• Journal of Environmental Impact Assessment
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• v.18 no.1
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• pp.31-39
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• 2009

A lot of data which are used in environment analysis of air pollution have characteristics that are distributed continuously in space. In this point, the collected data value such as precipitation, temperature, altitude, pollution density, PM10 have spatial aspect. When geostatistical data analysis are needed, acquisition of the value in every point is the best way, however, it is impossible because of the costs and time. Therefore, it is necessary to estimate the unknown values at unsampled locations based on observations. In this study, spatial interpolation method such as local trend surface model, IDW(inverse distance weighted), RBF(radial basis function), Kriging were applied to PM10 annual average concentration of Seoul in 2005 and the accuracy was evaluated. For evaluation of interpolation accuracy, range of estimated value, RMSE, average error were analyzed with observation data. The Kriging and RBF methods had the higher accuracy than others.

• Journal of Biosystems Engineering
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• v.26 no.4
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• pp.363-370
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• 2001

This study intended to estimate the willingness-to-pay amount by farmers for the automatic guidance technology of Combine. Contingent Valuation Method was employed for this estimation using survey data from 65 Combine using farmers. Based on the dichotomous choice model, farmers’willingness-to-pay for the automatic guidance technology was ranged from ￦4,772,000(median) to ￦5,268,000(mean). The estimated willingness-to-pay by the for the new technology was approximately one quarter of the average value based on the willingness-to-pay for the new technology was approximately one quarter of the average value of Combine in sample farms. This implies that there is an economic rationals for developing the new technology as long as it will be available with the cost less than the amount of estimated willingness-to-pay.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.4
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• pp.651-662
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• 1995

The purpose of this study was 1) to find out the benefits sought factors of jeans and to segment the consumer market 2) to analyze Purchase behavior, brand loyalty, and demo- graphic characteristics of benefit segments. The subjects were 350 male and female university students who have purchased at least one of the nine jeans brands selected for this study. For statistical analysis, reliability test, percentage, factor analysis, cluster analysis, x2-test, and analysis of variance were used. The results of this study were as follows; 1. Benefits sought by consumer were found to include four different factors-brand value, individuality, fashionability, and practicality. 2. As a result of subdividing the consumers, three distinctive groups were formed on the basis of benefit factors-individuality.fashion oriented group, brand value oriented group, and practicality oriented group. 3. Brand value oriented group rated the highest in all of following variables number of jeans possessed and purchased annually, brand loyalty, average household income, average monthly allowences, and amount of money spent in purchasing clothes in each season. Individuality - fashion oriented group rated the second.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.125-130
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• 2022

In modern society, as many data are used for research or commercial purposes, the value of data is gradually increasing. In related fields, research is being actively conducted to collect valuable data, but it is difficult to collect proper data because the value of collection is determined according to the performance of existing sensors. To solve this problem, a method to effectively reduce noise has been proposed, but there is a point in which performance is degraded due to damage caused by noise. In this paper, a device capable of collecting time series data was designed to correct such data noise, and a correction technique was performed by giving an error value based on the representatively collected ultrafine dust data, and then comparing before and after Compare performance. For the correction method, Kalman, LPF, Savitzky-Golay, and Moving Average filter were used. Savitzky-Golay filter and Moving Average Filter showed excellent correction rate as an experiment. Through this, the performance of the sensor can be supplemented and it is expected that data can be effectively collected.

• Tunnel and Underground Space
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• v.25 no.2
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• pp.199-209
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• 2015

The rebound hardness test using the SilverSchmidt hammer was performed for diorite, granodiorite, and andesite exposed around the King Sejong Station, Barton peninsula. Then, the R-value and uniaxial compressive strength (UCS) of these rocks were estimated from the Q-values which were obtained from the SilverSchmidt hammer. The Q-value of diorite was distributed in the range from 67.0 to 89.5, granodiorite of the range from 57.5 to 89.0, and andesite of the range from 58.0 to 76.5. The average Q-values of diorite, granodiorite, and andesite were 76.0, 72.0, and 67.0, respectively. The converted UCS of diorite was distributed in the range from 118 to 195 MPa, granodiorite of the range from 91 to 193 MPa, and andesite of the range from 92 to 148 MPa. The average UCS of diorite, granodiorite, and andesite were 147, 136, and 117 MPa, respectively. The converted R-value of diorite was distributed in the range from 53.0 to 72.2, granodiorite of the range from 45.4 to 71.8, and andesite of the range from 45.8 to 60.9. The average Q-values of diorite, granodiorite, and andesite were 60.0, 58.0, and 53.0, respectively. The R-value was represented approximately 20% lower than the Q-value. In conclusion, it will be possibile that the R-value and UCS of rocks under the extreme area from the SilverSchmidt Q-value are evaluated.

