• Transactions on Electrical and Electronic Materials
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• v.9 no.1
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• pp.38-43
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• 2008

Using an arterial pressure-volume (APV) model, we performed an analysis of the conventional blood pressure estimation method using an oscillometric sphygmomanometer with computer simulation. Traditionally, the maximum amplitude algorithm (MAA) has been applied to the oscillation waveforms of the APV model to obtain the mean arterial pressure and the characteristic ratio. The estimation of mean arterial pressure and characteristic ratio was significantly affected by the shape of the blood pressure waveforms and the cutoff frequency of high-pass filter (HPF) circuitry. Experimental errors result from these effects when estimating blood pressure. To determine an algorithm independent of the influence of waveform shapes and parameters of HPF, the volume oscillation of the APV model and the phase shift of the oscillation with fast Fourier transform (FFT) were tested while increasing the cuff pressure from 1 mmHg to 200 mmHg (1 mmHg/s). The phase shift between ranges of volume oscillation was then only observed between the systolic and the diastolic blood pressures. The same results were obtained from simulations performed on two different arterial blood pressure waveforms and one hyperthermia waveform.

• Journal of Korean Society for Quality Management
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• v.44 no.4
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• pp.751-770
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• 2016

Purpose: Two-stage ${\bar{X}}$ chart is a useful tool for process control when a surrogate variable may be used together with a performance variable. This paper extends the two-stage ${\bar{X}}$ chart to a three stage version by decomposing the first stage into the preliminary stage and the main stage. Methods: The expected cost function is derived using Markov-chain approach. The optimal designs are found for numerical examples using a genetic algorithm combined with a pattern search algorithm and compared to those of the two-stage ${\bar{X}}$ chart. Sensitivity analysis is performed to see the parameter effects. Results: The proposed design outperforms the optimal design of the two-stage ${\bar{X}}$ chart in terms of the expected cost per unit time unless the correlation between the performance and surrogate variables is modest and the shift in process mean is smallish. Conclusion: Three-stage ${\bar{X}}$ chart may be a useful alternative to the two-stage ${\bar{X}}$ chart especially when the correlation between the performance and surrogate variables is relatively high and the shift in process mean is on the small side.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.381-399
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• 2004

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC re-duces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been need for an integrated process control (IPC) procedure which combines the two strategies. This paper considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process model under consideration is an IMA(1,1) model with a step shift. The EPC part of the scheme adjusts the process, while the SPC part of the scheme detects the occurrence of a special cause. For adjusting the process repeated adjustment is applied according to the predicted deviation from target. For detecting special causes the exponentially weighted moving average control chart is applied to the observed deviations. It was assumed that the adjustment under the presence of a special cause may increase the process variability or change the system gain. Reasonable choices of parameters for the IPC procedure are considered in the context of the mean squared deviation as well as the average run length.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.637-644
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• 2006

Biomedical image is often complex. An applied image analysis system should deal with the images which are of quite low quality and are challenging to segment. This paper presents a framework for color cell image segmentation by learning and classification online. It is a robust two-stage scheme using kernel method and watershed transform. In first stage, a two-class SVM is employed to discriminate the pixels of object from background; where the SVM is trained on the data which has been analyzed using the mean shift procedure. A real-time training strategy is also developed for SVM. In second stage, as the post-processing, local watershed transform is used to separate clustering cells. Comparison with the SSF (Scale space filter) and classical watershed-based algorithm (those are often employed for cell image segmentation) is given. Experimental results demonstrate that the new method is more accurate and robust than compared methods.

• Korean Journal of Occupational Health Nursing
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• v.18 no.1
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• pp.106-115
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• 2009

Purpose: Occupational stress is a determinant risk factor for cardiovascular disease and work disability. This study aims to describe occupational stress and identify its related factors among aged security guards. Methods: A random sample of 76 aged security guards were interviewed by three research assistants. The criteria of the subjects were as follows : 50 or older male with 40 or more working hours a week working with colleagues ranged from 3 to 50. The data were collected in September, 2007 and analyzed by multiple regression using SAS Version 9.1. Results: The mean score of occupational stress among aged security guards was 47.2. The mean scores of its sub-scales were 31.3(physical environment), 33.8(occupational demand), 80.8occupational control), 44.6(interpersonal conflict), 51.3 (occupational insecurity), 53.6(occupational system), 57.5(lack of reward), and 30.3(work environment). The scores of occupational control, interpersonal conflict, and occupational insecurity were higher than the scores of Korean average occupational stress sub-scales. Significant variables affecting occupational stress and its sub-scales were work place, work type, and employment type. Conclusion: In order to reduce occupational stress among security guards, sufficient occupational control and interpersonal conflict control, appropriate reward, and employment stability should be considered. Also long working hours and work shift should be improved.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.63-66
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• 2015

