• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.603-616
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• 2023

In this study, machine learning-based clustering and classification of residential noise in apartment buildings was conducted using frequency and temporal characteristics. First, a residential noise source dataset was constructed . The residential noise source dataset was consisted of floor impact, airborne, plumbing and equipment noise, environmental, and construction noise. The clustering of residential noise was performed by K-Means clustering method. For frequency characteristics, L_eq and L_max values were derived for 1/1 and 1/3 octave band for each sound source. For temporal characteristics, Leq values were derived at every 6 ms through sound pressure level analysis for 5 s. The number of k in K-Means clustering method was determined through the silhouette coefficient and elbow method. The clustering of residential noise source by frequency characteristic resulted in three clusters for both L_eq and L_max analysis. Temporal characteristic clustered residential noise source into 9 clusters for L_eq and 11 clusters for L_max. Clustering by frequency characteristic clustered according to the proportion of low frequency band. Then, to utilize the clustering results, the residential noise source was classified using three kinds of machine learning. The results of the residential noise classification showed the highest accuracy and f1-score for data labeled with L_eq values in 1/3 octave bands, and the highest accuracy and f1-score for classifying residential noise sources with an Artificial Neural Network (ANN) model using both frequency and temporal features, with 93 % accuracy and 92 % f1-score.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Venture Innovation
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• v.4 no.3
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• pp.125-139
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• 2021

As the 4th industrial revolution progresses, new technologies and services are being born, growing, and maturing. Now, beyond the mobile era, the metaverse is being discussed as a new paradigm. Therefore, in this study, in preparation for the metaverse era, we tried to analyze what factors have an important influence when consumers want to use new technologies. In particular, the research was conducted focusing on how the context in which consumers use the technology changes depending on whether they are B2C or B2B. For this, augmented reality (AR) was selected in the B2C context by linking the research subject with the metaverse era, and the smart factory was selected in the B2B context. The research model for the analysis was established by deriving and setting common influence variables by reflecting the characteristics of the research target technology based on the modified extended unified theory of acceptance and use of technology. A survey was conducted for empirical analysis, and 150 AR and 150 smart factory subjects were analyzed. The empirical study results are as follows. The relationship between performance expectancy and intention to use, technology readiness and intention to use was found to have a significant positive (+) effect on both AR and smart factory. On the other hand, it was found that effort expectancy, social influence, and trust had a positive (+) effect on intention to use only in AR. Only in smart factory, facilitating conditions had a significant positive (+) effect on intention to use. It was also found that the perceived risk had a significant negative (-) effect on the intention to use only in the smart factory. The results of this study are academically significant in that we empirically test that influencing factors of technology use varies depending on the context in which it is used by consumers. In practice, it provided an implication of what to focus on first is being implemented.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.125-140
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• 2023

Careful preparation for a start-up can lower the risk of failure and create a successful business model. However, there are still challenges for middle-aged entrepreneurs, as start-up services and policies are often not readily accessible or fully utilized. Despite active research on middle-aged start-ups, previous studies have not delved deeply into the demographics of start-up preparation and various preparation behaviors. In response to this, a study was conducted to identify which start-up support services middle-aged entrepreneurs use, and how start-up preparation can be classified based on this. Data from 324 middle-aged tech start-up owners, based in Seoul and who started their businesses within the past 7 years, was collected and analyzed. The results showed that middle-aged entrepreneurs had moderate start-up preparation, with the greatest focus on the preparation period and the least focus on start-up education. Latent Profile Analysis revealed three groups of start-up preparation types among middle-aged entrepreneurs: "Overall Tribal Type," "Lack of Start-up Education Type," and "Comprehensive Preparation Type." BCH was performed on start-up satisfaction, start-up competence, fear of failure, access to start-up services, and support needs for middle-aged entrepreneurs based on the preparation type. The results showed that "Overall Tribal Type" had statistically lower start-up satisfaction, competence, and service accessibility compared to the other groups. Meanwhile, "Comprehensive Preparation Type" had a statistically lower fear of failure than the other types. "Overall Tribal Type" also had lower accessibility to middle-aged start-up services. All types had a high recognition of the need for support for specialized middle-aged start-ups. The findings highlight the need for more comprehensive support for middle-aged entrepreneurs. This could include expanding support projects to enhance their level of preparation, providing customized support based on their level of preparation, and improving the visibility and accessibility of start-up support services for middle-aged individuals. Additionally, specialized education that addresses the characteristics of middle-aged individuals should be provided.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.217-240
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• 2023

