• The Journal of Fisheries Business Administration
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• v.45 no.1
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• pp.63-77
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• 2014

This study is to estimate the recent changes in total factor productivity of 15 Korean adjacent water fisheries based on Malmquist productivity indices. The study adopted both input and output oriented productivity measures utilizing a hyperbola distance function. In addition to this point, the study also calculated the 95% confidence interval for the various components of the productivities in order to access the statistical significance of estimates using 2000 times of re-sampling process through the smoothed bootstraping. The results of the study showed us that there was 18% reduction in the overall total factor productivity during the study period from 2007 to 2011, which turned out to be 5% of annual decrease in productivity. The study found that the main reason of this decrease in total productivity is about 22% downward shift of a fisheries production function due to recent conditions of a devastated fishing ground. When we evaluated the statistical significance of changes in technical efficiency combining both pure technical and scale efficiency based on the 95% confidence intervals, we could not find any evidence of changes in those components of total factor productivity. When we accessed the productivity of the each of 15 adjacent water fisheries methods, only the large danish seine fisheries showed us about 7% increase in productivity. Even though the large trawling and the large tow-boat trawling revealed no changes in productivity, all of the other 12 fisheries suffered the decreases in productivities.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1109-1114
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• 2015

This paper presents an improved learning-based visual inspection method for auto parts inspection in severe lighting changes. Automobile sunroof frames are produced automatically by robots in most production lines. In the sunroof frame manufacturing process, there is a quality problem with some parts such as volts are missed. Instead of manual sampling inspection using some mechanical jig instruments, a learning-based machine vision system was proposed in the previous research[1]. But, in applying the actual sunroof frame production process, the inspection accuracy of the proposed vision system is much lowered because of severe illumination changes. In order to overcome this capricious environment, some selective feature vectors and cascade classifiers are used for each auto parts. And we are able to improve the inspection accuracy through the re-learning concept for the misclassified data. The effectiveness of the proposed visual inspection method is verified through sufficient experiments in a real sunroof production line.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.78-87
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• 2012

In this paper, we address the tracking problem caused by camera motion and rolling shutter effects associated with CMOS sensors in consumer handheld cameras, such as mobile cameras, digital cameras, and digital camcorders. A modified particle filtering method is proposed for simultaneously tracking objects and compensating for the effects of camera motion. The proposed method uses an elastic registration algorithm (ER) that considers the global affine motion as well as the brightness and contrast between images, assuming that camera motion results in an affine transform of the image between two successive frames. By assuming that the camera motion is modeled globally by an affine transform, only the global affine model instead of the local model was considered. Only the brightness parameter was used in intensity variation. The contrast parameters used in the original ER algorithm were ignored because the change in illumination is small enough between temporally adjacent frames. The proposed particle filtering consists of the following four steps: (i) prediction step, (ii) compensating prediction state error based on camera motion estimation, (iii) update step and (iv) re-sampling step. A larger number of particles are needed when camera motion generates a prediction state error of an object at the prediction step. The proposed method robustly tracks the object of interest by compensating for the prediction state error using the affine motion model estimated from ER. Experimental results show that the proposed method outperforms the conventional particle filter, and can track moving objects robustly in consumer handheld imaging devices.

• Journal of Korean Society on Water Environment
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• v.35 no.6
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• pp.539-549
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• 2019

In 2016, Benthic Macroinvertebrates Streambed Index (BMSI) was proposed as an index to evaluate streams as benthic macroinvertebrate depending on the substrate type of streambed. However, orignal BMSI were selected without consideration of water quality. Analyzes without water quality do not constitute biological indices based solely on the substrate type of streambed. Therefore, in this study, the indicator value was improvement in consideration of water quality, and the distribution characteristics of benthic macroinvertebrates according to the substrate type of streambed were analyzed under relatively equal water quality conditions. We surveyed 20,155 sampling units in Korea from 2008 to 2018, and we re-estimated each lithophility of 191 taxa. As a result of estimating the streambed of each newly lithophilic value classification group considering the water quality, it was different from the original lithophilic value. Representative integer lithophilic values were newly calculated from 126 taxa among the 191 index taxa used in the analysis. The correlation between new constructed BMSI and community structure was compared and analyzed. It showed extreamely significance (p<0.001) in the dominance index, diversity index, abundance index, and evenness index of the community structure. Diversity index, abundance index, and evenness index showed positive correlation, and dominance index showed negative correlation. The correlation coefficient (r) was the highest in the richness index of about 0.664.

