• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.93-102
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• 2021

This study aims is to determine the factors that influence Indonesian rubber export supply based on the export destination countries. Indonesian rubber export supply is thought to be influenced by the variables like the volume of Indonesia rubber exports, the price of Indonesian natural rubber, the volume of domestic rubber production, the export volume of the previous period, the rupiah exchange rate against US$, the interest rate and real Gross Domestic Product (GDP). The data used is the annual time series from 1995-2015 based on export countries encompassing the United States, China, and Japan. Multiple linear regression with the Ordinary Least Square (OLS) method is applied to analyse the data. The results showed that the volume of Indonesian rubber exports to China is not influenced by domestic natural rubber prices and the Rupiah exchange rate against the Chinese Yuan. The volume of Indonesian rubber exports to Japan is influenced by the volume of domestic rubber production. The volume of Indonesian rubber exports to the three destination countries is influenced by the volume of domestic rubber production, interest rate, and real GDP.

• Journal of Korea Port Economic Association
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• v.30 no.4
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• pp.131-149
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• 2014

The objective of this study is to describe and determine how and to what extent size of firm, operating vessels and interest cost, leverage, debit maturity, growth opportunity and cash flow affect the cash holdings of Korean shipping companies. A sample of 38 Korean shipping firms for a period of 9 years(from 2005 to 2013) was selected. In panel data regression, this study finds that cash holdings are negatively affected by firm size, operating vessel size and debit maturity, and positively affected by volume of interest costs. In firm's group of relatively large volume of operating vessel, it's cash holdings are affected by debit maturity, cash flows and growth opportunity but in firm's group of small volume of it, interest cost, debit maturity and operating vessel's size are related with cash holdings. It proved that determinants of cash holdings in a high interest costing group are size of operating vessel, interest cost and debt maturity. On the other hand, debit maturity, growth opportunity, firm size and extent volume of vessels are associated with cash holdings in relatively row interest costing group.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.2
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• pp.164-172
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• 2021

Purpose: The purpose of this study was to analyze the level of interest that common Internet users have in dental implant using a Google Trends, and to compare the level of interest with big data from National Health Insurance Service. Materials and methods: Google Trends provides a relative search volume for search keywords, which is the average data that visualizes the frequency of searches for those keywords over a specific period of time. Implant was selected as the search keyword to evaluate changes in time flows of general Internet users' interest from 2015 to 2019 with trend line and 6 month moving average. Relative search volume for implant was analyzed with the number of patients who received National Health Insurance coverage for implant. Interest in implant and conventional denture was compared and popular related search keywords were analyzed. Results: Relative search volume for implant has increased gradually and showed a significant positive correlation with the total number of patients (P<.01). Interest in implant was higher than denture for most of the time. Keywords related to implant cost were most frequently observed in all years and related search on implant procedure was increasing. Conclusion: Within the limitations of this study, the public interest in dental implant was gradually increasing and specific areas of interest were changing. Web-based Google Trends data was also compared with traditional data and significant correlation was confirmed.

• The Korea Journal of Herbology
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• v.36 no.5
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• pp.1-14
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• 2021

Objectives : From January 2020, when the first confirmed case of COVID-19 in Korea, the use of health information using the Internet is expected to increase. It is expected that there will be a significant change in the general public's interest in Korean herbal medicines for health care. Therefore, in this study, we tried to confirm the change in the search trend of Korean herbal medicines after the COVID-19 epidemic. Methods : Using the "Naver DataLab (http://datalab.naver.com)" service of a Korean portal site Naver, search volume was investigated with 606 Korean herbal medicines as keywords. The search period was from January 2020, right after the onset of COVID-19, to June 2021. The search results were sorted by the peak search volume and the total search volume. Results : 'Cheonsangap (천산갑, 穿山甲, Manitis Squama)' was the most searched Korean herbal medicine in the peak search volume and total search volume with least bias. Conclusions : The problem of supply and demand of Korean herbal medicines of high public interest was identified. Broadcasting and media exposure were the factors that had a big impact on the search volume for Korean herbal medicines. As it was confirmed that the search volume for Korean herbal medicines increased rapidly due to media exposure, it is necessary to provide correct information about Korean herbal medicines, improve public awareness, and manage stable supply and demand based on continuous search trend monitoring.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.35-42
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• 2018