For a while, Functional cosmetics, Cosmeceutical cosmetics, and Derma cosmetics have gained trust and become popular due to the consumers' strong interest in ingredients & efficacy. It's remarkable that Clean or Vegan brands are growing fast because they are emphasizing on different values from the other cosmetic brands. It's needed to attempt to analyze the influence relationship between consumer lifestyle and social value in these changes, and to find out whether the consumption of vegan cosmetics is related to satisfying the need for self-expression in a social atmosphere where ESG is emphasized on. This study analyzed the effect of lifestyle types and self-expression needs on the purchase intention of vegan cosmetics by mediating social values for cosmetics consumers. Lifestyle types were classified into appearance-oriented, health-oriented, and fashion-oriented. For empirical analysis, 321 questionnaires collected from cosmetics consumers living across the country were used. SPSS v26.0 and PROCESS macro v4.2 were used to analyze based on a single mediating model as a single mediator. As a result of the analysis, first, lifestyle types and self-expression needs, excluding appearance-oriented types, were found to have a positive (+) effect on social values. Second, it was found that social value had a positive (+) significant effect on the purchase intention of vegan cosmetics. Third, appearance-oriented, health-oriented, trend-seeking lifestyle types and self-expression needs were all found to have a positive (+) effect on the purchase intention of vegan cosmetics. Fourth, social values were found to mediate lifestyle types, self-expression needs, and purchase intentions, except for appearance-oriented types. Appearance-oriented consumers do not directly affect social values but affect purchase intentions, suggesting that appearance-oriented consumers may not be significantly affected by product-related social values. In a comparison of the relative influence size using standardization coefficients, self-expression needs had the greatest impact on the purchase intention of vegan cosmetics when mediating social values, and health-oriented ones had the least impact. The academic implications of this study include contributing to consumer behavior research by providing insights, mediation mechanisms, and consideration of the niche consumer sector, and directing further research into the cosmetics industry beyond forming marketing strategies and sustainable business practices.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.169-185
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• 2022

This study analyzed the effect of entrepreneurial competency on entrepreneurial intentions by using the entrepreneurial opportunity recognition as a mediator for middle and middle-aged office workers. The sub-variables of entrepreneurial competency are classified into management competency, technology competency, business competency and funding competency. 222 copies of questionnaires collected from middle-aged and elderly office workers residing across the country centered on the metropolitan area were used for empirical analysis. Based on a simple mediating model with singular mediator using SPSS v22.0 and PROCESS macro v4.0. was analyzed. As a result of the analysis, first, among entrepreneurial competencies, business competency and funding capacity were found to have a positive (+) significant effect on the entrepreneurial intentions, but management and technical competency did not have a significant effect. The higher the business competency and funding competency. Second, it was found that all of the sub-variables of entrepreneurial competency had a significant effect in the positive (+) direction on the recognition of entrepreneurial opportunities. It was confirmed that management competency has the greatest influence on the entrepreneurial opportunity recognition and technology competence has the smallest effect. Third, it was found that the entrepreneurial opportunity recognition had a significant effect on entrepreneurial intentions. The discovery of an opportunity recognizing opportunities for start-up is a prerequisite for entrepreneur. Fourth, it was found that the entrepreneurial opportunity recognition mediates between the management competency, technological competency, business competency, funding competency, and entrepreneurial intention. It suggests that opportunity discovery by recognizing opportunities for entrepreneurship is a prerequisite for start-up. As implications of this study, it suggests that in order to inspire middle-aged and elderly office workers to start their own business, it is necessary to have indirect experience with education and to establish and promote a government support system for financing.. Second, It suggests that education on leadership and organizational management is particularly necessary to strengthen the opportunity recognition. Third, it suggests that the discovery of opportunities to recognize opportunities for start-up is a prerequisite for entrepreneur. Therefore, it is necessary to prepare a manual and conduct training on opportunity search, recognition, evaluation, and utilization according to the stage of opportunity development. Fourth, it suggests that in order to strengthen the intention to start a business, ALso, it is necessary to manage both the entrepreneurial competency and entrepreneurial opportunities recognition at the same time. By presenting the practical directions that can be given differentially, we intend to contribute to the provision of practical directions and policy establishment for the promotion of entrepreneurial activities of office workers who can give vitality to the ecosystem.

