• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.52-55
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• 2024

In this paper, a state change study was conducted through Frequency Domain Reflectometry (FDR) technology for the process chamber of plasma equipment for semiconductor manufacturing. In the experiment, by direct connecting the network analyzer to the RF matcher input of the 300 mm plasma enhanced chemical vapor deposition (PECVD) chamber, S11 was measured in a situation where plasma was not applied, and the frequency domain reacting to the chamber state change was searched. Response factors to changes in the status, such as temperature, spacing of the heating chuck, internal pressure difference, and process gas supply state were confirmed. Through this, the frequency domain in which a change in the reflection value was detected through repeated experiments. The reliability of the measured micro-displacement was verified through reproducibility experiments.

• Journal of Technology Innovation
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• v.7 no.1
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• pp.14-35
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• 1999

This paper presents the relationship between the pace of structural change and the magnitude of employment growth in the manufacturing sector in OECD countries. To measure the pace of structural change, the compositional change index in value-added in manufacturing sector is introduced. For mid to long-term there seems to be a positive relationship between the pace of structural change and the magnitude of employment growth. In those countries with higher value of the compositional index, the employment growth in manufacturing sector was generally higher. To analyse the characteristics of structural change in manufacturing sector, this paper classifies manufacturing industries into groups: one based on technology, one on orientation, one on wages and one on skills. The international comparison of manufacturing sector's employment patterns based on above four classifications are presented. International comparison suggests that Korean manufacturing sector move into jobs with more skills and knowledge The structural change of SMEs and large firms are compared based on above four classification methods. It is shown that SMEs' employment in low value sectors, that is low-technology, labor-intensive, tow-wage, and unskilled sectors, have risen faster than SMEs' employment in high-technology, science-based, high-wage and skilled sectors. Large firms' employment have been mainly increased in high value sectors. However, the employment growth of both large and small firms have been concentrated on production worker-intensively-using sectors, i.e. unskilled sectors. This widened the wage differential of production workers by firm sizes and concurrently led to severe shortage of production workers for SMEs, which has little ability to pay high wage to production workers because they usually belong to low-wage sectors. Korea need to push SMEs forward to high value sectors. The premise of that is, however, to pull large firms out of production worker-intensively-using sectors.

• Journal of Institute of Convergence Technology
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• v.2 no.1
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• pp.1-6
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• 2012

The cold chain system in South-East Asia is requiring to maintain freshness of refrigerated or frozen food. In this study, Thermal storage system using Phase change material (PCM) was developed and evaluated its performance about temperature and cold keeping time. For various application of cold chain system, we developed portable cold box, cold roll container and freezing station. Keeping time on laboratory tests of portable cold box in case of refrigeration and freezing were 6 hours and 4 hours, respectively. Cold container was developed to 2.5 ton scale. Evaluation in Indonesia, it was showed to keep the setting temperature of $-10^{\circ}C$ over 40 hours at $30^{\circ}C$ of ambient air. Freezing station using PCM was kept over 24 hours under $-20^{\circ}C$.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.433-446
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• 2021

In this study, the future flood inundation changes under a climate change were simulated in the Tonle Sap basin in Cambodia, one of the countries with high vulnerability to climate change. For the flood inundation simulation using the rainfall-runoff-inundation (RRI) model, globally available geological data (digital elevation model [DEM]; hydrological data and maps based on Shuttle elevation derivatives [HydroSHED]; land cover: Global land cover facility-moderate resolution imaging spectroradiometer [GLCF-MODIS]), rainfall data (Asian precipitation-highly-resolved observational data integration towards evaluation [APHRODITE]), climate change scenario (HadGEM3-RA), and observational water level (Kratie, Koh Khel, Neak Luong st.) were constructed. The future runoff from the Kratie station, the upper boundary condition of the RRI model, was constructed to be predicted using the long short-term memory (LSTM) model. Based on the results predicted by the LSTM model, a total of 4 cases were selected (representative concentration pathway [RCP] 4.5: 2035, 2075; RCP 8.5: 2051, 2072) with the largest annual average runoff by period and scenario. The results of the analysis of the future flood inundation in the Tonle Sap basin were compared with the results of previous studies. Unlike in the past, when the change in the depth of inundation changed to a range of about 1 to 10 meters during the 1997 - 2005 period, it occurred in a range of about 5 to 9 meters during the future period. The results show that in the future RCP 4.5 and 8.5 scenarios, the variability of discharge is reduced compared to the past and that climate change could change the runoff patterns of the Tonle Sap basin.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2286-2291
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• 2011

Technology on the rolling stock is very composition and system engineering. We have to consider to many parameters on the rolling stock design. High speed train is interface between rolling stock and infra system of rail, signal, communication etc. For many years testing operation has experienced substantial growth based on various advanced new technology. Recently some problems was clearly stated on effective management, practical use and testing operation of the the rolling stock on the technology change. This paper presents some results of the study on necessary requirements of the operation testing for rolling stock technology change. We propose a general plan to suggest the operation testing and the parameters of the rolling stock on the technology change in the text.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.49-49
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• 2016

