• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.267-279
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• 2023

This research assessed the feasibility of using high-resolution aerial images and deep learning algorithms for estimating the land-use and land-cover areas at the Approach 3 level, as outlined by the Intergovernmental Panel on Climate Change. The results from different sampling densities of high-resolution (51 cm) aerial images were compared with the land-cover map, provided by the Ministry of Environment, and analyzed to estimate the accuracy of the land-use and land-cover areas. Transfer learning was applied to the VGG16 architecture for the deep learning model, and sampling densities of 4 × 4 km, 2 × 4 km, 2 × 2 km, 1 × 2 km, 1 × 1 km, 500 × 500 m, and 250 × 250 m were used for estimating and evaluating the areas. The overall accuracy and kappa coefficient of the deep learning model were 91.1% and 88.8%, respectively. The F-scores, except for the pasture category, were >90% for all categories, indicating superior accuracy of the model. Chi-square tests of the sampling densities showed no significant difference in the area ratios of the land-cover map provided by the Ministry of Environment among all sampling densities except for 4 × 4 km at a significance level of p = 0.1. As the sampling density increased, the standard error and relative efficiency decreased. The relative standard error decreased to ≤15% for all land-cover categories at 1 × 1 km sampling density. These results indicated that a sampling density more detailed than 1 x 1 km is appropriate for estimating land-cover area at the local level.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.97-107
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• 2009

Television News has significant impact on the information analysis of viewers by delivering world news to anonymous individuals everyday. We need to pay more attention to resolution considering the fact that even slight facial expression and the dress of TV anchor can be noticed by viewers in the high definition age, called HD TV, by radical changes in broadcasting situation. As a result, the beauty of expression that lighting technology has is extremely important in the high definition age. In news broadcast, as a phenomenon according to this change in trend, people have been looking for change in order to break with traditional TV news production by adopting DLP(Digital Lighting Processing) or LED(Light Emitting Diode). This effort has contributed to creating proper picture quality appropriate for HD TV. Nowadays Digital imaging is creating new trend in TV news production method from traditional analog-based lighting environment thanks to the development of IT(Information Technology) and digitalized lighting equipment. This change has led to building of HD studio and appropriate sets and lighting system. There are film set and projector which projects image on the screen and PDP, LCD, and DLP which has been used widely in recent years and LED which is often used as background in news program as examples, which has appeared since 1990s with HD TV. In this article, I analyzed the KBS News 9 lnce 1990s with in order to research the influence of television image component on the alyzed the KBS of TV article, I. I wille uggest the category of TV anchor image formulation in delivering information by means of lnce 1990s with based on the analysis result.

• Journal of Popular Narrative
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• v.25 no.2
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• pp.169-216
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• 2019

This study proposes the concept of Bachchin's Chronotope as a tool for analyzing coevolution between the genre of the epic and society. Bachchin says through the concept of chronotope, literary works are on the foundation on which the axs of time and space intersect, and the literary works standsuch intersections are always conversing with social and historical chronotopes and mutually penetrating. Thus, finding and analyzing chronotope in literary works and extended things such as films and dramas reveals how chronotope and chronotope of a society have created specific social realities through a process of resonance. To make analytical use of this concept, we proposed a "cronotope drama analysis method" and concretely analyzed the genre of Korean medical dramas. The naturalized categories of health care, health, and disease are socially constructed entities, and the analysis of public works that has a significant impact on this process of social construction is essential but was underperformed. According to the analysis, the Korean medical drama's "Chronotope" has evolved using "Chronotope of the school" and "Chronotope of the secret chamber". At this time, the genre of Chronotope was expanding spatially and converging in time. In other words, the influence of structures and systems within the genre has grown, and the capacity of individual actors has decreased. This change in chronotope was interpreted as resonating with the social reality of neo-liberalistic spatial expansion and simultaneous production. The neo-liberalistic trend that dominates Korean society has embraced the category of health care and was further influencing the chronotope of drama text. It can also be inferred that the popular understanding of health care produced by the medical drama genre has taken a break in the process of forming a social reality of health care again.

