• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.2
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• pp.139-148
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• 2008

The direct inspection of the outward aspects by field engineers is the important and critical part for structural safety assessment according to the related reports. This study presents an improved method of the state assessment for concrete floor slab by separating and evaluating the individual damage types. First, the various types of damage symptoms are separated, which have been included and dealt in a group. Secondly, they are weighted and scored independently based on the present guide and references. Overall procedures other than the above are retained as same as possible to avoid the confusion. The proposed method is applied and tested to a performed assessment project for a bridge for validation. The result shows that it is reasonable and applicable in respect that it is able to make up for the controversial points of the present guide revealed in practices. Careful check of excessively deteriorated parts in addition to the reasonable assessment of system by this method grants the structural repair and reinforcement propriety and economy, and assures of more safety. Twofold appraisal of this approach expands the applicable areas of value engineering to the structural maintenance.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.130-139
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• 2024

Artificial intelligence models are being used to detect facility anomalies using physics data such as vibration, current, and temperature for predictive maintenance in the manufacturing industry. Since the types of facility anomalies, such as facility defects and failures, anomaly detection methods using autoencoder-based unsupervised learning models have been mainly applied. Normal or abnormal facility conditions can be effectively classified using the reconstruction error of the autoencoder, but there is a limit to identifying facility anomalies specifically. When facility anomalies such as unbalance, misalignment, and looseness occur, the facility vibration frequency shows a pattern different from the normal state in a specific frequency range. This paper presents an N-segmentation anomaly detection method that performs anomaly detection by dividing the entire vibration frequency range into N regions. Experiments on nine kinds of anomaly data with different frequencies and amplitudes using vibration data from a compressor showed better performance when N-segmentation was applied. The proposed method helps materialize them after detecting facility anomalies.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.149-157
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• 2011

In this paper, we propose a new cardiac disorder classification method using an support vector machine (SVM) to combine hidden Markov model (HMM) and murmur existence information. Using cepstral features and the HMM Viterbi algorithm, we segment input heart sound signals into HMM states for each cardiac disorder model and compute log-likelihood (score) for every state in the model. To exploit the temporal position characteristics of murmur signals, we divide the input signals into two subbands and compute murmur probability of every subband of each frame, and obtain the murmur score for each state by using the state segmentation information obtained from the Viterbi algorithm. With an input vector containing the HMM state scores and the murmur scores for all cardiac disorder models, SVM finally decides the cardiac disorder category. In cardiac disorder classification experimental results, the proposed method shows the relatively improvement rate of 20.4 % compared to the HMM-based classifier with the conventional cepstral features.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.621-635
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• 2023

The assessment of structural condition is a crucial process for evaluating its usability and determining the diagnostic cycle. The currently employed manpower-based methods suffer from issues related to safety, efficiency, and objectivity. To address these concerns, research based on deep learning using images is being conducted. However, acquiring structural damage data is challenging, making it difficult to construct a substantial amount of training data, thus limiting the effectiveness of deep learning-based condition assessment. In this study, we propose a foundation model-based 2-step structural damage analysis to overcome the lack of training data in image-based structural condition assessments. We subdivided the elements of structural condition assessment into instantiation and quantification. In the quantification step, we applied a foundation model for image segmentation. Our method demonstrated a 10%-point increase in mean intersection over union compared to conventional image segmentation techniques, with a notable 40%-point improvement in the case of rebar exposure. We anticipate that our proposed approach will enhance performance in domains where acquiring training data is challenging.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2072-2078
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• 2011

In photovoltaic(PV) system, for obtaining maximum efficiency of solar power systems, the solar tracking system must be controlled to match position of the sun. In this paper, we design the solar tracking system to track movement of the sun using CdS sensor modules and to determine direction of the sun under shadow of directions. In addition, for an intelligent computation in tracking of the sun, a fuzzy controller is allocated to space avaliable for splitting area of fuzzy part for the fuzzy input space(grid-type fuzzy partition) in which a fuzzy grid partition divides fuzzy rules bases. As well, a simple model of solar tracking system is designed by two-axis motor control systems and the 8-direction sensor module that can measure shadow from CdS sensor modules by matching of axis of CdS modules and PV panels. We demonstrate this systems is effective for fixed location and moving vessels and our fuzzy controller can track the satisfactorily.

