• Journal of Digital Convergence
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• v.14 no.1
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• pp.203-209
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• 2016

In this paper, we introduce a fuzzy inference systems for nonlinear inference using fuzzy cluster. Typically, the generation of fuzzy rules for nonlinear inference causes the problem that the number of fuzzy rules increases exponentially if the input vectors increase. To handle this problem, the fuzzy rules of fuzzy model are designed by dividing the input vector space in the scatter form using fuzzy clustering algorithm which expresses fuzzy cluster. From this method, complex nonlinear process can be modeled. The premise part of the fuzzy rules is determined by means of FCM clustering algorithm with fuzzy clusters. The consequence part of the fuzzy rules have four kinds of polynomial functions and the coefficient parameters of each rule are estimated by using the standard least-squares method. And we use the data widely used in nonlinear process for the performance and the nonlinear characteristics of the nonlinear process. Experimental results show that the non-linear inference is possible.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.2
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• pp.152-159
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• 2005

In this paper, we propose a diagnosis algorithm using fusion wかd based on PCA and LDA to detect fault states of the induction motor that is applied to various industrial fields. After yielding a feature vector from the current value measured by an experiment using PCA and LDA, training data is made to produce each matching value. In a diagnostic step, two matching values yielded by PCA and LDA are fused by probability model and finally verified. Since the proposed diagnosis algorithm takes only merits of PCA and LDA it shows excellent results under noisy environments. The simulation results to verify the usability of the proposed algorithm showed better performance than the case just using conventional PCA or LDA.

• International Commerce and Information Review
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• v.18 no.1
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• pp.107-127
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• 2016

This paper attempts to investigate determinants of foreign direct investment in transition countries of Mongolia and Central Asia five countries of Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan and Turkmenistan. FDI inflows in this transition economies have been far increasing due to their rapid growth, GDP, gross capital formation, wage, labor force, open trading, infrastructure and natural resources as well as the factors demonstrating the economic variables and political variables of these countries by Vector Error Correction Model. The results of empirical analysis based on data from 1993 to 2013 confirmed that FDI and open trade and gross capital formation and political than GDP, wage, labor force, infrastructure and natural resources had a significant impact on Central Asia and Mongolia. In addition, if Mongolia and Central Asian five countries can maintain the country's economic growth, reduce unemployment level, achieve certain improvements in domesticating new technologies and improving skills and knowledge sphere as well as promoting stable domestic price increase, attracting and improving the FDI by paying more attention to the indicators focusing on country's GDP, wage, labor force, infrastructure and natural resource.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.633-644
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• 2020

Rice paper is an element of Vietnamese cuisine that can be used to wrap vegetables and meat. Rice and starch are the main ingredients of rice paper and their mixing ratio is important for quality control. In a commercial factory, assessment of food safety and quantitative supply is a challenging issue. A rapid and non-destructive monitoring system is therefore necessary in commercial production systems to ensure the food safety of rice and starch flour for the rice paper wrap. In this study, fluorescence hyperspectral imaging technology was applied to classify grain flours. Using the 3D hyper cube of fluorescence hyperspectral imaging (fHSI, 420 - 730 nm), spectral and spatial data and chemometric methods were applied to detect and classify flours. Eight flours (rice: 4, starch: 4) were prepared and hyperspectral images were acquired in a 5 (L) × 5 (W) × 1.5 (H) cm container. Linear discriminant analysis (LDA), partial least square discriminant analysis (PLSDA), support vector machine (SVM), classification and regression tree (CART), and random forest (RF) with a few preprocessing methods (multivariate scatter correction [MSC], 1^st and 2^nd derivative and moving average) were applied to classify grain flours and the accuracy was compared using a confusion matrix (accuracy and kappa coefficient). LDA with moving average showed the highest accuracy at A = 0.9362 (K = 0.9270). 1D convolutional neural network (CNN) demonstrated a classification result of A = 0.94 and showed improved classification results between mimyeon flour (MF)1 and MF2 of 0.72 and 0.87, respectively. In this study, the potential of non-destructive detection and classification of grain flours using fHSI technology and machine learning methods was demonstrated.

• Journal of Korea Port Economic Association
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• v.27 no.4
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• pp.207-218
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• 2011

This paper investigates the determinants of trade on Southeast Asia via Korean ports using monthly data. I employ Johansen cointegration methodology since the model must be stationary to avoid the spurious results. Johansen(1988) and Johansen and Juselius(1990) propose two statistics for testing the number of cointegrating vectors: the trace and maximum eigenvalue statistics. The null hypothesis that there is no cointegrating vector should be rejected at the 5% level. The results indicate that there is a long-run relationship between trade and variables. This also suggests that these variables have a meaningful equilibrium relationship between trade and variables would not move too far away from each other, displaying a comovement phenomenon for the export and import. Apparently, the error correction term reflects market information in a state of disequilibrium that is bound to be corrected when moving toward the long-run level.

