• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.171-186
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• 2020

Purpose: The purpose of this study is conducting of predictive models that considered multicollinearity of independent variables in order to carry out more efficient and reliable predictions about differential pressure in seawater reverse osmosis. Methods: The main variables of each RO system are extracted through factor analysis. Common variables are derived through comparison of RO system # 1 and RO system # 2. In order to carry out the prediction modeling about the differential pressure, which is the target variable, we constructed the prediction model reflecting the regression analysis, the artificial neural network, and the support vector machine in R package, and figured out the superiority of the model by comparing RMSE. Results: The number of factors extracted from factor analysis of RO system #1 and RO system #2 is same. And the value of variability(% Var) increased as step proceeds according to the analysis procedure. As a result of deriving the average RMSE of the models, the overall prediction of the SVM was superior to the other models. Conclusion: This study is meaningful in that it has been conducting a demonstration study of considering the multicollinearity of independent variables. Before establishing a predictive model for a target variable, it would be more accurate predictive model if the relevant variables are derived and reflected.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.765-773
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• 2017

Ultra-high definition videos, panorama contents, and ultra-wide viewing videos have a huge spatial resolution. However, a whole region of images is not always interesting to viewers due to limitations of system resources and display devices. To allow one or more interesting tiles to be decoded freely without decoding other tiles, this paper introduces a tile-based independent coding method. The propose method restraints motion vectors to be within a tile region shifting motion search area and modifying an initial motion vector. Experiments results show that any desired tile is capable to be decoded independently of other tiles.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.4
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• pp.61-66
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• 2017

Environmental awareness and its relation to the development of economy has garnered increased attention in recent years. Researchers, over the years, have argued that sustainable development warrants for minimizing environmental degradation since one depends on the other. This study analyzes the relationship between environmental degradation (carbon emission taken as proxy for degradation), economic growth, total energy consumption and industrial production index growth in Bangladesh from year 1998 to 2013. This study uses Vector Autoregression (VAR) Model and variance decomposition of VAR to analyze the effect of these variables on carbon emission and vice-versa. The findings of VAR model suggest that industrial production and GDP per capita has significant relationship with carbon emission. Further analysis through variance decomposition shows carbon emission has consistent impact on industrial production over time, whereas, industrial production has high impact on emission in the short run which fades in the long run which is consistent with Environmental Kuznets Curve (EKC) hypothesis. Carbon emission rising along with GDP per capita and at the same time having low impact in the long run on industrial index indicates there may be other sources of pollution introduced with the rise in income of the economy over time.

• Korea Trade Review
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• v.43 no.3
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• pp.125-145
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• 2018

The Baltic Shipping Exchange is reporting the Baltic Dry Index (BDI) which represents the average charter rate for bulk carriers transporting major cargoes such as iron ore, coal, grain, and so on. And the current BDI index is reflected in the proportion of capesize 40%, panamax 30% and spramax 30%. Like mentioned above, the capesize plays a major role among the various sizes of bulk carriers and this study is to analyze the influence of the factors influencing on charter rate of capesize carriers which transport iron ore and coal as the major cargoes. For this purpose, this study verified causality between variables using Vector Error Correction Model (VECM) and tried to derive a long-run equilibrium model between the dependent variable and independent variables. Regression analysis showed that every six independent variable has a significant effect on the capesize charter rate, even at the 1% level of significance. Charter rate decreases by 0.08% when capesize total fleet increases by 1%, charter rate increases by 0.04% when bunker oil price increases by 1%, and charter rate decreases by 0.01% when Yen/Dollar rate increases by 1%. And charter rate increases by 0.02% when global GDP increases by one unit (1%). In addition, the increase in cargo volume of iron ore and coal which are major transportation items of capesize carriers has also been shown to increase charter rates. Charter rate increases by 0.11% in case of 1% increase in iron ore cargo volume, and 0.09% in case of 1% increase in coal cargo volume. Although there have been some studies to analyze the influence of factors affecting the charterage of bulk carriers in the past, there have been few studies on the analysis of specific size vessels. At present moment when ship size is getting bigger, this study carried out research on capesize vessels, which are biggest among bulk carriers, and whose utilization is continuously increasing. This study is also expected to contribute to the establishment of trade policies for specific cargoes such as iron ore and coal.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.7
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• pp.76-81
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• 2013

