• The Korean Journal of Financial Management
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• v.12 no.2
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• pp.273-298
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• 1995

1960년대, 각국의 환율이 미국의 달러화에 연동(pegging)된 고정환율제도를 근간으로 하는 브레튼우즈(Bretton Woods)체제하에서 각국의 중앙은행은 환율을 일정한 범위 내로 유지하기 위한 정책수단으로 외환시장개입을 적극 활용하였다. 1973년 브레튼우즈체제하의 고정환율제도가 붕괴되고 변동환율제도가 채택된 이후에도 각국의 외환시장개입정책은 계속되었다. 1980년대에 레이건 행정부의 재정팽창정책과 미연방준비은행의 긴축통화정책으로 금리의 지속적인 상승과 미달러화의 큰폭의 절상이 이루어 졌다. 이에 국제무역의 위기를 우려한 미국, 독일, 프랑스, 영국, 일본 등 선진 5개국(Group-5, G5)은 1985년 9월 22일 미 달러화의 절하를 위해 외환시장에 공동으로 개입할 것을 주내용으로 한 플라자합의(Plaza Agreement)를 발표하였다. 그후에도 1987년 2월 23일 열린 루브르협정(Louvre Accord, G-6 Communique)에서 환율을 현수준으로 유지시키기 위한 목표환율대(Target zone)를 설정하고 외환시장개입을 통해 이를 유지하기로 합의한 바 있다. 이후의 구미각국은 환율의 관리를 위하여 국가가 공동으로 외환시장에 개입하곤 했다. 본 논문은 1987년 루브르협정 이후 미국, 독일 및 일본의 중앙은행의 외환시장 개입 정책이 소기의 목적을 달성했는지의 여부를 규명해 보고자 한다. 즉, Federal Reserve, Bundesbank 및 Bank of Japan의 외환시장개입이 현물환율시장(spot market)에서 각각의 변동성을 감소 시켰는지의 여부를 독일의 마르크화 및 일본의 엔화를 중심으로 규명해 보고자 한다. 1981년 루브르협정이후, 미국, 독일 및 일본의 중앙은행은 미국 달러화에 대한 마르크 및 엔화의 환율을 안정시키기 위해 꾸준히 외환시장에 개입해 왔다. 외환시장의 개입유형은 크게 태화외환시장개입(non-sterilized intervention)과 불태화외환시장개입(sterilized intervention)으로 구분할 수 있는데, 전자는 외환당국이 민간부문과 외화채권을 거래함으로써 본원통화의 크기가 변하는 개입형태를 의미하는 반면에 후자는 외환당국의 순외화자산의 크기변화가 본원통화의 변화를 초래하지 않는 경우이다. 즉, 불태화외환시장개입은 순외화자산의 증감이 순국내자산의 증감과 반비례해서 이루어지기 때문에 본원통화의 크기에는 변함이 없다. 외환시장개입이란 외환당국이 은행간 시장에서 민간시잔 참가자들과 행하는 적극적인 외환거래를 의미한다. 반면, 넓은 의미에서의 외환시장개입에는 수동적 외환시장개입이라고 불리는 고객거래가 포함된다. 후자의 거래는 국내통화 및 외화표시 자산의 상대적 공급규모를 변화시킨다는 의미에서 전통적외환시장개입과 동일한 효과를 갖기 때문에 광의의 외환시장 개입으로 분류된다. 외환시장의 개입목적은 크게 세 가지로 분류할 수 있다. 첫째, 환율의 안정적 운영이다. 환율수준이 자유롭게 변화되는 변동환율제도하에서 환율의 지나친 변동으로 인한 실물경제로의 부정적인 영향을 최소화하기 위해서 환율의 지나친 변동으로 인한 실물경제로의 부정적인 영향을 최소화하기 위해서 환율의 안정을 정책 목표로 설정하는 경우와 고정환율제도하에서 환율을 일정수준으로 유지시키기 위해서 외환당국이 외환시장에 개입하는 경우가 여기에 해당된다고 볼 수 있다. 둘째, 환율수준의 균형수준으로의 조정이다. 이때 야기될 수 있는 문제점으로는 환율균형 수준을 어떻게 정의, 추정할 것이냐 하는 점과 목표환율정책이 다른 정책목표와 상충될 수 있다는 점이다. 셋째, 외환당국이 공적외환보유액이나 구성을 변화시킬 목적으로 외환시장에 개입하는 경우이다. 이때의 외환시장개입은 현재의 환율수준이 개입으로 인하여 과도하게 이탈하는 문제가 발생하지 않을 것을 전제로 한다. 본고에서는 현물환율에 영향을 미치는 요소로 미국, 독일 및 일본의 중앙은행의 개입효과, 요일효과, 통화의 공급량(M1), 무역적자의 폭, 산업의 생산량, 생산가격지수(PPI), 소비자물가지수(CPI), 실업률, 옵션의 내재적 변동성 등을 고려한다. 환율의 변동성을 추정하는 식은 GARCH 모델이 사용된다. 본 추정모델은 Dominguez(1993)의 확장이다. Dominguez (1993)의 논문은 GARCH 모델을 써서 미국, 독일 및 일본의 중앙은행의 시장개입효과를 분석했으나, 거시변수를 고려대상에서 제외시켰다. 본 논문은 위의 방법에 거시변수를 삽입하고 모델을 변형시켜서 더 확실한 시장개입효과와 거시변수효과를 밝혔다. 또한 옵션의 내제적 변동성을 구하는 과정에서 American option model을 사용하는 대신, Bourtha & Courtadon (1987)등이 밝힌 바와 같이 American style option이라 할지라도, European Model을 쓰면 더욱더 간편하고, 예측력도 American Model에 뒤지지 않음을 이용하여, European Model을 써서 내재적 변동성을 구한 다음 이것을 독립변수로 이용하였다. 본 모델의 추정 결과는 3국의 시장개입정책이 현물환율과 옵션의 내재적 변동성을 증가시켜서 Louvre 협정이후 각국은 시장개입의 목적을 달성하지 못한 것으로 나타났다.

