• Journal of the Korean Data and Information Science Society
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• 제18권2호
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• pp.345-356
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• 2007

This study deals with an early detection problem of structural change in won/dollar exchange market. A CUSUM algorithm is developed to monitor relevant economic variables indicating structural change in won/dollar exchange market. We applied the CUSUM algorithm to examine whether or not it was possible to alarm the 1997 economic crisis of Korea in advance.

• 대한장애인치과학회지
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• 제3권2호
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• pp.87-90
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• 2007

$DIFOTI^{(R)}$ 가시광선 파장을 이용하여 방사선 노출 없이도 실시간으로 교합면, 인접면, 평활면 우식, 재발성 우식 및 치아 파절이나 불소증 등을 효과적으로 진단할 수 있는 영상 장비이다. 시진 및 방사선 사진에 비해 치아 우식 탐지에 있어서 민감도가 매우 높은 것으로 나타나고 있으며, 이를 통해 치아의 탈회를 조기 진단하여 보다 보존적인 치료가 가능하리라 사료된다.

• 한국시스템다이내믹스연구
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• 제17권1호
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• pp.25-40
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• 2016

This research aims to identify important variables and their effects on diabetes prevention or progression from prediabetes to diabetic complication using system thinking. Based on the existing studies, we have constructed a causal loop diagram explaining dynamics of diabetes and have found 7 important reinforcing loops and 3 balancing loops in the causal loop diagram. The CLD displays an effect of increasing prediabetes early detection and awareness on diabetes prevention. The findings indicate that the projects in Korea for reducing incidence of diabetes and potential risk of complication have focused on variables which are related only on diabetes even though prediabetes has been a critical point on diabetes prevention and management. Thus, it also concludes that the effect of projects focusing only on diabetes have faced limitation to manage diabetes accordingly.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.768-773
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• 2011

Today's urban transit system is regarded as the important public transportation service which saves passengers' time and provides the safety. Many researches focus on the rapid and protective responses that minimize the losses when dangerous situation occurs. In this paper we proposed the early fire detection and corresponding rapid response method in urban transit system by combining automatic fire detection for video input and the sensor system. The fire detection method consists of two parts, spark detection and smoke detection. At the spark detection, the RGB color of input video is converted into HSV color and the frame difference is obtained in temporal direction. The region with high R values is considered as fire region candidate and stepwise fire detection rule is applied to calculate its size. At the smoke detection stage, we used the smoke sensor network to secure the credibility of spark detection. The proposed system can be implemented at low prices. In the future work, we would improve the detection algorithm and the accuracy of sensor location in the network.

• 대한의용생체공학회:의공학회지
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• 제30권5호
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• pp.412-417
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• 2009

The purpose of this study was to assess the ability of this device during clinically important episodes of extravasation. The extravasation detection accessory (EDA) system was based of infrared ray with detection sensor, an amplifier, alarm device, receiver, cable and a computer based system. This study was a prospective, observational study in which the EDA system was used to monitor the automated mechanical injection of contrast media. Three hundred patients referred for contrast media enhanced body computed tomography studied in a prospective, observation study in which the EDA system was used to identify and interrupt any injection associated with clinically important extravasation. There were 8 true-positive cases, 276 true-negative cases, 15 false-positive cases and 1 false-negative cases. The EDA system had a sensitivity of 88.8% and a specificity of 94.8% for the detection of clinically important extravasation. The EDA system had good sensitivity for the detection of clinically important extravasation and the EDA system has the clinical potential for the early detection of extravasation of the contrast medium that is administered with power injectors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권1호
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• pp.68-80
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• 2013

Lung cancer is considered to be the leading cause of cancer death worldwide. A technique commonly used consists of analyzing sputum images for detecting lung cancer cells. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid errors. The manual screening of sputum samples has to be improved by using image processing techniques. In this paper we present a Computer Aided Diagnosis (CAD) system for early detection and diagnosis of lung cancer based on the analysis of the sputum color image with the aim to attain a high accuracy rate and to reduce the time consumed to analyze such sputum samples. In order to form general diagnostic rules, we present a framework for segmentation and extraction of sputum cells in sputum images using respectively, a Bayesian classification method followed by region detection and feature extraction techniques to determine the shape of the nuclei inside the sputum cells. The final results will be used for a (CAD) system for early detection of lung cancer. We analyzed the performance of a Bayesian classification with respect to the color space representation and quantification. Our methods were validated via a series of experimentation conducted with a data set of 100 images. Our evaluation criteria were based on sensitivity, specificity and accuracy.

