• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.553-558
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• 2004

Periodic profiling by level is a conventional method for monitoring topographic changes in a specific part of tidal zone. Periodic aerial photographs are used for monitoring topographic change of broad tidal zone area. In this study, spot heights at interval of 50m on 5 profiling lines were leveled periodically for precise monitoring topographic change of tidal zone. For monitoring broad topographic change of tidal zone, aerial photographs were also taken by film camera loaded on pilotless helicopter periodically Periodic profiling shows the change of heights on the lines well. On the other hand, aerial photographs taken by film camera loaded on pilotless helicopter have some problems to detect topographic change of tidal zone precise. Because the scale and incline of the photographs were not same, it is hard to compare them. Therefore, for more precise monitoring of topographic changes in tidal zone, it is need to take aerial pictures with same scale and same incline.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.129-131
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• 2015

We have initiated single-dish monitoring observations of ~400 methanol maser sources at 6.7 GHz using the Hitachi 32-m radio telescope from December 2012 to systematically research periodic flux variations, which are observed in some methanol maser sources associated with high-mass (proto-)stars. In our monitoring, we have made daily monitoring, so that each source has been observed every nine days with an integration time of 5 min (typical $3{\sigma}$ detection sensitivities of 0.9 Jy). The monitoring observations help us statistically understand periodic flux variations with a period longer than 50 days. As an initial result, we present a new detection of periodic flux variations in the 6.7 GHz methanol maser source G 036.70+00.09. The period of the flux variations is ~53 days (~0.019 cycles $day^{-1}$), and seems to be stable over 9 cycles, at least until the middle of August 2014.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.3
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• pp.294-299
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• 2017

The aim of this study was to detect the status of epilepticus and seizure based on the initial patterns observed in the first 30 minutes of continuous electroencephalogram (cEEG) monitoring. An cEEG was recorded digitally using electrodes applied according to the International 10~20 System. The EEG data were reviewed from January 2014 to December 2015. The baselines of the EEG patterns were characterized by lateralized periodic discharges, generalized periodic discharges, burst suppression, focal epileptiform, asymmetric background, generalized slowing, and generalized periodic discharges with a triphagic wave. The etiology was classified into five categories. The subjects of this study were 128 patients (age: $56.9{\pm}17.5years$, male:female, 74:54). The mean cEEG monitoring duration was $5.5{\pm}5.1$ (min:max, 1:33) days. The EEG pattern categories included lateralized periodic discharges (N=7), generalized periodic discharges (N=10), burst suppression (N=6), focal epileptiform (N=19), asymmetric background (N=24), generalized slowing (N=51), and generalized periodic discharges with a triphagic wave (N=11). The etiological classifications of the patients with status epilepticus were remote symptomatic (N=4), remote symptomatic with acute precipitant (N=9), acute symptomatic (N=6), progressive encephalopathy (N=2), and febrile seizure (N=1). cEEG monitoring was found to be useful for the diagnosis of non-convulsive epileptic seizures or status epilepticus. The seizure was confirmed by the EEG pattern.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.321-324
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• 2014

Kwon et al. (2013) studied the optimal monitoring interval of systems with finite life cycle. It is assumed that there are several failure modes from several failure causes and the occurrence of causes follows a homogeneous Poisson process. The total expected cost is used as an optimization criterion. In this article, we derive newly the total expected cost under the same assumptions and consider some extended models.

• Structural Engineering and Mechanics
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• v.31 no.5
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• pp.527-544
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• 2009

In this study, the periodic seismic performance evaluation scheme is proposed using a structural health monitoring system in terms of seismic fragility. An instrumented highway bridge is used to demonstrate the evaluation procedure involving (1) measuring ambient vibration of a bridge under general vehicle loadings, (2) identifying modal parameters from the measured acceleration data by applying output-only modal identification method, (3) updating a preliminary finite element model (obtained from structural design drawings) with the identified modal parameters using real-coded genetic algorithm, (4) analyzing nonlinear response time histories of the structure under earthquake excitations, and finally (5) developing fragility curves represented by a log-normal distribution function using maximum likelihood estimation. It is found that the seismic fragility of a highway bridge can be updated using extracted modal parameters and can also be monitored further by utilizing the instrumented structural health monitoring system.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.2
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• pp.143-148
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• 2013

