• Korean journal of communication and information
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• v.51
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• pp.47-64
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• 2010

Korea film market is heterogeneously divided market that comes from competition between Korean movies and foreign imported movies. This research empirically analyzes genre differentiation in Korean film market with three dimensions (film audience preference, production and import, box office hit). The results indicate that, first, audiences who preferring Korean movie preferred 'cultural factor oriented genres', but audiences who preferring foreign movie preferred 'high budget oriented genres'. Second, imported foreign movie genre distribution was little bit different with box office hit genre of foreign movies. Foreign movie was imported not only hit genre (action genre) but also low cost genre (comedy and Drama/melodrama genre), but most of all Korean film was produced in box office hit genres (comedy and Drama/melodrama genre), third, Korean movies hit a box office in comedy and Drama/melodrama genre, but foreign movies hit a box office in action and SF/Fantasy genre. Those results show that Korea movies' genres are concentrated very much in cultural factor oriented genre. Those results can give implication of diversity policy and movie production strategy of Korea film market.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1353-1356
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• 2021

블록체인은 다수의 노드 네트워크 내에서 거래내역을 분산 저장함으로써 투명성을 확보하는 기술이다. 최근에는 금전적 가치를 지닌 선하증권(Bill of Lading, B/L 서류)에 블록체인을 적용하여 무결성을 확보하고 거래 과정을 간소화 하기위한 연구가 진행되고 있다. 본 논문에서는 거래자 중심의 블록체인 기반의 선하증권 시스템을 제안한다. 수출자는 발행 받은 선하증권을 AI(Artificial intelligence)기반의 OCR(Optical character recognition)기능을 통해 블록체인에 등록하고, 각국 은행에서 열람하여 신용장거래를 진행한다. 수입자는 선하증권 정보를 담은 QR(Quick Response code)코드로 자기증명을 하여 물품을 인도 받게 된다. 이는 수출자 측에서는 선적서류를 우편으로 보낼 시간과 비용을 단축하고, 서류의 무결성을 입증할 수 있다는 점에서 큰 효과를 얻을 수 있다. 수입자 측에서는 서류가 등록됨과 동시에 확인할 수 있고, 해당 거래를 신뢰할 수 있다는 이점을 갖는다. 마지막으로 은행 측에서는 선적서류에 대해 보안성을 갖출 수 있고 검증이 더 신속하게 이루어질 수 있다.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.188.2-188.2
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• 2010

북한은 자급자족의 형태로 지하자원과 수력을 이용하여 에너지원으로 사용하고 수입연료를 자제하는 실정이다. 하지만 기존의 발전 설비들의 노후화와 지하자원의 확보의 어려움이 증가 되어 신재생에너지의 개발을 확대하고 있다. 이에 우리나라에서는 남북의 기술교류 확대 및 미래 에너지 자원의 확보를 위하여 북한 자원자원에 대한 연구가 이뤄지고 있다. 기존의 연구에서는 북한지역의 관측값을 활용하거나 저해상도의 바람지도들이 작성되었다. 북한 지역의 바람의 분포를 세밀히 파악하기 위하여 기존의 바람지도 보다 상세한 풍력-기상자원지도가 필요하기 때문에 연구를 진행하였다. 북한의 풍력-기상자원지도를 개발하기 위해 미국 NCAR에서 개발한 중규모 모형인 WRF(Weather Research & Forcasting)을 활용하였다. 좋은 풍력자원을 갖춘 장소에 풍력 단지를 조성하기 위해서는 고해상도의 기상자원지도를 이용해서 파악하는 것이 필요하므로 해상도를 1km으로 설정하여 수행되었다. 본 연구의 결과로 지상 80 m에서의 1km 해상도를 갖는 풍력-기상자원지도를 작성하였다. 개발된 풍력-기상자원지도의 검증을 위해서 우리나라에서 확보가 가능한 북한 27개 지점의 지상 10 m 바람자료들을 활용하였다. 풍속에 대한 검증은 Bias와 RMSE을 이용하였으며, 풍향의 검증은 MAE을 활용하였다. 연 평균의 북한의 풍력-기상자원지도를 보면, 북한의 산맥을 중심으로 다른 지역보다 높은 풍속 분포를 보이고 있으며, 황해도를 포함한 북한의 서해안지역에서 비교적 높은 풍속의 분포를 나타내고 있다. 계절별로 살펴보면 봄철과 겨울철에 여름과 가을철보다 높은 풍력자원이 나타나며, 여름철이 가장 낮은 풍력자원을 갖는 것으로 분석되었다.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Korean Journal of Culture and Social Issue
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• v.15 no.1
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• pp.95-132
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• 2009