This paper presents an effective pedagogical method for nodal analysis in linear circuit. In the proposed method, basic equations are built only for passive elements and independent current sources. And then, the basic equations are modified by considering other sources such as voltage sources and dependent current sources. In the proposed method, the equations are presented in form of a matrix and a vector of which elements are built systematically by considering every element in a circuit one by one. This make the proposed method easy to apply to intricately composed circuit and easy to solve the final simultaneous equations and easy to realize as computer program for nodal analysis and easy to memorize compared to the conventional method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.13-22
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• 2004

Because video sequence consists of dynamic objects in nature, the object motion in video is an effective feature in describing the contents of video sequence and motion feature plays an important role in video retrieval. In this paper, we propose a method that converts motion vectors (MVs) to a uniform set on MPEG coded domain, independent of the frame type and the direction of prediction, and utilizes these normalized MVs (N-MVs) as motion descriptor to understand video contents. We describe a frame-type independent representation of the various types of frames presented in an MPEG video in which all frames can be considered equivalently, without full-decoding. In the experiments, we show that the proposed method is better than the conventional one in terms of performance.

• The Journal of Industrial Distribution & Business
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• v.9 no.9
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• pp.7-14
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• 2018

Purpose - Social welfare is a social insurance system that provides funds and services for all citizens to maximize their life quality. Its ultimate goal is to alleviate social contradictions. Therefore, this paper explores the determinants of social welfare in terms of macroeconomics. Research design, data, and methodology - Based on the vector error correction model, the annual time series from 1990 to 2017 will be used to conduct an empirical analysis. The real GDP, the real income, the inflation and the degree of openness will be treated as independent variables. The input of social welfare will be treated as a dependent variable. These variables will be used to perform the cointegration test and the vector error correction model to explore how the macroeconomic variables affect social welfare both in long run and short run. Result - Via the empirical analysis, it can be summarized that the real GDP, the real income and the degree of openness are the driving determinants to enlarge the social welfare. Conversely, the inflation is the obstructive determinant to reduce the social welfare. Conclusion - The positive and negative determinants of social welfare exist simultaneously, China's government should take macroeconomic regulation and control to balance them to enlarge social welfare.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.33-40
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• 2005

The aim of remotely sensed data classification is to produce the best accuracy map of the earth surface assigning each pixel to its appropriate category of the real-world. The classification of satellite multi-spectral image data has become tool for generating ground cover map. Many classification methods exist. In this study, MLC(Maximum Likelihood Classification), ANN(Artificial neural network), SVM(Support Vector Machine), Naive Bayes classifier algorithms are compared using IKONOS image of the part of Dalsung Gun, Daegu area. Two preprocessing methods are performed-PCA(Principal component analysis), ICA(Independent Component Analysis). Boosting algorithms also performed. By the combination of appropriate feature selection pre-processing and classifier, the best results were obtained.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.354-357
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• 2001

The developed method is proposed to identify rotor dynamic parameters. The method known imbalance vector, which renders over-determined linear system equation. The solution of the system equation can be obtained using least square method. The sensitivity analysis is performed to extract optimized solution, which is considered to be insensitive to inherent measurement errors. As an alternative approach to identify the parameters of bearings and rotor, adding a known imbalance to the rotor produces another equation set to make the system equations over-determined and linearly independent.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.1-8
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• 2004

According to the development of the Internet and the pervasion of Data Base, it is not easy to search for necessary information from the huge amounts of data. In order to do efficient analysis of a large amounts of data, this paper proposes a method for pattern classification based on the effective strategy for dimension reduction for narrowing down the whole data to what users wants to search for. To analyze data effectively, Radial Basis Function Networks based on VC-dimension of Support Vector Machine, a model of statistical teaming, is proposed in this paper. The model of Radial Basis Function Networks currently used performed the preprocessing of Perceptron model whereas the model proposed in this paper, performing independent analysis on VD-dimension, classifies each datum putting precise labels on it. The comparison and estimation of various models by using Machine Learning Data shows that the model proposed in this paper proves to be more efficient than various sorts of algorithm previously used.