• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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• pp.89-100
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• 2024

Purpose : The objective of this study was to determine the major factors influencing the onset of diabetes and prediabetes and for collection of the basic data required to reduce the prevalence of diabetes and plan for administration of an effective health care system. By classifying the level of blood sugar management according to three categories: normal, prediabetes, and diabetes diagnosis, and determining the causes of diabetes in consideration of various variables, we will conduct an analysis of the main factors to be addressed for effective management of blood sugar and for preparation of basic data for use in early management. Methods : In this study, an analysis of raw data from the 8th National Health and Nutrition Examination Survey collected over a period of three years from 2019 to 2021, including 8,110 subjects in 2019, 7,359 subjects in 2020, and 7,090 subjects in 2021 was performed. A total of 22,559 subjects were aged 19 years or older, and 15,821 subjects were classified as subjects for inclusion in the final analysis. In the analysis, categorical variables were tested for difference, analysis of continuous variables using regression was performed, and analysis of influencing factors was performed using multinomial logistic analysis. Result : Significant factors related to the onset of diabetes and prediabetes included age (p<.001), marital status (p<.001), occupation (p<.001), hypertension (p<.001), dyslipidemia (p<.001), cardiovascular disease (p=.008), alcohol (p=.030) smoking (p=.005), systolic blood pressure (p<.001), diastolic blood pressure (p<.001), body mass index (p<.001) and waist circumference (p=.037), blood triglycerides (p<.001), and blood cholesterol (p<.001). Conclusion : Diabetes, a complex disease affected by a variety of diseases, requires active management from the prediabetes stage, and providing an appropriate level of medical information and services to elderly individuals without family support is considered a long-term health care system requirement in Korean society where the demographic structure is changing. In particular, determining the causes of prediabetes and development of a preventive approach to administering the health care system will be important for efficient management of diabetic patients.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.38.1-38.10
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• 2023

Background: Hearing loss (HL) is linked to an elevated risk of cardiovascular diseases (CVDs). The pathogeneses of HL and CVD commonly involve inflammatory responses. Previous studies investigated elevated levels of inflammatory biomarkers in subjects with HL, however, their findings did not demonstrate statistical significance. In our cross-sectional and longitudinal study, we investigated the correlation between HL and increased high-sensitivity C-reactive protein (hsCRP) levels to determine how HL is associated with CVDs. Methods: We conducted a cross-sectional study with workers aged over 18 years who underwent health check-ups at our institution between 2012 and 2018 (n = 566,507), followed by conducting a longitudinal study of workers aged > 18 who underwent health checkups at least twice at our institution between 2012 and 2018 (n = 173,794). The definition of HL was as an average threshold of ≥ 20 dB in pure-tone air conduction at 0.5, 1.0, and 2.0 kHz in both ears. The incidence of increased hsCRP levels throughout the follow-up period was defined as a level exceeding 3 mg/L. Logistic regression and generalized estimating equations were performed to estimate the risk of increased hsCRP levels according to the occurrence of HL in groups stratified by age. Results: In the cross-sectional study, the multivariate-adjusted odds ratio (OR) was 1.17 (95% confidence interval [CI]: 1.02-1.34); the OR was 0.99 (95% CI: 0.80-1.22) in those under 40 and 1.28 (1.08-1.53) in those over 40. In the longitudinal study, the multivariable-adjusted OR was 1.05 (95% CI: 0.92-1.19); the OR was 1.10 (95% CI: 0.90-1.35) in those under 40 and 1.20 (1.01-1.43) in those over 40. Conclusions: This cross-sectional and longitudinal study identified an association between HL and increased hsCRP levels in workers aged over 40 years.

