• Analyses & Alternatives
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• v.8 no.2
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• pp.65-86
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• 2024

This study delves into the geopolitical tensions surrounding Ukraine throughout modern European history, aiming to shed light on its significance in geopolitical discourse. Since the 19th century, European powers, particularly the Anglo-Saxons and Germans, have formulated distinct geopolitical strategies concerning the Eurasian continent, with Ukraine at its focal point. The Crimean War and the German-Soviet War serve as key events to analyze these powers' geopolitical ambitions and interests. The British Empire, driven by its doctrine of thwarting land powers with sea power, intervened in the Crimean War against Russia. Its objective was to disrupt Russian dominance over Ukraine, thereby hindering Russian expansion into the Black Sea and Central Europe. On the other hand, the Third Reich of Germany, fixated on creating a European sphere exclusive from Anglo-Saxon sea powers and the Russian land power, initiated the German-Soviet War. This move aimed to secure a vast territory, including Ukraine, to facilitate expansion into the Caucasus and establish a buffer zone against the Soviet Union. Three key insights emerge from this analysis. Firstly, the absence of a dominant power rooted in Ukraine since the fall of the Principality of Kiev made geopolitical clashes inevitable. Secondly, these clashes ultimately result in a hollow victory for all involved parties, signifying the high costs and minimal gains of such confrontations. Lastly, the root cause of these clashes lies in the discord between exclusive geopolitical visions that fail to accommodate sustainable coexistence among diverse geopolitical spheres. In essence, the study underscores Ukraine's pivotal role in shaping European geopolitics and highlights the recurring clashes driven by competing visions of dominance and control over its territory. From the Crimean War to the German-Soviet War, the struggle for influence over Ukraine reflects broader geopolitical dynamics and the pursuit of strategic advantage by major powers. Ultimately, the study emphasizes the enduring significance of Ukraine in European geopolitics and the complexities inherent in managing its geopolitical tensions.

• Journal of the East Asian Society of Dietary Life
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• v.14 no.1
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• pp.1-10
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• 2004

This study was conducted to investigate the dietary behavior and image and preference of Japanese foods. The Subjects were consisted of 570 university students(243 males and 327 females) in Daegu and Kyungbuk area, Korea. The students responses to the 10 questions about image of Japanese foods were also measured on 5 point Likert scale. Data were presented by using frequency, percentage, chi-square test and T-test. The results of this study were as follows: (1) On the eating habits, 'the whole family has breakfast together with same foods everyday'scored high as 42.3％ and 'foods put in a big platter by gathering everyday'as 35.8％. (2) About the eating customs, 53.5％ of the subjects responded that the seat was fixed at meal time, 56.4％ didn't start to eat before the patriarch started a meal and 30.9％ responded that the head of a family had more foods in number and quantity. (3) On the table manners, 13.4％ of the subjects were scolded about 'watching TV on eating', 11.5％ about 'making left-over foods', 8.0％ about 'misuse of spoon and chopsticks'. (4) The preferred ethnic foods by University students was in other of Korean, Chinese, Italian, Japanese and French foods. (5) Among subjects, 93.8％ had no experience of visiting Japan and 92.6％ wanted to visit Japan. Images on the Japanese foods were 'the price is too expensive' (mean 4.15) and 'the decoration is wonderful'(mean 4.05). But the subjects did not think Japanese foods as 'hot'(mean 2.21) and 'greasy'(mean 2.51). (6) The favorite Japanese food of subjects was Udon(mean 3.98), Sushi(mean 3.85) and Tempura(mean 3.69). So Udon turned out to be the most popular Japanese foods by university students in Daegu and Kyungbuk area, Korea. But they did not prefer Natto(mean 2.68), Ochazuke(mean 2.76), Okonomiyaki(mean 2.87) and Misosiru and did not eat. From the above results, Korean university students preferred Udon to Natto among Japanese traditional foods, and they estimated Japanese foods as 'too expensive'. Therefore, lowering the price and developing the cooking method for Korean taste were needed to increase the intake of Japanese traditional foods by Korean university students and.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• The Korean Journal of Air & Space Law and Policy
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• v.32 no.1
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• pp.327-353
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• 2017