3차원 영상을 생성하기 위해 스테레오 매칭을 통해 깊이 정보를 획득한다. 이때 발생하는 경계영역과 텍스처가 부족한 부분의 깊이정보 부정확성 문제를 해결하기 위해 영상 분할 기반 스테레오 매칭 방법을 제안한다. 일반적으로 사용하는 윈도우 기반 스테레오 매칭 결과를 기반으로 분할된 영상 내에서 최적의 변위 값을 재 할당함으로서 깊이정보의 정확성을 향상시킬 수 있다. Mean-shift는 참조 영상에서 화소 간 평균값 차이가 최대가 되는 영역들을 반복적으로 찾는다. 유사한 평균값을 갖는 영역들을 기반으로 영상을 분할하는 것을 Mean-shift를 이용한 영상분할 이라고 한다. 분할된 영상은 각 영역을 대표하는 패치 구조를 가지고 있어 참조 영상에 포함되어있는 잡음에 강인한 특성을 지닌다. 스테레오 매칭을 통해 화소별로 변위 값을 할당해주는 대신, 분할된 영상을 이용하여 각 분할 영역에 동일한 변위 값을 할당한다. 분할된 영상에 동일한 변위 정보를 할당할 경우 객체와 배경의 경계영역에서 잘못된 변위 값이 할당되는 경우가 발생한다. 이러한 경계 영역의 변위정보 부정확성을 보완하기 위해 화소의 기울기 항을 비용 값 계산 과정에 추가하여 단점을 보완한다. 최종 비용 값 계산을 통해 획득한 초기 변위 지도에 중간 값 필터를 적용하여 분류된 영역에 동일한 변위 값을 할당한다. 제안한 방법을 적용하여 경계영역의 정확도가 향상된 최종 변위 지도를 획득한다.

• Smart Structures and Systems
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• v.17 no.6
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.357-365
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• 2010

This paper considers the integrated process control procedure for detecting special causes in an IMA(1,1) noise process that is being adjusted using a minimum mean squared error adjustment. As a SPC procedure, we use a GLR chart for detecting special causes whose effects are the sustained shift or the sustained drift in the process mean, and the sustained shift in the process variance. For the design of the GLR chart, we derive expressions for the control limit which accurately satisfies the given in-control ARL.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.159-164
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• 2019

Recent developments in ICT technology have increased interest in the care and health of pets such as dogs and cats. In this paper, cluster analysis was performed based on the component data of pet food to be used in various fields of the pet industry. For cluster analysis, the similarity was analyzed by analyzing the correlation between components of 300 dogs and cats in the market. In this paper, clustering techniques such as Hierarchical, K-Means, Partitioning around medoids (PAM), Density-based, Mean-Shift are clustered and analyzed. We also propose a personalized recommendation system for pets. The results of this paper can be used for personalized services such as feed recommendation system for pets.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.645-657
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• 2021

Along with the rapid development of the economy, the urban scale has extended rapidly, leading to the formation of different types of urban function districts (UFDs), such as central business, residential and industrial districts. Recognizing the spatial distributions of these districts is of great significance to manage the evolving role of urban planning and further help in developing reliable urban planning programs. In this paper, we propose an automatic UFD division method based on big data analysis of point of interest (POI) data. Considering that the distribution of POI data is unbalanced in a geographic space, a dichotomy-based data retrieval method was used to improve the efficiency of the data crawling process. Further, a POI spatial feature analysis method based on the mean shift algorithm is proposed, where data points with similar attributive characteristics are clustered to form the function districts. The proposed method was thoroughly tested in an actual urban case scenario and the results show its superior performance. Further, the suitability of fit to practical situations reaches 88.4%, demonstrating a reasonable UFD division result.