• Environmental and Resource Economics Review
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• v.24 no.4
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• pp.727-745
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• 2015

This paper analyzes the firms' optimization behavior in response to rising demand for non-priced renewable energy in the manufacturing industries by using an input distance function. The annual estimates of the shadow price of renewable energy is derived and the trend of its shadow price over time is analyzed. The degree of substitution of renewable energy for fossil-fuels is examined. The input-based Malmquist productivity index, defined as a composite of the technical efficiency and technical change measures, is measured. The contribution of renewable energy input growth to the Malmquist index is analyzed. Empirical results indicate that the shadow price of renewable energy declined at an average annual rate of 17% over the period 1992-2012. Substitutability between renewable energy and fossil-fuels was limited. On average, a 1% increase in renewable energy would decrease Malmquist index by 0.04% per year.

• Environmental and Resource Economics Review
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• v.15 no.4
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• pp.673-692
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• 2006

In order to test for the dynamic optimality condition for the use of nonrenewable resource, it is necessary to estimate the shadow value of the resource in situ. In the previous literatures, a time series for in situ price has been derived either as the difference between marginal revenue and marginal cost or by differentiating with respect to the quantity of ore extracted the restricted cost function in which the quantity of ore is quasi-fixed. However, not only inconsistent estimates are likely to be generated due to the nonmalleability of capital, but the estimate of marginal revenue will be affected by market power. Since firms will likely fail to minimize the cost of the reproducible inputs subject to market prices under realistic circumstances where imperfect factor markets, strikes, or government regulations are present, the shadow in situ values obtained by estimating the restricted cost function can be biased. This paper provides a valid methodology for checking the dynamic optimality condition for a nonrenewable resource by using the input distance function. Our methodology has some advantages over previous ones: only data on quantities of inputs and outputs are required; nor is the maintained hypothesis of cost minimization required; adoption of linear programming enables us to circumvent autocorrelated errors problem caused by use of time series or panel data. The dynamic optimality condition for domestic coal mining does not hold for constant discount rates ranging from 2 to 20 percent over the period 1970~1993. The dynamic optimality condition also does not hold for variable rates ranging from fourth to four times the real interest rate.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.273-275
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• 2006

In this paper, we introduce a new design of fuzzy neural networks using input-output data information of target system. The proposed fuzzy neural networks is constructed by input-output data information and used the center of data distance by HCM clustering to obtain the characteristics of data. A membership function is defined by HCM clustering and is applied input-output dat included each rule to conclusion polynomial functions. We use triangular membership functions and simplified fuzzy inference, linear fuzzy inference, and modified quadratic fuzzy inference in conclusion. In the networks learning, back propagation algorithm of network is used to update the parameters of the network. The proposed model is evaluated with benchmark data.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.100-112
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• 1992

In this paper, an integrated document input/output system is developed which constructs the graphic document from a text file, converts the document into encoded facsimile data, and also recognizes printed/handwritten alphanumerics and Korean characters in a facsimile or graphic document. For an output system, we develop the method which generates bit-map patterns from the document consisting of the KSC5601 and ASCII codes. The binary graphic image, if necessary, is encoded by the G3 coding scheme for facsimile transmission. For a user friendly input system for documents consisting of alphanumerics and Korean characters obtained from a facsimile or scanner, we propose a document recognition algirithm utilizing several special features(partial projection, cross point, and distance features) and the membership function of the fuzzy set theory. In summary, we develop an integrated document input/output system and its performance is demonstrated via computer simulation.

• Environmental and Resource Economics Review
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• v.30 no.3
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• pp.471-501
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• 2021

We measure Environmental Efficiency (EE) based on CO₂ in four income groups from 1998 to 2018, using the Meta Stochastic Frontier Analysis method by Input Distance Function. Our results showed that economic growth and energy consumption would increase carbon dioxide emissions, and increasing labor and capital input will reduce it. Moreover, we compared Group Environmental Efficiency (GEE), Meta Environmental Efficiency (MEE), and Environmental Gap Ratio (EGR). The results showed that GEEs were be overestimated. Furthermore, the MEE showed a downward trend during this period. The lower-middle-income group had the highest EGR performance. High-income and upper-middle-income groups showed less efficiency in MEE and EGR. To improve environmental efficiency, we must reduce fossil fuels and find more scientific and technological ways to solve existing environmental problems as soon as possible.