The issue submitted to the Court of Justice on the merits of case C---573/13 originated from a claim brought in the context of a dispute between Air Berlin and the German Federal Union of Consumer Organisations and Associations. The challenge concerned the way in which air fares were displayed in Air Berlin's computerised booking system. The system was organised in such a way that, after selecting a date and a departure airport, one would find all possible flight connections in a summary table. However, the final price of the ticket was displayed only for the clicked connection, and not for all connections, thus preventing customers from being able to compare such price with the prices of other connections. The German Federal Union took the view that this practice did not meet the requirements laid down by Article 23 of Regulation (EC) No. 1008/2008, which requires transparency in the prices set for air services. This led the German State to bring an injunctive action to cause Air Berlin to discontinue said practice. The claim was upheld at both the application and appeal stage of the relevant proceedings. Subsequently, Air Berlin submitted the matter to the German Federal High Court, which decided to stay the proceedings and ask for a preliminary ruling from the Court of Justice as to 1. whether Article 23 of Regulation (EC) No. 1008/2008 must be interpreted as meaning that, during the computerised booking process, the final price to be paid must be indicated at all times when prices of air services are shown, including when they are shown for the first time; and 2. whether, during the computerised booking process, the final price must be indicated only for the air service specifically selected by the customer or for each air service shown. In a nutshell, the Court, by the here---discussed judgment determined that Article 23 of Regulation (EC) No. 1008/2008 must be interpreted as meaning that, in the context of a computerised air ticket booking system, the final price to be paid must be indicated not only for the air service specifically selected by the customer, but also for each air service in respect of which the fare is shown. Clearly the above judgment will place air companies under an obligation to update and adjust (when needed) their computerised ticket booking and payment systems, in consideration of the primary need for consumers to be aware at all times of the actual price payable for a ticket and be able to compare the price of the service selected with the prices for other air services in respect of which the fare is shown.

• Radiation Oncology Journal
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• v.29 no.2
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• pp.91-98
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• 2011

Purpose: To assess the usefulness of implanted fiducial markers in the setup of hypofractionated radiotherapy for prostate cancer patients by comparing a fiducial marker matched setup with a pelvic bone match. Materials and Methods: Four prostate cancer patients treated with definitive hypofractionated radiotherapy between September 2009 and August 2010 were enrolled in this study. Three gold fiducial markers were implanted into the prostate and through the rectum under ultrasound guidance around a week before radiotherapy. Glycerin enemas were given prior to each radiotherapy planning CT and every radiotherapy session. Hypofractionated radiotherapy was planned for a total dose of 59.5 Gy in daily 3.5 Gy with using the Novalis system. Orthogonal kV X-rays were taken before radiotherapy. Treatment positions were adjusted according to the results from the fusion of the fiducial markers on digitally reconstructed radiographs of a radiotherapy plan with those on orthogonal kV X-rays. When the difference in the coordinates from the fiducial marker fusion was less than 1 mm, the patient position was approved for radiotherapy. A virtual bone matching was carried out at the fiducial marker matched position, and then a setup difference between the fiducial marker matching and bone matching was evaluated. Results: Three patients received a planned 17-fractionated radiotherapy and the rest underwent 16 fractionations. The setup error of the fiducial marker matching was $0.94{\pm}0.62$ mm (range, 0.09 to 3.01 mm; median, 0.81 mm), and the means of the lateral, craniocaudal, and anteroposterior errors were $0.39{\pm}0.34$ mm, $0.46{\pm}0.34$ mm, and $0.57{\pm}0.59$ mm, respectively. The setup error of the pelvic bony matching was $3.15{\pm}2.03$ mm (range, 0.25 to 8.23 mm; median, 2.95 mm), and the error of craniocaudal direction ($2.29{\pm}1.95$ mm) was significantly larger than those of anteroposterior ($1.73{\pm}1.31$ mm) and lateral directions ($0.45{\pm}0.37$ mm), respectively (p<0.05). Incidences of over 3 mm and 5 mm in setup difference among the fractionations were 1.5% and 0% in the fiducial marker matching, respectively, and 49.3% and 17.9% in the pelvic bone matching, respectively. Conclusion: The more precise setup of hypofractionated radiotherapy for prostate cancer patients is feasible with the implanted fiducial marker matching compared with the pelvic bony matching. Therefore, a less marginal expansion of planning target volume produces less radiation exposure to adjacent normal tissues, which could ultimately make hypofractionated radiotherapy safer.