• Health Policy and Management
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• v.14 no.2
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• pp.17-33
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• 2004

The present study attempts to examine the progressivity of health care financial sources based on the income approach, for which it decomposes redistributive effects into vertical, horizontal, and re-ranking components. The study data include Korean Household Expenditure Survey (2000) conducted every 5 year by Korea National Statistical Office. The data were sampled from the national population by the multistage probabilistic sampling method, and amounts to 23,270 households. For the better application of the income approach, the study employs household total expenditure in Korea instead of total income, because the former data source is more reliable and less fluctuated over time. Progressivity of health care financing was measured by Kakwani index. Aronson's decomposition equation was used in case of the analysis where differential treatment of health care expenditure needs to be considered. Despite the progressivity of Korea's governmental contributions, total expenditure of health care showed regressive pattern, which may largely be attributable to the higher regressivity in out-of-pocket money. With the result of negative Kakwani index, differential treatment increased income redistribution biased for better-off. It is worth to note that social insurance displays not only negative Kakwani index, but also horizontal inequality, suggesting that the first step of health care financing reform should be the revision of social insurance premium rates toward effective and equable way.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.45-53
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• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• Fashion & Textile Research Journal
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• v.13 no.2
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• pp.173-185
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• 2011

This study aimed to clarify the difference between consumers and hands-on staff in evaluation of the attributes importance of asset evaluation attributes and the relationship between difference from consumers and hands-on staff in evaluation of the attributes and the performance. Subjects for the quantitative research, quota sampling was adopted in the areas where the subject brands were in place, and 452 questionnaires (141 of hands-on staff, 311 of consumers) were analyzed. The results were as follows; 1. The factors that hands-on staff and consumers regarded as most important as to asset evaluation attributes of department store-exclusive importation brands included preference and product quality in the order, and then image, recognition, reliability, and country of origin in the case of hands-on staff, and reliability, image, recognition, and country of origin in the case of consumers in the order. 2. As a result of examining the effect of the difference between hands-on staff and consumers regarding exclusive importation brands(GAP, ZARA) of certain department stores on business achievement and consumer attitude, it turned out that the smaller the difference between the two groups with regard to evaluation, the higher the business achievement and consumer attitude.

• Proceedings of the Korean Association for Survey Research Conference
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• 2003.06a
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• pp.34-41
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• 2003

In many cases, the measurement error variances may be functions of the unknown true values or related covariates. This paper develops estimators of the parameters of a linear measurement error variance function based on wi thin-unit sample variaoces. This paper devotes to: (1) define measurement error scale factor $\delta$: (2) develop estimators of the parameters of the 1inear measurement error variance function under stratified multistage sampling design and small error conditions; (3) use propensity methods to adjust survey weights to account for possible selection effects at the replicate level. The proposed methods are applied to medical examination data from the U S Third National Health and Nutrition Examination Survey(NHANES III)

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.141-148
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• 2009

Recently there have been many research efforts focused on imbalanced data classification problems, since they are pervasive but hard to be solved. Approaches to the imbalanced data problems can be categorized into data level approach using re-sampling, algorithmic level one using cost functions, and ensembles of basic classifiers for performance improvement. As an algorithmic level approach, this paper proposes to use multilayer perceptrons with higher-order error functions. The error functions intensify the training of minority class patterns and weaken the training of majority class patterns. Mammography and thyroid data-sets are used to verify the superiority of the proposed method over the other methods such as mean-squared error, two-phase, and threshold moving methods.

• Journal of Environmental Health Sciences
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• v.21 no.4
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• pp.63-74
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• 1995

The objective of this study were to identify the state of re. cognition and attitude of residents in Seoul city about air environment and to identify factors affecting attitude toward air environment. Study object was residents in Seoul city sampled by multistage random proportional sampling. Sample size was 0.0067%(500 persons) of total residents in Seoul city. The results were divided into two parts: (1) descriptive results of recognition and attitude toward air environment, (2) results of factor analysis to classify categories of attitudes toward air environment and regression analysis to identify factors affecting attitude toward air environment. Most of resident in Seoul city recognized that air environment in Seoul city was highly polluted and was not satisfactory. Experience of damage of air pollution was reported in about 70% of residents in Seoul city. More than 60% of residents in Seoul city had concern about air environment. Attitude toward air environment were classified into four categories using factor analysis: Necessity of intervention of local government for air environment conservation, Participation of residents and enterprises for air environment conservation, Optimistic attitude about air pollution, Preference of economy. Factors affecting the above attitudes were knowledge about air pollution, knowledge about policies and institutions related air environment conservation, concern about air environment, educational level, subjective assessment of air environment, sex, marital status. In conclusion this study suggested providing information of air environment in Seoul city to the residents and to educating residents for making positive attitude about air environment conservation.