• Architectural research
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• 제13권4호
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• pp.53-60
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• 2011

Damage detection algorithms based on a one-dimensional beam model can detect damage within a beam span caused by flexure only but cannot detect damage at a joint with prescribed boundary conditions or at the middle part of a beam section where the neutral axis is located. Considering the damage at a welded joint of beam elements in steel structures and modeling the damage with twodimensional plane elements, this study presents a new approach to detecting damage in the depth direction of the joint and beam section. Three damage scenarios at the upper, middle, and lower parts of a welded joint of a rectangular symmetric section are investigated. The damage is detected by evaluating the difference in the receptance magnitude between the undamaged and damaged states. This study also investigates the effect of measurement locations and noise on the capability of the method in detecting damage. The numerical results show the validity of the proposed method in detecting damage at the beam's welded joint.

• Asian Journal of Atmospheric Environment
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• 제11권4호
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• pp.283-299
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• 2017

An analytical method using high-performance liquid chromatography (HPLC) with fluorescence (FL) detection was developed for simultaneously analyzing 10 polycyclic aromatic hydrocarbons (PAHs) and 18 nitro-derivatives of PAHs (NPAHs). The two-dimensional HPLC system consists of an on-line clean-up and reduction for NPAHs in the 1st dimension, and separation of the PAHs and the reduced NPAHs and their FL detection in the 2nd dimension after column-switching. To identify an ideal clean-up column for removing sample matrix that may interfere with detection of the analytes, the characteristics of 8 reversed-phase columns were evaluated. The nitrophenylethyl (NPE)-bonded silica column was selected because of its shorter elution band and larger retention factors of the analytes due to strong dipole-dipole interactions. The amino-substituted PAHs (reduced NPAHs), PAHs and deuterated internal standards were separated on polymeric octadecyl-bonded silica (ODS) columns and by dual-channel detection within 120 min including clean-up and reduction steps. The limits of detection were 0.1-9.2 pg per injection for PAHs and 0.1-140 pg per injection for NPAHs. For validation, the method was applied to analyze crude extracts of fine particulate matter ($PM_{2.5}$) samples and achieved good analytical precision and accuracy. Moreover, the standard reference material (SRM1649b, urban dust) was analyzed by this method and the observed concentrations of PAHs and NPAHs were similar to those in previous reports. Thus, the method developed here-in has the potential to become a standard HPLC-based method, especially for NPAHs.

• 한국가시화정보학회:학술대회논문집
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• 한국가시화정보학회 2001년도 Proceedings of 2001 Korea-Japan Joint Seminar on Particle Image Velocimetry
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• pp.100-107
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• 2001

A simple new technique of particle depth position measurement, which can be applied for three-dimensional velocity measurement of fluid flows, is proposed. Two color illumination system that intensity is encoded as a function of z-coordinate is introduced. A calibration procedure is described and a profile of small sphere is detected by using the present method as preliminary test. Then, this method is applied to three-dimensional velocity field measurement of simple flow fields seeded with tracer particles. The motion of the particles is recorded by color 3CCD camera. The particle position in the image plane is read directly from the recorded image and the depth of each particle is measured by calculation of the intensity ratio of encoded two color illumination. Therefore three-dimensional velocity components are reconstructed. Although the result includes to some extent error, the feasibility of the present technique for three-dimensional velocity measurement was confirmed.

• Bulletin of the Korean Chemical Society
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• 제33권10호
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• pp.3391-3396
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• 2012

Two-dimensional infrared (2D-IR) spectroscopy can probe the fast structural evolution of molecules under thermal equilibrium. Vibrational frequency fluctuation caused by structural evolution produced the time-dependent line shape change in 2D-IR spectrum. A variety of methods has been used to connect the evolution of 2D-IR spectrum with Frequency-Frequency Correlation Function (FFCF), which connects the experimental observables to a molecular level description. Here, a new method to extract FFCF from 2D-IR spectra is described. The experimental observable is the time-dependent frequency shift of maximum peak position in the slice spectrum of 2D-IR, which is taken along the excitation frequency axis. The direct relation between the 2D-IR peak shift and FFCF is proved analytically. Observing the 2D-IR peak shift does not need the full 2D-IR spectrum which covers 0-1 and 1-2 bands. Thus data collection time to determine FFCF can be reduced significantly, which helps the detection of transient species.

• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.989-995
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• 2015

Due to the recent increase of the importance and demand of security services, the importance of a surveillance monitor system that makes an automatic security system possible is increasing. As the market for surveillance monitor systems is growing, price competitiveness is becoming important. As a result of this trend, surveillance monitor systems based on an embedded system are widely used. In this paper, an object detection algorithm based on an embedded system for a surveillance monitor system is introduced. To apply the object detection algorithm to the embedded system, the most important issue is the efficient use of resources, such as memory and processors. Therefore, designing an appropriate algorithm considering the limit of resources is required. The proposed algorithm uses two background models; therefore, the embedded system is designed to have two independent processors. One processor checks the sub-background models for if there are any changes with high update frequency, and another processor makes the main background model, which is used for object detection. In this way, a background model will be made with images that have no objects to detect and improve the object detection performance. The object detection algorithm utilizes one-dimensional histogram distribution, which makes the detection faster. The proposed object detection algorithm works fast and accurately even in a low-priced embedded system.

• 대한전자공학회논문지TC
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• 제49권7호
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• pp.1-5
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• 2012

자기 저장장치의 한계가 보이는 현 시점에서 홀로그래픽 저장장치는 빠른 데이터 전송율과 높은 기록밀도를 가지고 차세대 광 저장장치의 매력적인 후보로 떠오르고 있다. 본 논문에서는 HDSS (Holographic data storage system)의 채널 환경에서 발생하는 2차원 심볼간 간섭효과와 픽셀 어긋남 문제로 인해 발생하는 비트 오검출 문제를 효율적으로 해결하기 위해서 축약 사상 이론 (contraction mapping theorem) 기반의 반복 2차원 등화 기법을 제안한다. 제안하는 기법의 성능을 평가하기 위해 다양한 홀로그래픽 채널 환경을 구성하고 모의 실험을 수행하여 제안하는 기법의 BER 성능을 측정하여 기존의 threshold detection 기법과 비교함으로써 제안 기법의 우수성을 확인하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권2호
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• pp.99-104
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• 2009

The turn-to-turn short is one major fault of the motor faults of BLDC motors and can appear frequently. When the fault happens, the motor can be operated without breakdown, but it is necessary to maintain the motor for continuous working. In past research, several methods have been applied to detect winding faults. The representative approaches have been focusing on current signals, which can give important information to extract features and to detect faults. In this study, current sensors were installed to measure signals for fault detection of BLDC motors. In this study, the Park's vector method was used to extract the features and to isolate the faults from the current measured by sensors. Because this method can consider the three-phase current values, it is useful to detect features from one-phase and three-phase faults. After extracting two-dimensional features, the final feature was generated by using the two-dimensional values using the distance equation. The values were used in fuzzy similarity to isolate the faults. Fuzzy similarity is an available tool to diagnose the fault without model generation and the fault was converted to the percentage value that can be considered as possibility of the fault.

• Ocean Systems Engineering
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• 제6권3호
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• pp.217-231
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• 2016

This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

• 산업경영시스템학회지
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• 제44권4호
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• 한국정보통신학회논문지
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• 제12권11호
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• pp.2050-2056
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• 2008

본 논문은 스테레오 라인 CCD와 광원을 이용한 2차원 평면에서 이동객체를 인식하고 이동경로를 추적하는 시스템 구현이다. 시스템 구현은 카메라 이미지를 직접 처리하는 대신 두개의 라인 CCD 센서와 입력된 라인 이미지의 밝기를 비교하여 2차원 거리를 측정한다. 알고리듬은 이동객체감지, 경로추적과 좌표변환 기법을 적용한다. 객체의 이동경로를 효과적으로 감지하기 위하여 측정된 거리의 신뢰성을 평가하는 알고리즘을 개발하였다. 시스템을 구현하여 실험한 결과 5mm 인식율과 100ms 주기 이상의 이동객체경로 추적이 가능하였다.