• Journal of Biomedical Engineering Research
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• v.24 no.5
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• pp.401-410
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• 2003

This study investigates the biomechanical efficacies of various cement augmentation techniques with or without pressurization for varying degrees of osteoporotic femur. For this study, a biomechanical analysis using a finite element method (FEM) was undertaken to evaluate surgical procedures, Simulated models include the non-cemented(i.e., hip screw only, Type I), the cement-augmented(Type II), and the cemented augmented with pressurization(Type III) models. To simulate the fracture plane and other interfacial regions, 3-D contact elements were used with appropriate friction coefficients. Material properties of the cancellous bone were varied to accommodate varying degrees of osteoporosis(Singh indices, II∼V). For each model. the following items were analyzed to investigate the effect surgical procedures in relation to osteoporosis of varying degrees : (a) von Mises stress distribution within the femoral head in terms of volumetric percentages. (b) Peak von Mises stress(PVMS) within the femoral head and the surgical constructs. (c) Maximum von Mises strain(MVMS) within the femoral head, (d) micromotions at the fracture plane and at the interfacial region between surgical construct and surrounding bone. Type III showed the lowest PVMS and MVMS at the cancellous bone near the bone-construct interface regardless of bone densities. an indication of its least likelihood of construct loosening due to failure of the host bone. Particularly, its efficacy was more prominent when the bone density level was low. Micromotions at the interfacial surgical construct was lowest in Type III. followed by Type I and Type II. They were about 15-20% of other types. which suggested that pressurization was most effective in limiting the interfacial motion. Our results demonstrated the cement augmentation with hip screw could be more effective when used with pressurization technique for the treatment of intertrochanteric fractures. For patients with low bone density. its effectiveness can be more pronounced in limiting construct loosening and promoting bone union.