• Journal of Korea Trade
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• v.23 no.4
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• pp.103-114
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• 2019

Purpose - This paper investigates the structure of exports across countries in terms of value added. Exports value added is examined under two categories, domestic and overseas. Using a statistical classification method by distance based on these two value added categories, this paper estimates the similarity of exports value added across countries including Korea. Design/methodology - The model of study is to employ a generalized distance function and then derive the Manhattan and Euclidean distances. The paper also performs cluster analysis using the Partitioning Around Medoids (PAM) and hierarchical methods to classify the 44 sample countries considered in this study. Findings - Our main findings are as follows. The 44 countries can be classified under 5 groups by their domestic and overseas value added in exports. Korea has a sandwich global value chains (GVCs) position between Japan, China, and Taiwan in the East Asian region. Originality/value - Existing papers point out the double counting problem of trade statistics as the intermediate goods trade across borders increases. This paper addresses the double counting problem by using the World Input-Output Table. The paper shows the need to explore the similarity of value added in exports structure across countries and investigate the GVCs position and role of each country.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.45-56
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• 2006

In order to construct an information pool on the production characteristics and efficiency of Korean railroad industry, various alternative approaches have to be applied. In this paper we present an empirical application of the distance function to measure the technical efficiency and the production characteristics of Korean railroad industry, The distance function firstly introduced by Shephard (1953) provides the advantage that it does not need information about prices, so it can accommodate the multiple output nature of the railway only using the quantifies as data. This is of great relevance in the context of the public sector such as railroad industry where there are often distinct control mechanisms on input prices. Also the distance function allows us to obtain a measure of technical efficiency as well as a measure of production characteristics. From annual data on Korean railroad industry during 1964-2004, multiple output distance function is estimated using quadratic programming model. The resulting technical efficiency estimates has tended to be improved over the period $1980{\sim}2004$. The indirect Morishima elasticities of substitution indicate that the substitutabilities for labor are relatively very low or impossible. The average scale elasticity is 2.7 which means that increasing the scale by 1per cent will result in an output increase by 2.7 percent. This result indicates that economies of scale are present in the Korean railroad industry.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.357-362
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• 2005

Iris recognition system is the one of the most reliable biometries recognition system. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transformed into polar coordinates. After performing three times Wavelet transformation, normalization was done using a sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compared pairs of two adjacent pixels. The binary code of the iris is transmitted to the server by the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the database. The process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.123-136
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• 2004

In this paper, complexity and regularity of polynomial multiplication over $GF({2^n})$ are defined by using Hamming weight of rows and columns of the matrix ever GF(2) which represents polynomial multiplication. It is shown experimentally that in order to construct the block cipher robust against differential cryptanalysis, polynomial multiplication of substitution layer and the permutation layer should have high complexity and high regularity. With result of the experiment, a way of constituting S box and G function is suggested in the block cipher whose structure is similar to SEED, which is KOREA standard of 128-bit block cipher. S box can be formed with a nonlinear function and an affine transform. Nonlinear function must be strong with differential attack and linear attack, and it consists of an inverse number over $GF({2^8})$ which has neither a fixed pout, whose input and output are the same except 0 and 1, nor an opposite fixed number, whose output is one`s complement of the input. Affine transform can be constituted so that the input/output correlation can be the lowest and there can be no fixed point or opposite fixed point. G function undergoes linear transform with 4 S-box outputs using the matrix of 4${\times}$4 over $GF({2^8})$. The components in the matrix of linear transformation have high complexity and high regularity. Furthermore, G function can be constituted so that MDS(Maximum Distance Separable) code can be formed, SAC(Strict Avalanche Criterion) can be met, and there can be no weak input where a fixed point an opposite fixed point, and output can be two`s complement of input. The primitive polynomials of nonlinear function affine transform and linear transformation are different each other. The S box and G function suggested in this paper can be used as a constituent of the block cipher with high security, in that they are strong with differential attack and linear attack with no weak input and they are excellent at diffusion.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.547-553
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• 2008

We propose a two-stage document layout segmentation method. At the first stage, as top-down segmentation, morphological distance map algorithm extracts a collection of rectangular regions from a given input image. This preliminary result from the first stage is employed as input parameters for the process of next stage. At the second stage, a machine-learning algorithm is adopted RBF network, one of neural networks based on statistical model, is selected. In order for constructing the hidden layer of RBF network, a data clustering technique bared on the self-organizing property of Kohonen network is utilized. We present a result showing that the supervised neural network, trained by 300 number of sample data, improves the preliminary results of the first stage.