• Progress in Medical Physics
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• v.15 no.4
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• pp.237-246
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• 2004

Even though the wedge factor was defined by ICRU, RTPS uses other definition different from the wedge factor to consider the wedge effect to correct dose. Because the factors with different concept are defined in a very different way, replacement of different factor could make severe error of dose and is unacceptable because their values are very different from each other. Radiotherapy machine installed in department includes physical wedges and function of dynamic wedge by upper jaws, and Eclipse and Pinnacle$^{3}$ such as RTPS are used. The wedge factors, relative wedge output factors and wedge field output factors of physical wedges and dynamic wedges were measured by an ionization chamber in water phantom. They are analyzed and compared in according to wedge position, field size, wedge angle, X-ray quality, measurement condition. Wedge factor, relative wedge output factors and wedge field output factors of dynamic wedges comparing physical wedges have an effect of several factors. Main factors effecting to the factors of dynamic wedges were field size and wedge angle. Beam quality of X-ray introduces a few effect to the factors. Because the factors related to wedge and defined with different concepts are different from each other, to reduce dose error it should be input by values proper to RTPS.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.3-20
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• 1990

The multisector model is designed to analyze and forecast structural change in industrial output, employment, capital and relative price as well as macroeconomic change in aggregate income, interest rate, etc. This model has 25 industrial sectors, containing about 1,300 equations. Therefore, this model is characterized by detailed structural disaggregation at the sectoral level. Individual industries are based on many of the economic relationships in the model. This is what distinguishes a multisector model from a macroeconomic model. Each industry is a behavioral agent in the model for industrial investment, employment, prices, wages, and intermediate demand. The strength of the model lies in the simulating the interactions between different industries. The result of its simulation will be introduced in the next paper. In this paper, we only introduce the structure of the multisector model and the coefficients of the equations. The multisector model is a dynamic model-that is, it solves year by year into the future using its own solutions for earlier years. The development of a dynamic, year-by-year solution allows us to combine the change in structure with a consideration of the dynamic adjustment required. These dynamics have obvious advantages in the use of the multisector model for industrial planning. The multisector model is a medium-term and long-term model. Whereas a short-term model can taken the labor supply and capital stock as given, a long-term model must acknowledge that these are determined endogenously. Changes in the medium-term can be analyzed in the context of long-term structural changes. The structure of this model can be summarized as follow. The difference in domestic and world prices affects industrial structure and the pattern of international trade; domestic output and factor price affect factor demand; factor demand and factor price affect industrial income; industrial income and relative price affect industrial consumption. Technical progress, as measured in terms of total factor productivity and relative price affect input-output coefficients; input-output coefficients and relative price determine the industrial input cost; input cost and import price determine domestic price. The differences in productivity and wage growth among different industries affect the relative price.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.300-301
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• 2002

Of many modalities for measuring output factor, we measured the outputs of 18mm, 14mm, 8mm and 4mm helmet in Gamma knife using ion chambers and a Gafrcromic MD-55 film and normalized the outputs of four helmets the one of a 18mm helmet. Ion chambers used for this paper were a PR-05P and a PinPoint having a volume of 0.07cc and 0.015cc respectively. The recommended output factors from a manufacture were 1, 0.984, 0.956, and 0.87. For PR-05P, the output factor of 14mm helmet showed a good agreement, but the ones of 8mm and 4mm helmet showed the difference of 4.6% and 47% respectively. For PinPoint, The output factors of 14mm and 8mm helmet showed a good agreement, but the one of a 4mm helmet showed a difference of 18%. The Gafcromic MD-55, however, showed a good agreement for all helmets.

• Journal of radiological science and technology
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• v.20 no.2
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• pp.28-33
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• 1997

For the Evaluation of X-ray image intensifier, we measured radiation dose at input of I. I., brightness and fluorescence at output of I. I. by using X-ray exposure meter, optometer and fluorescence meter for the relative conversion factor. Especially, by using fluorescence meter, we could easily get relative conversion factor without having regulated machine by JIS. Since using, the quality of image intensifier is going down. Consequently, it needs continuous quality maintenance.

• Progress in Medical Physics
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• v.13 no.1
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• pp.21-26
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• 2002

A practical calculation algorithm which calculates the relative output factor(ROF) for irregular shaped electron field has been developed and evaluated the accuracy of the algorithm. The algorithm adapted two-source model, which assumes that the electron dose can be express as sum of the primary source component and the scattered component from the shielding block. Original two-source model has been modified in order to make the algorithm simpler and to reduce the number of parameters needed in the calculation, while the calculation error remains within clinical tolerance range. The primary source is assumed to have Gaussian distribution, while the scattered component follows the inverse square law. Depth and angular dependency of the primary and the scattered are ignored ROF can be calculated with three parameters such as, the effective source distance, the variance of primary source, and the scattering power of the block. The coefficients are obtained from the square shaped-block measurements and the algorithm is confirmed from the rectangular or irregular shaped-fields used in the clinic. The results showed less than 1.0 ％ difference between the calculation and measurements for most cases. None of cases which have bigger than 2.1 ％ have been found. By improving the algorithm for the aperture region which shows the largest error, the algorithm could be practically used in the clinic, since one can acquire the 1011 parameter's with minimum measurements(5∼6 measurements per cones) and generates accurate results within the clinically acceptable range.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.1-13
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• 2017