• Horticultural Science & Technology
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• v.33 no.6
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• pp.911-922
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• 2015

This study was carried out to evaluate growth characteristics of Kimchi cabbage cultivated in various highland areas, and to create a predicting model for the production of highland Kimchi cabbage based on the growth parameters and climatic elements. Regression model for the estimation of head weight was designed with non-destructive measured growth variables (NDGV) such as leaf length (LL), leaf width (LW), head height (HH), head width (HW), and growing degree days (GDD), which was $y=6897.5-3.57{\times}GDD-136{\times}LW+116{\times}PH+155{\times}HH-423{\times}HW+0.28{\times}HH{\times}HW{\times}HW$, ($r^2=0.989$), and was improved by using compensation terms such as the ratio (LW estimated with GDD/measured LW ), leaf growth rate by soil moisture, and relative growth rate of leaf during drought period. In addition, we proposed Excel spreadsheet model for simulation of yield prediction of highland Kimchi cabbage. This Excel spreadsheet was composed four different sheets; growth data sheet measured at famer's field, daily average temperature data sheet for calculating GDD, soil moisture content data sheet for evaluating the soil water effect on leaf growth, and equation sheet for simulating the estimation of production. This Excel spreadsheet model can be practically used for predicting the production of highland Kimchi cabbage, which was calculated by (acreage of cultivation) ${\times}$ (number of plants) ${\times}$ (head weight estimated with growth variables and GDD) ${\times}$ (compensation terms derived relationship of GDD and growth by soil moisture) ${\times}$ (marketable head rate).

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.107-134
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• 2007

This paper tests the relationship among returns, volatilities, contracts and open interests of KOSPI 200 futures markets with the various dynamic models such as granger-causality, impulse response, variance decomposition and ARMA(1, 1)-GJR-GARCH(1, 1)-M. The sample period is from July 7, 1998 to December 29, 2005. The main empirical results are as follows; First, both contract change and open interest change of KOSPI 200 futures market tend to lead the returns of that according to the results of granger-causality, impulse response and variance decomposition with VAR. These results are likely to support the KOSPI 200 futures market seems to be inefficient with rejecting the hypothesis 1. Second, we also find that the returns and volatilities of the KOSPI 200 futures market are effected by both contract change and open interest change of that due to the results of ARMA(1,1)-GJR-GARCH(1,1)-M. These results also reject the hypothesis 1 and 2 suggesting the evidences of inefficiency of the KOSPI 200 futures market. Third, the study shows the asymmetric information effects among the variables. In addition, we can find the feedback relationship between the contract change and open interest change of KOSPI 200 futures market.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.42-51
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• 2020

This study was performed to support the 6th forest basic planning by Korea Forest Service as predicting the change of forestland area by the transition of land use type in the future over 35 years in South Korea. It is very important to analyze upcoming forestland area change for future forest planning because forestland plays a basic role to predict forest resources change for afforestation, production and management in the future. Therefore, the transitional interaction between land use types in future of South Korea was predicted in this study using econometrical models based on past trend data of land use type and related variables. The econometrical model based on maximum discounted profits theory for land use type determination was used to estimate total quantitative change by forestland, agricultural land and urban area at national scale using explanatory variables such as forestry value added, agricultural income and population during over 46 years. In result, it was analyzed that forestland area would decrease continuously at approximately 29,000 ha by 2027 while urban area increases in South Korea. However, it was predicted that the forestland area would be started to increase gradually at 170,000 ha by 2050 because urban area was reduced according to population decrement from 2032 in South Korea. We could find out that the increment of forestland would be attributed to social problems such as urban hollowing and localities extinction phenomenon by steep decrement of population from 2032. The decrement and increment of forestland by unbalanced population immigration to major cities and migration to localities might cause many social and economic problems against national sustainable development, so that future strategies and policies for forestland should be established considering such future change trends of land use type for balanced development and reasonable forestland use and conservation.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.19-36
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• 2015

Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.

• Korean Journal of Food Science and Technology
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• v.51 no.2
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• pp.160-168
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• 2019

This study aimed to determine whether double-processed ginseng berry extract (PGBC) could improve learning and memory in an $A\hat{a}42$-induced Alzheimer's mouse model. Passive avoidance test (PAT) and Morris water-maze test (MWMT) were performed after mice were treated with PGBC, followed by acetylcholine (ACh) measurement and glial fibrillary acidic protein (GFAP) detection for brain damage. Furthermore, acetylcholinesterase (AChE) activity and choline acetyltransferase (ChAT) expression were analyzed using Ellman's and qPCR assays, respectively. Results demonstrated that PGBC contained a high amount of ginsenosides (Re, Rd, and Rg3), which are responsible for the clearance of $A{\hat{a}} 42$. They also helped to significantly improve PAT and MWMT performance in the $A{\hat{a}} 42-induced$ Alzheimer's mouse model when compared to the normal group. Interestingly, ACh and ChAT were remarkably upregulated and AChE activities were significantly inhibited, suggesting PGBC to be a palliative adjuvant for treating Alzheimer's disease. Altogether, PGBC was found to play a positive role in improving cognitive abilities. Thus, it could be a new alternative solution for alleviating Alzheimer's disease symptoms.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.4
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• pp.289-302
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• 2023