• Asia Marketing Journal
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• v.15 no.4
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• pp.1-32
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• 2014

The purpose of this paper is to investigate upon a diversification strategy through market creation of CJ Group, which has contributed in positioning of the firm as one of the leading conglomerates in South Korea. With such objective, the background of CJ Group, followed by its business diversification strategies were explored, with reference to several case studies. The history of CJ Group began with establishment of CheilJedang Industrial Corporation in 1953, as the first domestic sugar producer and exporter of South Korea. The corporation gradually expanded its business ever since at both national and global level, to include the fields of food production, pharmaceutical, biotechnology, and life chemicals. Later, CheilJedang (CJ) Group was established as an affiliate of CheilJedang Industrial Corporation. With such independence, extension of business has been witnessed across the industries of media, entertainment, finance, information technology and distribution. Thus, the current CJ Group pursues to define itself as a progressive global living culture company with four major business categories from food and food service, biotechnology, entertainment and media, and logistics. Despite its success in today's market, CJ Group underwent hardships in its business diversification in 1990s due to indiscreet management, along with the Asian financial crisis. Here, many firms overcame the financial difficulties by taking advantage of the exchange rate for overseas expansion. Though, CJ Group tried to differentiate itself by focusing on the domestic market by creating something out of nothing. Hence, CJ Group takes a unique position among many cases of business diversification and their categorization. In an effort to identify and classify the types of growth experienced by the top 30 companies in South Korea, the firms were categorized into four groups according to their diversification strategies adapted after the Asian financial crisis. Based on the mode and time of entry, corporations were identified either as the 'Explorer', 'Invader', 'Venture Capitalist', or 'Assimilator'. Here, the majority of the firms showed the qualities of Invader, entering mature markets through large-scaled mergers and acquisitions. However, CJ Group was the only firm that was categorized as an Explorer, for its focus on the newly emerging service sector in culture-contents industry. This diversification strategy through market creation is worth examining, due to its contribution in generating simultaneous growth between the market and the company itself. Diverse brands of CJ Group have been referred to as case studies in this regard, from 'Hatban', 'Cine de Chef', 'VIPS' to 'CJ GLS'. These four businesses, each to represent processed food, film, restaurant service, and logistics industries respectively, show CJ Group's effectiveness in creating a whole new category of goods and services that are innovative. In fact, such businesses not only contributed in advancement of consumers' wellbeing, but toward generating additional value and employment. It is true that the diversification strategy of CJ Group requires long-term capital investment with high risk, compared to the other strategies mentioned in the paper. However, this model does create high employment and additional values that are positive to both the society and the firm itself. Therefore, the paper comes to a conclusion that the diversification strategy through market creation conveys the most positive impact relative to the others.

• Journal of Venture Innovation
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• v.6 no.3
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• pp.185-202
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• 2023

The COVID-19 pandemic catalyzed major changes in our work environment, underscoring the critical role of workplace flexibility. While a wealth of research exists on specific flexible work strategies and schedules, a broader understanding of workplace flexibility has been somewhat overlooked. This study aimed to bridge this gap by examining the correlation between workplace flexibility and organizational commitment. Our sample consisted of 300 employees from foreign businesses in the ICT(information and communications technology) service sector and the manufacturing industry, along with those from the top 50 leading Korean enterprises. We bifurcated workplace flexibility into two distinct categories for this study: quantitative and qualitative. Our results revealed that within the quantitative category, the flexibility of continuity of work and flexible place significantly enhanced organizational commitment. Interestingly, the flexibility of work schedules didn't have a marked impact on commitment levels. On the qualitative side, job autonomy and teamwork emerged as significant drivers of organizational commitment. It's worth noting that qualitative aspects of workplace flexibility had a more pronounced effect on organizational commitment than the quantitative elements. These findings highlight the necessity of approaching workplace flexibility from a comprehensive perspective, embracing both its quantitative and qualitative dimensions. For businesses aiming to maximize the benefits of flexibility, it's essential to cultivate a culture of open communication, champion collaboration, and prioritize job autonomy and teamwork. Establishing a work environment that actively supports feedback-oriented communication stands as a key component in this endeavor.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.45-55
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• 2024

This study analyzed the efficiency determinants of specialty construction companies by industry using the DEA model and the Tobit model. The analysis targets are 394 specialty construction companies as of 2022. As a result of analysis of efficiency determinants using 12 company characteristics as independent variables, the biggest problem for specialty construction companies was overall efficiency reduction due to rising labor costs. In addition, in a situation where construction companies' loan regulations are severe, the debt ratio was found to have a positive effect on efficiency. Company size had a different impact by industry, and the number of businesses held, credit score, and total capital turnover had an effect only on some industries. This study presents results that are an advance on existing research in that it strategically analyzes factors for improving the efficiency of specialty construction companies. However, it has limitations such as limiting the analysis to only specialty construction companies subject to external audit, insufficient number of companies subject to analysis by industry, and analyzing relative efficiency in the same category for each industry.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.157-167
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• 2024

