• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.735-742
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• 2023

Non-alcoholic fatty liver disease is an independent risk factor for the development of cardiovascular disease, diabetes, hypertension, and kidney disease, and the clinical importance of non-alcoholic fatty liver disease has recently been increasing. In this study, we aim to extract feature values by applying GLCM, a texture analysis method, to ultrasound images of patients with non-alcoholic fatty liver disease. By applying an artificial neural network model using extracted feature values, we would like to classify the degree of fat deposition in non-alcoholic fatty liver into normal liver, mild fatty liver, moderate fatty liver, and severe fatty liver. As a result of applying the GLCM algorithm, the parameters Autocorrelation, Sum of squares, Sum average, and sum variance showed a tendency for the average value of the feature values to increase as it progressed from mild fatty liver to moderate fatty liver to severe fatty liver. The four parameters of Autocorrelation, Sum of squares, Sum average, and sum variance extracted by applying the GLCM algorithm to ultrasound images of non-alcoholic fatty liver disease were applied as inputs to the artificial neural network model. The classification accuracy was evaluated by applying the GLCM algorithm to the ultrasound images of non-alcoholic fatty liver disease and applying the extracted images to an artificial neural network, showing a high accuracy of 92.5%. Through these results, we would like to present the results of this study as basic data when conducting a texture analysis GLCM study on ultrasound images of patients with non-alcoholic fatty liver disease.

• Industry Promotion Research
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• v.8 no.4
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• pp.267-276
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• 2023

Based on the tourism input-output data of five provinces and cities in China's Bohai Rim region from 2015~2021, this study analyzes the efficiency of regional tourism using DEA-BCC and DEA-Malmquist index, as well as its contribution to regional economic efficiency, and identifies factors influencing the comprehensive efficiency. The research results indicate that the comprehensive efficiency of the tourism industry in the China Bohai Sea region has reached an optimal level of 88.9%, but there is still room for improvement, with overall fluctuations. The overall productivity of the tourism industry exhibits a "U"-shaped fluctuating pattern, with growth mainly driven by technological advancements. Due to the impact of the COVID-19 pandemic, the region experienced a nearly 50% decrease in total factor productivity in 2019~2020. However, in 2021, with the implementation of various government stimulus policies, the tourism efficiency rapidly recovered to 80% of pre-pandemic levels. In terms of the impact of the tourism industry on the regional economy in the China Bohai Sea region, Hebei Province stands out as a significant contributor. Based on the aforementioned research findings, the following recommendations are proposed in three aspects: optimizing the supply structure, increasing innovation investment, and strengthening internal collaboration. These recommendations provide valuable insights for enhancing regional tourism efficiency and promoting regional synergy.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.672-680
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• 2023

Weight is a critical factor in the ship design process given that it has a substantial impact on the hydrodynamic performance of ships. Typically, ships are optimally designed for specific conditions with a fixed draft and displacement. However, in reality, weight and draft can vary within a certain range owing to operational activities, such as fuel consumption, ballast adjustments, and loading conditions . Therefore, we investigated how resistance changes under three different loading conditions, namely overload, design-load, and lightship, for small craft, using both model experiments and numerical simulations. Additionally, we examined the sensitivity of weight changes to resistance to enhance the performance of ships, ultimately reducing power requirements in support of the International Maritime Organization's (IMO) goal of reducing CO2 emissions by 50% by 2050. We found that weight changes have a more significant impact at low Froude Numbers. Operating under overload conditions, which correspond to a 5% increase in draft and an 11.1% increase in displacement, can lead to a relatively substantial increase in total resistance, up to 15.97% and 14.31% in towing tests and CFD simulations, respectively.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.543-551
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• 2023

