• Environmental and Resource Economics Review
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• v.22 no.3
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• pp.499-520
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• 2013

This study proposes an iterative approach to the estimation of the marginal abatement costs of undesirable outputs by computing the slope of the efficient production possibilities frontier on the basis of the efficient projection points generated by the directional output distance function approach due to Fare et al. (2005) based on duality theory. In case of the latter methodology, the estimated marginal abatement costs differ significantly depending on the choice of the directional output vector. In addition, depending on the curvature of the underlying PPF the efficient projection points may be located at a significant distance away from their actually observed counterparts. While it would be more logical to estimate marginal abatement costs as a PPF slope at a point corresponding to the actually observed emissions level, the methodology based on duality theory is likely to produce unstable results due to the problems associated with applying the theorem of implicit function differentiation. Since our methodology is not based on duality theory, our results are immune to both of these problems. We apply our methodology to a sample of Western European countries for the period of 1995-2011 to illustrate our approach.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.171-181
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• 2010

The integrated transit fare system of Seoul metropolitan area has given positively evaluated with reduction of user cost and activating the transfer behavior from its opening year, July 2007. However, there were only few research about railway demand forecasting methodology, especially mode share, has conducted under the integrated fare system. This study focuses on the utility estimation by each mode under the integrated fare system, and on the coefficient actualization relates on travel time and travel cost estimation with Household Travel Survey Data 2006. Also the railway demand analysis methodology under various fare systems is presented. The methodology from this study is expected to improve accuracy and usefulness in railway demand analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.102-114
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• 2021

NDF (No Defect Found) is a phenomenon in which defects have been found in the manufacturing, operation and use of a product or facility, but phenomenon of defects is not reproduced in the subsequent investigation system or the cause of the defects cannot be identified. Recently, with the development of the fourth industrial revolution, convergence of hardware and software technologies in various fields is spreading to products such as aircraft, home appliances, and mobile devices, and the number of parts is increasing due to functional convergence. The application of such convergence technologies and the increase in the number of parts are major factors that lead to an increase in NDF phenomena. NDF phenomena have a significant negative impact on cost, reliability, and reliability for both manufacturers, service providers and operators. On the other hand, due to the nature of NDF phenomena such as difficult and intermittent cause identification and ambiguity in judgment, it is common to underestimate the cost of NDF or fail to take appropriate countermeasures in corporate management. Therefore, in this paper, we propose a methodology for estimating NDF costs by the PAF model which is a quality cost analysis model and ABC (Activity Based Costing) technique. The methodology of this study suggests a detailed procedure and the concept to accurately estimate the NDF costs, using ABC analysis, accounting system information, and IT system data. In addition case studies have validated the methodology. We think this could be a valid methodology to refer to when estimating the cost of other parts. And, it is meaningful to provide important judgment information in the decision-making process based on quality management and ultimately reduce NDF costs by visualizing them separately by major variable factors.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.347-355
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• 2017

Methane and nitrous oxide are main greenhouse gases from agricultural system and their global warming potential are 25 and 258 times stronger than that of $CO_2$, respectively. In 2016, the emission was $21,290Gg\;tone\;CO_2-eq$. which was emitted from agriculture sector and about 3.1% of total GHG emission of Korea. Those guidelines that were published by IPCC have methodology for GHGs emission calculation as well as emission factor and so on. For recent 5 years, GHGs emissions in Korea have calculated by MRV which has been improved every year based on IPCC guidelines. Analysis as estimating method improvement showed that the methane emissions from rice cultivation were the lowest on 2012 methodology, and the highest on 2014 methodology. On the other hand, the emissions of agricultural soils were the lowest on 2015 methodology and the highest on 2012 methodology. Total emissions from agriculture sector were the lowest on 2015 methodology and the highest on 2012 methodology. Compared with 2016 methodology, the GHGs emitted as few as $-1,865Gg\;tone\;CO_2-eq$ and as many as $2,717Gg\;tone\;CO_2-eq$. GHGs emissions can vary greatly, depending on how to use the emission factor and activity data. Therefore, it need constantly a detailed analysis for methodology and GHGs emission in the future.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.189-199
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• 2012

