• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.360-365
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• 2016

The purpose of this study is to provide the basic information for the early enforcement and extension of the improvement project of management scale of private forest land by understanding the characteristics of forest owners, who have an influence on the participation of the project as one of the private forest management vitalization plans. To achieve this goal, a questionnaire survey targeting 373 forest owners was conducted and analyzed by Binary-Logistic Regression. The variables for binary-logistic regression included gender, age, academic ability, occupation, income, residence, purpose of forest ownership, and status of cooperative membership. As a result of the analysis, 267 forest owners (71.6%) of total 373 forest owners have the intention to participate in the scaling project for private forest management. The rest of forest owners (106 forest owners, 28.4%) would not be willing to participate in the project. As a result of binary-logistic regression, the most important variables, which have an impact on the participation of private forest management scale improvement project, are age, job and forest own purpose.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.197-206
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• 2004

In ranking data, respondents are required to rank a number of alternatives in order of their preferences and an exploded logit model is generally used. It assumes that each rank contains the same amount of random noise. This study investigates the reliability of ranking data and identifies whether there are different decision rules at each rank stage. The results show that there were differences in the amount of unexplained variation in different ranking stage. A single scaling parameter could not explain the difference of variations of individual coefficients between two ranking data average difference of variations. This paper also investigated the optimal explosion depth in the exploded logit model by using the suggested scaling approach. The scaling approach should be based on particular variables which have different variances rather than based on the whole data set. The empirical analysis show that an explosion depth of 2 is appropriate after scaling the second rank data set, while an explosion including the third rank is inappropriate even though the third rank data set is scaled.

• Journal of the Korean Geographical Society
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• v.42 no.5
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• pp.691-709
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• 2007

This paper investigates the social and political construction of geographical scale in conjunction with Korean housing politics. Recently, attention has been drawn to the issue of the social and political construction of geographical scale. Spatial scales have increasingly been regarded as socially constructed and politically contested rather than ontologically pregiven or fixed. The scale literature has paid attention to how different spatial scales can be used or articulated in social movements, with an emphasis on 'up-scaling' and 'scales of activism' rather than 'down-scaling' and 'scales of regulation.' Furthermore, the scale literature has focused on the aspect of empowerment. However, it is worthwhile to examine how scale-especially 'down-scaling' and 'scales of regulation'-can be used not only for marginalizing or excluding unprivileged social groups, but also for controlling the (re)production of space, including housing space. Under a regulatory regime, the Korean central government gained more control over the (re)production of housing space at geographical multi-scales by means of 'jumping scales,' specifically 'down-scaling.' The Korean central government has increasingly obtained the capacity to 'jump scales' by using not only multiscalar strategies for housing developments, but also taking advantage of various scales of institutional networking among the central and local governments, quasi-governmental institutions, and Chaebols, across the state. Traditionally, scale has been regarded as an analytical spatial unit or category. However, scale can be seen as means of inclusion(and exclusion) and legitimation. Choosing institutions to include or exclude cannot be separated from the choices and range of spatial scale, and is closely connected to 'scale spatiality of politics.' Facilitating different forms of 'scales of regulation,' the Korean central government included Chaebols and upper- and middle-income groups for the legitimization of housing projects, but excluded local-scale grassroots organizations and unprivileged social groups as decision-makers.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.666-673
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• 2020

The purpose of this study was to investigate the relationship between dental decision factors and dental service satisfaction of the high school students. The study participants consisted of 300 high school students in some regions. A total of 288 were used for the final analysis, except 12 with insufficient responses. The data was analyzed by using SPSS 18.0 program. According to general characteristics, if there was no scaling experience, orthodontic treatment, high satisfaction with school life, the higher the subjective oral health status, the higher the satisfaction of the dental hospital. Hospital decision factors according to the general characteristics of the subjects most frequently answered that employee service satisfaction was important. As a result of testing the correlation between hospital decision factors and medical service satisfaction, there was a significant positive correlation between medical service satisfaction, such as facility, recommendation of others, use procedures, service adequacy, employee service satisfaction. As a factor influencing dental hospital satisfaction, subjective oral health was shown as a good criterion, and usage procedures and staff service satisfaction showed positive relevance. Continuous trust builds up is important to improve patient satisfaction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.43-53
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• 2006

