• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.91-100
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• 2006

This paper examines the situation and tasks of UK rail privatization, especially focusing on after the Hatfield rail accident. Earlier research which focused on the UK's Privatization had little knowledge of the explanations for recent changes. Moreover they had difficulty making a direct comparison between national rail and the privatized rail. Therefore we aye left without a good explanation which has a comprehensive perspective. I attempt to show the change in the rail privatization Process and its outcome, focusing on after the Hatfield rail accident. This Paper argues that the UK's vail privatization process has a regulatory framework which is too complicated with overlapping responsibilities that brought about inefficiency, increasing costs and a superficial safety regime. Especially the planning of rail and infrastructure maintenance did not come to play an appropriate role. However after 2000, the government took charge of setting the strategy for railways, and the Office of Rail Regulation covered safety performance and cost. explain that these changes present a good opportunity to solve the problem of passing the buck for poor performance. Through the analysis, I find that the passenger rail network is well-suited to deliver long distance business and commuters and that the subsidy from the government is decreasing. However, performance, for example punctuality and reliability. should be improved. Especially the Hatfield rail accident caused a reduction in the satisfaction of passengers. In future. the problems of rising costs and monopoly franchise system should be addressed.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.65-78
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• 2006

This paper investigates the cost structure ot the Korea and Japan railroad industry with respect to density, scale and scope economies as well as productivity growth rate using a generalized trans)og multiproduct cost function model. The paper then assumes that the Korea and Japan railway companies pi·educe three outputs (incumbent railway passenger-kilometers. Shinkansen passenger-kilometers, ton-kilometers of freight) using four input factors (labor, fuel, maintenance, rolling stock and capital). The specified cost function includes foul other independent variables: track lengths to reflect network effects, two dummies to reflect nation and ownership effects, and time trend as a proxy for technical change. The simultaneous equation system consisting of a cost function and three input share equations is estimated with the Zellner's iterative seemingly unrelated regression. The unbalanced panel data used in the paper, a total of 154 observations. are collected from the annual records of the Korea National Railroad (KNR) for the yews $1977{\sim}2003$, Japan National Railways (JNR) for the years $1977{\sim}1984$. seven Japan Railways (JR's) for the years $1987{\sim}2003$. The findings show that the Korean and Japanese railways exhibit product-specific and overall economies of density but product-specific diseconomies of scale with respect to incumbent railway passenger-kilometers, Shinkansen-kilometers and ton-kilometers. However, the railways experience mild overall economies of scale which result from economies of scope associated with the joint production of incumbent railway/Shinkansen and feight, freight/incumbent railway and Shinkansen except Shinkansen/incumbent railway and freight. In addition, the economies of density and scale in the KNR, JR east, JR central, and JR west companies at the point of the years $1990{\sim}2003$ average is generally analogous to the above results at the point of sample average. There also appear to be economies of ssope associated with the joint Production of the incumbent railway and Shinkansen in JR central but diseconomies of scope in JR East and JR West. The findings also indicate that the productivity growth rate of the privately-owned JR's is larger than that of the government-owned KNR.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.72-78
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• 2009

The demand for rainfall data in gridded digital formats has increased in recent years due to the close linkage between hydrological models and decision support systems using the geographic information system. One of the most widely used tools for digital rainfall mapping is the PRISM (parameter-elevation regressions on independent slopes model) which uses point data (rain gauge stations), a digital elevation model (DEM), and other spatial datasets to generate repeatable estimates of monthly and annual precipitation. In the PRISM, rain gauge stations are assigned with weights that account for other climatically important factors besides elevation, and aspects and the topographic exposure are simulated by dividing the terrain into topographic facets. The size of facet or grid cell resolution is determined by the density of rain gauge stations and a $5{\times}5km$ grid cell is considered as the lowest limit under the situation in Korea. The PRISM algorithms using a 270m DEM for South Korea were implemented in a script language environment (Python) and relevant weights for each 270m grid cell were derived from the monthly data from 432 official rain gauge stations. Weighted monthly precipitation data from at least 5 nearby stations for each grid cell were regressed to the elevation and the selected linear regression equations with the 270m DEM were used to generate a digital precipitation map of South Korea at 270m resolution. Among 1.25 million grid cells, precipitation estimates at 166 cells, where the measurements were made by the Korea Water Corporation rain gauge network, were extracted and the monthly estimation errors were evaluated. An average of 10% reduction in the root mean square error (RMSE) was found for any months with more than 100mm monthly precipitation compared to the RMSE associated with the original 5km PRISM estimates. This modified PRISM may be used for rainfall mapping in rainy season (May to September) at much higher spatial resolution than the original PRISM without losing the data accuracy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.2
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• pp.70-80
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• 2003

