LDA (Latent Dirichlet Allocation) topic modeling and network analysis. The results revealed that the complaints on endangered wildlife peaked in June-August, and the interest shifted from insects to various endangered wildlife in the living area, such as mammals, birds, and amphibians. In addition, the complaints on endangered wildlife could be categorized into 8 topics and 5 clusters, such as discovery report, habitat protection and response request, information inquiry, investigation and action request, and consultation request. The co-occurrence network analysis for each topic showed that the keywords reflecting the call center reporting procedure, such as photo, send, and take, had high centrality in common, and other keywords such as dung beetle, know, absence and think played an important role in the network. Through this analysis, we identified the main keywords and their relationships within each topic and derived the main issues for each topic. This study confirmed the increasing and diversifying public interest and complaints on endangered wildlife and highlighted the need for professional response. We also suggested developing and extending participatory conservation plans that align with the public's preferences and demands. This study demonstrated the feasibility of using complaint big data on endangered wildlife and its implications for policy decision-making and public promotion on endangered wildlife.

• Journal of IKEEE
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• v.28 no.3
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• pp.352-359
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• 2024

This paper proposes a CNN-ViT hybrid model that automatically evaluates the aesthetic quality of images by combining local and global features. In this approach, CNN is used to extract local features such as color and object placement, while ViT is employed to analyze the aesthetic value of the image by reflecting global features. Color composition is derived by extracting the primary colors from the input image, creating a color palette, and then passing it through the CNN. The Rule of Thirds is quantified by calculating how closely objects in the image are positioned near the thirds intersection points. These values provide the model with critical information about the color balance and spatial harmony of the image. The model then analyzes the relationship between these factors to predict scores that align closely with human judgment. Experimental results on the AADB image database show that the proposed model achieved a Spearman's Rank Correlation Coefficient (SRCC) of 0.716, indicating more consistent rank predictions, and a Pearson Correlation Coefficient (LCC) of 0.72, which is 2~4% higher than existing models.