The impact of land cover changes on streamflow of the Akaki catchment will be assessed using Soil and Water Assessment Tool (SWAT) model. The study will analyze the historical land cover changes (1993 to 2016) that have taken place in the catchment and its effect on the streamflow of the study area. Arc GIS will be used to analysis the satellite images obtained from the United States Geological Survey (USGS). To investigate the impact of land cover change on streamflow the model set up will be done using readily available spatial and temporal data, and calibrated against measured discharge. Two third of the data will be used for model calibration (1993?2000) and the remaining one-third for model validation (2001?2004). Model performance will be evaluated by using Nash and Sutcliff efficiency (NS) and coefficient of determination (R2). The calibrated model will be used to assess two land cover change (2002 and 2016) scenarios and its likely impacts of land use changes on the runoff will be quantified. The evaluation of the model response to these changes on streamflow will be presented properly. The study will contribute a lot to understand land use and land cover change on streamflow. This enhances the ability of stakeholder to implement sound policies to minimize undesirable future impacts and management alternatives which have a significant role in future flood control of the study area.

• Food Science of Animal Resources
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• v.36 no.1
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• pp.29-36
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• 2016

This study was performed to investigate the role of pH and temperature postmortem, and to demonstrate the importance of these factors in determining meat quality. Postmortem pH_45min (pH at 45 min postmortem or initial pH) via analysis of Pearson’s correlation showed high positive correlation with pH change pH_c24 (pH change from pH_45min to pH_24h postmortem). However, postmortem pH after 24 h (pH_24h or ultimate pH) had a high negative correlation with pH change, pH_c24, CIE L*, and protein content. Initial temperature postmortem (T_1h ) was positively associated with a change in temperature from 45 min to 24 h postmortem (T_c24) and cooking loss, but negatively correlated with water holding capacity. Temperature at 24 h postmortem (T_24h) was negatively associated with T_c24. Collectively, these results indicate that higher initial pH was associated with higher pH_c24, T_1h, and T_c24. However, higher initial pH was associated with a reduction in carcass weight, backfat thickness, CIE a* and b*, water holding capacity, collagen and fat content, drip loss, and cooking loss as well as decreased shear force. In contrast, CIE a* and b*, drip loss, cooking loss, and shear force in higher ultimate pH was showed by a similar pattern to higher initial pH, whereas pH_c24, carcass weight, backfat thickness, water holding capacity, fat content, moisture content, protein content, T_1h, T_24h, and T_c24 were exhibited by completely differential patterns (p<0.05). Therefore, we suggest that initial pH, ultimate pH, and temperatures postmortem are important factors in determining the meat quality of pork.

• Journal of Climate Change Research
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• v.1 no.2
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• pp.179-188
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• 2010

To cope with various issues in the aspect of climate change adaptation of UNFCCC, Korea began preparing a Five-year National Climate Change Adaptation Plan in 2010 to be implemented from 2011~2015, for the purposes of securing a concrete system to adapt to climate change. Compared with the policies and measurement tools of developed countries, Korea's climate change adaptation capabilities suffers from a number of limitations including insufficiencies of basic information, human resources for research on climate change, and technology in risk and vulnerability assessment. At the same time, Korea maintains superior information technology systems, and comparatively strong climate change adaptation technologies. Recently, with the establishment of the Korea Adaptation Center for Climate Change as a specialized research organization in climate change adaptation, Korea has upgraded its ability to adapt to climate change and to provide support to other Asian countries which are vulnerable to climate change. In consideration of the close relation between climate change adaptation policy and technology development with the environmental industry, Korea's pursuit of cooperation and technical support for developing countries in the Asia region can be seen as the commencement of a long term investment for the nation's future. International cooperation on climate change adaptation between countries in the region can build a mutually complementary and integrated partnership in business, research, education, and other areas. Furthermore, Korea can also participate in the exploration of common issues as landmark projects that can attract global interest with developing countries.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.37-39
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• 2000

The purpose of this paper is to present a neural network model based on change-point detection for the prediction of the U.S. Treasury Securities. Interest rates have been studied by a number of researchers since they strongly affect other economic and financial parameters. Contrary to other chaotic financial data, the movement of interest rates has a series of change points due to the monetary policy of the U.S. government. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in interest rates forecasting. The proposed model consists of three stages. The first stage is to detect successive change points in the interest rates dataset. The second stage is to forecast the change-point group with the backpropagation neural network (BPN). The final stage is to forecast the output with BPN. This study then examines the predictability of the integrated neural network model for interest rates forecasting using change-point detection.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.235-241
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• 2000

This article suggests integrated neural network models for the interest rate forecasting using change point detection. The basic concept of proposed model is to obtain intervals divided by change point, to identify them as change-point groups, and to involve them in interest rate forecasting. the proposed models consist of three stages. The first stage is to detect successive change points in interest rate dataset. The second stage is to forecast change-point group with data mining classifiers. The final stage is to forecast the desired output with BPN. Based on this structure, we propose three integrated neural network models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported neural network model, (2) case based reasoning (CBR)-supported neural network model and (3) backpropagation neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. This article is then to examine the predictability of integrated neural network models for interest rate forecasting using change-point detection.