• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.34.1-34.1
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• 2013

The first generation stars in the universe are not observed as discrete objects by using current observational facilities, but their contributions are redshifted to the near infrared wavelength bands at present universe. Therefore, investigation of background radiation at near infrared is important for the study of the first stars. In this study, we present new observations of spatial fluctuations in sky brightness toward the north ecliptic pole using data from AKARI. Among pointed observation program of AKARI, we used two pointing surveys named Monitor field and NEP wide field at three wavelength bands 2.4, 3.2, and 4.1 ${\mu}m$. To obtain spatial fluctuations from observed images, first of all, we exclude pixels affected by resolved foreground objects and then obtain diffuse map which consists of diffused radiation only. Because the diffuse map contains not only cosmological components but also various foreground components, in order to detect cosmological components, we estimate the contributions of foreground components separately. The results of this study show that there remains excess spatial fluctuation that cannot be explained by known foreground sources. This work is based on observations with AKARI, a JAXA project with the participation of ESA.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.35.1-35.1
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• 2013

The first generation stars in the universe are not observed as discrete objects by using current observational facilities, but their contributions are redshifted to the near infrared wavelength bands at present universe. Therefore, investigation of background radiation at near infrared is important for the study of the first stars. In this study, we present new observations of spatial fluctuations in sky brightness toward the north ecliptic pole using data from AKARI. Among pointed observation program of AKARI, we used two pointing surveys named Monitor field and NEP wide field at three wavelength bands 2.4, 3.2, and 4.1 ${\mu}$. To obtain spatial fluctuations from observed images, first of all, we exclude pixels affected by resolved foreground objects and then obtain diffuse map which consists of diffused radiation only. Because the diffuse map contains not only cosmological components but also various foreground components, in order to detect cosmological components, we estimate the contributions of foreground components separately. The results of this study show that there remains excess spatial fluctuation that cannot be explained by known foreground sources. This work is based on observations with AKARI, a JAXA project with the participation of ESA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.61-65
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• 2011

Recently, LCD (liquid crystal display) industry is needed to goods of high reliability and wide range temperature condition and it is interested in products for extremely cold condition without failure of light-up. In this experiment, we made the LED backlight unit for Automotive-navigation under the extremely cold condition. And for making this backlight unit, we used to eight side emitting type white LEDs with 3W high power LED. We could know that this backlight unit releases to 18,000 nit in 24W power consumption and start up voltage time is under the 1ms in the ambient temperature at -40.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1814-1820
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• 2018

State estimation of power systems has become vital in recent days of power operation and control. SCADA and EMS are intended for the state estimation and to communicate and monitor the systems which are operated at specified time. Although various methods are used we can achieve the better results by using PMU technique. On placing the PMU, operating time is reduced and making the performance reliable. In this paper, PMU placement is done in two ways. Those are 'optimal technique with pruning operation' and 'depth of unobservability' considering incomplete and complete observability of a network. By Depth of Unobservability Number of PMUs are reduced to attain Observability of the network. Proposed methods are tested on IEEE 14, 30, 57, SR-system and Sub systems (1, 2) with bus size of 270 and 444 buses. Along with achieving complete observability analysis, single PMU loss condition is also achieved.

• Journal of Mechanical Science and Technology
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• v.20 no.6
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• pp.864-873
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• 2006

As fuel cells approach commercialization, hydrogen production becomes a critical step in the overall energy conversion pathway. Reforming is a process that produces a hydrogen-rich gas from hydrocarbon fuels. Hydrogen production via autothermal reforming (ATR) is particularly attractive for applications that demand a quick start-up and response time in a compact size. However, further research is required to optimize the performance of autothermal reformers and accurate models of reactor performance must be developed and validated. The design includes the requirement of accommodating a wide range of experimental set ups. Factors considered in the design of the reformer are capability to use multiple fuels, ability to vary stoichiometry, precise temperature and pressure control, implementation of enhancement methods, capability to implement variable catalyst positions and catalyst arrangement, ability to monitor and change reactant mixing, and proper implementation of data acquisition. A model of the system was first developed in order to calculate flowrates, heating, space velocity, and other important parameters needed to select the hardware that comprises the reformer. Predicted performance will be compared to actual data once the reformer construction is completed. This comparison will quantify the accuracy of the model and should point to areas where further model development is required. The end result will be a research tool that allows engineers to optimize hydrogen production via autothermal reformation.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.91-105
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• 2019

The paper aims to combine balance sheet analysis at the firm level with the International Monetary Fund's public debt sustainability assessment framework to assess state-owned enterprises' (SOE) leverage as a contingent liability to the public sector. Based on company data and the interest coverage ratio as a measure of debt at risk, aggregate baseline scenarios are projected to gauge the magnitude of SOE debt as a contingency. SOE's financial and debt ratios are first bootstrapped to generate firm-level distributions and then averaged into a fan chart of the economy-wide SOE contingent liability. Applied to the People's Republic of China as an example, the study finds that by the end of 2015 SOE leverage had grown to a substantial liability. However arbitrary the assumptions underlying these projections, it would appear that even if authorities had to mop up as much as 20% of SOE debt at risk gone bad, this would have been manageable at roughly 2.7% of the gross domestic product in 2016 or 5.5% by 2021. This projection framework is fully amenable to alternative assumptions and settings, which makes it a useful analytical tool to monitor contingent liabilities from non-financial corporate debt that have been building in emerging and advanced economies alike.