We report the first direct measurement of $CO_2$ flux over Kwangneung broadleaf deciduous forest, one of the tower flux sites in KoFlux network. Eddy covariance system was installed on a 30 m tower along with other meteorological instruments from June to August in 2002. Although the study site was non-ideal (with valley-like terrain), turbulence characteristics from limited wind directions (i.e., 90$\pm$45$^{\circ}$) was not significantly different from those obtained at simple, homogeneous terrains with an ideal fetch. Despite very low rate of data retrieval, preliminary results from our analysis are encouraging and worthy of further investigation. Ignoring the role of advection terms, the averaged net ecosystem exchange (NEE) of $CO_2$ ranged from -1.2 to 0.7 mg m$^{-2}$ s$^{-1}$ from June to August in 2002. The effect of weak turbulence on nocturnal NEE was examined in terms of friction velocity (u*) along with the estimation of storage term. The effect of low uf u* NEE was obvious with a threshold value of about 0.2 m s$^{-1}$ . The contribution of storage term to nocturnal NEE was insignificant; suggesting that the $CO_2$ stored within the forest canopy at night was probably removed by the drainage flow along the hilly terrain. This could be also an artifact of uncertainty in calculations of storage term based on a single-level concentration. The hyperbolic light response curves explained ＞80% of variation in the observed NEE, indicating that $CO_2$ exchange at the site was notably light-dependent. Such a relationship can be used effectively in filling up the missing gaps in NEE data through the season. Finally, a simple scaling analysis based on a linear flow model suggested that advection might play a significant role in NEE evaluation at this site.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.25-34
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• 2015

In this research, we applied a procedure of quality control (QC) to the agro-meteorological data measured at the Suwon weather station of Korea Meteorological Administration (KMA). The QC was conducted through six steps based on the KMA Real-time Quality control system for Meteorological Observation Data (RQMOD) and four steps based on the International Soil Moisture Network (ISMN) QC modules. In addition, we set up our own empirical method to remove erroneous data which could not be filtered by the RQMOD and ISMN methods. After all these QC procedures, a well-refined agro-meteorological dataset was complied at both air and soil temperatures. Our research suggests that soil moisture requires more detailed and reliable grounds to remove doubtful data, especially in winter with its abnormal variations. The raw data and the data after QC are now available at the NCAM website (http://ncam.kr/page/req/agri_weather.php).

• Korea journal of population studies
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• v.21 no.2
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• pp.182-227
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• 1998

Korean government decided to adopt an explicit population control policy in 1961 and from the following year the establishment and operation of the national family planning programme was included in each of the Five-Year Economic Development Plans that began in 1962. This policy was pursued in the understanding that without proper population control measures korea could not be able to achieve economic development. Korean national family planning programme is characterized by contraceptive target system through public health network with distribution of free contraceptives by family planning field workers and clinical contraceptive services such as IUD, vasectomy and tubaligation at designated clinics by the government. In addition, IE&C activities by the Planned Parenthood Federation of Korea and programme evaluation and research by the Korea Institute for Health and Social Affairs contributed to the development of the government programme. Between 1960 and mid 1980s the nation's total fertility rate was reduced from 6.0 to population replacement level of 2.1 and thereafter it has been maintained at 1.6 to 1.7 of below replacement level. With a short period of less than three decades fertility transition was completed in Korea. It is estimated that if the current level of below replacement fertility continues, the population in Korea stabilize at around 52.78 million people by the year 2028, and it will begin to decrease thereafter. Under this circumstances, the government adopted new directions and strategies of the population policy in June 1996, focused primarily on population quality and social welfare than on demographic arenas. In spite of over 80 percent of high contraceptive prevalence among married women, high incidence of induced abortions is maintained. Moreover, the prevalence of sex selective induced abortions using procedures to determine the sex of the fetus has resulted in an imbalance in the sex ratio at birth. In order to overcome those problems associated with reproductive health new policy for population quality control and health promotion programme should be highly strengthened in the future.

• Korean Journal of Environment and Ecology
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• v.34 no.2
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• pp.99-105
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• 2020

Migratory birds use a variety of breeding and wintering sites, and it is particularly important to understand more information on breeding and feeding sites for the conservation and management of endangered species. Black-faced spoonbills (Platalea minor) are an international endangered species distributed in East Asia. The majority of black-faced spoonbills breed on uninhabited islets off the west coast of the Korean Peninsula during the breeding season, and they are distributed in East Asia such as Taiwan, Hong Kong, southern China, Japan, and Jeju island during the winter season. In this study, we used a wild animal location tracking system to analyze and compare home ranges of three black-faced spoonbills spending the post-fledging stage in Gujido islet in Incheon and Chilsando islet in Yeonggwang each in 2015. The tree black-faced spoonbills in Guji islet showed a home range in coastal areas in Hwanghaenam-do and Gangneung-gun. The home range size (mean±SD) was estimated to be 425.49±116.95 ㎢ using 100% MCP, 43.61±18.51 ㎢ using KDE 95%, and 7.46±3.68 ㎢using KDE 50%. The tree black-faced spoonbills in Chilsando islet showed a home range in the Baeksu tidal flat and the Buan Saemangeum area with a size of 99.38±55.29 ㎢ using 100% MCP, 19.87±6.05 ㎢ using KDE 95%, and 1.16±0.53 ㎢ using KDE 50%. The figured indicated that the tree black-faced spoonbills breeding in Gujido islet had a wider home range than those breeding in Chilsando islet. During the post-fledging stage, the home ranges of black-faced spoonbills were mostly breeding in mudflats. Therefore, it is necessary to minimize human intervention, such as the construction of roads and structures and the human access, to protect the habitats during the period.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.1-19
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• 2010