Direct volume rendering (DVR) is an important 3D visualization method for medical images as it depicts the full volumetric data. However, because DVR renders the whole volume, regions of interests (ROIs) such as a tumor that are embedded within the volume maybe occluded from view. Thus, conventional 2D cross-sectional views are still widely used, while the advantages of the DVR are often neglected. In this study, we propose a new visualization algorithm where we augment the 2D slice of interest (SOI) from an image volume with volumetric information derived from the DVR of the same volume. Our occlusion-based DVR augmentation for SOI (ODAS) uses the occlusion information derived from the voxels in front of the SOI to calculate a depth parameter that controls the amount of DVR visibility which is used to provide 3D spatial cues while not impairing the visibility of the SOI. We outline the capabilities of our ODAS and through a variety of computer tomography (CT) medical image examples, compare it to a conventional fusion of the SOI and the clipped DVR.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.67-73
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• 1996

The objective of this research is to investigate the behavior of the $F\"{o}rstner$ interest operator, which has been widely used for detecting distinct points in the field of digital photogrammetry and computer vision, in scale space. Considering the hugh volume of digital image utilized in digital photogrammetry, the scale space (image pyramid) approach which appears to be a solution for enhancing image processing, began to gain its attention. The investigation of the $F\"{o}rstner$ interest operator in scale space generated by the Gaussian kernel shows its behavior and feasibility for being used in practice.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.133-140
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• 2019

Following the recent US trade deficit, the trade war began between Korea and Japan in July. Korea's trade dependence is about 60% or more, indicating high export dependence and import dependence. The purpose of this study is to examine export amount, export volume, export price index, Treasury bond interest rate and analyze how index affects export amount. This study attempts to analyze the comovement and volatility with export amount. For this purpose, monthly data for each indicator were selected for a total of 234 months from January 2000 to June 2019. As a result of analysis, exports amount and exports volume showed very high comovement, exports amount and interest rates showed low comovement, but exports amount and exports prices showed very low comovement. In the future, Korea should continue to increase exports amount in view of its high dependence on trade, along with policies to expand the domestic market. To this end, strategy to increase exports volume should be presented. Korea should increase the logistics environment and competitiveness of each port and airport, improve domestic and overseas network construction and support services of logistics companies.

• Imaging Science in Dentistry
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• v.53 no.2
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• pp.153-159
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• 2023

Purpose: The objective of this study was to assess the fractal dimension, lacunarity, trabecular microarchitecture parameters, and cortical linear measurements in the mandibles of male and female individuals to identify differences between them. Materials and Methods: In total, 116 cone-beam computed tomography scans of healthy individuals of different ages (57 men and 59 women, aged between 20 and 60 years) were selected. The following bone parameters were measured: 1) buccal, lingual, and basal cortical bone thickness in 5 standard parasagittal sections (the midline, the left and right sides of the lower lateral incisors, and the left and right sides of the lower canines); 2) the bone volume fraction of 10 sequential axial sections from each patient by creating a volume of interest in the area between the lower canines; and 3) fractal dimension and lacunarity using grayscale images of the same region of the volume of interest in the anterior mandible. Spearman correlation coefficients and the Mann-Whitney test were used. Results: A significant and positive correlation was found between age and cortical thickness, especially in the region of the central incisors. Significant differences between sexes in terms of fractal dimension, lacunarity, and bone volume were found. Women revealed lower fractal dimension values and higher lacunarity and bone volume ratio values than men. Conclusion: Fractal dimension, lacunarity, trabecular bone volume, and cortical thickness were different between men and women of different ages.

• The Korea Journal of Herbology
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• v.31 no.4
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• pp.93-100
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• 2016

Objectives : The internet is the most common method to investigate information. It is showed that 75.2% of Internet users of 20s had health information search experience. So this study is aim to understanding of interest of public about the herbal medicine using internet search query volume data.Methods : The Naver that is the top internet portal web service of the Republic of Korea has provided an Internet search query volume data from January 2007 to the current through the Naver data lab (http://datalab.naver.com) service. We have collected search query volume data which was provided by the Naver in 606 herbal medicine names and sorted the data by peak and total search volume.Results : The most frequently searched herbal medicines which has less bias and sorted by peak search volume is 'wasong (와송)'. And the most frequently searched herbal medicines which has less bias and sorted by total search volume is 'hasuo (하수오)'.Conclustions : This study is showed that the rank of interest of public about herbal medicines. Among the above herbal medicines, some herbal medicines had supply issue. And there are some other herbal medicines that had very little demand in Korean medicine market, but highly interested public. So it is necessary to monitor for these herbal medicines which is highly interested of the public. Furthermore if the reliability of the data obtained on the basis of these studies, it is possible to be utilizing herbal medicine monitoring service.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.