• The Research Journal of the Costume Culture
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• v.2 no.1
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• pp.167-186
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• 1994

The purpose of his study is to investigate the relationship between the business cycle and the fashion of silhouette from 1956 to 1992. Correlation analysis an regression analysis were used to investigate the relation of them. In this study, the coincident composite index was used as business cycle and change of skirt in length and width, collar and pants in width wee thoroughly checked through graphs and photographs. The results of analysis are as follows. 1. When the economy is to ascend, the skirts are short and narrow. On the country, when the economy is descend, they are long and wide. 2. The business cycle gives influence on skirts line and with, that is, about 18%, 33% of total changes. 3. In change of fashion, skirts length and width had significant positive correlation and they showed a tendency to move together. On the other hand, the change of collar and patterns in width have no connection with business fluctuation. 4. The change of fashion is affected by the movement of itself. According to analysis that includes the trend of skirts, about 50%, and 35% of changes in skirts length and width were decided by them,. and about 52% and 35% of change in collar and patterns width were decided by them.

• Journal of Korean Clinical Nursing Research
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• v.16 no.3
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• pp.111-121
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• 2010

Purpose: This meta-analysis was aimed to investigate the evidence of proper period of the ventilator circuit change using existing research. Methods: For this study, 14 published studies between 1995 and 2010 were tested by Macaskill, Funnel Plot, the Odds Ratio of DerSimonian and Laird, Fisher and Liptak analysis. Results: There were no publication bias found in the subjects. The results of the meta-analysis demonstrated no statistically significant differences were observed in neither the Odds Ratio (OR=1.18, 95% CI=0.94-1.47) of the frequency of ventilator-associated pneumonia and the mortality based on the period of the ventilator circuit change (Fisher p=.332, Liptak p=.498), nor the ventilation duration of ventilator (Fisher p=.843, Liptak p=.506), and the hospital length of stay (Fisher p=.254, Liptak p=.480). Conclusion: In order to present more concrete guidelines on the period of the ventilator circuit change, further research is warranted to thoroughly control confounding variables which related to the periods of the ventilator circuit change.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1075-1087
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• 2017

In this study, we tried to utilize results of the change detection analysis for satellite images as the basis for updating the land cover map. The Sequential Spectral Change Vector Analysis ($S^2CVA$) was applied to multi-temporal multispectral satellite imagery in order to extract changed areas, efficiently. Especially, we minimized the false alarm rate of unsupervised change detection due to the seasonal variation using the direction information in $S^2CVA$. The binary image, which is the result of unsupervised change detection, was integrated with the existing land cover map using the zonal statistics. And then, object-based analysis was performed to determine the changed area. In the experiment using PlanetScope data and the land cover map of the Ministry of Environment, the change areas within the existing land cover map could be detected efficiently.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.3
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• pp.270-280
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• 2014

The objective of this research is to quantitatively valuate the economic value of analysis model related to climate change mitigation and adaptation. Due to the fact that the subject of this research, which is the Korean climate change mitigation and adaptation model, has not been actualized, a conjoint analysis applying stated preference data has utilized. As results, among the many attributes considered in this research, the value of the attribute related to reflecting Korea's current situation is analyzed to be largest in both greenhouse gas (GHG) mitigation model and climate change adaptation model. Additionally, if all the considered functional aspects are assumed to be feasible, the economic value of the Korean GHG mitigation model is assumed to be 60.3 billion Korean won(KRW) and the Korean climate change adaptation model is assumed to be 51 billion KRW.

• Journal of Auto-vehicle Safety Association
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• v.10 no.1
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• pp.38-44
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• 2018

This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.51-58
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• 2019

Temporal analysis is very useful and important for digital forensics for reconstructing the timeline of digital events. Forgery of a file's timestamp can lead to inconsistencies in the overall temporal relationship, making it difficult to analyze the timeline in reconstructing actions or events and the results of the analysis might not be reliable. The purpose of the timestamp change is to hide the data in a steganographic way, and the other purpose is for anti-forensics. In both cases, the time stamp change tools are requested to use. In this paper, we propose a classification method based on the behavior of the timestamp change tools. The timestamp change tools are categorized three types according to patterns of the changed timestamps after using the tools. By analyzing the changed timestamps, it can be decided what kind of tool is used. And we show that the three types of the patterns are closely related to API functions which are used to develop the tools.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.33-47
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• 2007

The requirements have been changed during development progresses, since it is impossible to define all of software requirements. These requirements change leads to mistakes because the developers cannot completely understand the software's structure and behavior, or they cannot discover all parts affected by a change. Requirement changes have to be managed and assessed to ensure that they are feasible, make economic sense and contribute to the business needs of the customer organization. We propose a feature-oriented requirements change management method to manage requirements change with value analysis and feature-oriented traceability links including intermediate catalysis using features. Our approach offers two contributions to the study of requirements change: (1) We define requirements change tree to make user requirements change request generalize by feature level. (2) We provide overall process such as change request normalization, change impact analysis, solution dealing with change request, change request implementation, change request evaluation. In addition, we especially present the results of a case study which is carried out in asset management portal system in details.

• Journal of Industrial Technology
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• v.35
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• pp.23-30
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• 2015

In recent, the various methods to predict the hydrological impacts due to climate change have been developed and applied. Especially, the variability of the meteorological factors such as rainfall, temperature, and evaporation can impact on the ecosystem in a basin. The variability caused by climate change on the meteorological factors can be divided by a gradual and abrupt change. Therefore, in this study, the gradual change is detected by simple linear regression and Mann-Kendall trend test. Also, the abrupt change is detected by Bayesian change point analysis. Finally, the result using these methods can identify the meteorological threats in the Cheongmicheon basin.

• Journal of Fashion Business
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• v.23 no.1
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• pp.116-126
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• 2019

The purpose of this study is to objectify the shape of curvature and average change rate of angular and arched eyebrow makeup. The data for the analysis were the final 336 pieces for the cosmetology students in the whole country. SPSS 20.0 program was used for the collected data, frequency analysis, factor analysis, reliability analysis, and crossover analysis were performed. First, the frequency of the average change rate of eyebrow makeup (angular and arcuate) was analyzed. As a result, the eyebrows suitable for the angled type showed the highest level of 'A-2' and the arched eyebrows had the highest level of 'B-2'. Second, to analyze the important factors of eyebrow makeup, frequency of eyebrows was the most important, followed by the inclination of eyebrows and eyebrow tail. Third, factor analysis and reliability analysis were conducted to examine each dimension of eyebrow makeup perception, and it was derived from three factors including acceptability, aggressiveness, and playability. Fourth, in order to analyze the difference of important factors in the form of the standard eyebrow makeup, the cross - analysis was performed with chi - square test, and it was confirmed that the angular eyebrow makeup showed the most objectivity when the average change rate was 0.29 and the curvature was 0.67. Fifth, arcuate eyebrow makeup showed the most objectivity when the average change rate was 0.57 and curvature was 0.56. The results of this analysis can be used as objective data of aesthetic criteria when designing the eyebrow shape.