• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.4
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• pp.327-336
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• 2021

In this paper, we will introduce the image processing methods for the remote pupillary light reflex measurement using the video taken by a general smartphone camera without a special device such as an infrared camera. We propose an algorithm for estimate the size of the pupil that changes with light using image data analysis without a learning process. In addition, we will introduce the results of visualizing the change in the pupil size by removing noise from the recorded data of the pupil size measured for each frame of the video. We expect that this study will contribute to the construction of an objective indicator for remote pupillary light reflex measurement in the situation where non-face-to-face communication has become common due to COVID-19 and the demand for remote diagnosis is increasing.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.170-175
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• 1992

A leak detection method for diagnosis of the leak position in a pipeline was developed using an estimation theory with the assumption that the measured flow rates and pressures are stochastic processes. A notch filter was designed using power spectral density analysis of measurements to reduce the effects of disturbances. The noise model dimension was determined by hypothesis testing and then recursive extended least square method was applied to estimate the leak position in real time. The proposed method was applied to an experimental system for evaluation of its performance.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.1
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• pp.52-54
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• 2002

This research presented in this paper focuses on a system development for checking stator's wedge of large generator in heavy industry. The system is composed of impactor, A/D converter and digital signal processing board. Also this paper proposes a method for detection of stator's insulating state using analysis algorithm. As developed impact system is acting, impact wave is generated real time and transferred data to microprocessor. Using communication program this signal move microprocessor to hard directory of note book with 1000 data/sec. The developed system and analysis program performed very well by real stator's wedge in large generator.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.224-229
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• 2011

In this paper, in order to improve safety of hybrid electric vehicle a fault detection algorithm is introduced. The proposed algorithm uses SVDD techniques. Two methods for learning a lot of data are used in this technique. One method is to learn the data incrementally. Another method is to remove the data that does not affect the next learning. Using lines connecting support vectors selection of removing data is made. Using this method, lot of computation time and storage can be saved while learning many data. A battery data of commercial hybrid electrical vehicle is used in this study. In the study fault boundary via SVDD is described and relevant algorithm for virtual fault data is verified. It takes some time to generate fault boundary, nevertheless once the boundary is given, fault diagnosis can be conducted in real time basis.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.33-41
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• 2008

Telematics system includes the "vehicle remote diagnosis technology", "driving pattern analysis technology" which are commercially attractive in the real life. To implement those technologies, we need vehicle signal interface, vehicle diagnosis interface, accelerometer/yaw-rate sensor interface, GPS data processing, driving pattern analysis, and CDMA data processing technique. Based on these technologies, we analyze the error existence by diagnosing the EMS(Engine Management System), TMS(Transmission Management System), ABS/TCS, A/BAG in real time. And we are checking about a driving pattern and management of the vehicle, which are sent to the information center through the wireless communication. These database results will make the efficient vehicle and driver management possible. We show the effectiveness of our results by field driving test after completing the H/W & S/W design and implementation for vehicle remote diagnosis and driving pattern analysis.

• Biomedical Science Letters
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• v.19 no.2
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• pp.153-157
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• 2013

Although culture is the gold standard method to identify mycobacteria, its use in tuberculous lymphadenitis (TBL) is limited due to formalin fixation of the submitted specimens. We evaluated the performance of quantitative real-time PCR (q-PCR) for Mycobacterium Tuberculosis (MTB) in granulomatous lymphadenitis using formalin-fixed paraffin-embedded (FFPE) tissues. From 2000 to 2010, a total number of 117 cases of lymph node samples with granulomatous inflammation which were surgically removed and fixed in formalin were studied. Hematoxylin & Eosin (H&E) and Ziehl-Neelsen-stained (ZN) slides were reviewed. qPCR using Real TB-Taq$^{(R)}$ was performed for all cases to identify Mycobacterium tuberculosis. Thirteen non-tuberculous lymphadenopathy cases were used as negative control. Cervical lymph nodes were more frequently affected (60%, 70/117) than other sites. ZN stain for acid fast bacilli was positive in 19 (16.24%) cases. qPCR for tuberculosis was positive in 92 (78.63%) cases. Caseous necrosis was found in 103 (88.03%) cases. While the ZN stain and qPCR were both negative in all control cases, the qPCR showed a significantly higher positive rate (78.63% vs. 16.24%) compared to ZN stain in histologically diagnosed TBL. Quantitative real-time PCR proves to be more sensitive than ZN stain for diagnosis of tuberculous lymphadenitis.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.875-880
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• 2015