• 한국인터넷방송통신학회논문지
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• 제20권3호
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• pp.25-30
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• 2020

본 연구는 무선환경에서 가입자 및 무선통신 이용자들에게 양질의 이동통신 서비스를 제공해 주기 위한 연구로서, 장애가 발생한 무선국을 조기에 처리하여 통화의 품질을 확보하는 방안에 대한 것이다. 본 연구의 목표는 5G이동통신에서 발생하는 혼신 및 불법무선국을 조기에 탐지 및 해결하기 위한 방안으로 이동통신 환경에 적합하며 휴대가 가능한 방향탐지 시스템을 설계하고 구현하는 것이다. 휴대용 방향탐지 시스템의 기본 구성을 설계하였으며, 제작 및 실험을 통하여 통하여 장애가 발생한 무선국을 빠른 시간에 찾아내어 유지보수를 진행할 수 있는 방안을 제안하였다.

• 대한기관식도과학회지
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• 제7권2호
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• pp.161-167
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• 2001

Background and Objectives： Total laryngectomy is often required for advanced cases. But this operation induced the many inconvenience of basic daily life. Early diagnosis of laryngeal cancer is very important to prevent from this disastrous condition. In this point of view, mass screening test for early detection of laryngeal cancer is necessary. Screening test using voice has many advantages such as simple, less interventional. Voice collection by Automatic Response System(ARS) is comfortable and easy to got acoustic sample. Thus author tried to got the acoustic parameters which can differentiate normal, benign. and malignant laryngeal diseases and also checked the availability of parameters on neural network system. Materials and Methods: Author has evaluated the voice from 17 laryngeal cancer patients and 45 benign laryngeal disease patients who visited at Department of Otolaryngology, Pusan National University Hospital from May 1998 to April 2001, and 15 normal control. Author chose the sir Parameters (Jitt. vFo, Shim, vAm, NHR, SPI) that was thought to be related with voice collected by ARS among thirty-three parameters analysed by a Multi-Dimensional Voice Program (MDVP). Two-step neural network was used for the availability of six parameters. Results: The detection rate of normal voice by ARS voice analysis is 78.5% and detection rate of abnormal voice was 97.1 o/o. Among abnormal voice, the detection rate of benign laryngeal diseases and laryngeal cancers were 82.4 o/o, 70.6% respectively. Conclusion: Author concluded that six parameters and Matlab based neural network software may be effective in development of acoustic screening system for laryngeal cancer and further study should be necessary for development of new acoustic parameters.

• Journal of electromagnetic engineering and science
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• 제15권3호
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• pp.158-166
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• 2015

The early detection of breast cancer is very important. The final goal of this study is to develop an inexpensive portable device for simply detecting the existence of breast cancer using microwaves. In this study, we proposed a detection algorithm and the system configuration of such a device. The feasibility of the proposed method was investigated by numerical simulation and actual measurement. A prototype sensing module was fabricated, and the measurement results for tumor phantoms were presented. The measurement results showed that the prototype sensing module worked well, and the simulation results revealed that the detection rate of the device could be about 60% for a 4 mm tumor and almost 100% for a 6 mm tumor. The proposed device can be used for the self-diagnosis of breast cancer. Further study is required to reduce the size of the sensing module.

• 품질경영학회지
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• 제45권1호
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• pp.25-38
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• 2017

Purpose: Hot strip rolling mill consists of a lot of mechanical and electrical units. In condition monitoring and diagnosis phase, various units could be failed with unknown reasons. In this study, we propose an effective method to detect early the units with abnormal status to minimize system downtime. Methods: The early warning problem with various units is defined. K-means and PAM algorithm with Euclidean and Manhattan distances were performed to detect the abnormal status. In addition, an performance of the proposed algorithm is investigated by field data analysis. Results: PAM with Manhattan distance(PAM_ManD) showed better results than K-means algorithm with Euclidean distance(K-means_ED). In addition, we could know from multivariate field data analysis that the system reliability of hot strip rolling mill can be increased by detecting early abnormal status. Conclusion: In this paper, clustering-based monitoring and fault detection algorithm using Manhattan distance is proposed. Experiments are performed to study the benefit of the PAM with Manhattan distance against the K-means with Euclidean distance.