• The Research Journal of the Costume Culture
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• v.1 no.1
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• pp.95-111
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• 1993

The purpose of this study was to find out the relationship between the conspicuous consumption of clothing and status inconsistency. For this study, two kinds of guestionnaires were conducted to collect data for the conspicuous consumption variables of clothing and status inconsistency variables. Status inconsistency was measured by educational levels and occupational levels of married women and their husbands, the family′s total income. Status inconsistency was defined by the inconsistency among married women′s and their husband′s educational levels, family′s total income, their husband′s occupational levels. In order to investigate status inconsistency effects, when their investment (education0 are lower than their rewards (income or occupation) they are classified as over-rewarded inconsistency, while their investments is higher than their rewards, as under-rewarded inconsistency, and their investments are equal to their rewards, as consistency. The conspicuous consumption variables in clothing were consisted of seven variables; Brand-oriented, Fashion-oriented, Leisure-showing, Leisure-oriented purchase of clothing and Excessive expenditure to purchase of clothing, purchase of Imitation clothing in well-known brand and purchase of Expensive clothing from abroad. Data were obtained fro m436 housewives living in Kwang-ju are a and analyzed by F-test, Pearson′s Correlation and Frequency. The results of this study were follow; When the subjects were divided into three group according to their status inconsistency type, there were significant differences (P<.05 or P<.01) among groups of conspicuous consumption variables in clothing. The groups of "under pivileged" status inconsistency type and "over rewarded" status inconsistency type were tend to show conspicuous consumption in clothing than other type of status inconsistency groups.

• 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.

• ETRI Journal
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• v.33 no.4
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• pp.506-516
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• 2011

In this paper, we develop a registration method to eliminate the geometric inconsistency between the stereo-images and light detection and ranging (LIDAR) data obtained by an airborne multisensor system. This method consists of three steps: registration primitive extraction, correspondence establishment, and exterior orientation parameter (EOP) adjustment. As the primitives, we employ object points and linked edges from the stereo-images and planar patches and intersection edges from the LIDAR data. After extracting these primitives, we establish the correspondence between them, being classified into vertical and horizontal groups. These corresponding pairs are simultaneously incorporated as stochastic constraints into aerial triangulation based on the bundle block adjustment. Finally, the EOPs of the images are adjusted to minimize the inconsistency. The results from the application of our method to real data demonstrate that the inconsistency between both data sets is significantly reduced from the range of 0.5 m to 2 m to less than 0.05 m. Hence, the results show that the proposed method is useful for the data fusion of aerial images and LIDAR data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.75-80
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• 2001

Rule inconsistency is an important issue that is needed to be addressed while designing efficient and optimal fuzzy rule bases. Automatic generation of fuzzy rules from data sets, using machine learning techniques, can generate a significant number of redundant and inconsistent rules. In this study we have shown that it is possible to provide a systematic approach to understand the fuzzy rule inconsistency problem by using the proposed measure called the Commonality measure. Apart from introducing this measure, this paper describes an algorithm to optimize a fuzzy rule base using it. The optimization procedure performs elimination of redundant and/or inconsistent fuzzy rules from a rule base.

• Journal of the Korean Home Economics Association
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• v.37 no.1
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• pp.29-44
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• 1999

The objectives of this study are (1) to identify sub-areas of the pro-environmental behavior, (2) to examine the level of the pro-environmental attitude and behavior, (3) to examine the degree of inconsistency between attitude and behavior, and (4) to investigate the reasons of the inconsistency. Data was collected from the questionnares with 299 married men and 378 married women and the deep interviews with 10 married women. The major findings are follows : (1) The pro-environmental behavior can be classified into 2 sub-areas : social-oriented area and individual-oriented area. (2) The level of pro-environmental attitude and behavior in the social-oriented area is lower than those in individual-oriented area. (3) The attitude-behavior inconsistency in the social-oriented sub-area is stronger than that in the individual-oriented sub-area. (4) The reasons of the pro-environmental attitude-behavior inconsistency are the lack of the sincere environmental consciousness and the existence of the pro-environmental behavior restriction factors.

• Journal of Fisheries and Marine Sciences Education
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• v.16 no.1
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• pp.60-68
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• 2004

This study was conducted to identify parenting factors relating to attachment style. Subjects were 418 college students. Participants completed 1) a brief demographic data questionnaires, 2) Parenting Behavior Inventory and 3) Relationship Questionnaire. Data were analyzed using discriminant analysis for the total sample and by gender. For men, affection, neglect, monitoring, intrusiveness, reasoning, inconsistency and physical abuse of both father and mother are important parenting behaviors that contribute to discriminating secure attachment style from insecure attachment style. For women, neglect, affection, reasoning, inconsistency, monitoring and physical abuse of father and affection, reasoning, neglect, inconsistency and monitoring of mother are important parenting behaviors that contribute to discriminating secure attachment style from insecure attachment style. The implications of this study for theory and practice were discussed and recommendations for future research were made.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.57-65
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• 2008

This research is aimed at offering a fundamental data for the adjustment of cadastral inconsistency of administrative boundary areas from this time onward by analyzing actual conditions of cadastral inconsistency at the study areas by the use of digital topographic map and digital cadastral map of si-gun-gu boundary area. As a result of examining the actual condition of cadastral inconsistency at the surveyed areas, the extent of cadastral inconsistency of the neighboring administrative boundary areas was assessed as ${\pm}3.15m$ of RMSE on X coordinates and also assessed as ${\pm}2.85\;m$ of RMSE on Y coordinates; in addition, RMSE of the neighboring district of the administrative boundary areas on X coordinates was assessed as ${\pm}1.33\;m$, and ${\pm}0.75\;m$ of RMSE on Y coordinates respectively-thus, this research could suggest the fact that there has arisen a lot of cadastral inconsistency areas at administrative boundary areas.

• Spatial Information Research
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• v.8 no.1
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• pp.1-14
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• 2000

Zoning data such as national land use planning map, urban land use planning map, agricultural promotion zoning ap, forest land zoning map has a relationship each other in law and spatial context. But difficulties in data share and the lack of accuracy of manual work makes serious inconsistence son zoning data relationship. This causes many trial and error in land use. For resolving this problem the data modellingmethod is presented as a technical solution.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.530-531
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• 2021

In this paper, I proposed a technique for identifying discrepancies between data input in the IoT sensor environment. The proposed technique can manage numerically input sensor data so that it can be applied to actual field problems. The proposed technique can detect when contradictory data is input from two or more sensors in an actual IoT sensor environment, and through this, it can be developed into a method that can identify and resolve sensor failure or intentional data disturbance.

• Journal of the Korean Home Economics Association
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• v.35 no.4
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• pp.1-14
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• 1997

The purpose of this study was to investigate the effects of consumer's status type (status consistency and status inconsistency) on clothing expenditures. Data were obtained from Urban Household Economy Survey published by the National Statistical Office. Multiple regression analyses of variance and Scheffe tests were4 utilized in this study. The effect of the status inconsistency was categorized by three variables such as education occupation and income levels of households. The overprivileged status group which had higher levels of income than the levels of occupation of education spent most on clothing whereas the underprivileged status group which had higher levels of income than the levels of occupation of education spent least on clothing. This study showed that there were significant differences in clothing expenditures among status groups classified by levels of income and education or by levels of income and occupation. Among status group classified by levels of education and income there was a significant difference in clothing expenditures between overprivileged status group and underprivileged status group. In conclusion income has the strongest effect on the clothing expenditures. The results of study can help to understand consumer buying behavior and also give insights of marketing strategy in the apparel industry.