• Korean Journal of Construction Engineering and Management
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• v.15 no.2
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• pp.87-94
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• 2014

This study aims to analyze the relationship. The study applies EDF (Expected Default Frequency) as a variable that indicates management status of a construction company. To analyze changes in business structure of construction companies, the study refers to the amounts of domestic and overseas project orders as variables. The data was retrieved from TS2000 established by Korea Listed Companies Association (KLCA), Statistics Korea and International Contractors Association of Korea. The analysis period is between first quarter of 2001 and fourth quarter of 2010. The analysis results showed that as more domestic and overseas orders rolled in for domestic companies, their business conditions improved as the hypothesis suggested. However, the level of improvement varied. Further, when construction companies' business slowed down, the proportion of overseas projects tended to rise, while the ratio of domestic business decreased.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6315-6324
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• 2015

This study analyses the effects of household finances on rental price of apartment in Seoul which play a major role in real estate policy. We estimate VAR models using time series data. Economy variables such as sales price of apartment in Seoul, consumer price index, hiring rate, real GNI and loan amount of housing mortgage, which relate to household finances and influence the rental price of apartment, are used for estimation. The main findings are as follows. In the short term, the rental price of apartment is impacted by economy variables. Specifically, Relative contributions of variation in rental price of apartment through structural shock of economy variables are most influenced by their own. However, in the long term, household variables are more influential to the rental price of apartment. These results are expected to contribute to establish housing price stabilization policies through understanding the relationship between economy variables and rental price of apartment.

• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.68-76
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• 2002

Multicast in mobile host has the problem of hast mobility, multicast decision, triangle routing, tunnel convergence, implosion of retransmission, and bandwidth waste. In particular, the bandwidth waste in radio is a definite factor that decreases transmission rate. To solve the problems, this paper proposes a new multicast transmission protocol called FIM(Forward Error Correction Integrated Multicast), which supports reliable packet recovery mechanism by integrating If Mobility Support for the host mobility, IGMP(Interned Group Management Protocol) for the group management, and DVMRP(Distance Vector Multicast Routing Protocol) for the multicast routing, and it also uses FEC and the local recovery method based on receiver. The performance measurement is performed by dividing the losses into the homogeneous independent loss, the heterogeneous independent loss, and the shared source link loss model.. The result shows that the performances improves in proportion to the size of local areal group when the size of transmission group exceeds designated size. This indicates FIM is effective in the environment where there are much of data and many receivers in the mobile host.

• Asia-Pacific Journal of Business
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• v.12 no.1
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• pp.209-223
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• 2021

Purpose - The purpose of this study was to investigate the relationship between Korea agricultural productions and Greenhouse Gas (GHG) emissions based on Environmental Kuznets Curve (EKC) hypothesis. Design/methodology/approach - This study utilized time series data of economic growth, greenhouse gas, agricultural productions, trade dependency, and energy usages. In order to econometric procedure of EKC hypothesis, this study utilized unit root test and cointegration test to check staionarity of each variable and also adopted Vector Error Correction Model (VECM) and Ordinary Least Square (OLS) to analyze the short and long run relationships. Findings - In the short run, greenhouse gas emissions resulting from economic growth show an inverse U-shape relationship, and an increase in agricultural production and energy consumption led to increase in greenhouse gas emission. In the long run, total GHG emissions and CO2 emissions show an N-shaped relationship with economic growth, and an increase in agricultural production has resulted in a decrease in total GHG and CO2 emissions. However, methane (CH4) and nitrous oxide (N2O) emissions showed an inverse U-shape relationship with economic growth, which indicated the environment and production process of agricultural production. Research implications or Originality - Korea agricultural production has different effects on the GHG emission sources, and in particular, methane (CH4) and nitrous oxide (N2O) emissions show to increase as the agricultural production expansions, so policy or technological development in related sector is required. Especially, in the context of the 2030 GHG reduction road-map, if GHG-related reduction technologies or policies are spread, national GHG emission reduction targets can be achieved and this is possible to predict the decline in production in the sector and damage to the related industries.

• International Area Studies Review
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• v.16 no.3
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• pp.77-97
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• 2012

Estimated coefficients has serious problems including inconsistency, biasness, etc. because many researches about the effect of fiscal decentralization on a country's economic growth use the traditional OLS method. Researches use the data intactly so that so called "spurious regression" phenomenon exists. This causes fundamental fallacy. This research tries unit root test, cointegration test, and then estimates the United States' economic time series by using VECM. The analysis of the effect of the state level-fiscal decentralization on economic growth shows two long term-equilibriums. During short term-dynamic adjustment, fiscal decentralization and economic growth move the same or different directions. In case of prediction GDP increases steeply and then from 2015 gently; and fiscal decentralization index shows a general reduction trend and then decreases slowly. At local level it shows two long term-equilibriums. During short term-dynamic adjustment, fiscal decentralization and economic growth also move the same or different directions. Impulse response analysis shows the very negative effect of fiscal decentralization on economic growth.