In FMEA, occurrence and detectability are not related to only failure modes itself but also their causes. It is assumed that any failure occurs after at least one cause corresponding to failure occurs in advance. Occurrence of the failure mode is described by occurrence time of its cause and elapsed time to the actual failure. Under the periodic monitoring plan, the monitoring interval is another factor to determine the detectability and occurrence of each failure mode. When a failure cause occurs, the failure does not occur if the cause is identified and remedied before it actually occurs. Under this situation, we construct an economic model for prioritizing failure modes. The loss function is based on the unfulfilled mission period. We also provide an optimal monitoring plan with an illustrative example.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.417-420
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• 2004

Recently, the applications of unmanned system are steadily increasing. Unmanned automatic system is suitable for routine mission such as reconnaissance, environment monitoring, resource conservation and investigation. Especially, for the ocean environment monitoring mission, many ocean engineers had scoped with the routine and even risky works. The automatic system can replace the periodic and routine missions: water sampling, temperature and salinity measuring, etc. In this paper, an unmanned surface vessel was designed for routine and periodic ocean environmental missions. An autonomous control system was designed and tested for the unmanned vessel. A GPS and gyro compass was used for navigation. A linear autopilot model for course control can be derived from the maneuvering model. Nomoto's 2nd-order response equation was derived. The design methodologies and performance of the surface vessel were illustrated and verified with this linearized equation of motion. A linear controller was designed and automatic route tracking performance was verified for yaw subsystem.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.83-90
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• 1999

Centralized safety stock in a periodic replenishment system which consists of one central warehouse and m regional warehouse can reduce backorders allocation the centralized safety stocks to regional warehouse in a certain instant of each replenishment cycle. If the central warehouse can not monitoring inventories in the regional warehouse, then we have to predetermine the instant of allocation according to demand distribution and this instant must be same for all different replenishment cycle. However, transition of inventory level in each cycle need not to be same, and therefore different instant of the allocation may results reduced shortage compare to the predetermined instant of allocation. In this research, we construct a dynamic model based on the assumption of monitoring inventories inventories in the regional warehouse everyday, and develop an algorithm minimize shortage in each replenishment cycle using dynamic programming approach.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1249-1252
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• 1996

With the expansion of research and development for the CIM and the IMS, the importance of introducing the communication network is being increased. This paper presents an implementation of robot workcell by using Fieldbus and investigates data operation of the robot workcell. Through experiments, the operations of periodic and real-time data, and non-periodic real-time data are studied. Also, the relationship between the network transmission rate and the monitoring results from the sensor is analyzed.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.573-587
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• 2019

A multi-temporal approach using remotely sensed time series data obtained over multiple years is a very useful method for monitoring land covers and land-cover changes. While spectral-based methods at any particular time limits the application utility due to instability of the quality of data obtained at that time, the approach based on the temporal profile can produce more accurate results since data is analyzed from a long-term perspective rather than on one point in time. In this study, a multi-temporal approach applying a multi-periodic harmonic model is proposed for classification of remotely sensed data. A harmonic model characterizes the seasonal variation of a time series by four parameters: average level, frequency, phase, and amplitude. The availability of high-quality data is very important for multi-temporal analysis.An satellite image usually have many unobserved data and bad-quality data due to the influence of observation environment and sensing system, which impede the analysis and might possibly produce inaccurate results. Harmonic analysis is also very useful for real-time data reconstruction. Multi-periodic harmonic model is applied to the reconstructed data to classify land covers and monitor land-cover change by tracking the temporal profiles. The proposed method is tested with the MODIS and GOCI NDVI time series over the Korean Peninsula for 5 years from 2012 to 2016. The results show that the multi-periodic harmonic model has a great potential for classification of land-cover types and monitoring of land-cover changes through characterizing annual temporal dynamics.