• Journal of Climate Change Research
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• v.9 no.1
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• pp.69-74
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• 2018

The purpose of this study is to suggest the methodology of $CO_2$ Emission Factor Verification and Quantitative Assessment in Ethylene Product Processes. At first, this study compare the IPCC (Intergovernmental Panel on Climate Change) 1996 Guideline and 2006 Guideline. And analyse methodology for estimating $CO_2$ emission and $CO_2$ emission factor in Ethylene product process. Also analyse cases of estimating $CO_2$ emission factor based on material balance. Methodology of $CO_2$ Emission Factor Verification and Quantitative Assessment are following the categories proposed by GIR (Greenhouse Gas Inventory and Research Center). There are total 12 factors in 8 categories and give 5 or 10 points according to their importance. Also this study suggests necessary data of document to meet the conditions. The result would help estimate accuracy Greenhouse Gas Inventory. Also contribute to establish policy on environmental assessment, air conservation, etc.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.239-245
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• 2017

This study aimed to suggest priority for developing emission factor (EF) and to develop the methodology of quantitative assessment of EF in the forestry sector. Based on the stock-difference method, 17 kinds of EFs (27 EFs based on forest types) were required to calculate the carbon emission in the forestry sector. Priority for developing EFs followed the standards, which is a development plan by the government agency, importance of carbon stock for greenhouse gas, and EFs by the species. Currently, the most urgent development of EFs was carbon fraction in biomass and carbon stock in dead wood. Meanwhile, the quantitative assessment of EF consisted of 7 categories (5 categories of compulsory and 2 categories of quality evaluation) and 12 verification factors. Category in compulsory verification consisted of administrative document, determination methodology of emission factors, emission characteristic, accuracy of measurement and analysis, and data representative. Category in quality evaluation consisted of data management and uncertainty estimates. Based on the importance of factors in the verification process, each factor was scored separately, however, the score needs to be coordinated by the government agency. These results would help build a reliable and accurate greenhouse gas inventory report of Korea.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.325-328
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• 2001

This paper describes a VHDL code coverage checker for If design and verification. Applying the verification coverage to IP design is a methodology rapidly gaining popularity. This enables the designers to improve the IP design quality and reduces the time-to-market by providing the Quantitative measure of simulation completeness and test benches. To support this methodology, a VHDL code coverage model was defined and the measurement tool was developed.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.117-136
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• 2019

In this study, a hybrid-type of day fog detection algorithm (DFDA) was developed based on the optical and textural characteristics of fog top, using the Himawari-8 /Advanced Himawari Imager data. Supplementary data, such as temperatures of numerical weather prediction model and sea surface temperatures of operational sea surface temperature and sea ice analysis, were used for fog detection. And 10 minutes data from visibility meter from the Korea Meteorological Administration were used for a quantitative verification of the fog detection results. Normalized albedo of fog top was utilized to distinguish between fog and other objects such as clouds, land, and oceans. The normalized local standard deviation of the fog surface and temperature difference between fog top and air temperature were also assessed to separate the fog from low cloud. Initial threshold values (ITVs) for the fog detection elements were selected using hat-shaped threshold values through frequency distribution analysis of fog cases.And the ITVs were optimized through the iteration method in terms of maximization of POD and minimization of FAR. The visual inspection and a quantitative verification using a visibility meter showed that the DFDA successfully detected a wide range of fog. The quantitative verification in both training and verification cases, the average POD (FAR) was 0.75 (0.41) and 0.74 (0.46), respectively. However, sophistication of the threshold values of the detection elements, as well as utilization of other channel data are necessary as the fog detection levels vary for different fog cases(POD: 0.65-0.87, FAR: 0.30-0.53).

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.256-261
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• 2017

The notion of System of Systems (SoS), which is composed by many independent systems (i.e., Constituent Systems, CS), has emerged in various domains including social infrastructure. It is widely expected that complex requirements, which cannot be achieved in each CS-level, will be achieved in an SoS-level. While verification of SoS-level goal achievement is one of the most important problems, concrete case studies on SoS modeling and verification are still rare. In this paper, we focus on the fact that each CS performs an action for its own purpose by its own decision-making mechanism. We propose a novel Action-Benefit-Cost (ABC) SoS model which caters to the independent decision-making mechanisms of CSs. Using an abstract SoS example, this proposal provides a case study for the modeling and quantitative verification of the ABC SoS model.

• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.360-366
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• 2003

Although multilayer perceptrons (MLPs) present several advantages against other pattern recognition methods, MLP-based speaker verification systems suffer from slow enrollment speed caused by many background speakers to achieve a low verification error. To solve this problem, the quantitative discriminative cohort speakers (QnDCS) method, by introducing the cohort speakers method into the systems, reduced the number of background speakers required to enroll speakers. Although the QnDCS achieved the goal to some extent, the improvement rate for the enrolling speed was still unsatisfactory. To improve the enrolling speed, this paper proposes the qualitative DCS (QlDCS) by introducing a qualitative criterion to select less background speakers. An experiment for both methods is conducted to use the speaker verification system based on MLPs and continuants, and speech database. The results of the experiment show that the proposed QlDCS method enrolls speakers in two times shorter time than the QnDCS does over the online error backpropagation(EBP) method.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.386-390
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• 2007

At recent times, an essential issue in the replacement of the old analogue I&C to computer-based digital systems in nuclear power plants becomes the quantitative software reliability assessment. Software reliability models have been successfully applied to many industrial applications, but have the unfortunate drawback of requiring data from which one can formulate a model. Software that is developed for safety critical applications is frequently unable to produce such data for at least two reasons. First, the software is frequently one-of-a-kind, and second, it rarely fails. Safety critical software is normally expected to pass every unit test producing precious little failure data. The basic premise of the rare events approach is that well-tested software does not fail under normal routine and input signals, which means that failures must be triggered by unusual input data and computer states. The failure data found under the reasonable testing cases and testing time for these conditions should be considered for the quantitative reliability assessment. We presented the quantitative reliability assessment methodology of safety critical software for rare failure cases in this paper.

• Journal of the Korean Society of Safety
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• v.35 no.2
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• pp.100-110
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• 2020

Recently, the frequency of typhoon and torrential rain due to climate change is increasing. In addition, the upsurge in the complexity of urban sewer network and impervious surfaces area aggravates the inland flooding damage. In response to these worsening situations, the central and local governments are conducting R&D tasks related to predict and mitigate the flood risk. Researches on the analysis of inundation in urban areas have been implemented through various ways, and the common features were to evaluate the accuracy and justification of the model by comparing the model results with the actual inundation data. However, the evaluation procesure using available urban flooding data are not consistent, and if there are no quantitative urban inundation data, verification has to be performed by using press releases, public complaints, or photos of inundation occurring through 'CCTV'. Because theses materials are not quantitative, there is a problem of low reliability. Therefore, this study intends to develop a comparative analysis procedure on the quantitative degree and applicability of the verifiable inundation data, and a systematic framework for the performance assessment of urban flood analysis model was proposed. This would contribute to the standardization of the evaluation and verification procedure for urban flooding modelling.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.81-90
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• 2018

"The Framework Act on Low-Carbon Green Growth" specifies the requirements for the development and verification of emission factors for establishing reliable national greenhouse gas statistics. The scope of the regulations covers the development and validation of energy, industrial processes, solvents and other product use, agriculture, land use, land use change and emission and absorption coefficients of the forestry and waste sector as defined in the 1996 IPCC Guideline and GPG 2000, The minerals sector to be covered in this study belongs to industrial processes. As a representative method for quantifying and evaluating GHG emission factors, there are emission grade quality grading and DARS (Data Rating Rating System) in the 'Procedures for Preparing Emission Factor Documents (1997)' reported by US-EPA. However, the above two methods are not specific and comprehensive, and lack the details for accurate emission factor verification. Therefore, there is a need for a method for verifying and quantifying certified greenhouse gas emission factors that reflects characteristics of each industry sector in Korea and accord with IPCC G/L and GHG target management. In this study, we conducted a weighted study on quantitative and evaluation lists of emission factor using questionnaires to develop a more accurate methodology for quantifying national greenhouse gas emission factors in the mineral sector. Quantification and evaluation of emission factor are classified into essential verification and quality evaluation. The essential verifications are : administrative compatibility, method of determining emission factors, emission characteristics, sampling methods and analysis methods, representativeness of data. The quality evaluations consisted of the quality control of the data, the accuracy of the measurement and analysis, the level of uncertainty, not directly affect the emission factor, but consisted of factors that determine data quality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4863-4870
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• 2015

Currently, as a priority to secure the safety of the railway signalling system, verification for satisfy of the safety integrity requirements(SIR) is required to the essential elements. Safety Integrity Requirements(SIR) verification is performed based on the system safety analysis. But the probability of securing basic data for system safety analysis significantly dropped because there is no experience yet performed in the country. Therefore we are had to rely on a qualitative analysis. There are methods such as qualitative risk analysis matrix, and risk graphs. The qualitative analysis is wide, the width of the accident. However, the reliability of the result is significantly less has a disadvantage. Therefore, it should be parallel quantitative safety analysis of the system/products in order to compensate for the disadvantages of the qualitative analysis. This paper presents a quantitative safety analysis method to overcome the disadvantages of the qualitative analysis. And through a result, highly reliable Safety Integrity Requirements(SIR) verification measures proposed. Verification results, the dangerous failure incidence for vital data processing device was calculated to be $1.172279{\times}10^{-9}$. The result was verified to exceed the required safety integrity targets more.