As wireless network technology has advanced, demands for multimedia contents through mobile environment have tendered to upward. Since network situation is changing every moment and types of user terminals are diverse, it is difficult for a content provider to consider network situation and type of user terminal to provide multimedia contents. As one solution, transcoding techniques have been proposed, but those have much complexity. In this paper, in order to reduce computational complexity, we propose a fast mode decision using input modes, motion vectors, and residual energies which are obtained from input bitstream for 2:1 down-scaling spatial transcoding application. The proposed method reduces processing time in mode decision by restricting possible mode types based on input information. Experimental results show that the proposed method achieves about 2.66 times improvement in encoding time compared to the normal encoding process while the PSNR is degraded by about 0.04dB, and bit-rate is increased by 1.6%.

• The Journal of Information Technology and Database
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• v.6 no.2
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• pp.115-130
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• 1999

The price structure of housing market varies depending upon market price policy rather than low or high price policy because of IMF. The object of this study is to develop an analysis system for analyzing housing market and its demand. The analysis system consists of four major categories: macro index analysis, market decision analysis, housing market analysis, and consumer analysis. We model each category by using a variety of techniques such as generalized linear model, categorical analysis, bubble analysis, drill-down analysis, price sensitivity meter analysis, optimum price index analysis, profit index measurement analysis, correspondence analysis, conjoint analysis, and multidimensional scaling analysis. Seoul apartment data is analyzed to demonstrate the practical usefulness of the system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.264-267
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• 1998

We are dealing with the preliminary diagnosis from the information of headache interview chart. We quantify the qualitative information based on the interview chart by dual scaling. Prototype of fuzzy diagnostic sets and the neural linear regression methods are established with these quantified data, These new methods can be used to classify new patient's tone of diseases with certain degrees of belief and its concerned symptoms. We call these procedures as neural Fuzzy Differential Diagnosis of Headache (NFDDH-1). Also we investigate three measures to medical diagnosis, where relations between symptoms and diseases are described by intutionistic fuzzy set (IFS) data. Two measures are described by nin-max and max-min IFS operators, respectively. Another measure is the similarity degree, i.e., IFS distance between patient's symptoms and prototypes of diseases. We consider some reasonable criteria for three measures in order to determine the label of headache, We will establish hree measures in NFDDH-2 and combine two packages as NFDDH

• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.810-813
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• 2004

Air void systems in hardened concrete has an important influence on concrete durability such as freeze-thaw resistance, water permeability, surface scaling resistance, and etc. Linear traverse method and point count method described at ASTM have been widely used to estimate the air void system in hardened concrete. These methods, however, are rarely used at present, because they require many efforts, are time consuming works, depend on each person's decision, and are not repeatable. Thus, new image analysis method using microscope and computer processes has been approached for analyzing air void system in hardened concrete. However, it is just in initial step. The purposes of this study were to develope an effective and reliable image analysis technique for estimating air void system in hardened concrete. The developed technique was proved to be accurate, reasonable and repeatable.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.225-242
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• 2008

PM (Inconsistency Pattern Modeling) is a hybrid supervised learning technique using the inconsistence pattern of input variables in mining data sets. The IPM tries to improve prediction accuracy by combining more than two different supervised learning methods. The previous related studies have shown that the IPM was superior to the single usage of an existing supervised learning methods such as neural networks, decision tree induction, logistic regression and so on, and it was also superior to the existing combined model methods such as Bagging, Boosting, and Stacking. The objectives of this paper is explore the characteristics of the IPM. To understand characteristics of the IPM, three experiments were performed. In these experiments, there are high performance improvements when the prediction inconsistency ratio between two different supervised learning techniques is high and the distance among supervised learning methods on MDS (Multi-Dimensional Scaling) map is long.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.73-74
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• 2021

This paper presents a scheme to downscale the patches in geometry atlas based upon its contents for MPEG Immersive Video (MIV). In proposed scheme, the geometric contents of a patch is analyzed across the intra period, and a decision is made, whether to downscale a patch or not. The patches containing homogeneous information is downscaled by half, while the patches having salient information about the object such as edges are retained. Experimental results show that the bitrate saving is achieved by incorporating the patch level downscaling.