• Nuclear Engineering and Technology
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• v.36 no.5
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• pp.420-429
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• 2004

The local power density should be estimated accurately to prevent fuel rod melting. The local power density at the hottest part of a hot fuel rod, which is described by the power peaking factor, is more important information than the local power density at any other position in a reactor core. Therefore, in this work, the power peaking factor, which is defined as the highest local power density to the average power density in a reactor core, is estimated by fuzzy neural networks using numerous measured signals of the reactor coolant system. The fuzzy neural networks are trained using a training data set and are verified with another test data set. They are then applied to the first fuel cycle of Yonggwang nuclear power plant unit 3. The estimation accuracy of the power peaking factor is 0.45% based on the relative $2_{\sigma}$ error by using the fuzzy neural networks without the in-core neutron flux sensors signals input. A value of 0.23% is obtained with the in-core neutron flux sensors signals, which is sufficiently accurate for use in local power density monitoring.

• Nuclear Engineering and Technology
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• v.41 no.9
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• pp.1181-1190
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• 2009

Knowing more about the Local Power Density (LPD) at the hottest part of a nuclear reactor core can provide more important information than knowledge of the LPD at any other position. The LPD at the hottest part needs to be estimated accurately in order to prevent the fuel rod from melting in a nuclear reactor. Support Vector Machines (SVMs) have successfully been applied in classification and regression problems. Therefore, in this paper, the power peaking factor, which is defined as the highest LPD to the average power density in a reactor core, was estimated by SVMs which use numerous measured signals of the reactor coolant system. The SVM models were developed by using a training data set and validated by an independent test data set. The SVM models' uncertainty was analyzed by using 100 sampled training data sets and verification data sets. The prediction intervals were very small, which means that the predicted values were very accurate. The predicted values were then applied to the first fuel cycle of the Yonggwang Nuclear Power Plant Unit 3. The root mean squared error was approximately 0.15%, which is accurate enough for use in LPD monitoring and for core protection that uses LPD estimation.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.6
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• pp.571-581
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• 2015

Soil moisture content is generally accepted as an important factor to understand the process of crop growth and is the basis of earth system models for analysis and prediction of the crop condition. To continuously monitor soil moisture changes at kilometer scale, it is demanded to create high resolution data from the current, several tens of kilometers. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Soil Moisture Content (SMC) from 10 km to 30 m resolution using a soil texture and field measurements that have a high correlation with the SMC. As a result, the soil moisture variations of both data (before and after downscaling) were identical, and the Root Mean Square Error (RMSE) of SMC exhibited the low values. Also, time series analyses showed that three kinds of SMC data (field measurement, original AMSR2, and downscaled AMSR2) had very similar temporal variations. Our method can be applied to downscaling of other soil variables and can contribute to monitoring small-scale changes of soil moisture by providing high resolution data.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.2
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• pp.245-254
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• 2021

The intelligent control algorithm based on the real-time biological monitoring system has been emphasized to enhance the survivability of the combat warrior in the future combat fields. In this study, AHP(Analytic Hierarchy Process) method was deployed to categorize the factors related to the improvement of survivability, then to determine the relative importances between them. As the details of the research process, the historical survivability determinants were firstly categorized, which was nextly judged their relative importance by the experts in the actual fileds through the survey of AHP. In this process, the consistency of the survey was investigated to filter out the error. As a result, the global priority of factors can be acquired to establish the optimized operational concepts in the intelligent warrior platform.

• Journal of the Korea Safety Management & Science
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• v.25 no.4
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• pp.87-94
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• 2023

This study analyzed and identified various causes of caustic alarms of 163 fire detectors that occurred from January 2019 to December 2021 at domestic semiconductor manufacturing plants equipped with about 30,000 fire detectors, and proposed a new non-fire prevention cause investigation plan by applying the NFPA 921 scientific methodology. The results of the study are as follows. First, in terms of necessary recognition and problem definition, an analog detector and an integrated monitoring system were proposed to quickly determine the location and installation space information of the fire detector. Second, in order to prevent speculative causes and errors in various analyses in terms of data analysis and hypothesis establishment, non-fire reports were classified into five by factor and defined, and the causes of occurrence by factor were classified and proposed. Finally, in terms of hypothesis verification and final hypothesis selection, a non-fire prevention improvement termination process and a final hypothesis verification sheet were proposed to prevent the cause from causing re-error.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.3
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• pp.331-339
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• 2024

Reliable and precise indoor localization is crucial for personal navigation, emergency rescue, and monitoring workers indoors. To use this technology in different applications, it is important to make it less dependent on infrastructure and to keep the error as small as possible. Fingerprinting stands out as a popular choice for indoor positioning because it leverages existing infrastructure and works with just a smartphone. However, its accuracy heavily relies on the quality of that infrastructure. For instance, having too few access points or beacons can greatly reduce its effectiveness. To reduce dependence on RF infrastructure, we have developed surface correlation (SC) using accumulated Received Signal Strength Indicator (RSSI) signals This approach constructs a user mask for radio map comparisons using an accumulated RSSI vector and the trajectory of the user, which is estimated through PDR. The location with the highest correlation is considered as the user's position after comparison. Through a simulation, the performance of short RSSI vector-based technology and SC is analyzed, and future directions for the development of SC are discussed.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1037-1051
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• 2020

The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.73-80
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• 2004

Recently, many maritime accidents have been increased and the collisions due to human error are given a great deal of proportions out if them We develop the Real-time Collision Risk Monitoring System (CRMS) for the navigational officers to cope with the emergency situation promptly and thus to reduce the probability if casualty. In this study, the risk of collision is evaluated by two kinds if method. The first method is based on Fuzzy algorithm, which evaluates the risk of collision between traffic ships. The second method is based on Environmental Stress (ES) Model, where the total risk if collision is evaluated by the environmental stress felt by human. The developed real-time CRMS has been installed to the ship handling simulator system and its capabilities have been tested through simulator experiments.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.507-514
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• 2015

The Spatial information research institute of the LX Korea land and geospatial informatix corporation manages infrastructure for the LX global navigation satellite system (GNSS), which comprises 30 monitoring stations nationwide. Since 2014, it has conducted network real-time kinematic (RTK) tests using the master-auxiliary concept (MAC). This study introduces the infrastructure of LX GNSS and presents the results of a performance analysis of the LX RTK service. The analysis was based on a total of 25 cadastral topographic control points in Jeonju, Seoul, and Incheon. For each point, performance was measured over one observation, two repeated observations, and five repeated observations. The measurements obtained from LX MAC and the VRS of the National Geographic Information Institute were compared with the announced coordinates derived from cadastral topographic control points. As a result, the two systems were found to have similar performance with average error and standard deviation differing only by 1 to 2 cm.

• Journal of IKEEE
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• v.23 no.4
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• pp.1122-1127
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• 2019

In this study, the bio-impedance of the human body is able to obtain a lot of information by monitoring the pathological and physiological conditions of clinical and biological tissues. The four electrode method system for biometrics measured the potential difference between two electrodes and the other two electrodes were used as electrodes for current flow. The newly developed dry gold electrode measured impedance from 1 Hz to 50 kHz and produced reproducible results. To verify the impedance measurement of the dry electrode, the pitting was performed using an equivalent circuit model of the bioelectrode skin, and the effectiveness was demonstrated through modeling. Fixed electrode types have a constant position of the electrodes attached during the measurement, so that a stable measurement can be obtained, thereby minimizing the error.