• Journal of Distribution Science
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• v.8 no.3
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• pp.17-26
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• 2010

Recently concerns have been raised due to the unbalanced supply of crops: the price of crops has been unstable and at one point the price went up so high that the word Agflation(agriculture+ inflation) was coined. Korea, in particular, is a small-sized country and needs to secure the stable supply of crops by investing in the produce importation at a national level. Investment in foreign produce importation is becoming more important as a measure for sufficient supply of crops, limited supply of domestic crops, weakened farming conditions worldwide, as well as recent changes in the use of crops due to the development of bio-fuels, influence of carbon emission on crops, the price increase in crops, and influx of foreign hot money. However, there are many problems with investing in foreign produce importation: lack of support from the government; lack of farming information and technology; difficulty in securing the capital; no immediate pay-off from the investment and insufficient management. Although foreign produce is originally more price-competitive than domestic produce, it loses its competiveness in the process of importation (due to high tariffs) and poor distribution system, which makes it difficult to sell in Korea. Therefore, investment in foreign produce importation is being questioned for feasibility; to make it possible, foreign produce must maintain the price-competitiveness. Especially, harvest of agricultural products depends on natural and geographical conditions of each country and those products have indigenous properties, so distribution system according to import and export of agricultural products should be treated more carefully than that of other industries. Distribution costs are differentiated into each item and include cost of sorting and wrapping, cost of wrapping materials, cost of domestic transport, cost of international transport and cost of clearing customs for import and export. So transporting and storing agricultural products generates considerable costs compared with other products. Also, due to upgrade of dietary life, needs for stability, taste and visible quality toward food including agricultural products are being raised and wrong way of storage causes decomposition of food and loss of freshness, making the storage more difficult than that in room temperature, so storage and transport in distribution of agricultural products needs specialty. In addition, because lack of specialty in distribution and circulation such as storage and wrapping does not solve limit factors in distance, the distribution and circulation has been limited to a form of import and export within short-distant region. Therefore, need for distribution out-sourcing which can satisfy specialty in managing distribution and circulation and it is needed to establish more effective distribution system. However, existing distribution system of agricultural products is exposed to various problems including problems in distribution channel, making distribution and strategy for distribution and those problems are as follows. First, in case of investment in overseas agricultural industry, stable supply of the products is difficult because areas of production are dispersed widely and influenced by outer factors due to including overseas distribution channels. Also, at the aspect of quality, standardization of products is difficult, distribution system is quite complicated and unreasonable due to long distribution channels according to international trade and financial and institutional support is not enough. Especially, there are quite a lot of ineffective factors including multi level distribution process, dramatic gap between production cost and customer's cost, lack of physical distribution facilities and difficulties in storage and transport due to lack of wrapping containers. Besides, because import and export of agricultural products has been manages under the company's own distribution according to transaction contract between manufacturers and exporting company, efficiency is low due to excessive investment in fixed costs and lack of specialty in dealing with agricultural products causes fall of value of products, showing the limit to lose price-competitiveness. Especially, because lack of specialty in distribution and circulation such as storage and wrapping does not solve limit factors in distance, the distribution and circulation has been limited to a form of import and export within short-distant region. Therefore, need for distribution out-sourcing which can satisfy specialty in managing distribution and circulation and it is needed to establish more effective distribution system. Second, among tangible and intangible services which promote the efficiency of the whole distribution, a function building distribution environment which includes distribution information, system for standard and inspection, distribution finance, system for diversification of risks, education and training, distribution administration and tax system is wanted. In general, such a function building distribution environment is difficult to be changed and supplement innovatively because its effect compared with investment does not appear immediately despite of its necessity. Especially, in case of distribution of agricultural products, as a function of collecting and distributing is performed individually through various channels, the importance of distribution information and standardization is getting more focus due to the problem of repetition of work and lack of specialty. Also, efficient management of distribution is quite difficult due to lack of professionals in distribution, so support to professional education is needed. Third, though effort to keep self-sufficiency ratio of staple food, rice is regarded as important at the government level, level of dependency on overseas of others crops is high. Therefore, plan for stable securing food resources aside from staple food is also necessary. Especially, governmental organizations of agricultural products distribution in Korea are production-centered and have unreasonable structure whose function at the aspect of distribution and consumption is quite insufficient. And development of new distribution channels which can deal with changes in distribution environment and they do not achieve actual results of strategy for distribution due to non-positive strategy for price distribution. That is, it implies the possibility that base for supply will become vulnerable because it does not mediate appropriate interests on total distribution channels such as manufacturers, wholesale dealers and vendors by emphasizing consumer protection excessively in the distribution of agricultural products. Therefore, this study examined fundamental concept and actual situation for our investment to overseas agriculture, drew necessities, considerations, problems, etc. of overseas agricultural investment and suggested improvements at the level of distribution for price competitiveness of agricultural products cultivated in overseas under five aspects; government's indirect support, distribution's modernization and distribution information function's strengthening, government's political support for distribution facility, transportation route, load and unloading works' improvement, price competitiveness' securing, professional manpower's cultivation by education and training, etc. Here are some suggestions for foreign produce importation. First, the government should conduct a survey on the current distribution channels and analyze the situation to establish a measure for long-term development plans. By providing each agricultural area with a guideline for planning appropriate production of crops, the government can help farmers be ready for importation, and prevent them from producing same crops all at the same time. Government can sign an MOU with the foreign government and promote the importation so that the development of agricultural resources can be stable and steady. Second, the government can establish a strategy for an effective distribution system by providing farmers and agriculture-related workers with the distribution information such as price, production, demand, market structure and location, feature of each crop, and etc. In order for such distribution system to become feasible, the government needs to reconstruct the current distribution system, designate a public organization for providing distribution information and set the criteria for level of produce quality, trade units, and package units. Third, the government should provide financial support and a policy to seek an efficient distribution channel for foreign produce to be delivered fresh: the government should expand distribution facilities (for selecting, packaging, storing, and processing) and transportation vehicles while modernizing old facilities. There should be another policy to improve the efficiency of unloading, and to lower the cost of distribution. Fourth, it is necessary to enact a new law covering exceptional cases for importing produce in order to maintain the price competitiveness; currently the high tariffs is keeping the imported produce from being distributed domestically. However, the new adjustment should be made carefully within the WTO regulations since it can create a problem from giving preferential tariffs. The government can also simplify the distribution channels in order to reduce the cost in the distribution process. Fifth, the government should educate distributors to raise the efficiency and to modernize the distribution system. It is necessary to develop human resources by educating people regarding the foreign agricultural environment, the produce quality, management skills, and by introducing some successful cases in advanced countries.

