• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.45-54
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• 2012

Location-based services with GPS positioning technology as a key technology, but recognizing the current location through satellite communication is not possible in an indoor location-aware technology, low-power short-range communication is primarily made of the study. Especially, as Chirp Spread Spectrum(CSS) based location-aware approach for low-power physical layer IEEE802.15.4a is selected as a standard, Ranging distance estimation techniques and data transfer speed enhancements have been more developed. It is known that the distance measured by CSS ranging has quite a lot of noise as well as its bias. However, the noise problem can be adjusted by modeling the non-zero mean noise value by a scaling factor which corresponds to the change of magnitude of a measured distance vector. In this paper, we propose a localization system using the CSS signal to measure distance for a mobile node taken a measurement of the exact coordinates. By applying the extended kalman filter and least mean squares method, the localization system is faster, more stable. Finally, we evaluate the reliability and accuracy of the proposed algorithm's performance by the experiment for the realization of localization system.

• Nuclear Engineering and Technology
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• v.21 no.1
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• pp.18-31
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• 1989

To analyze the impact of air pollution control on electricity generation cost, a computer program was developed. POGEN calculates levelized discounted power generation cost including additional air pollution control cost for coal power plant. Pollution subprogram calculates total capital and variable costs using governing equations for flue gas control. The costs are used as additional input for levelized discounted power generation cost subprogram. Pollution output for Rue Gas Desulphurization direct cost was verified using published cost data of well experienced industrialized countries. The power generation costs for the year 2001 were estimated by POGEN for three different regulatory scenarios imposed on coal power plant, and by levelized discounted power generation cost subprogram for nuclear power. Because of uncertainty expected in input variables for future plants, sensitivity and uncertainty analysis were made to check the importance and uncertainty propagation of the input variables using Latin Hypercube Sampling and Multiple Least Square method. Most sensitive parameter for levelized discounted power generation cost is discount rate for both nuclear and coal. The control cost for flue gas alone reaches additional 9-11 mills/kWh with standard deviation less than 1.3 mills/kWh. This cost will be nearly 20% of power generation cost and 40% of one GW capacity coal power plant investment cost. With 90% confidence, the generation cost of nuclear power plant will be 32.6-51.9 mills/kWh, and for the coal power plant it will be 45.5-50.5 mills/kWh. Nuclear is favorable with 95% confidence under stringent future regulatory requirement in Korea.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.5
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• pp.278-284
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• 2014

Water temperature due to climate change can be estimated using the air temperature because the air and water temperatures are closely related and the water temperatures have been widely used as the indicators of the environmental and ecological changes. It is highly necessary to estimate the frequency distribution of the air and water temperatures, for the climate change derives the change of the coastal water temperatures. In this study, the distribution function of the air temperatures is estimated by using the long-term coastal air temperature data sets in Korea. The candidate distribution function is the bi-modal distribution function used in the previous studies, such as Cho et al.(2003) on tidal elevation data and Jeong et al.(2013) on the coastal water temperature data. The parameters of the function are optimally estimated based on the least square method. It shows that the optimal parameters are highly correlated to the basic statistical informations, such as mean, standard deviation, and skewness coefficient. The RMS error of the parameter estimation using statistical information ranges is about 5 %. In addition, the bimodal distribution fits good to the overall frequency pattern of the air temperature. However, it can be regarded as the limitations that the distribution shows some mismatch with the rapid decreasing pattern in the high-temperature region and the some small peaks.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.6
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• pp.458-467
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• 2019

The purpose of this study is the suggestion of optimized parameters in OI (Optimal Interpolation) by experimental study. The observation of applying optimal interpolation is ADCP (Acoustic Doppler Current Profiler) data at the southwestern sea of Korea. FVCOM (Finite Volume Coastal Ocean Model) is used for the barotropic model. OI is to the estimation of the gain matrix by a minimum value between the background error covariance and the observation error covariance using the least square method. The scaling factor and correlation radius are very important parameters for OI. It is used to calculate the weight between observation data and model data in the model domain. The optimized parameters from the experiments were found by the Taylor diagram. Constantly each observation point requires optimizing each parameter for the best assimilation. Also, a high accuracy of numerical model means background error covariance is low and then it can decrease all of the parameters in OI. In conclusion, it is expected to have prepared the foundation for research for the selection of ocean observation points and the construction of ocean prediction systems in the future.

