• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2A
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• pp.171-179
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• 2009

The porosity in porous media like concrete can be considered as a durability index since it may be a routine for the intrusion of harmful ions and room for the keeping moisture. Recently, modeling and analysis techniques for deterioration are provided based on the pore structure with the significance of durability and the relationship between porosity and durability characteristics is an important issue. In this paper, a series of mortar samples with five water to cement ratios are prepared and tests for durability performance are carried out including porosity measurement. The durability test covers those for compressive strength, air permeability, chloride diffusion coefficient, absorption, and moisture diffusion coefficient. They are compared with water to cement ratios and porosity. From the normalized data, when porosity increases to 1.45 times, air permeability, chloride diffusion coefficient, absorption, and moisture diffusion coefficient decrease to 2.3 times, 2.1 times, 5.5 times and 3.7 times, respectively, while compressive strength decreases to 0.6 times. It was evaluated that these are linearly changed with porosity showing high corelation factors. Additionally, intended durability performances are established from the test results and literature studies and a porosity for durable concrete is proposed based on them.

• Journal of the Korean Society for information Management
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• v.39 no.4
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• pp.269-306
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• 2022

This study aimed to develop indicators that can measure the digital transformation performance of science and technology information construction and sharing systems by utilizing the Digital Curation Maturity Models. For digital transformation, it is necessary to consider not only simple service improvement but also organizational and business changes. In this study, we aimed to develop a model for measuring the digital transformation of KISTI, Korea's representative science and technology information service organization. KISTI has already carried out BPR work for digital transformation and borrowed the concept of a maturity model. However, in BPR, there is no method to measure the result. Therefore, in this paper, we developed an index to measure digital transformation based on the maturity model. Indicator development was carried out in two ways: model development and evaluation. Cases for model construction were made through a comprehensive review of existing KISTI and various domestic and foreign cases. The models before verification were technology (37), data (45), strategy (18), organization (36), and (social)influence (14) based on the major categories. After verification using confirmatory factor analysis, the model is classified as technology (20 / 17 indicators dropped), data (36 / 9 indicators dropped), strategy (18 / maintenance), organization(30 / 6 indicators dropped), and (social) influence (13 indicators / 1 indicator dropped).

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.825-834
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• 2023

The demands of people who purchase fashion products on Internet shopping are gradually increasing, and attempts are being made to provide user-friendly images with 3D contents and web 3D software instead of pictures and videos of products provided. As a reason for this issue, which has emerged as the most important aspect in the fashion web shopping industry, complaints that the product is different when the product is received and the image at the time of purchase has been heightened. As a way to solve this problem, various image processing technologies have been introduced, but there is a limit to the quality of 2D images. In this study, we proposed an automatic conversion technology that converts 2D images into 3D and grafts them to web 3D technology that allows customers to identify products in various locations and reduces the cost and calculation time required for conversion. We developed a system that shoots a mannequin by placing it on a rotating turntable using only 8 cameras. In order to extract only the clothing part from the image taken by this system, markers are removed using U-net, and an algorithm that extracts only the clothing area by identifying the color feature information of the background area and mannequin area is proposed. Using this algorithm, the time taken to extract only the clothes area after taking an image is 2.25 seconds per image, and it takes a total of 144 seconds (2 minutes and 4 seconds) when taking 64 images of one piece of clothing. It can extract 3D objects with very good performance compared to the system.

• 지역과문화
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• v.4 no.1
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• pp.1-26
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• 2017

