• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.4
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• pp.283-289
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• 2016

Islanding protection of a grid-connected photovoltaic (PV) inverter is a key function for standards compliance. Unintentional islanding results in safety hazards, reliability, and many other issues. Therefore, many anti-islanding schemes have been examined. However, existing anti-islanding schemes have poor power quality and non-detection zone issues. Moreover, most schemes have problems that deteriorate the performance of islanding detection under parallel operation. Therefore, this paper proposes a novel anti-islanding scheme that has negligible power quality degradation and has no non-detection zone and islanding detection under a parallel operation. Both simulation and experimental results validate the proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.912-928
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• 2019

Crowd behavior analysis research has revealed a central role in helping people to find safety hazards or crime optimistic forecast. Thus, it is significant in the future video surveillance systems. Recently, the growing demand for safety monitoring has changed the awareness of video surveillance studies from analysis of individuals behavior to group behavior. Group detection is the process before crowd behavior analysis, which separates scene of individuals in a crowd into respective groups by understanding their complex relations. Most existing studies on group detection are scene-specific. Crowds with various densities, structures, and occlusion of each other are the challenges for group detection in diverse crowded scenes. Therefore, we propose a group detection approach called Collective Interaction Filtering to discover people motion interaction from trajectories. This approach is able to deduce people interaction with the Expectation-Maximization algorithm. The Collective Interaction Filtering approach accurately identifies groups by clustering trajectories in crowds with various densities, structures and occlusion of each other. It also tackles grouping consistency between frames. Experiments on the CUHK Crowd Dataset demonstrate that approach used in this study achieves better than previous methods which leads to latest results.

• Smart Structures and Systems
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• v.30 no.3
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• pp.303-315
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• 2022

The degradation of wheel tread may result in serious hazards in the railway operation system. Therefore, timely wheel defect diagnosis of in-service trains to avoid tragic events is of particular importance. The focus of this study is to develop a novel wheel defect detection approach based on the relevance vector machine (RVM) which enables online detection of potentially defective wheels with trackside monitoring data acquired under different running-speed conditions. With the dynamic strain responses collected by a trackside monitoring system, the cumulative Fourier amplitudes (CFA) characterizing the effect of individual wheels are extracted to formulate multiple probabilistic regression models (MPRMs) in terms of multi-kernel RVM, which accommodate both variables of vibration frequency and running speed. Compared with the general single-kernel RVM-based model, the proposed multi-kernel MPRM approach bears better local and global representation ability and generalization performance, which are prerequisite for reliable wheel defect detection by means of data acquired under different running-speed conditions. After formulating the MPRMs, we adopt a Bayesian null hypothesis indicator for wheel defect identification and quantification, and the proposed method is demonstrated by utilizing real-world monitoring data acquired by an FBG-based trackside monitoring system deployed on a high-speed trial railway. The results testify the validity of the proposed method for wheel defect detection under different running-speed conditions.

• Geophysics and Geophysical Exploration
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• v.9 no.3
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• pp.225-230
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• 2006

Fluid replacement and conductivity logging have been applied to three boreholes in coastal aquifer in order to identify permeable fractures and to estimate the origin of saline groundwater. Fluid replacement technique measures and monitors the change of borehole fluid conductivity with depth under ambient or pumping condition after replacing the original borehole fluid with different one (by pumping out original one and injecting simultaneously new one at the hole bottom). After the replacement of borehole fluid, the change of fluid conductivity can be the direct indicator of the intake flow of formation water through aquifer such as permeable fractures or porous formations. The conductivity profiles measured with times therefore indicate the locations of permeable zone or fractures within the open hole or the fully slotted casing hole. As a result of fluid conductivity logging for three boreholes at coastal area in Yeonggwang, Jeonam Province, it is interpreted that the seawater intrusion in this area is not by remnant saline groundwater after land reclamation but mainly by intrusion of saline water through fractured rock. This approach might be useful for assessing the characteristics of seawater intrusion, the design of optimal pumping, the mitigation of seawater intrusion using freshwater injection, and estimating the hydraulic characteristics in coastal aquifer.