• Korean Journal of Community Nutrition
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• v.10 no.1
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• pp.101-110
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• 2005

This survey was carried out to obtain the information concerning nutritional status, including factors of food habits and nutrient intake of the long-lived elderly men and women living in Ganghwa-gun. In order to assess the quality of dietary intake among the elderly, a survey was conducted during December 2003 of 103 subjects who were over 85 years of age. Dietary nutrient intake data were obtained through the 24 hr recall method. Chi-square test and t-test were the main data analysis method. Their dietary habits such as three meals a day and a regular meal time have shown that they have generally good eating habits. Average daily calorie intake ($\%$ RDA) was 1233.2 kcal ($68.8\%$) for male and 1215.8 kcal ($75.8\%$) for female which were lower than the Recommended Dietary Allowances (RDA) for Koreans. Energy intake of females got closer to RDA than that of male. Protein intake was 49.3 g for male and 46.9 g for female (which was $82.3\%$ RDA for male and $85.1\%$ RDA for female) for elderly person, the proportion of animal protein to total protein intake were $45.2\%$ for male and $39.0\%$ for female. Average CPF ratio of energy intake for both male and female were 68.7 : 16.1 : 15.2 and 69.6 : 15.4 : 15.0. SFA : MUFA : PUFA ratio of the subject was 0.78 : 1.03 : 1.00 for male and 0.64 : 0.92 : 1.00 for female. Calcium intakes for both males and females were 321.3 mg and 377.2 mg. Vitamin A was the nutrient found to be least sufficient. Mean daily intakes of most of the vitamins and minerals for both males and females were lower than RDA except vitamin C and Zn for female, especially $\%$ RDAs of vitamin A, Ca for male and vitamin A for females were less than $50\%$ of RDA. In conclusion, long-lived elderly in Ganghwa areas did not consume enough nutrients quantitatively as well as qualitatively, especially Ca, Fe, vitamin A, vitamin $B_2$ and vitamin E. These results suggest that nutritional guidelines for older Koreans should focus on the maintenance of adequate energy intake. In addition, selection of foods with high protein and calcium, such as dairy food, should be emphasized, particularly in the long-lived elderly.

• Journal of Veterinary Clinics
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• v.27 no.2
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• pp.170-174
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• 2010

With the ease availability of statistical software and powerful computers the application of statistical methods in domestic veterinary journals is on the increase. In parallel with this benefit, statistical errors are not uncommon even in renowned scientific and medical journals. These errors may lead to misinterpretation of the data, thereby, subjected to faulty conclusions. A systematic review of articles published in 8 issues of the Journal of Veterinary Clinics during 2006-2007 was performed to assess the statistical methodology and reporting. Ninety-four (72.9%) articles of the 129 original articles screened included any inferential statistical analysis in the article, including comparison of 3 or more groups (53 or 56.4%), comparison of independent 2 groups (40 or 42.6%), and paired t-test (9 or 9.6%) in order. Of the 94 articles in which statistical analysis was done 62 (or 66.0%) had at least 1 statistical error. Errors included failure to apply or incorrectly applying independent Student's t-test for paired data or vice versa, inappropriate use of t-test for more than 3 groups and failure in chi-square test to consider continuity-correction for small expected frequencies. The common errors in ANOVA were failure to validate assumption of the test, inappropriate post-hoc multiple-comparison and incorrect assumption of independence of data in repeated measures design. Reporting errors included failure to state statistical methods and failure to state specific test if more than 1 test was done. It is suggested that an editorial effort would be necessary to achieve the improvement of appropriate statistical procedures through the publication of statistical guidelines to author(s).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.331-339
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• 2013

LiDAR has been one of the widely used and important technologies for 3D modeling of ground surface and objects because of its ability to provide dense and accurate range measurement. The objective of this research is to develop a method for automatic detection and modeling of railroad power lines using high density LiDAR data and RANSAC algorithms. For detecting railroad power lines, multi-echoes properties of laser data and shape knowledge of railroad power lines were employed. Cuboid analysis for detecting seed line segments, tracking lines, connecting and labeling are the main processes. For modeling railroad power lines, iterative RANSAC and least square adjustment were carried out to estimate the lines parameters. The validation of the result is very challenging due to the difficulties in determining the actual references on the ground surface. Standard deviations of 8cm and 5cm for x-y and z coordinates, respectively are satisfactory outcomes. In case of completeness, the result of visual inspection shows that all the lines are detected and modeled well as compare with the original point clouds. The overall processes are fully automated and the methods manage any state of railroad wires efficiently.