The 21st century recognizes culture as a high value-added strategic industry as it is called the culture era, and the cultural industry plays a role in driving regional economic development by raising the value added of other industries due to various ripple effects. As the institutional apparatus for developing such cultural industry, the Culture Industry Promotion Basic Law was enacted. Based on this, the Central Government designated the Jung-gu Dong and Seo-gu Dong as the Cultural Industry Promotion District of Andong City in 2010 but it has not been activated until 2017. The purpose of this study is understanding the situation and problems of the Cultural Industry Promotion District of Andong city and to discuss the direction of development. The research methods were analyzed by using questionnaires using AHP analysis technique for experts and practitioners related to culture industry. SPSS 23 was used for the validity and reliability of the questionnaire, and VBA was used for weighting and consistency index calculation in AHP analysis. As a result in the upper layer, Economy efficiency was found to be the most important factor of the three upper layer factors (Economy, Publicity, and Sociality) in order to activate the Cultural Industry Promotion District of Andong city. In the case of the Lieutenant layer, it is analyzed that the Job Creation is an important factor in the Economy category, the Settlement and Environment for Cultural Industry in the Publicity category, and the Activation of Urban Culture Activity in the Sociality category. As a result of analyzing the direction of promotion of the Cultural Industry Promotion District of Andong City centered on these factors, it concluded that the industry related to performance should be focused.

• Smart Media Journal
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• v.12 no.10
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• pp.93-101
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• 2023

Climate change has emerged as a global problem, with frequent temperature increases, droughts, and floods, and it is predicted that it will have a great impact on the characteristics and productivity of crops. Cnidium officinale is used not only as traditionally used herbal medicines, but also as various industrial raw materials such as health functional foods, natural medicines, and living materials, but productivity is decreasing due to threats such as continuous crop damage and climate change. Therefore, this paper proposes a model that can predict the physiologically active ingredient index according to the climate change scenario of Cnidium officinale, a representative medicinal crop vulnerable to climate change. In this paper, data was first augmented using the CTGAN algorithm to solve the problem of data imbalance in the collection of environment information, physiological reactions, and physiological active ingredient information. Column Shape and Column Pair Trends were used to measure augmented data quality, and overall quality of 88% was achieved on average. In addition, five models RF, SVR, XGBoost, AdaBoost, and LightBGM were used to predict phenol and flavonoid content by dividing them into ground and underground using augmented data. As a result of model evaluation, the XGBoost model showed the best performance in predicting the physiological active ingredients of the sacrum, and it was confirmed to be about twice as accurate as the SVR model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.883-896
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• 2023

As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.213-224
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• 2023

Type II solar radio bursts show frequency drifts from high to low over time. They have been known as a signature of coronal shock associated with Coronal Mass Ejections (CMEs) and/or flares, which cause an abrupt change in the space environment near the Earth (space weather). Therefore, early detection of type II bursts is important for forecasting of space weather. In this study, we develop a deep-learning (DL) model for the automatic detection of type II bursts. For this purpose, we adopted a 1-D Convolution Neutral Network (CNN) as it is well-suited for processing spatiotemporal information within the applied data set. We utilized a total of 286 radio burst spectrum images obtained by Hiraiso Radio Spectrograph (HiRAS) from 1991 and 2012, along with 231 spectrum images without the bursts from 2009 to 2015, to recognizes type II bursts. The burst types were labeled manually according to their spectra features in an answer table. Subsequently, we applied the 1-D CNN technique to the spectrum images using two filter windows with different size along time axis. To develop the DL model, we randomly selected 412 spectrum images (80%) for training and validation. The train history shows that both train and validation losses drop rapidly, while train and validation accuracies increased within approximately 100 epoches. For evaluation of the model's performance, we used 105 test images (20%) and employed a contingence table. It is found that false alarm ratio (FAR) and critical success index (CSI) were 0.14 and 0.83, respectively. Furthermore, we confirmed above result by adopting five-fold cross-validation method, in which we re-sampled five groups randomly. The estimated mean FAR and CSI of the five groups were 0.05 and 0.87, respectively. For experimental purposes, we applied our proposed model to 85 HiRAS type II radio bursts listed in the NGDC catalogue from 2009 to 2016 and 184 quiet (no bursts) spectrum images before and after the type II bursts. As a result, our model successfully detected 79 events (93%) of type II events. This results demonstrates, for the first time, that the 1-D CNN algorithm is useful for detecting type II bursts.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.133-145
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• 2023

