• Environmental and Resource Economics Review
• /
• v.26 no.4
• /
• pp.473-498
• /
• 2017

This study examines the effect of environmental regulation considering the endogeneity on the productivity of Korean manufacturing industry based on the Porter hypothesis using data from the Mining and Manufacturing Survey, Survey of Research and Development in Korea, and Environmental Statistics Portal from 2003 to 2013 with fixed effect model. In order to eliminate the bias of the missing variables that may occur in the existing studies, we analyze factors affecting productivity such as market competition, R&D investment as explanatory variables. And, in order to eliminate measurement error and inverse causality, we use instrumental variable approach. The main results are as follows. First, our findings that the environmental regulation improve the productivity of Korean manufacturing in the long-run support the Porter hypothesis. Second, our findings suggest that measurement error and reverse causality are main sources of the endogeneity, while omitted variable is not. Finally, environmental technology R&D has reduced productivity in the short-run.

• International Commerce and Information Review
• /
• v.15 no.4
• /
• pp.147-170
• /
• 2013

The Free Trade Agreement between Korea and Peru entered into force in 2011. Under the agreement, both countries will eliminated all tariffs within ten years after it takes effect. The Korea-Peru Free Trade Agreement turned out to have significantly boosted Korea's exports to the South American state, as well as its relative share in the local import market. Korea mainly imports resources such as zinc and copper, and exports such goods as passenger car and color televisions. The FTA opens up a larger market for Korean home appliances like color televisions. Korea's trade with Peru has been mainly about concentrated investment into mining and exporting limited variety of export items. This paper analyzes the recent trends of problems of trade between Korea and Peru and suggests solutions for boosting trade to provide proper strategic guidelines for Korea that are planning to expand to Peruvian market

• The KIPS Transactions:PartB
• /
• v.8B no.6
• /
• pp.625-632
• /
• 2001

The electronic stores have realized that they need to understand their customers and to quickly response their wants and needs. To be successful in increasingly competitive Internet marketplace, recommender systems are adapting data mining techniques. One of most successful recommender technologies is collaborative filtering (CF) algorithm which recommends products to a target customer based on the information of other customers and employ statistical techniques to find a set of customers known as neighbors. However, the application of the systems, however, is not very suitable for seasonal products which are sensitive to time or season such as refrigerator or seasonal clothes. In this paper, we propose a new adjusted item-based recommendation generation algorithms called the exponentially weighted collaborative filtering recommendation (EWCFR) one that computes item-item similarities regarding seasonal products. Finally, we suggest the recommendation system with relatively high quality computing time on main memory database (MMDB) in XML since the collaborative filtering systems are needed that can quickly produce high quality recommendations with very large-scale problems.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.6
• /
• pp.1-15
• /
• 2017

Recently terrorism targets unspecified masses and causes massive destruction, which is so-called Super Terrorism. Many countries have tried hard to protect their citizens with various preparation and safety net. With inexpensive and advanced technologies of sensors, the surveillance systems have been paid attention, but few studies associated with the classification of the pedestrians' trajectories and the difference among themselves have attempted. Therefore, we collected individual trajectories at Samseoung Station using an analytical solution (system) of pedestrian trajectory by LiDAR sensor. Based on the collected trajectory data, a comprehensive framework of classifying the types of pedestrians' trajectories has been developed with data normalization and "trajectory association rule-based algorithm." As a result, trajectories with low similarity within the very same cluster is possibly detected.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.6 no.4
• /
• pp.509-520
• /
• 1996

Ultrafine calcim carbonate powders with the size of $0.05~0.1\;{\mu}m$ and the calcite phase were synthesized by the nozzle spouting method, which could be only obtained when high calcium ion concentration within slurry was maintained at the beginning of the reaction. But, in the regions of low ${Ca(OH)}_2$ concentration (0.5~1.0 wt%) or high ${Ca(OH)}_2$ concentration (<3.0 wt%), synthesized calcium carbonate powder was shown the large particle size with agglomeration. To obtain ultrafine calcium carbonate powder in this region, the methods of slurry circuation and $CO_{2}$ gas supply were changed during reaction. Resultly, it was possible to synthesize ultrafine particles (${\approx}0.05{\mu}\textrm{m}$)in the regions of low ${Ca(OH)}_2$ concentration (${\approx}0.5wt%$) and high ${Ca(OH)}_2$ concentration (${\approx}0.5wt%$), which can not be obtained the fine calcium carbonate powder still now.