As climate change continues to prompt an increasing demand for advancements in disaster and safety management technologies to address abnormal high water temperatures, typhoons, floods, and droughts, sea surface temperature has emerged as a pivotal factor for swiftly assessing the impacts of summer harmful algal blooms in the seas surrounding Korean Peninsula and the formation and dissipation of cold water along the East Coast of Korea. Therefore, this study sought to gauge predictive performance by leveraging statistical methods and deep learning algorithms to harness sea surface temperature data effectively for marine anomaly research. The sea surface temperature data employed in the predictions spans from 2018 to 2022 and originates from the Heuksando Tidal Observatory. Both traditional statistical ARIMA methods and advanced deep learning models, including long short-term memory (LSTM) and gated recurrent unit (GRU), were employed. Furthermore, prediction performance was evaluated using the attention LSTM technique. The technique integrated an attention mechanism into the sequence-to-sequence (s2s), further augmenting the performance of LSTM. The results showed that the attention LSTM model outperformed the other models, signifying its superior predictive performance. Additionally, fine-tuning hyperparameters can improve sea surface temperature performance.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.493-499
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• 2023

Trade credit refers to a transaction where a product supplier allows an distributor to defer payment for a certain period of time for the purchase cost of the products. This practice is generally permitted as a means of differentiation between competing companies. Such trade credit is commonly granted based on the volume of transactions, aiming to increase customer orders. From the perspective of the distributor, trade credit allows for a deferred payment period for the purchase cost, leading to cost savings in inventory investment. These cost savings in inventory investment can be a factor in reducing selling prices with the aim of increasing customer demand. In this study, we analyze a model that determines the optimal selling price and order quantity from the perspective of the distributor, assuming that the supplier allows a deferred payment period dependent on the transaction volume. We assume that the final customer's annual demand exhibits an exponential decrease with respect to the distributor's selling price, using a constant price elasticity function. To analyze the problem, we assume that the product deteriorates at a constant rate over time and aim to establish an inventory model for the intermediate distributor. We also want to analyze the impact of deterioration on the inventory policies of the intermediate distributor.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.79-87
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• 2022

Recently, as the awareness of the necessity of entrepreneurship education has spread in secondary education, the competency of educators in the field of education has become more important. This study tried to derive the priority of education needs by exploring the competency of educators to practice entrepreneurship education and the result from analysis of the difference in importance and performance. For conducting the analysis, this study conceptualized entrepreneurship education competency based on the TPACK (Technological Pedagogical Content Knowledge) model and developed a questionnaires to measure those competencies. Using TPACK and developed questionnaires, a survey was conducted on 217 secondary school teachers who were interested in entrepreneurship education, and derived the difference between importance-level and current-level was analyzed with a t-test. As a result of the study, for all sub-factors of TPACK, the mean of importance-level was higher than the mean of current-level, indicating that educational prescription was required. Also, as a result of analysis of Borich's requirements and The Locus for Focus Model, it was found that the factor with the highest priority in education was CK(Content Knowledge). Based on the results of study, implications for strengthening competencies for entrepreneurship educators were derived.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.45-55
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• 2022

Accelerator is a private investment institution that provides startups with comprehensive solutions to solve various difficulties such as startup facilities, funds, commercialization, securing a market etc. In addition to the role of an investor as a new startup support model, accelerators have contributed much to improvement of business ability of startups through intensive mentoring. Considering that previous studies gave weight to the determinants of investment from the perspective of investors, this study made a comparative analysis on the relative importance of determinants of investment in startups among accelerators, investors and entrepreneurs through the method of AHP. Results show that accelerators and investors regard "managerial characteristics" of startups as of the highest importance, whereas entrepreneurs think that "market characteristics" of startups are the most important. The result stems from an empirical judgment from the perspective of investors that success of startups depends on the ability of entrepreneur, and it is considered that investors evaluated marketability of startups as the most important factor in consideration of investment payback period. The result is similar to the result of previous studies on the determinants of investment determinants of angel investors and venture capitals. This paper is expected to make a contribution to the advancement of investment decision-making model for accelerators to discover startups with high possibility to grow and achieve more in incubation and investment.

• Journal of the Korean Regional Science Association
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• v.39 no.4
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• pp.33-51
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• 2023