Background: Several previous studies have shown that commuting is a source of stress for undergraduate students. However, few studies have investigated the effect of commuting on academic stress among undergraduate students, and there has been little awareness of the environmental impact of commuting. Objectives: To evaluate the associations between commute type and/or time and academic stress among undergraduate students in South Korea, focusing on environmental sustainability. Methods: We conducted an online survey and obtained information on commute types, commute times, and academic stress from 510 undergraduate students aged ≥19 years. Academic stress was comprised of five sub-categories of stress, and total academic stress ranged from 5 to 25 points. Multiple linear regression analysis was used to analyze the associations between commute type and commute time and academic stress. Furthermore, the students were grouped into 21 categories based on their transportation mode for commuting. CO₂ emission factors per each commuting category were calculated using the transportation type's CO₂ emission data from previous studies. Spearman's correlation analysis was used to confirm the correlation between CO₂ emission factors and total academic stress. Results: Students using home-to-school transportation without transfers (vs. walking) showed a significantly higher total academic stress of 2.19 points (95% CI: 0.58, 3.80). In contrast, students using school-to-home transportation without transfers (vs. walking) showed a significantly lower total academic stress of 1.96 points (95% CI: -3.55, -0.38). Moreover, students using transportation with lower CO₂ emission factors had lower academic stress scores (home-to-school: correlation coefficient = 0.507, p<0.001; school-to-home: correlation coefficient = 0.491, p<0.001). Conclusions: Our findings suggest that both commute type and time are significantly associated with academic stress among South Korean undergraduate students. When students select environmentally-friendly transportation, they may not only improve their mental health but also improve climate resilience.

• Information Systems Review
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• v.24 no.1
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• pp.39-57
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• 2022

This paper proposes the GMOPTBoost algorithm to improve the performance of the AdaBoost algorithm for bankruptcy prediction in which class imbalance problem is inherent. AdaBoost algorithm has the advantage of providing a robust learning opportunity for misclassified samples. However, there is a limitation in addressing class imbalance problem because the concept of arithmetic mean accuracy is embedded in AdaBoost algorithm. GMOPTBoost can optimize the geometric mean accuracy and effectively solve the category imbalance problem by applying Gaussian gradient descent. The samples are constructed according to the following two phases. First, five class imbalance datasets are constructed to verify the effect of the class imbalance problem on the performance of the prediction model and the performance improvement effect of GMOPTBoost. Second, class balanced data are constituted through data sampling techniques to verify the performance improvement effect of GMOPTBoost. The main results of 30 times of cross-validation analyzes are as follows. First, the class imbalance problem degrades the performance of ensembles. Second, GMOPTBoost contributes to performance improvements of AdaBoost ensembles trained on imbalanced datasets. Third, Data sampling techniques have a positive impact on performance improvement. Finally, GMOPTBoost contributes to significant performance improvement of AdaBoost ensembles trained on balanced datasets.

• The Korean Journal of Medicine
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• v.93 no.6
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• pp.538-547
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• 2018

Background/Aims: The impact of left ventricular (LV) diastolic function and filling pressure on clinical outcomes in young patients with acute myocardial infarction (AMI) has been poorly studied. Therefore, the aim of this study was to investigate the impact of LV diastolic function and LV filling pressure on major adverse cardiac events (MACEs) in young patients with AMI. Methods: A total of 200 young patients (males < 45 year, females < 55 year) with AMI were divided into two groups according to the diastolic function; normal (n = 46, $39.5{\pm}5.3$ years) versus abnormal (n = 154, $43.5{\pm}5.1$ years). Results: Despite regional wall motion abnormalities, normal LV diastolic function was not uncommon in young AMI patients (23.0%). During the 40 months of clinical follow-up, MACEs developed in 26 patients (13.0%); 14 re-percutaneous coronary intervention (7.0%), 8 recurrent MI (4.0%), and 4 deaths (2.0%). MACEs did not differ between the normal and abnormal diastolic function group (13.6% vs. 10.9%, p = 0.810), but MACEs were significantly higher in the high LV filling pressure group than the normal LV filling pressure group (36.8% vs. 10.5%, p < 0.001). On multivariate analysis, high LV filling pressure was an independent predictor of MACEs (hazard ratio 3.022, 95% confidence interval 1.200-7.612, p = 0.019). Conclusions: This study suggested that measurement of the LV filling pressure (E/e' ratio) would be useful in the risk stratification of young patients with AMI. However, it would be necessary to monitor this category of patient more carefully.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.