• Journal of the Korea Society for Simulation
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• v.30 no.2
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• pp.49-64
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• 2021

M&S techniques are widely used as scientific means to systematically develop response plans to chemical and biological (CB) hazards. However, while the theoretical area of hazard dispersion modeling has achieved remarkable practical results, the operational analysis area to simulate CB hazard response plans is still in an early stage. This paper presents a model to simulate CB hazard response plans such as detection, protection, and decontamination. First, we present a possible way to display high-fidelity hazard dispersion in a combat simulation model, taking into account weather and terrain conditions. We then develop an improved vulnerability model of the combat simulation model, in order to simulate CB damage of combat simulation entities based on other casualty prediction techniques. In addition, we implement tactical behavior task models that simulate CB hazard response plans such as detection, reconnaissance, protection, and decontamination. Finally, we explore its feasibility by analyzing contamination detection effects by distributed CB detectors and decontamination effects according to the size of the {contaminated, decontamination} unit. We expect that the proposed model will be partially utilized in disaster prevention and simulation training area as well as analysis of combat effectiveness analysis of CB protection system and its operational concepts in the military area.

• Journal of the Korean Solar Energy Society
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• v.26 no.4
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• pp.17-23
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• 2006

This paper proposes a novel active frequency drift (AFD) method for the islanding prevention of grid-connected photovoltaic inverter. To detect the islanding phenomenon of grid-connected photovoltaic (PV) inverters concerning about the safety hazards and the damage to other electric equipments, many kinds of anti-islanding methods have been presented. Among them, AFD method using chopping fraction enables the islanding detection to drift up (or down) the frequency of the voltage during the islanding situation. In this paper, injecting the periodic zero current into the basic AFD method is proposed. This proposed method shows the analytical design value of cf to meet the test procedure of IEEE Std. 1547 with various load conditions. Detection of islanding is verified using simulation tool PSIM.

• Journal of Power Electronics
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• v.7 no.1
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• pp.64-71
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• 2007

This paper proposes a novel active frequency drift (AFD) method to improve the islanding detection performance with minimum current harmonics. To detect the islanding phenomenon of grid-connected photovoltaic (PV) inverters concerning the safety hazards and possible damage to other electric equipment, anti-islanding methods have been described. The AFD method that uses chopping fraction (cf) enables the islanding detection to drift up (or down) the frequency of the voltage during the islanding situation. However, the performance of the conventional AFD method is inefficient and causes difficulty in designing the appropriate cf value to meet the limit of harmonics. In this paper, the periodic chopping fraction based on a novel AFD method is proposed. This proposed method shows the analytical design value of cf to meet the test procedure of IEEE Std. 929-2000 with power quality and islanding detection time. To verify the validation of the proposed method, the islanding test results are presented. It is confirmed that the proposed method has not only less harmonic distortion but also better performance of islanding detection compared with the conventional AFD method.

• Safe Food
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• v.2 no.4
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• pp.17-22
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• 2007

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.3
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• pp.247-254
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• 2015

Unintentional islanding results in safety hazards, power quality degradation, and many other issues. Thus, islanding detection of grid-connected distributed generation system is a key function for standards compliance. Many anti-islanding schemes are currently being studied; however, existing anti-islanding schemes used in inverters have power quality degradation and non-detection zone issues. Therefore, this paper analyzes existing anti-islanding schemes by using frequency drift in accordance with both islanding detection performance and power quality. This paper also proposes a new anti-islanding scheme by using frequency drift. Both simulation and experimental results show that the proposed scheme has negligible power quality degradation and no non-detection zones compared with other existing schemes.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1705-1707
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• 2005

This paper proposes a novel active frequency drift(AFD) method for the islanding prevention of grid-connected photovoltaic inverter. To detect the islanding phenomenon of grid-connected photovoltaic(PV) inverters concerning about the safety hazards and the damage to other electric equipments, many kinds of anti-islanding methods have been presented. Among them, AFD method using chopping fraction(cf) enables the islanding detection to drift up(or down) the frequency of the voltage during the islanding situation. However, the performance of the conventional AFD methods, which have a certain value of cf only, is inefficient and difficult to design the appropriate cf value analytically to meet the limit of harmonics. In this paper, the periodic chopping fraction based on an AFD method is proposed. This proposed method shows the analytical design value of cf to meet the test procedure of IEEE Std. 929-2000 with the power quality and islanding detection time. To verify the validation of the proposed method, the islanding test results are presented. It is confirmed that the proposed method has not only less harmonic distortion but also good performance of islanding detection compare with the conventional AFD method.