• Korean Journal of Remote Sensing
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• v.23 no.3
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• pp.181-188
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• 2007

The objective of this research was to investigate the optimal land cover classification algorithm for the monitoring of North Korea with MODIS multi-temporal data based on monthly phenological characteristics. Three frequently used land cover classification algorithms, ISODATA1), SMA2), and SOM3) were employed for this study; the land cover categories were forest, grass, agricultural, wetland, barren, built-up, and water body. The outcomes of the study can be summarized as follows. First, the overall classification accuracy of ISODATA, SMA, and SOM was 69.03%, 64.28%, and 73.57%, respectively. Second, ISODATA and SMA resulted in a higher classification accuracy of forest and agricultural categories, but SOM performed better for the built-up area, bare soil, grassland, and water. A possible explanation for this difference would be related to the difference of sensitivity against the vegetation activity. This would be related to the capability of SOM to express all of their values without any loss of data by maintaining the topology between pixels of primitive data after classification, while ISODATA and SMA retain limited amount of data after normalization process. Third, we can conclude that SOM is the best algorithm for monitoring the land cover change of North Korea.

• Journal of IKEEE
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• v.23 no.2
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• pp.580-585
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• 2019

Batteries are being used in ESS, electric vehicles and uninterruptible power backup systems. Lead-acid batteries are the most used batteries for high capacity power back up equipment due to their high reliability and low price advantages. It is very important to estimate the chargeable capacity(SoH), and many algorithms were proposed to estimate the internal resistance of the battery. In this paper, the Battery Monitoring System(BMS) for high capacity uninterruptible power supply for IDC is proposed. A simple algorithm for estimating internal resistance was proposed. An computational block diagram of the proposed signal processing algorithm and BMS system configuration of CPU and analog circuit were shown. The proposed method was proved useful by presenting data examples of application to actual IDC sites.

• Journal of Platform Technology
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• v.6 no.4
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• pp.41-48
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• 2018

Accidents involving infants and toddlers are occurring frequently, and if elementary measures are not smooth, they can lead to even greater accidents. Rapid elementary measures require an appropriate monitoring system, and it is necessary to build a system that can accurately monitor the child's living condition and notify the emergency situation immediately. Recently, with the development of IoT technology, various types of sensors are being developed in a very small size, and development of wearable devices connected with smart phones is accelerating with the development of smart phones. By using these wearable devices, it is possible to reduce the risk of infant accidents and to respond promptly in case of an accident. In this paper, we propose a wearable system that can monitor the infant condition and present a service to prevent infant accidents.

• Structural Monitoring and Maintenance
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• v.8 no.4
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• Smart Structures and Systems
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• v.28 no.6
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• pp.827-838
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• 2021

The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

• Korean Journal of Applied Biomechanics
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• v.18 no.2
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• pp.59-64
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• 2008

D. W. KANG, J. S. CHOI, and G. R. TACK, A Study on Real-Time Sports Activity Classification & Monitoring Using a Tri-axial Accelerometer. Korean Jouranl of Sport Biomechanics, Vol. 18, No. 2, pp. 59-64, 2008. This study was conducted to study the real-time sports activity classification and monitoring using single waist mounted tri-axial accelerometer. This monitoring system detects events of sports activities such as walking, running, cycling, transitions between movements, resting and emergency event of falls. Accelerometer module was developed small and easily attachable on waist using wireless communication system which does not constrain sports activities. The sensor signal was transferred to PC and each movement pattern was classified using the developed algorithm in real-time environment. To evaluate proposed algorithm, experiment was performed with several sports activities such as walking, running, cycling movement for 100sec each and falls, transition movements(sit to stand, lie to stand, stand to sit, lie to sit, stand to lie and sit to lie) for 20 times each with 5 healthy subjects. The results showed that successful detection rate of the system for all activities was 95.4%. In this study, through sports activity monitoring. it was possible to classify accurate sports activities and to notify emergency event such as falls. For further study, the accurate energy consumption algorithm for each sports activity is under development.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.289-291
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• 2005

Even though a lot of routing algorithms have been proposed, an omnipotent algorithm of routing technique, which has optimal efficiency, does not exist. Therefore, A routing algorithm in a sensor network is an application oriented; the best effective routing algorithm depends on which application it is used to. In this paper, the routing algorithm is proposed for the purpose of monitoring a movement of Assets in office. This Paper proposes a new multi-hop routing algorithm, that is, RSS(Received Signal Strength) value which was used in a localization of sensor network is applied to routing algorithm.

• Convergence Security Journal
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• v.12 no.1
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• pp.49-54
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• 2012

Special applications designed for smart phone, so called "Apps" are rapidly emerging as unique and effective sources of environmental monitoring tools. Using the advantages of Information and Communication Technology (ICT), this paper propose an application that provides Indoor Gas Monitoring System. In this paper, use four wireless gas sensor modules to acquire sensors data wirelessly coupled with the advantages of existing portable smart device based on Android platform to display the real-time data from the sensor modules. Additionally, this paper adapts a simple gas classification algorithm to inform in-door Gas for users real-time based.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.2
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• pp.84-91
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• 2014

This paper introduces the application of supervisory monitoring system for substation automation based on IEC 61850. The objective of proposed system is detection of such a malfunction or degradation of devices. The supervisory monitoring procedure consists of a two step - topology processor and state estimation. The topology processor using artificial intelligence is a preprocessing step of state estimation. Topology processor identifies the topology structure of switches in substation and detects an error of ON/OFF state data. The state estimation is an algorithm that minimizes an error between optimal estimation values and real values. The proposed system is applied to standard digital substation based on IEC 61850 for performance verification.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.350-354
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• 1995

The Tension Leveller of Cold Rolling Mill In POSCO performs levelling the strip in high speed line. But minor variations in operating condition of driving machines such as motor, gear box, and support bearings, a small gap-variation of supporter and strip slip by poor roll revolutions can cause serious problems in the quality of strip. In this study, firstly, A condition monitoring standard for each sensor is made through with the detail analysis of vibration and strip slip. Secondly, An automatic monitoring and diagnosing system was developed to monitor the condition of Tension Leveller, and diagnose the cause of abnormal condition. Finally, A diagnosing algorithm for abnormal condition and man-machine interface (MMI) for easy operation are developed.