• Tuberculosis and Respiratory Diseases
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• v.67 no.1
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• pp.21-26
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• 2009

Background: Non-invasive positive pressure ventilation (NPPV) ensures adequate gas exchange during bronchoscopy in spontaneously breathing, hypoxemic patients, thus avoiding endotracheal intubation. However, in some patients, endotracheal intubation is eventually required after bronchoscopy. This study investigated the incidence of intubation and predictors of a need for emergency intubation prior to NPPV bronchoscopy initiation. Methods: On a retrospective basis, we reviewed the medical records of 36 patients (median age, 55 years; interquartile range [IQR], 43~65 years) with acute hypoxemic respiratory failure who required NPPV during bronchoscopy between January 2005 and October 2007. Results: All patients were hypoxemic (median $PaO_2/FiO_2$ ratio 155; IQR 90~190), but tolerated bronchoscopy with NPPV support. SOFA score and SAPS II score immediately before NPPV initiation were 4 (3~7) and 36 (30~42), respectively. Seventeen (47%) patients needed endotracheal intubation at a median time of 22 (2~50) hours after bronchoscopy. Patients who needed intubation after bronchoscopy had a higher in-hospital mortality (11 [65%] vs. 4 [21%], p=0.017). Upon multiple logistic regression analysis, the need for intubation after bronchoscopy was independently associated with a $P_aO_2/FiO_2$ ratio (OR, 0.961; 95% CI, 0.924~0.999; p=0.047) immediately before NPPV initiation for bronchoscopy. Conclusion: The severity of the hypoxemia immediately prior to NPPV initiation for bronchoscopy was associated with the need for intubation after bronchoscopy in patients with hypoxemic respiratory failure.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.27-40
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• 2024

