• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.2
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• pp.138-149
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• 2003

Korean regional network of tower flux sites, KoFlux, has been initiated to better understand $CO_2$, water and energy exchange between ecosystems and the atmosphere, and to contribute to regional, continental, and global observation networks such as FLUXNET and CEOP. Due to heterogeneous surface characteristics, most of KoFlux towers are located in non-ideal sites. In order to quantify carbon and energy exchange and to scale them up from plot scales to a region scale, applications of various methods combining measurement and modeling are needed. In an attempt to infer regional-scale flux, four methods (i.e., tower flux, convective boundary layer (CBL) budget method, MM5 mesoscale model, and NCAR/NCEP reanalysis data) were employed to estimate sensible heat flux representing different surface areas. Our preliminary results showed that (1) sensible heat flux from the tower in Haenam farmland revealed heterogeneous surface characteristics of the site; (2) sensible heat flux from CBL method was sensitive to the estimation of advection; and (3) MM5 mesoscale model produced regional fluxes that were comparable to tower fluxes. In view of the spatial heterogeneity of the site and inherent differences in spatial scale between the methods, however, the spatial representativeness of tower flux need to be quantified based on footprint climatology, geographic information system, and the patch scale analysis of satellite images of the study site.

• Management & Information Systems Review
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• v.34 no.3
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• pp.125-140
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• 2015

KOSDAQ market reorganized their division system from two types to four types of division departments such as blue chip, venture, medium, and technology development departments in 2011. However, under the current new division system, financially unhealthy firms attempting to take advantage of the classifying opportunity of blue chip department are likely to engage in pernicious earnings management. The objective of this study is to investigate the earnings management behavior surrounding the time of KOSDAQ firms entering the blue chip department via new division system. More specifically, we test whether the firms classified blue chip department tend to engage in upward earnings management using accruals and real activities before and after they achieve blue chip status. In this study, we analyzed 111 firms classified blue chip department in 2011 according to new division system in KOSDAQ market. Major test results indicate that firms entering the blue chip department according to current KOSDAQ division system in general, tend to inflate reported earnings by means both of accruals and real activities right before the entering year. This result suggests that the firms classified blue chip department engage in opportunistic earnings management with a view to uplifting their market values. Our study is expected to provide clues useful for searching policy directions which intend to ameliorate adverse side effects of the current KOSDAQ division system. In sum, the regulatory authorities and enforcement bodies need to exercise caution in deliberating more stringent review procedures so that financially healthy and promising candidates are properly segregated from their poor and risky counterparts, thus enhancing the beneficial effects, while mitigating adverse side effects of the system.

• Management & Information Systems Review
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• v.36 no.2
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• pp.207-221
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• 2017

The career management concept is changing rapidly in the career management field in recent years. It becomes very difficult to have a lifetime employment within the same firm. As there is career interruption that is pervasive phenomenon in the women's career management area, many academics and practitioners have been interested in it. The purpose of this study was to examine the influence of women's career-interruptions as the effective career strategy on career development actors and career success. To test the effects of the proactive career management of career-interrupted women, data were divided into two groups including proactive career management group and general career management group based on whether career-interruptions are voluntary or not. The results showed that the proactive development actors was significantly different depending on women's proactive career management and general career management group. First, proactive-career women were more self-directed to learn and have a significant impact on developing skills through training. Second, the career successes were not significantly different depending on and general career management group.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.751-759
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• 2007

We have developed several methods for the optimization problem having large-scale and highly nonlinear system. First, step by step method in optimization process was employed to improve the convergence. In addition, techniques of furnishing good initial guesses for analysis using sensitivity information acquired from optimization iteration, and of manipulating analysis/optimization convergency criterion motivated from simultaneous technique were used. We applied them to flow control problem and verified their efficiency and robustness. However, they are based on quasi-Newton method that approximate the Hessian matrix using exact first derivatives. However solution of the Navier-Stokes equations are very cost, so we want to improve the efficiency of the optimization algorithm as much as possible. Thus we develop a true Newton method that uses exact Hessian matrix. And we apply that to the three-dimensional problem of flow around a sphere. This problem is certainly intractable with existing methods for optimal flow control. However, we can attack such problems with the methods that we developed previously and true Newton method.

• Korean Association of Arts Management
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• no.57
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• pp.5-32
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• 2021

The purpose of this study is to find out what kind of experience docent programs provide to visitors in museums by means of Giorgi's phenomenological method. In-depth interview was conducted with 6 visitors who had experienced firsthand. As a result of the coding based upon Giorgi's method, it was divided into 6 categories and 21 subcategories, and the following results were obtained. First, the reason that the subjects of the study participated in the docent program was due to factors such as information, coincidence, induction of companions, and habits. Second, from participating in the docent guide, they felt that the docent led them to actively visit the exhibition, get the educational effect, and generate interest and curiosity. Third, looking at the reaction after participating in the docent guide, in addition to the positive influence, the docent's reading-like explanation and the problem of the microphone facility were negative experiences. Through this study, it was confirmed that there were many visitors who recognized that the docent guide was helpful in viewing the exhibition and experienced positive reactions. In addition, in the evaluation of the commentary of docent, there was a difference of views between art-related majors and non-majors. In addition, as a result of analyzing the participants' experiences according to Holt's frame of experiential consumption, it was found that the docent experience was a comprehensive consumption behavior appearing in all four fields.