Traditional semiconductor process control has been performed through statistical process control techniques in a constant process-recipe conditions. However, the complexity of the interior of the etching apparatus plasma physics, quantitative modeling of process conditions due to the many difficult features constraints apply simple SISO control scheme. The introduction of the Advanced Process Control (APC) as a way to overcome the limits has been using the APC process control methodology run-to-run, wafer-to-wafer, or the yield of the semiconductor manufacturing process to the real-time process control, performance, it is possible to improve production. In addition, it is possible to establish a hierarchical structure of the process control made by the process control unit and associated algorithms and etching apparatus, the process unit, the overall process. In this study, the research focused on the methodology and monitoring improvements in performance needed to consider the process management of future developments in the semiconductor manufacturing process in accordance with the age of the APC analysis in real applications of the semiconductor manufacturing process and process fault diagnosis and control techniques in progress.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.97-110
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• 2012

High performance sensors and modern data logging technology with real-time telemetry facilitate system fault diagnosis in a very precise manner. Fault detection, isolation and identification in fault diagnosis systems are typical steps to analyze the root cause of failures. This systematic failure analysis provides not only useful clues to rectify the abnormal behaviors of a system, but also key information to redesign the current system for retrofit. The main barriers to effective failure analysis are: (i) the gathered data (event) logs are too large in general, and further (ii) they usually contain noise and redundant data that make precise analysis difficult. This paper therefore applies suitable pre-processing techniques to data reduction and feature extraction, and then converts the reduced data log into a new format of event sequence information. Finally the event sequence information is decoded to investigate the correlation between specific event patterns and various system faults. The efficiency of the developed pre-filtering procedure is examined with a terminal box data log of a marine diesel engine.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2733-2737
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• 2014

Objective: Molecular pathology tests are often carried for clinicopathological diagnosis and pathologists have established large collections of formalin-fixed, paraffin-embedded tissue (FFPE) banks. However, extraction of DNA from FFPE is a laborious and challenging for researchers in clinical laboratories. The aim of this study was to compare two widely used DNA extraction methods: using a QIAamp DNA FFPE kit from Qiagen and a Cobas Sample Preparation Kit from Roche, and evaluated the effect of the DNA quality on molecular diagnostics. Methods: DNA from FFPE non-small cell lung carcinoma tissues including biopsy and surgical specimens was extracted with both QIAamp DNA FFPE and Cobas Sample Preparation Kits and EGFR mutations of non-small cell lung carcinomas were detected by real-time quantitative PCR using the extracted DNA. Results and Conclusion: Our results showed that DNA extracted by QIAamp and Cobas methods were both suitable to detect downstream EGFR mutation in surgical specimens. Howover, Cobas method could yield more DNA from biopsy specimens, and gain much better EGFR mutation results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2391-2398
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• 2009

Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and prevention of possible life threatening cardiac diseases. Most of the algorithms detecting PVC reported in literature is not always feasible due to the presence of noise and P wave making the detection difficult, and the process being time consuming and ineffective for real time analysis. To solve this problem, a new approach for the detection of PVC is presented based rhythm analysis and beat matching in this paper. For this purpose, the ECG signals are first processed by the usual preprocessing method and R wave was detected. The algorithm that decides beat type using the rhythm analysis of RR interval and beat matching of QRS width is developed. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate sensitivity of 99.74%, positive predictivity of 99.81% and sensitivity of 93.91%, positive predictivity of 96.48% accuracy respectively for R wave and PVC detection.