The study area was Gangnim-myeon, Hoengseong-gun, Gangwon-do, composed of the Chiaksan gneiss complex, and it was revealed that the concentrations of uranium (U) and thorium (Th) within the groundwater of the study area exceeded their water quality standards. Hence, artificial weathering experiments were conducted to elucidate mineralogically the mechanisms of their leaching using drilling cores obtained from the corresponding groundwater aquifers. First of all, the mineralogical compositions of core samples were observed, and the results indicated that the content of clinochlore, a member of the chlorite group of minerals that can form through low- and intermediate-temperature metamorphisms, was relatively higher. In addition, the Th concentration was measured ten times higher than that of U. The results of artificial weathering experiments suggested that the Th concentrations gradually increased through the dissolution of radioactive-element-bearing minerals up to the first day, and then they tended to decrease. It could be attributed to the fact that Th was leached with the dissolution of thorite, which might be a secondary mineral, and then dissolved Th was re-precipitated as the various forms of salt, such as sulfate. Even though the U content was lower than that of Th in the core samples, the U concentration was one hundred times higher than that of Th after the weathering experiments. It is likely caused by the gradual dissolution and desorption of U included in intensively weathered thorite or adsorbed as a form of UO₂²⁺ on the mineral surface. In addition, the leaching tendency of U and Th was positively correlated with the bicarbonate concentration. However, the concentrations between U and Th in groundwater exhibited a relatively lower correlation, which might result from the fact that they occurred from different sources, as aforementioned. Among various kinetic models, the parabolic diffusion and pseudo-second-order kinetic models were confirmed to best fit the dissolution kinetics of both elements. The period that would be taken for the U concentration to exceed its drinking-water standard was inferred using the regressed parameters of the best-fitted models, and the duration of 29.4 years was predicted in the neutral-pH aquifers with relatively higher concentrations of HCO₃, indicating that U could be relatively quickly leached out into groundwater.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.5
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• pp.431-449
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• 2022

As many tunnels generally have been constructed, various experiences and techniques have been accumulated for tunnel design as well as tunnel construction. Hence, there are not a few cases that, for some usual tunnel design works, it is sufficient to perform the design by only modifying or supplementing previous similar design cases unless a tunnel has a unique structure or in geological conditions. In particular, for a tunnel blast design, it is reasonable to refer to previous similar design cases because the blast design in the stage of design is a preliminary design, considering that it is general to perform additional blast design through test blasts prior to the start of tunnel excavation. Meanwhile, entering the industry 4.0 era, artificial intelligence (AI) of which availability is surging across whole industry sector is broadly utilized to tunnel and blasting. For a drill and blast tunnel, AI is mainly applied for the estimation of blast vibration and rock mass classification, etc. however, there are few cases where it is applied to blast pattern design. Thus, this study attempts to automate tunnel blast design by means of machine learning, a branch of artificial intelligence. For this, the data related to a blast design was collected from 25 tunnel design reports for learning as well as 2 additional reports for the test, and from which 4 design parameters, i.e., rock mass class, road type and cross sectional area of upper section as well as bench section as input data as well as16 design elements, i.e., blast cut type, specific charge, the number of drill holes, and spacing and burden for each blast hole group, etc. as output. Based on this design data, three machine learning models, i.e., XGBoost, ANN, SVM, were tested and XGBoost was chosen as the best model and the results show a generally similar trend to an actual design when assumed design parameters were input. It is not enough yet to perform the whole blast design using the results from this study, however, it is planned that additional studies will be carried out to make it possible to put it to practical use after collecting more sufficient blast design data and supplementing detailed machine learning processes.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.145-165
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• 2023

Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.