PURPOSES: The purpose of this study is to propose a new methodology for developing statistical collision models and to show the validation results of the methodology. METHODS: A new modeling method of introducing variables into the model one by one in a multiplicative form is suggested. A method for choosing explanatory variables to be introduced into the model is explained. A method for determining functional forms for each explanatory variable is introduced as well as a parameter estimating procedure. A model selection method is also dealt with. Finally, the validation results is provided to demonstrate the efficacy of the final models developed using the method suggested in this study. RESULTS: According to the results of the validation for the total and injury collisions, the predictive powers of the models developed using the method suggested in this study were better than those of generalized linear models for the same data. CONCLUSIONS: Using the methodology suggested in this study, we could develop better statistical collision models having better predictive powers. This was because the methodology enabled us to find the relationships between dependant variable and each explanatory variable individually and to find the functional forms for the relationships which can be more likely non-linear.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.1-7
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• 2023

The advent of deep learning technologies has led to the development of various medical applications, making healthcare services more convenient and effective. Among these applications, heart rate estimation is considered a vital method for assessing an individual's health. Traditional methods, such as photoplethysmography through smart watches, have been widely used but are invasive and require additional hardware. Recent advancements allow for contactless heart rate estimation through facial image analysis, providing a more hygienic and convenient approach. In this paper, we propose a lightweight methodology capable of accurately estimating heart rate in mobile environments, using a specialized 2-channel network structure based on 2D convolution. Our method considers both subtle facial movements and color changes resulting from blood flow and muscle contractions. The approach comprises two major components: an Encoder for analyzing image features and a regression layer for evaluating Blood Volume Pulse. By incorporating both features simultaneously our methodology delivers more accurate results even in computing environments with limited resources. The proposed approach is expected to offer a more efficient way to monitor heart rate without invasive technology, particularly well-suited for mobile devices.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.9
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• pp.389-401
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• 2002

To complement the conventional fusion methodologies of state fusion and measurement fusion, a time-propagated measurement fusion methodology is proposed. Various aspects of common process noise are investigated regarding information preservation. Based on time-propagated measurement fusion methodology, four compression filters are derived. The derived compression filters are efficient in asynchronous sensor fusion and fault detection since they maintain correct statistical information. A new batch Kalman recursion is proposed to show the optimality under the time-propagated measurement fusion methodology. A simple simulation result evaluates estimation efficiency and characteristic.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.93-100
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• 2004

For accurate construction contract time estimation, few parameters are more significant than crew production rates and factors affecting the rates. However, statistical analysis techniques for finding such factors are not always simple mainly because there are many factors and the interaction between factors is not well quantitatively understood. This paper presents methodology of identifying factors driving crew production rates. The methodology is further demonstrated with representative data collected by the author from 13 on-going highway constructions. Three factors were identified as statistically significant drivers of Cap crew production rate: 'Cap Size (m3/ea)'; 'Cap Length (m)'; and 'Cap Shape (Rectangle vs. Inverted 'T')'. It was also found that the production rates are best explained by a multiple regression model with two of the drivers; 'Cap Size' and 'Cap Shape'.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.11
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• pp.1631-1638
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• 2015

This paper describes the design methodology of the operator training simulator for power monitor and control system in the railway system. In power system, the purpose of energy management system was to monitor, control, and analyze the performance of generation and transmission system based on H/W and S/W. Network analysis applications provide a clear picture of power system characteristics using state estimation, power flow and short circuit analysis. In this respect, the operator training system in the railway system should be equipped with the methodology of these systems. First, the proposed database structure in the railway system was introduced. Then the overall structure of operator training system based on railway analysis applications was proposed. Finally, a methodology to verify the performance of the developed applications was described.