• Journal of Technology Innovation
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• v.17 no.1
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• pp.1-48
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• 2009

Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has $-0.354{\sim}-0.124$ in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.

• Journal of Food Hygiene and Safety
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• v.20 no.2
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• pp.118-122
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• 2005

Immu-Forte (Dong-Ahm Bio's. Corp., Korea) was evaluated fir its effectiveness as a nonspecific immunostimulator in mice. The effects of Immu-Forte were determined by analysis of cytokines using ELISh and phenotype of leukocyte subpopulations using monoclonal antibodies specific to mouse leukocyte differentiation antigens and flow cytometry. CD4 T cells, CD8 T cells, macrophages, IL-12 and IFN-r in Immu-Forte EX-treated middle dose group increased in 3 months posttreatment and were significantly higher (p<0.05) than that of control at 3 months posttreatment. All T cells, all B cells, macrophages, IL-2, IL-4 and IL-12 in Immu-Forte EX-treated low dose uoup increased in 3 months posttreatment and were significantly higher (p<0.05) than that of control at 3 months posttreatment. In the Immu-Forte soy-treated group, CD4 T cells, IL-2, IL-4 and IL-12 were significantly higher in high dose-treated group, and CD 4 T cell, macrophages, IL-2, IL-4 and IL-12 were significantly higher in middle dose-treated group, and all T cell, IL-2, IL-4 and IL-12 were significantly higher in low dose-treated group. In the Itnmu-Forte A-treated group, macrophages, m cells and IL-12 in high dose-treated group and all T cells, macrophages, NK cells, IL-2, IL-4 and IL-12 in middle dose-treated group and NK cells in low dose-treated group were significantly higher (p<0.05) than that of control at 3 months posttreatment. In the Immu-Forte F-treated Group, all B cells, IL-4 and IL-12 in high dose-treated group and all T cells, aBl B cells, CD 4 T cells, CD8 T cells, macrophage, IL-2, IL-4, IL-12 and IFN-r in middle dose-treated group and NK cells and IL-12 in low dose-treated group were significantly higher (p<0.05) than that of control at 3 months posttreatment. In conclusion, the study has demonstrated that Immu-Forte had an immunostimulatory effect on mice through proliferation and activation of mouse immune cells.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• The Journal of Korean Academy of Prosthodontics
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• v.46 no.2
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• pp.157-168
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• 2008

Statement of problem: Over the past two decades, implant supported fixed prosthesis have been widely used. However, there are few studies conducted systematically and intensively on the splinting effect of implant systems in mandible. Purpose: The purpose of this study was to investigate the changes in stress distributions in the mandibular implants with splinting or non-splinting crowns by performing finite element analysis. Materials and methods: Cortical and cancellous bone were modeled as homogeneous, transversely isotropic, linearly elastic. Perfect bonding was assumed at all interfaces. Implant models were classified as follows. Group 1: $Br{{\aa}}nemark$ length 8.5mm 13mm splinting type Group 2: $Br{{\aa}}nemark$ length 8.5mm 13mm Non-splinting type Group 3: ITI length 8.5mm 13mm splinting type Group 4: ITI length 8.5mm 13mm Non-splinting type An load of 100N was applied vertically and horizontally. Stress levels were calculated using von Mises stresses values. Results: 1. The stress distribution and maximum von Mises stress of two-length implants (8.5mm, 13mm) was similar. 2. The stress of vertical load concentrated on mesial side of implant while the stress of horizontal load was distributed on both side of implant. 3. Stress of internal connection type was spreading through abutment screw but the stress of external connection type was concentrated on cortical bone level. 4. Degree of stress reduction was higher in the external connection type than in the internal connection type.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.