• 복식문화연구
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• 제1권1호
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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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• 제15권1호
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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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• 제33권4호
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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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• 제1권1호
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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.

• 대한가정학회지
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• 제37권1호
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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.

• 수산해양교육연구
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• 제16권1호
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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.

• 대한공간정보학회지
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• 제16권1호
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• pp.57-65
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• 2008

본 연구에서는 시 군 구 경계지역의 지적도면 전산화 데이터와 현황을 참조할 수 있는 데이터를 이용하여 대상 지역에서의 지적불부합지 실태를 분석하여 봄으로써 향후 행정경계 지역에서의 지적불부합지 정리를 위한 기초자료를 제공하고자 하였다. 조사지역의 지적불부합 실태를 조사한 결과, 행정경계 주변지역의 지적불부합 정도는 X좌표의 RMSE가 ${\pm}3.15m$, Y좌표의 RMSE가 ${\pm}2.85m$로 산출되었고, 행정경계 비주변 지역은 X좌표의 RMSE가 ${\pm}1.33m$, Y좌표의 RMSE가 ${\pm}0.75m$로 산출되어 행정구역 경계지역에서 지적불부합지가 많이 발생되고 있음을 확인 할 수 있었다.

• Spatial Information Research
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• 제8권1호
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• pp.1-14
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• 2000

국토이용계획도, 도시계획도, 농업진흥지역도, 산지이용구분도 등 용도지역·지구 자료는 법적·공간적 특성으로 자료간 연관성을 가지고 있다. 그러나 부처별·부서별 제도운용에 따른 자료공유의 어려움, 수작업체계에 의한 용도지역·지구 경계선의 저확성 한P 등으로 자료간의 관계가 일관성이 결여되어 토지 이용에 많은 문제가 발생하고 있다. 이 연구에서는 GIS의 중첩기법을 이용하여 용도지역·지구 자료간 불부합 실태와 원인을 분석하고, 이러한 문제를 해결할 수 있는 방안으로서 자료간 연관성을 고려한 데이터모델링 방안을 제시하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.530-531
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• 2021

이 논문에서는 IoT 센서 환경에서 입력되는 데이터들 간의 불일치를 파악하기 위한 기법을 제안한다. 제안된 기법은 실제 현장 문제에 적용할 수 있도록 수치적으로 입력되는 센서 데이터들을 관리할 수 있다. 제안한 기법은 실제 IoT 센서 환경에서 2개 이상의 센서에서 모순된 데이터가 입력되는 경우를 감지할 수 있으며, 이를 통해 센서의 고장 또는 의도적인 데이터 교란을 파악하여 해결할 수 있는 방안으로 발전시킬 수 있다.

• 대한가정학회지
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• 제35권4호
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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.