This study examines how specific technology from Information and Communications Technology (ICT)-which plays a critical role in increasing productivity by promoting a spread of technology across the society though the use of big data, mobile or wearable devices-impacts of the productivity of society and productivity of added values, respectively. The impact of technology was studied from the perspective of efficiency levels of input. In order to provide an analysis, we have categorized ICT into 16 specific technologies and have set the number of companies and number of employees each as an input factor while setting the respective output and the output of added values as an output factor. Afterwards, we have applied data envelopment analysis (DEA) which is a form of nonparametric frontier analysis and measured the productivity and efficiency of added values for each technology. According to the analysis results, there were 2 technologies by the CRS standards, and 3 technologies by the VRS standards that showed relative efficiency levels. We have also presented some efficiency improvement strategies for specific technologies that revealed relative inefficiency and offered a reference set and projection point. In addition, we provide an analysis on scale efficiencies (SE), diminishing returns to scale (DRS), and increasing returns to scale (IRS) of each ICT.

• Health Policy and Management
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• v.6 no.2
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• pp.91-114
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• 1996

In this research, the Data Envelopment Analysis(DEA) was applied to measure production efficiency of Public Corporation Medical Centers(PCMCs) operating in Korea. The focus of this research is triple. First, identifing convenience and usefulness of DEA to measure the relative efficiency among PCMCs. Second, assessing magnitudes of the relative efficiency for each PCMC. Third, adding insights into some factors resulting inefficiency in PCMCs. Then, in this paper technical efficiency and scale efficiency measured by DEA[introduced by Charnes, Cooper, and Rhoides(1978) and Banker, Charnes, and Cooper(1984)] were analyzed and a new separate variable was introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decresing returns to scale(in multiple input and output situations). And a multi-factor Tobit analysis was conducted to see which variables are associated with PCMC's efficiency.

• Journal of Technology Innovation
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• v.21 no.3
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• pp.41-72
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• 2013

In this study, a comparison has been made among the countries regarding recent ICT practices being performed based on the measures of relative efficiency and productivity growth that use multiple inputs and outputs. Efficiency measures a country's ICT performance relative to a benchmark at a given point of time and productivity measures a country's performance over a period of time. An output-oriented Data Envelopment Analysis and Malmquist Index has been used for comparison among 28 countries over the period 2008-2011 by incorporating 9 variables. The empirical findings disclose gross inefficiencies in national ICT practices, which show that there is room for enhancing output gains through increased efficiency in their operations. In addition, 13 countries have performed better than others in total factor productivity mainly because of their improvement in the underlying technological progress in ICT. For those technically inefficient countries, however, technical inefficiency may hamper the growth of total factor productivity of ICT practices.

• Journal of Information Technology Services
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• v.12 no.4
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• pp.255-265
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• 2013

This paper proposes a DEA-AR model for the efficiency evaluation of the iron ore brands in an integrated steel mill. The input factor is defined as unit cost of each brand based on CIF and two output factors are chosen as Fe and Al which are the important ingredients of iron ore. The relative importance between two output factors is determined by several experts using AHP model. The efficiency of each brand is determined using DEA and DEA-AR models. The negative correlation between the DEA-AR efficiency and the unit cost (CIF) is shown as significant whereas no significant correlation exist between the efficiency and the output factors. Also, the Kruskal Wallis rank sum test shows that there exist efficiency differences among the iron ore types whereas no difference is shown among the countries. The result could be utilized in selecting good brands of iron ores based on the DEA-AR efficiency in an integrated steel mill.

• Journal of Korea Port Economic Association
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• v.22 no.1
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• pp.125-149
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• 2006

The main purpose of this study is to develop new measurement device of the quality of terminal service, applying the existing research output of service marketing to the specific industrial aspect of container terminal. Especially we tried to help marketing managers present the points of effective marketing strategy with each dimension of service quality. To achieve this aim, we defined the service quality demensions of container port as the following three ones; the internal, the external, and the interactive qualities. The applied measuring instruments could be divided into three dimensions by carrying out factor analysis. Additionally, by analyzing the relative effects of the three dimensions of service quality on customer satisfaction, we found that the relative importance are as follows; interaction quality>internal quality> external quality. We confirmed that the three dimensions of service quality could affect customer loyalty and information, through customer satisfaction.