This study aims to investigate the changes in the employment structure of occupational groups by job characteristics and analyze the factors influencing wage premiums in local labor markets from 2010 to 2020. This study's analysis involves three primary steps. First, the occupational characteristics data from the Korea Network for Occupations and Workers are subjected to an exploratory factor analysis, and then a non-routine task intensity index is calculated by each occupations. Then, we conduct an exploratory analysis of changes in the distribution of employment by occupation from 2010 to 2020 by combining data from the Population Census with data from the Korean Labor and Income Panel Study to construct individual-level and regional-level data. Thirdly, we employ a hierarchical linear model to examine the individual-level and regional-level factors influencing wage premiums. Since 2010, the proportion of employment in occupations requiring non-routine task has continued to rise and now dominates the metropolitan labor market. Moreover, agglomeration effects resulting from urbanization produce a substantial wage premium for wage workers in occupations requiring non-routine tasks. This study seeks to provide policy implications to mitigate inequality and polarization in local labor markets by empirically analyzing the transition of occupational structure and wage inequality in relation to the local labor market context.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.402-412
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• 2020

Objective: To evaluate the performance of predicting early recurrence using preoperative factors only in comparison with using both pre-/postoperative factors. Materials and Methods: We retrospectively reviewed 549 patients who had undergone curative resection for single hepatcellular carcinoma (HCC) within Milan criteria. Multivariable analysis was performed to identify pre-/postoperative high-risk factors of early recurrence after hepatic resection for HCC. Two prediction models for early HCC recurrence determined by stepwise variable selection methods based on Akaike information criterion were built, either based on preoperative factors alone or both pre-/postoperative factors. Area under the curve (AUC) for each receiver operating characteristic curve of the two models was calculated, and the two curves were compared for non-inferiority testing. The predictive models of early HCC recurrence were internally validated by bootstrap resampling method. Results: Multivariable analysis on preoperative factors alone identified aspartate aminotransferase/platelet ratio index (OR, 1.632; 95% CI, 1.056-2.522; p = 0.027), tumor size (OR, 1.025; 95% CI, 0.002-1.049; p = 0.031), arterial rim enhancement of the tumor (OR, 2.350; 95% CI, 1.297-4.260; p = 0.005), and presence of nonhypervascular hepatobiliary hypointense nodules (OR, 1.983; 95% CI, 1.049-3.750; p = 0.035) on gadoxetic acid-enhanced magnetic resonance imaging as significant factors. After adding postoperative histopathologic factors, presence of microvascular invasion (OR, 1.868; 95% CI, 1.155-3.022; p = 0.011) became an additional significant factor, while tumor size became insignificant (p = 0.119). Comparison of the AUCs of the two models showed that the prediction model built on preoperative factors alone was not inferior to that including both pre-/postoperative factors {AUC for preoperative factors only, 0.673 (95% confidence interval [CI], 0.623-0.723) vs. AUC after adding postoperative factors, 0.691 (95% CI, 0.639-0.744); p = 0.0013}. Bootstrap resampling method showed that both the models were valid. Conclusion: Risk stratification solely based on preoperative imaging and laboratory factors was not inferior to that based on postoperative histopathologic risk factors in predicting early recurrence after curative resection in within Milan criteria single HCC patients.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.71-86
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• 2023

Although starting a business plays a key role in strengthening national competitiveness and creating jobs, it is recognized as a risky choice. Failure to start a business can result in a wide range of negative effects, such as loss of personal wealth as well as deterioration of national competitiveness. This study considers startups that have reached a level of sustainable growth by achieving performance above the minimum profitability and sales standards for KOSDAQ listing, or achieved EXIT through sale or listing, as successful startups. based on the practical experiences of 23 successful entrepreneurs and Based on perception, the importance and priorities of startup success factors were derived through stratification analysis (Analytic Hierarchy Process, AHP), and interviews were conducted. In particular, using the ERIS model, we comprehensively analyze various variables of a start-up by considering the four elements of the entrepreneur, resources, industry, and strategy, and examine the changes and importance of success factors according to the characteristics of each growth stage of the start-up. As a goal, we specifically identified the challenges and opportunities faced by entrepreneurs at each stage. As a result of the study, the order of importance of the top factors of success factors in the start-up period was found to be the entrepreneur, resources, industry, and strategy. In particular, the importance of the entrepreneur's entrepreneurship spirit, special capabilities, general capabilities, and human resources was emphasized. The order of importance of the top factors of success factors during the growth period was found in the following order: entrepreneur, resources, industry, and strategy. In particular, the importance of general capabilities, entrepreneurship, and human and organizational resources was emphasized. This study is significant in that it analyzes startup success factors from the perspective of successful entrepreneurs and provides useful insights and directions to entrepreneurs and policy makers.