• Journal of radiological science and technology
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• v.32 no.3
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• pp.313-323
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• 2009

Diffusion-weighted imaging (DWI) has been demonstrated to be a practical method for the diagnosis of various brain diseases such as acute infarction, brain tumor, and white matter disease. In this study, we used two techniques to examine the average signal intensity (SI) and apparent diffusion coefficient (ADC) of the brains of patients who ranged in age from 10 to 60 years. Our results indicated that the average SI was the highest in amygdala (as derived from DWI), whereas that in the cerebrospinal fluid was the lowest. The average ADC was the highest in the cerebrospinal fluid, whereas the lowest measurement was derived from the pons. The average SI and ADC were higher in $T_2^*$-DW-EPI than in FLAIR-DW-EPI. The higher the b-value, the smaller the average difference in both imaging techniques; the lower the b-value, the greater the average difference. Also, comparative analysis of the brains of patients who had experienced cerebral infarction showed no distinct lesion in the general MR image over time. However, there was a high SI in apparent weighted images. Analysis of other brain diseases (e.g., bleeding, acute, subacute, chronic infarction) indicated SI variance in accordance with characteristics of the two techniques. The higher the SI, the lower the ADC. Taken together, the value of SI and ADC in accordance with frequently occurring areas and various brain disease varies based on the b-value and imaging technique. Because they provide additional useful information in the diagnosis and treatment of patients with various brain diseases through signal recognition, the proper imaging technique and b-value are important for the detection and interpretation of subacute stroke and other brain diseases.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.73-76
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• 1999

In this paper, we propose a new design of turbo decoder. It contains the simple additional unit which automatically decides the number of the iteration by detecting of the reliability value as threshold value. We investigate the relationship between the reliability value and the number of the iteration. We find the optimal threshold value without noticeable loss in performance. As a results of the simulation, it reduces the average number of the iteration compared with the conventional turbo decoder.

• Journal of Agricultural Extension & Community Development
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• v.17 no.4
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• pp.897-918
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• 2010

This paper researches conservative value evaluation of rural tourism villages with "CVM(Contingent Valuation Method)" focusing on visitor to offer the guide for preservation and management in landscape of rural tourism villages based on critical consciousness for conservation and utilization by regional development. The option value is 37,624won(36.7%), the bequest value is 34,856won(34.0%), existence value is 30,073 won(29.3%), and overall average willingness to pay of conservation value is 102,517won(100.0%) for conservative value of sesim-village in Kyung-Ju. The results show that landscape of rural tourism villages has great value historically and culturally. In conclusion, it suggested that planners and staffs of rural tourism villages recognize that it is positively necessary to be considered not only multiple landscape index but also conservation policy in process of development planning in rural tourism villages.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.508-514
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• 2021

In this paper, to propose a classifier based on supervised learning, three types of fuzzy membership functions that determine the membership of each feature of classification data are proposed. In addition, the possibility of improving the classifier performance was suggested by using the average value calculation method used in the process of deriving the classification result using the average value of the membership degrees for each feature, not by using a simple arithmetic average, but by using a weighted average using various weights. To experiment with the proposed methods, three standard data sets were used: Iris, Ecoli, and Yeast. As a result of the experiment, it was confirmed that evenly excellent classification performance can be obtained for data sets of different characteristics. It was confirmed that better classification performance is possible through improvement of fuzzy membership functions and the weighted average methods.

• Journal of Soil and Groundwater Environment
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• v.22 no.5
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• pp.13-22
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• 2017

Accurate assessment of agricultural groundwater usage is an essential task to cope with drought that occurs irregularly in time and location. In this study, the agricultural groundwater usage was calculated in nationwide public wells (1,386 bedrock wells) during 5-year period (2010-2014) by using electric power consumption and well specification data. National average of agricultural groundwater usage per each well was estimated as $66.2m^3/day$, corresponding to 21.6% of total permitted volume of groundwater in each well. Chungcheong Nam-do had the highest usage with 38-55.6%. The value increased to 58.1% when the total permitted volume was based upon the supply standard against drought, and the value reached 100% in Chungcheong Nam-do. In Ganghwa distirct that suffered from severe drought in recent years, the average groundwater usage was 61.4%. In 2014, when the drought was the most severe with 45% precipitation of the average annual rainfall, the nationwide usage was turned out to be 25.6%, indicating about 4% higher than average agricultural groundwater usage 21.6%. Therefore, the quantitative assessment of groundwater usage in this study signifies that adequate use of groundwater is crucial to cope with agricultural drought.