• The KIPS Transactions:PartD
• /
• v.13D no.3 s.106
• /
• pp.309-316
• /
• 2006

We propose a novel technique to categorize XML documents and extract a concept efficiently using domain ontology. First, we create domain ontology that use text mining technique and statistical technique. We propose a DScore technique to classify XML documents by using the structural characteristic of XML document. We also present TScore technique to extract a concept by comparing the association term set of domain ontology and the terms in the XML document. To verify the efficiency of the proposed technique, we perform experiment for 295 papers in the computer science area. The results of experiment show that the proposed technique using the structural information in the XML documents is more efficient than the existing technique. Especially, the TScore technique effectively extract the concept of documents although frequency of term is few. Hence, the proposed concept-based retrieval techniques can be expected to contribute to the development of an efficient ontology-based knowledge management system.

• The KIPS Transactions:PartC
• /
• v.10C no.6
• /
• pp.717-726
• /
• 2003

In this paper, we analyze the associated rule based deductive algorithm which creates the rules automatically for intrusion detection from the vast packet data. Based on the result, we also suggest the deductive algorithm which creates the rules of intrusion pattern fast in order to apply the intrusion detection systems. The deductive algorithm proposed is designed suitable to the concept of clustering which classifies and deletes the large data. This algorithm has direct relation with the method of pattern generation and analyzing module of the intrusion detection system. This can also extend the appication range and increase the detection speed of exiting intrusion detection system as the rule database is constructed for the pattern management of the intrusion detection system. The proposed pattern generation technique of the deductive algorithm is used to the algorithm is used to the algorithm which can be changed by the supporting rate of the data created from the intrusion detection system. Fanally, we analyze the possibility of the speed improvement of the rule generation with the algorithm simulation.

• Journal of Distribution Science
• /
• v.8 no.2
• /
• pp.5-12
• /
• 2010

The allotment rate for railway transportation keeps an yearly 6% in Korea. However, the railway logistics will cause the opposite result according to the continuous investment and logistics rationalization. The study on railway logistics as well as inter-Korean railway that might highly contribute to the development of railway logistics is not enough at all. The purpose of this paper is to study the revitalization strategy for inter-Korean railway by forecasting the demand and the scale of railway logistics depot. The revitalization strategies for inter-Korean railway through railway logistics depot are as followings. First, it is necessary to strengthen the partnership with coal user in the logistics depot. Second, it is encouraged to provide the financial assistance that are needed in the maintenance of the decrepit North Korea's track as well as the establishment of Donghae northern line that is from Gangneung to Jejin. Third, the railway cost on long/short transportation and large sized shipper is needed to apply in a flexible way. Fourth, it is necessary to obtain the railway traffic right by involving the foreign mining development. Fifth, it is encouraged to constantly find the small sized shipper like cement company.

• The Journal of the Convergence on Culture Technology
• /
• v.5 no.4
• /
• pp.413-420
• /
• 2019

The purpose of the present study is to develop a model for predicting hypercholesterolemia using an integrated set of body fat mass variables based on machine learning techniques, beyond the study of the association between body fat mass and hypercholesterolemia. For this study, a total of six models were created using two variable subset selection methods and machine learning algorithms based on the Korea National Health and Nutrition Examination Survey (KNHANES) data. Among the various body fat mass variables, we found that trunk fat mass was the best variable for predicting hypercholesterolemia. Furthermore, we obtained the area under the receiver operating characteristic curve value of 0.739 and the Matthews correlation coefficient value of 0.36 in the model using the correlation-based feature subset selection and naive Bayes algorithm. Our findings are expected to be used as important information in the field of disease prediction in large-scale screening and public health research.

• Journal of Korea Trade
• /
• v.24 no.8
• /
• pp.39-62
• /
• 2020

Purpose - Korean exports account for a vast proportion of Korean GDP, and large volumes of Korean products are sold in the United States. Identifying and characterizing actual and potential product hazards related to Korean products is critical to safeguard Korean export trade, as severe quality issues can impair Korea's reputation and reduce global consumer confidence in Korean products. In this study, we develop country-of-origin-based product risk analysis methods for social media with a specific focus on Korean-labeled products, for the purpose of safeguarding Korean export trade. Design/methodology - We employed two social media datasets containing consumer-generated product reviews. Sentiment analysis is a popular text mining technique used to quantify the type and amount of emotion that is expressed in the text. It is a useful tool for gathering customer opinions regarding products. Findings - We document and discuss the specific potential risks found in Korean-labeled products and explain their implications for safeguarding Korean export trade. Finally, we analyze the false positive matches that arise from the established dictionaries that were used for risk discovery and utilize these classification errors to suggest opportunities for the future refinement of the associated automated text analytic methods. Originality/value - Various studies have used online feedback from social media to analyze product defects. However, none of them links their findings to trade promotion and the protection of a specific country's exports. Therefore, it is important to fill this research gap, which could help to safeguard export trade in Korea.