• Structural Monitoring and Maintenance
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• v.2 no.2
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• pp.95-113
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• 2015

The knowledge of the behavior of any roller compacted concrete (RCC) dam and its foundation is gained by studying the service action of the dam and its foundation using measurements of an external and internal nature. The information by which a continuing assurance of structural safety of the RCC dam can be gauged is of primary importance. Similarly, the fact that the information on structural and thermal behavior and the properties of concrete that may be used to give added criteria for use in the design of future RCC dams is of secondary importance. Wide spread attention is now being given to the installation of more expensive instrumentation for studying the behavior of concrete dams and reservoirs and forecasting of any adverse trends. In view of this, the paper traces installation and need of the comprehensive instrumentation scheme implemented to monitor the structural and thermal behavior of 102.4 m high RCC dam constructed near Mumbai in India. An attempt is made in the present paper to emphasize the need to undertake an instrumentation program and evaluate their performance during construction and post construction stage of RCC structures. Few typical results, regarding the thermal and structural behavior of the dam, obtained through instrumentation installed at the dam site are presented and compared with the design considerations. The fair agreement is seen in the response observed through instrumentation with that governing the design criteria.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.352-357
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• 2001

This study presents an analysis of healthcare quality indicators using data mining for developing quality improvement strategies. Specifically, important factors influencing the inpatient mortality were identified using a decision tree method for data mining based on 8,405 patients who were discharged from the study hospital during the period of December 1, 2000 and January 31, 2001. Important factors for the inpatient mortality were length of stay, disease classes, discharge departments, and age groups. The optimum range of target group in inpatient healthcare quality indicators were identified from the gains chart. In addition, a decision support system was developed to analyze and monitor trends of quality indicators using Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. In the future, other quality indicators should be analyze to effectively support a hospital-wide continuous quality improvement (CQI) activity and the decision support system should be well integrated with the hospital OCS (Order Communication System) to support concurrent review.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1553-1561
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• 2024

Nondestructive radiography using cosmic ray muons has been used for decades to monitor nuclear reactor and spent nuclear fuel storage. Because nuclear fuel assemblies are highly dense and large, typical radiation probes such as x-rays cannot penetrate these target imaging objects. Although cosmic ray muons are highly penetrative for nuclear fuels as a result of their relatively high energy, the wide application of muon tomography is limited because of naturally low cosmic ray muon flux. This work presents a new image reconstruction algorithm to maximize the utility of cosmic ray muon in tomography applications. Muon momentum information is used to improve imaging resolution, as well as muon scattering angle. In this work, a new convolution was introduced known as M-value, which is a mathematical integration of two measured quantities: scattering angle and momentum. It captures the objects' quantity and density in a way that is easy to use with image reconstruction algorithms. The results demonstrate how to reconstruct images when muon momentum measurements are included in a typical muon scattering tomography algorithm. Using M-value improves muon tomography image resolution by replacing the scattering angle value without increasing computation costs. This new algorithm is projected to be a standard nondestructive radiography technique for spent nuclear fuel and nuclear material management.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.27-32
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• 1997

Continual monitoring of abnormal operating conditions i a key issue in maintaining high product quality and safe operation, since the undetected process abnormality may lead to the undesirable operations, finally producing low quality products, or breakdown of equipment. The statistical projection method recently highlighted has the advantage of easily building reference model with the historical measurement data in the statistically in-control state and not requiring any detailed mathematical model or knowledge-base of process. As the complexity of process increases, however, we have more measurement variables and recycle streams. This situation may not only result in the frequent occurrence of process Perturbation, but make it difficult to pinpoint trouble-making causes or at most assignable source unit due to the confusing candidates. Consequently, an ad hoc skill to monitor and diagnose in plat-wide scale is needed. In this paper, we propose a hierarchical plant-wide monitoring methodology based on hierarchical decomposition and principal component analysis for handling the complexity and interactions among process units. This have the effect of preventing special events in a specific sub-block from propagating to other sub-blocks or at least delaying the transfer of undesired state, and so make it possible to quickly detect and diagnose the process malfunctions. To prove the performance of the proposed methodology, we simulate the Tennessee Eastman benchmark process which is operated continuously with 41 measurement variables of five major units. Simulation results have shown that the proposed methodology offers a fast and reliable monitoring and diagnosis for a large scale chemical plant.