• Journal of the Korean Society of Radiology
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• v.82 no.3
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• pp.670-681
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• 2021

Purpose This study aimed to investigate the optimal threshold value in Hounsfield units (HU) on CT to detect the solid components of pulmonary subsolid nodules using pathologic invasive foci as reference. Materials and Methods Thin-section non-enhanced chest CT scans of 25 patients with pathologically confirmed minimally invasive adenocarcinoma were retrospectively reviewed. On CT images, the solid portion was defined as the area with higher attenuation than various HU thresholds ranging from -600 to -100 HU in 50-HU intervals. The solid portion was measured as the largest diameter on axial images and as the maximum diameter on multiplanar reconstruction images. A linear mixed model was used to evaluate bias in each threshold by using the pathological size of invasive foci as reference. Results At a threshold of -400 HU, the biases were lowest between the largest/maximum diameter of the solid portion of subsolid nodule and the size of invasive foci of the pathological specimen, with 0.388 and -0.0176, respectively. They showed insignificant difference (p = 0.2682, p = 0.963, respectively) at a threshold of -400 HU. Conclusion For quantitative analysis, -400 HU may be the optimal threshold to define the solid portion of subsolid nodules as a surrogate marker of invasive foci.

• Journal of Nutrition and Health
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• v.57 no.1
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• pp.1-15
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• 2024

Purpose: This study aimed to develop a comprehensive tool for assessing dietary guideline adherence among older Korean adults, focusing on the domains of food and nutrient intake, eating habits, and dietary culture. Methods: Candidate items were selected through a literature search and expert advice. The degree of adherence to dietary guidelines was then evaluated through a face-to-face survey conducted on 800 elderly individuals across five nationwide regions. The items for dietary guideline adherence evaluation tool were selected through exploratory factor analysis of the candidate items in each of the three areas of the dietary guidelines, and construct validity was verified by performing confirmatory factor analysis. Using the path coefficient of the structural equation model, weights were assigned to each area and item to calculate the dietary guideline adherence score. A rating system for the evaluation tool was established based on national survey results. Results: A total of twenty-eight items were selected for evaluating dietary guideline adherence among the elderly. Thirteen items related to food intake, seven to eating habits, and eight to dietary culture. The average score for dietary guideline adherence was 56.9 points, with 49.8 points in the food intake area, 63.2 points in the eating habits area, and 58.6 points in the dietary culture area. Statistically significant correlations were found between dietary guideline adherence scores and food literacy (r = 0.679) and nutrition quotient scores (r = 0.750). Conclusion: The developed evaluation tool for dietary guideline adherence among Korean older adults can be used as a simple and effective instrument for comprehensively assessing their food and nutrient intake, dietary habits, and dietary culture.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.2
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• pp.127-139
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• 2024

Climate change has increased extreme weather events likewise heatwaves, heavy rain, and drought. Unlike other natural disaster, drought is a slowly developing phenomenon and thus drought damage increases as the drought continues. Therefore, it is necessary to understand the characteristics and mechanism of drought occurrence. Agricultural drought occurs when the water supply needed by crops becomes insufficient due to lack of soil water. Therefore, soil water is used as a key variable affecting agricultural drought. In this study, we examined the spatio-temporal distribution and trends of drought across the Korean Peninsula by determining the soil available water content (SAWC) through a model that integrated soil, meteorological, and crop data. Moreover, an investigation into the correlation between meteorological variables and the SAWC was conducted to assess how meteorological characteristics influence the nature of drought occurrences. During the soybean cultivation period, the average SAWC was lowest in 2018 at 88.6% and highest in 2021 at 103.2%. Analysis of the spatial distribution of SAWC by growth stage revealed that the lowest SAWC occurred during the flowering stage (S3) in 2018, during the leaf extension stage (S2) in 2019, during the seedling stage (S1) in 2020, again during the flowering stage (S3) in 2021, and during the seedling stage (S1) in 2022. Based on the average SAWC across different growth stages, the frequency of upland drought was the highest at 22 times during the S3 in 2018. The lowest SAWC was primarily influenced by a significant negative correlation with rainfall and evapotranspiration, whereas the highest SAWC showed a significant positive correlation with rainfall and relative humidity, and a significant negative correlation with reference evapotranspiration.