Can money buy happiness? If not, what are the factors that influence happiness? What makes people happy? What are the factors that influence happiness among Korean adults? How can we better explain factors that influence happiness? These are the research questions that led to the analyses of psychological, relational, financial resources that influence happiness. To examine differences in socio-economic status, adults and elderly from three different districts that vary wealth and income were interviewed in their own home. A total of 313 respondents (male=133, female=180) between the ages of 20 through 80 completed a questionnaire that contained background information, emotional support scale and happiness scale developed by the present researcher and resiliency of efficacy developed by Bandura(1995). The results are as follows. First, monthly income influence happiness to some extent, but when the variable was excluded from the path analysis, the goodness-of-fit did not change significantly. Although those who have more money can be happier, those without much money can also be happy. These results indicate that financial resource has limited influence on happiness. In addition, monthly income did influence self-efficacy of respondents indicating that those with more money were not necessarily more confident about themselves. Second, an important factor influencing happiness is the relational resource. Emotional support was the most powerful predictor of happiness, four to five times more important than monthly income. Third, self-efficacy influenced happiness. Those respondents with higher resiliency of efficacy had higher happiness scores and the influence was two times greater than monthly income. Moreover, self-efficacy played a mediating role between emotional support and happiness. Fourth, those respondents with higher occupational achievement reported higher happiness score and the influence was two times greater than monthly income. Fifth, success of children influenced happiness score and the influence was 1.5 times greater than monthly income. Sixth, education did not directly influence happiness, but had an indirect influence through self-efficacy and occupational achievement. Seventh, age was not related to self-efficacy and happiness.

• Analytical Science and Technology
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• v.34 no.3
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• pp.134-141
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• 2021

In this study, the fatty acid (FA) composition of commercial sesame oils (n = 62) was investigated using gas chromatography with flame ionization detector (GC-FID). Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA), were applied to the chromatographic data of the FAs to discriminate the geographical origin of sesame oils. A statistically significant difference was observed in the content of C16:0, C18:0, C18:1, and C18:2 between domestic and imported sesame oils. A satisfactory recovery rate of 82.8-100.2 % was achieved for C16:0, C18:0, C18:1, C18:2, and C18:3. The correlation of C16:0, C18:1, and C18:2 in domestic sesame oils showed opposite trends compared to imported oils. The PCA plot demonstrated that sesame oils were clustered in distinct groups according to their origin. LDA was used to predict sesame oil samples in one of the two groups. C16:0 (Wilks λ = 0.361) and C18:1 (Wilks λ = 0.637) demonstrated the highest discriminant power for classifying the origin of the samples. The correct prediction rates were 88.9 % and 100 % for the domestic and imported samples, respectively. Further, 60 of the 62 sesame oil samples (96.8 %) were correctly classified, indicating that this approach can be used as a valuable tool to predict and classify the geographical origin of sesame oils.

• Environmental and Resource Economics Review
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• v.15 no.4
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• pp.673-692
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• 2006

In order to test for the dynamic optimality condition for the use of nonrenewable resource, it is necessary to estimate the shadow value of the resource in situ. In the previous literatures, a time series for in situ price has been derived either as the difference between marginal revenue and marginal cost or by differentiating with respect to the quantity of ore extracted the restricted cost function in which the quantity of ore is quasi-fixed. However, not only inconsistent estimates are likely to be generated due to the nonmalleability of capital, but the estimate of marginal revenue will be affected by market power. Since firms will likely fail to minimize the cost of the reproducible inputs subject to market prices under realistic circumstances where imperfect factor markets, strikes, or government regulations are present, the shadow in situ values obtained by estimating the restricted cost function can be biased. This paper provides a valid methodology for checking the dynamic optimality condition for a nonrenewable resource by using the input distance function. Our methodology has some advantages over previous ones: only data on quantities of inputs and outputs are required; nor is the maintained hypothesis of cost minimization required; adoption of linear programming enables us to circumvent autocorrelated errors problem caused by use of time series or panel data. The dynamic optimality condition for domestic coal mining does not hold for constant discount rates ranging from 2 to 20 percent over the period 1970~1993. The dynamic optimality condition also does not hold for variable rates ranging from fourth to four times the real interest rate.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.4
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• pp.258-263
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• 2019

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages. The objective of this study was to evaluate the potential of NIRS, applied to imported forage, to estimate the moisture and chemical parameters for imported hays. A population of 392 imported hay representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1 nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation(R²) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS predicted the chemical parameters with very high degree of accuracy. The R² and SECV for imported hay calibration were 0.92(SECV 0.61%) for moisture, 0.98(SECV 0.65%) for acid detergent fiber, 0.97(SECV 0.40%) for neutral detergent fiber, 0.99(SECV 0.06%) for crude protein and 0.97(SECV 3.04%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of imported hay in Korea for routine analysis method to evaluate the feed value.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.468-474
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• 2020

Metal ducts for transporting air conditioning and heating inside ships have recently been replaced by cloth ducts that have the advantage of delivering air evenly to the compartments, with excellent noise reduction in major compartments, such as combat command rooms, steering rooms, and sound detector cabins. Since the performance requirements of fabric ducts for vessels are strict, and the entire length of the ducts was imported from Korea, the government wants to create economic effects through localization of fabric ducts. Air permeability and fire prevention performance tests verified the applicability to naval vessels of fabric ducts developed by Hyundai Heavy Industries and HiDact, and performance requirements presented in the POS were verified. As a result of the tests, the fabric ducts met the requirements for air permeability and fireproof performance.