In offline environment, unlike traditional advertising model through TV, newspaper, and radio, online advertising model draws instantaneous responses from potential consumers and it is convenient to assess. This kind of characteristics of Internet advertising model has driven the growth of advertising model among various Internet business models. There are, conventionally classified, CPM (Cost Per Mile), CPC (Cost Per Click), and CPS (Cost Per Sales) models as Internet advertising expenditure model. These can be examined in manners regarding risks that stakeholders should stand and degree of responsibility. CPM model that is based on number of advertisement exposure is mechanically exposed to users but not actually recognized by users resulting in risk of wasted expenditure by advertisers without any advertising effect. While on aspect of media, CPS model that is based on conversion action is the most risky model because of the conversion action such as product purchase is determined by capability of advertisers not that of media. In this regard, while there are issue of CPM and CPS models disadvantageously affecting only one side of Internet advertising business model value network, CPC model has been evaluated as reasonable both to advertisers and media, and occupied the largest segment of Internet advertising market. However, CPC model also can cause fraudulent behavior such as click fraud because of the competition or dishonest amount of advertising expenditure. On the user aspect, unintentionally accessed advertisements can lead to more inappropriate expenditure from advertisers. In this paper, we suggest "CPCD"(Cost Per Coupon Download) model. This goes beyond simple clicking of advertisements and advertising expenditure is exerted when users download a coupon from advertisers, which is a concept in between CPC and CPS models. To achieve the purpose, we describe the scenario of advertiser perspective, processes, participants and their benefits of CPCD model. Especially, we suggest the new value in online coupon; "possibility of storage" and "complement for delivery to the target group". We also analyze the working condition for advertiser by a comparison of CPC and CPCD models through advertising expenditure simulation. The result of simulation implies that the CPCD model suits more properly to advertisers with medium-low price products rather than that of high priced goods. This denotes that since most of advertisers in CPC model are dealing with medium-low priced products, the result is very interesting. At last, we contemplate applicability of CPCD model in ubiquitous environment.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.45-67
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• 2016

Given the recent development of smart devices, users are producing, sharing, and acquiring a variety of information via the Internet and social network services (SNSs). Because users tend to use multiple media simultaneously according to their goals and preferences, domestic SNS users use around 2.09 media concurrently on average. Since the information provided by such media is usually textually represented, recent studies have been actively conducting textual analysis in order to understand users more deeply. Earlier studies using textual analysis focused on analyzing a document's contents without substantive consideration of the diverse characteristics of the source medium. However, current studies argue that analytical and interpretive approaches should be applied differently according to the characteristics of a document's source. Documents can be classified into the following types: informative documents for delivering information, expressive documents for expressing emotions and aesthetics, operational documents for inducing the recipient's behavior, and audiovisual media documents for supplementing the above three functions through images and music. Further, documents can be classified according to their contents, which comprise facts, concepts, procedures, principles, rules, stories, opinions, and descriptions. Documents have unique characteristics according to the source media by which they are distributed. In terms of newspapers, only highly trained people tend to write articles for public dissemination. In contrast, with SNSs, various types of users can freely write any message and such messages are distributed in an unpredictable way. Again, in the case of newspapers, each article exists independently and does not tend to have any relation to other articles. However, messages (original tweets) on Twitter, for example, are highly organized and regularly duplicated and repeated through replies and retweets. There have been many studies focusing on the different characteristics between newspapers and SNSs. However, it is difficult to find a study that focuses on the difference between the two media from the perspective of supply and demand. We can regard the articles of newspapers as a kind of information supply, whereas messages on various SNSs represent a demand for information. By investigating traditional newspapers and SNSs from the perspective of supply and demand of information, we can explore and explain the information dilemma more clearly. For example, there may be superfluous issues that are heavily reported in newspaper articles despite the fact that users seldom have much interest in these issues. Such overproduced information is not only a waste of media resources but also makes it difficult to find valuable, in-demand information. Further, some issues that are covered by only a few newspapers may be of high interest to SNS users. To alleviate the deleterious effects of information asymmetries, it is necessary to analyze the supply and demand of each information source and, accordingly, provide information flexibly. Such an approach would allow the value of information to be explored and approximated on the basis of the supply-demand balance. Conceptually, this is very similar to the price of goods or services being determined by the supply-demand relationship. Adopting this concept, media companies could focus on the production of highly in-demand issues that are in short supply. In this study, we selected Internet news sites and Twitter as representative media for investigating information supply and demand, respectively. We present the notion of News Value Index (NVI), which evaluates the value of news information in terms of the magnitude of Twitter messages associated with it. In addition, we visualize the change of information value over time using the NVI. We conducted an analysis using 387,014 news articles and 31,674,795 Twitter messages. The analysis results revealed interesting patterns: most issues show lower NVI than average of the whole issue, whereas a few issues show steadily higher NVI than the average.