• Korean Journal of Cognitive Science
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• v.17 no.2
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• pp.75-102
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• 2006

Three experiments were conducted using a verification task to examine good and poor readers' generation of causal inferences(with because sentences) and contrastive inferences(with although sentences). The unfamiliar, critical verification statement was either explicitly mentioned or was implied. In Experiment 1, both good and poor readers responded accurately to the critical statement, suggesting that both groups had the linguistic knowledge necessary to the required inferences. Differences were found, however, in the groups' verification latencies. Poor, but not good, readers responded faster to explicit than to implicit verification statements for both because and although sentences. In Experiment 2, poor readers were induced to generate causal inferences for the because experimental sentences by including fillers that were apparently counterfactual unless a causal inference was made. In Experiment 3, poor readers were induced to generate contrastive inferences for the although sentences by including fillers that could only be resolved by making a contrastive inference. Verification latencies for the critical statements showed that poor readers made causal inferences in Experiment 2 and contrastive inferences in Experiment 3 doting comprehension. These results were discussed in terms of context effect: Specific encoding operations performed on anomaly backgrounded in another passage would form part of the context that guides the ongoing activity in processing potentially relevant subsequent text.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Broadcast Engineering
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• v.10 no.1 s.26
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• pp.43-56
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• 2005

In the existing broadcasting environment, it is not easy to serve the bi-directional service between a broadcasting server and a TV audience. In the uni-directional broadcasting environments, almost TV programs are scheduled depending on the viewers' popular watching time, and the advertisement contents in these TV programs are mainly arranged by the popularity and the ages of the audience. The audiences make an effort to sort and select their favorite programs. However, the advertisement programs which support the TV program the audience want are not served to the appropriate audiences efficiently. This randomly provided advertisement contents can occur to the audiences' indifference and avoidance. In this paper, we propose the target advertisement service for the appropriate distribution of the advertisement contents. The proposed target advertisement service estimates the audience's profile without any issuing the private information and provides the target-advertised contents by using his/her estimated profile. For the experimental results, we used the real audiences' TV usage history such as the ages, fonder and time of the programs from AC Neilson Korea. And we show the accuracy of the proposed target advertisement service algorithm. NDS (Normalized Distance Sum) and the Vector correlation method, and implementation of our target advertisement service system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.267-275
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• 2023

This study predicted rice harvest date in South Korea using 11-year (2012-2022) hindcasts based on dynamically downscaled 2m air temperature at subseasonal (1-month lead) timescale. To obtain high (5 km) resolution meteorological information over South Korea, global prediction obtained from the NOAA Climate Forecast System (CFSv2) is dynamically downscaled using the Weather Research and Forecasting (WRF) double-nested modeling system. To estimate rice harvest date, the growing degree days (GDD) is used, which accumulated the daily temperature from the seeding date (1 Jan.) to the reference temperature (1400℃ + 55 days) for harvest. In terms of the maximum (minimum) temperatures, the hindcasts tends to have a cold bias of about 1. 2℃ (0. 1℃) for the rice growth period (May to October) compared to the observation. The harvest date derived from hindcasts (DOY 289) well simulates one from observation (DOY 280), despite a margin of 9 days. The study shows the possibility of obtaining the detailed predictive information for rice harvest date over South Korea based on the dynamical downscaling method.

• The Korean Journal of Archival Studies
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• no.17
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• pp.157-202
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• 2008

Archival Objects are defined as objects having historical, aesthetic, and artistic value as well as archival value created and used with a particular purpose in business process. Increasingly, many countries including Canada, Australia, China are recognized the importance of Archival Objects and designated them as national records. In Korea, Archival Objects are involved in national records through '2006 Plan for the Archives and Records Management Reform'. So National Archives and Records Service provided a foothold for comprehensive plan of national records management including Archival Objects. And also, by revising Records and Archives Management Act in 2007, National Archives and Records Service declared aggressive will to management Archival Objects. Until now, Objects held in public institution were easy to be damaged because definition or scope of Archival Objects was ambiguous and management system for material character wasn't exist. Even though the revised Records and Archives Management Act suggest definition and declare the responsibility of management, management system focused on various shape and material of objects need to be established. So this study has defined Archival Objects shortly and carried out a research 5 institutions on the actual management condition. By researching the result of institution survey, Records and Archives Management Act and actual Records Management System, we could find some problems. In solving these problems, We provide objects management process in the order capture ${\rightarrow}$ register ${\rightarrow}$ description ${\rightarrow}$ preservation ${\rightarrow}$ use${\rightarrow}$disposition. In addition, close cooperation between records center and museum of institution should be established for the unitive management at national level. This study has significance in introducing a base to manage Archival Objects systematically. By studying more, we hope to advance in management of valuable Archival Objects.