This paper examines whether investors have adapted to the venture capital(VC) investment style. VC firms invest in privately held companies and generate returns by selling them after the lock-up period expires. We analyze the impact on stock prices before and after the lock-up period expiration, and compare the Cumulative Abnormal Return(CAR) between the past period(2015-2017) and the recent period(2020-2022) to investigate the effect of the second venture boom. The main findings are as follows. First, unlike in the past, stock price returns around the lock-up period expiration have been lower than the KOSDAQ index in recent years. Second, the impact on stock prices is significant for both 1-month and 12-month lock-up periods. Specifically, it is confirmed that stocks held by venture capital and professional investors with a 1-month lock-up period respond in advance to their information after the second venture boom. Finally, we find that there is a difference in CAR depending on whether or not the company received VC investment after the second venture boom. Based on our findings, we suggest that VC firms need to revise their exit strategies to improve performance. This includes finding ways to reduce information asymmetry and fees, as well as developing strategies to mitigate market volatility. Additionally, the current lock-up period for VCs should be reconsidered as it may increase the risk of stock price decline. We recommend that the government revise the scope and duration of lock-up periods to protect investors after IPO.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.27-40
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• 2023

This study analyzes the factors affecting the survival of young start-up companies. A youth start-up company was defined as a company with a founder's age under 39. The study was based on evaluation data from 3,540 companies evaluated by the Technology Guarantee Fund to support youth start-up guarantees during the period from 2012 to 2015. In this study, independent variables were defined as founder characteristics, start-up environment, and start-up strategy, and entrepreneurship, knowledge level, and development capabilities were set as variables for start-up characteristics, competition conditions and comparative advantage with alternatives in the start-up environment, and item novelty, commercialization plan and financing plan were set as variables. For variable measurement, the evaluation index of the youth start-up evaluation model of the Technology Guarantee Fund was used. Management performance was defined as the survival of a company, and the survival of 12, 36, 60, and 84 months was measured based on the occurrence of insolvency registered by the Korea Technology Guarantee Fund. The Cox proportional risk model was used for hypothesis testing. As a result of the analysis, knowledge level and development capability were statistically significant in the characteristics of the founder, and the financing plan in the start-up strategy was statistically significant regardless of the survival period. Among the start-up strategies, the novelty of the item had a positive effect on survival after 36 months. Entrepreneurship was significant only in 12-month survival. The most important order for survival was identified in the order of financing plan, knowledge level, item novelty and development capability, of which the founder's knowledge level in the beginning and the funding plan in the second half had the greatest impact.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.1
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• pp.49-62
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• 2024

Purpose : This study was conducted to compare two non-face-to-face exercise interventions depending on whether mobile applications and wearable exercise aids are used to find out which interventions are more effective in improving senile sarcopenia. Ultimately, it was conducted to provide basic data for developing non-face-to-face intervention methods to improve sarcopenia. Method : In this study, 18 elderly sarcopenia and possible sarcopenia aged 65 or older were randomly assigned to the digital and self-exercise intervention groups. The digital exercise intervention group performed eight exercise programs with mobile applications and wearable exercise aids to record and manage the elderly performing the programs in real time. And the self-exercise intervention group performed the same program on its own as implemented in the digital exercise group. The intervention was applied for 8 weeks, and before and after the intervention, sarcopenia evaluation and physical function evaluation were performed. Results : In the digital exercise intervention group, arm muscle mass, skeletal muscle index, SPPB, 5TSTS, and BBS were improved, and in the self-exercise intervention group, grip strength, SPPB, 5TSTS, and BBS were improved. Conclusion : It was confirmed that both groups are effective in improving physical performance and physical function, the digital exercise intervention is effective in improving muscle mass and self-exercise intervention is effective in improving muscle strength. Therefore, this study proposes to apply intervention methods separately according to the indicators to improve and prevent sarcopenia, and also simplify the instructions of applications used to improve sarcopenia and to create an environment where users can be trained regularly on how to use it. And, In the future, studies for the development of devices to be designed to help non-face-to-face exercise interventions or studies on the differences between face-to-face and non-face-to-face exercise interventions should be conducted in terms of the effect of improving sarcopenia.