• Korean Journal of Optics and Photonics
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• v.8 no.6
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• pp.486-491
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• 1997

A division-of-amplitude type photopolarimeter has been constructed for the analysis of the dynamic optical characteristics of liquid crystal panels, one of the essential components of liquid crystal displays. In this instrument an incoming light ray, whose state of polarization is to be determined, is divided into three rays of nearly same intensities and of identical polarization state by using NPBS'(non-polarizing beam splitters). Each of the three rays is further divided into two components of orthogonal polarization states by using a PBS(polarizing cube beamsplitter) or by using a combination of a quater wave plate followed by a PBS. The intensity of each ray is measured by using a photodiode to produce a set of six photo-signals, which in turn are converted into four Stokes parameters describing the state of polarization of the incoming ray. Performance test of the insrument shows that its time resolution is 80 $mutextrm{s}$, accuracy $\pm$0.3 degrees when the state of polarization of the incoming ray is representated on the Poincare sphere.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3
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• pp.90-95
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• 1998

본 논문에서는 CHMM인 CDHMM과 ARHMM을 이용하여 화자적응화 하는 방법을 각각 연구하였다. CDHMM에서는 최대사후화확률 추정법에 의하여 각 상태마다 하나의 가 지를 이용하여 화자에 적응시킨다. 본 논문에서는 음성의 다양한 음향학적 특징을 표현하기 위하여 상태마다 여러 개의 가지를 갖는 방법을 제안하였다. 상태마다의 적절한 가지 수를 결정하기 위하여 각 상태에 속하는 프레임 수와 특징 벡터들의 분산행렬의 행렬식값을 이용 하였다. ARHMM에서는 특징벡터로 선형예측계수를 사용하기 때문에 최대사후화확률 추정 법을 사용할 수 없게 된다. 따라서 화자독립모델을 이용하여 적응화자에 대한 음성을 Viterbi 알고리듬으로 상태별로 분할한 후 k-means 알고리듬을 이용하여 각 상태마다 하나 의 가지를 갖는 모델로 적응시키는 방법을 제안하였다.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.7
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• pp.760-764
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• 2015

Wireless sensors, installed on machinery, and Time Division Multiple Access (TDMA) transmission make an ideal system for monitoring machine conditions in industrial plants because there is no need for electronic wiring. However, there has not yet been a successful field application of such a system, capable of continuously transmitting data at sample rates greater than 100 Hz. In this research, a TDMA network protocol capable of acquiring data from multiple sensors at sample rates greater than 100 Hz was developed for field application. The protocol was implemented in a single cluster-star topology network, and the system was evaluated based on the node number and transmission distance. Network simulator 2 (ns-2) was used for a real field simulation. Non-TDMA and TDMA protocol cases were compared using four sensor nodes. In the cases of 20-s and 40-s transmission times, there was little difference between the reception rates of the non-TDMA and TDMA systems. However, the difference was much greater when using a 60-s transmission time.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1970_1971
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• 2009

한의학에서 혀는 장부의 건강 상태를 표면적으로 보여주는 중요한 요소 중의 하나이다. 특히 장부가 혀의 영역에 연결이 되어 각 장부의 특성을 파악하는데 매우 요긴하게 사용되고 있다. 이 연구에서는 비침습적으로 카메라와 조명 장치를 이용한 설진기를 이용하여 객관적으로 혀 영역을 촬영하고 진단을 위한 혀 영역의 객관적인 지표를 자동으로 찾는 방법을 개발하는 것을 목표로 한다. 이를 위해서 가장 중요한 일은 혀의 컬러 요소를 파악하여 정확한 위치를 찾아내는 것이다. 컬러를 색상, 채도, 명암으로 분해하고 지역 영역의 히스토그램을 분석하여 분할 임계값을 선택, 전체 영역을 분할한다. 결론적으로 이 방법은 설태가 있는 영역을 찾아내고 설태의 종류를 구분하는 방법을 제안하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.77-79
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• 2000

공간 데이터베이스에서의 질의에 대한 선택률 추정에 대해서는 많은 연구가 있었지만 공간 데이터베이스에서의 공간 질의에 대한 선택률 추정이 매우 중요함에도 불구하고 이에 대한 연구는 아직 미흡한 상태이다. 이 논문에서는 공간 검색 조건의 정확한 선택률 추정을 위해 공간 데이터 분포를 통계 데이터로 저장하고 이를 이용하여 선택률을 추정하는 방법을 제안하고 구현하였다. 공간 질의에 대한 선택률 추정을 위해서 기존의 통계 데이터를 작성하는 방법으로 균등 분할 방법과 비균등 분할 방법이 사용되고 있지만 보다 정확한 선택률을 추정하기 위해서 본 논문에서는 새로운 통계 데이터 작성 방법인 크기별 분할 방법을 제안하였다. 각 방법의 성능은 다양한 파라미터에 대한 선택률 오차를 산출하여 평가하였다.