• Journal of Distribution Science
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• v.16 no.8
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• pp.79-89
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• 2018

Purpose - This research aims to investigate the factors that influence consumer's overseas online shopping behavior. Consumers adopt overseas online shopping as a new buying way and more and more consumers prefer overseas online shopping than traditional shopping ways. Consumers' behaviors in this shopping experience can be different from other shopping experiences. With the increase of overseas online shopping, we need to find antecedents and results of overseas online shopping. Especially there would be positive or negative factors which influence overseas online shopping motivation. To find the relationship, this study examines self-efficacy and impulsivity as major factors which influence overseas online shopping. We also suggest that several attitude factors increase self-efficacy and it is positively related to customer satisfaction. On the other hand, we assume that overseas online shopping factors influence impulsivity of buying and it will decrease customer satisfaction. Research design, data, and methodology - This empirical study data were collected from Korean people who experience overseas online shopping. The subjects for this study were confined to shoppers who used overseas online shopping within the past six months. A total of 267 responses were gathered. SPSS 23.0, PLS 2.0 software were used in the data analysis. Descriptive statistics were used to show sample characteristics. We examined reliability, validity test for constructs. All measurement items used seven-point scales(1= very strong disagree, 7 = very strongly agree) drawn from previously published papers. Partial Least Square method was applied to find the relationship between antecedent factors and dependent factors and hypotheses were estimated. Results - Results show that perceived superiority, perceived ease of use, perceived transaction safety, perceived behavioral control positively affect self-efficacy. Self-efficacy influences positively to consumer's post purchase satisfaction. Perceived monetary benefit and perceived uniqueness motivated impulse buying. This can make consumer's post purchase dissatisfaction. Conclusions - This paper attempted to confirm the existence of both the positive and negative faces of overseas online shopping. The result reveals that self-efficacy is a major factor which may increase satisfaction in the overseas online shopping. Usually, we can think monetary benefit and uniqueness of products motivate overseas online shopping. But it can also intrigue impulse buying and negatively affect customer relationship. Therefore companies should provide enough products information to their potential customers and they might apply adequate processes such as recommendation, comparing systems to build long term relationship with their customers.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.1-9
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• 2021

In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.

• Journal of Korea Trade
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• v.27 no.5
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• pp.113-136
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• 2023

Purpose - Global production chains and their impacts on economic growth have drawn extensive attention from researchers. Close relationships among global production chains, export and economic growth have been illuminated, as evidenced by the fast and stable economic growth of East Asian economies. These economies perform various roles within global production chains using offshoring, in which the impact of import on domestic gross output is as strong as that of export. The impact of import on economic growth would depend on whether imported inputs substitute or complement domestic inputs production, which is likely to vary according to individual countries' functions within global production chains. The economic growth of concerned countries would also be diverse. However, little attention has been paid to the impact brought by imports compared to its significance. Design/methodology - The principal methodology used in this paper is structural decomposition analysis (SDA), widely chosen to elucidate the impact of various factors on domestic gross output using input-output tables. This paper extracts trade data of six Asian economies from the World Input-Output Database (WIOD) 2016 release that covers 43 countries for the period 2000-2014. The extracted data is then categorised into 37 sectors. First, this paper calculates the Feenstra-Hanson Offshoring Index (OSI) of each country. It then applies SDA to measure the changes in each economy's gross output, export, import input coefficients, and domestic input coefficients. Finally, after taking the first difference from pooled time-series data, it estimates the correlations between imported input coefficients and OSI using the ordinary least square (OLS) method. Findings - The main findings of this paper can be summarised as follows. Firstly, all six countries have increasingly engaged in global production chains, as evidenced by the growing size of OSI. Secondly, there are negative correlations in five countries except Japan, with sectoral differences. Thirdly, changes in import input coefficients are not negative in all six countries, indicating that offshoring does not necessarily substitute for domestic inputs production but does complement it and, therefore, fosters their economic growth. This is observed in China, Indonesia, Korea and Taiwan. Offshoring has led to an increase in the use of imported inputs, which has, in turn, stimulated domestic inputs production in these countries. Originality/value - While existing studies focus on the role of export in evaluating the impact of participating global production chains, this paper explicitly examines the unexplored impact of import on domestic gross output by considering both the substitution and the complementary effect, using the WIOD. The findings of this paper suggest that Asian economies have achieved fast and stable economic growth not only through successful export management but also through effective import management within global production chains. This paper recommends that the Korean government and enterprises carefully choose offshoring strategies to minimise disruption to domestic production chains or foster them.