This study empirically derives the factors affecting the practice of corporate social responsibility (CSR) of venture firms in Korea from the perspective of Slack Resource Theory and the company's growth strategy, and provides implications for future expansion of venture firm's CSR activities. In Korea, venture firms have grown into important players in the national economy since the late 1990s through social contributions such as economic value creation, job creation, and technological development. As venture companies grow in status, positive relationships with stakeholders and responsibility for environmental and social values are required. Now, CSR is becoming an important strategic choice for SMEs and venture firms. However, until now, CSR-related academic research has mainly focused on large or listed corporations, and there is not much research on SMEs or venture firms. In particular, research on the factors that lead venture companies to make important business decisions of participating in CSR activities is not there yet. This study applied logistic multiple regression analysis using the '2023 Survey on Venture Firms' conducted by the Ministry of SMEs and Startups. As a result of this study, operating profit, which is an available resources of venture companies, and government support, which is a potential resource, have a positive impact on venture firms's CSR activities. Also, business relationships with large corporations and expectation for future cooperation also have a positive impact on CSR activities as the determinants. On the other hand, it was analyzed that in venture firms where ownership and management are not separated, the higher the CEO's shareholding ratio, the more negatively it affects CSR activities. This study contributes academically as the first empirical study on the determinants of CSR activities of venture firms in Korea and provides implications that government policy support and collaboration between large corporations and venture firms are important in order to expand CSR activities of venture firms.

• 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."

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Journal of agricultural medicine and community health
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• v.35 no.3
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• pp.287-300
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• 2010

Objectives: We identified factors associated with any participation and with "good participation" (as assessed by frequency of attendance) in health promotion programs at a public health center in Korea. Methods: The subjects included 199 women who attended a baseline examination of health promotion programs during the first half of 2009. We collected data by structured interviews and physical examinations. Participation status was quantified by the frequency of attendance to the program. We classified the subjects as non-participants (0) and participants (1+ times), and as poor participants (0-29 times) and good participants (30+ times). Results: Of the 199 subjects, there were 57 (28.6%) non-participants, while 56 (28.1%) were classified as good participants. The factors that significantly affected participation status, as identified by univariate analysis, were personal factors (age, educational level, marital status, religion, living with someone, monthly income), environmental factors (method of access, accessibility of other facilities), body mass index, hypertension, perceived barriers to health, emotional salience, affectionate domain of social support, and depression. Multiple logistic regression analyses indicated that method of access was the most significant factor affecting participation in the health promotion program, and that the factors most highly associated with good participation were emotional salience, hypertension and body mass index. Conclusions: Our findings suggest that specific factors determine and enhance participation in health promotion programs offered by public health centers. These factors should be considered during the design and evaluation of health promotion programs that are offered by public health centers.

• Journal of Hospice and Palliative Care
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• v.5 no.2
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• pp.155-162
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• 2002

Purpose : The purpose of this study is to provide preliminary information on the hospice care needs of hospice volunteers. Methods : The sample of this study was obtained from those who completed the hospice volunteer education program in three different areas in Korea. This study was conducted by a self-administered questionnaire. The sample analyzed for this study contained 88 hospice volunteers. Frequency, percentage, mean, standard deviation, and logistic regression analysis were performed to produce the findings of this study. Results : The characteristics of the study sample were $40{\sim}49$ aged, middle class, christianity, married women with high school diplomas. They attended at the hospice center with less than 1 year experience. Majority of them had no family members who received a hospice care. The hospice care was strongly required in the field of information, particularly regarding their diseases and treatments. The identified hospice care needs were the prevention and treatment of gangrene in the field of physical needs, the maintenance of closer relationship with their doctors in the field of emotional needs, and the support of supporting medical insurance in the field of socioeconomic needs. The significant predictors were 'having hospice care taker among family members' in the field of the total hospice care needs and physical needs. Two predictable variables were found in the field of emotional needs. However, none were found to be a predictable variable in the field of information and socioeconomic needs. Conclusion : The findings or this study have a weekness of generalizability due to the sampling methodology used in this study. Thus, further research should be designed in relation to this topic with a probability sampling method.