• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.801-804
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• 2013

We propose a new tongue examination model according to the taste division of tongue. The proposed sytem consists of image acquisition, region segmentation, color distribution analysis and abnormality decision of tongue. Tongue DB which is classified into abnormality is constructed with tongue images captured from oriental medicine hospital inpatients. We divided 4 basic taste(bitter, sweet, salty and sour) regions and performed color distribution analysis targeting each region under HSI(Hue Saturation Intensity) color model. To minimize the influence of illumination, the histograms of H and S components only except I are utilized. The abnormality of taste regions each by comparing the proposed diagnosis model with diagnosis results by a doctor of oriental medicine. We confirmed the 87.5% of classification results of abnormality by proposed algorithm is coincide with the doctor's results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.795-805
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• 2019

Recently, there is a growing interest in network anomaly detection technology to tackle unknown attacks. For this purpose, diverse studies using data mining, machine learning, and deep learning have been applied to detect network anomalies. In this paper, we evaluate the decision tree to see its feasibility for network anomaly detection on NSL-KDD data set, which is one of the most popular data mining techniques for classification. In order to handle the over-fitting problem of decision tree, we select 13 features from the original 41 features of the data set using chi-square test, and then model the decision tree using TensorFlow and Scik-Learn, yielding 84% and 70% of binary classification accuracies on the KDDTest+ and KDDTest-21 of NSL-KDD test data set. This result shows 3% and 6% improvements compared to the previous 81% and 64% of binary classification accuracies by decision tree technologies, respectively.

• Research in Plant Disease
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• v.23 no.3
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• pp.278-282
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• 2017

Maize is one of the most cultivated cereals as a staple food in the world. The harvested maize is mainly stored after drying, but its quality and nutrition could be debased by fungal spoilage and mycotoxin contamination. In this study, we surveyed mycotoxin contamination fungal infection of maize kernels that were stored for almost one year after harvest in 2015. The amount of deoxynivalenol and zearalenone detected were higher than the other mycotoxin, such as aflatoxin, ochratoxin, fumonisin and T-2 toxin. In particular, level of deoxynivalenol was detected as $1200{\pm}610{\mu}g/kg$ in small size kernels, which was four to six times higher than the large and the medium size kernels. Moreover, the amount of deoxynivalenol, zearalenone, and fumonisin were increased with discolored kernels. 10 species including Fusarium spp., Aspergillus spp. and Penicillium spp. were isolated from the maize kernels. F. graminearum was predominant in the discolored kernels with detection rates of 60% (red) and 40% (brown). Our study shows that the mycotoxin contents of stored maize can be increased by discolored maize kernels mixed. Therefore elimination of the contaminated maize kernels will help prevent fungal infection and mycotoxin contamination in stored maize.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.705-711
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• 2013

QRS detection of ECG is the most popular and easy way to detect cardiac-disease. But it is difficult to analyze the ECG signal because of various noise types. Also in the healthcare system that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. In other words, the design of algorithm that exactly detects QRS wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, efficient QRS detection and PVC classification based on profiling method is presented in this paper. For this purpose, we detected QRS through the preprocessing method using morphological filter, adaptive threshold, and window. Also, we applied profiling method to classify each patient's normal cardiac behavior through hash function. The performance of R wave detection, normal beat and PVC classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.77% in R wave detection and the rate of 0.65% in normal beat classification error and 93.29% in PVC classification.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.477-480
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• 2022

반도체 성능 향상으로 신호를 전달하는 회로의 단위가 마이크로 미터에서 나노미터로 미세화되어 선폭(linewidth)이 점점 좁아지고 있다. 이러한 변화는 검출해야 할 불량의 크기가 작아지고, 정상 공정상태와 비정상 공정상태의 차이도 상대적으로 감소되어, 공정오차 및 공정조건의 허용범위가 축소되었음을 의미한다. 따라서 검출해야 할 이상징후 탐지가 더욱 어렵게 되어, 높은 정밀도와 해상도를 갖는 검사공정이 요구되고 있다. 이러한 이유로, 미세 공정변화를 파악할 수 있는 신규 검사 및 계측 공정이 추가되어 TAT(Turn-around Time)가 증가하게 되었고, 웨이퍼가 가공되어 완제품까지 도달하는데 필요한 공정시간이 증가하여 제조원가 상승의 원인으로 작용한다. 본 논문에서는 웨이퍼의 검계측 데이터가 아닌, 제조공정 과정에서 발생하는 다양한 센서 및 장비 데이터를 기반으로 웨이퍼 제조 결과가 양품인지 그렇지 않으면 불량인지 구별할 수 있는 가상계측 모델을 제안한다. 기계학습의 여러 알고리즘 중에서 다양한 장점을 갖는 XGBoost 알고리즘을 이용하여 예측모델을 구축하였고, 데이터 전처리(data-preprocessing), 주요변수 추출(feature selection), 모델 구축(model design), 모델 평가(model evaluation)의 순서로 연구를 수행하였다. 결과적으로 약 94% 이상의 정확성을 갖는 모형을 구축하는데 성공하였으나 더욱 높은 정확성을 확보하기 위해서는 반도체 공정과 관련된 Domain Knowledge 를 반영한 모델구축과 같은 추가적인 연구가 필요하다.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.869-873
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• 2007

본 논문은 고속으로 생산되는 제품의 영상을 캡쳐한 후 영상처리 기법 중 에지 추출 알고리즘을 응용하여 조명에 투과된 제품의 에지를 추출 및 필터링 하는 방법으로 결함 검출 시스템을 설계한다. 소형의 임베디드 기기에 패턴 매칭 영상처리 기법을 이용하여 결함을 검출하고 패턴의 비 매칭 정도를 기준점에 따라 정상 또는 불량 판정을 할 수 있는 어플리케이션을 개발하고 탑재하였고, 어플리케이션의 불량 판정 알고리즘으로는 NGC (Normalized GrayScale Corelation) 기법을 사용하였고 검출 판정 결과 적절한 판정값을 입력하는 것으로 기준 패턴과 형상이 다른 대상의 불량을 판정한다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.6
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• pp.28-32
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• 1980

A digital system has been designed for the detection of abnormal spikes appearing in the epileptic patient's electroencephalogram(EEG). The detection is based on the waveform characteristics of spikes, such as the large slope, the sharpness of the apex, and the time duration of the spike. After the patient's data are collected and processed suing a minicomputer and A/D converter, the computer algorithms recognize the spikes based on the parameters representing the above waveform characteristics.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.220.1-220.1
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• 2012

우주물체 전자광학 감시체계(OWL: Optical Wide-field Patrol)는 광학망원경을 통해 우주물체를 검출하는 시스템이다. 검출기 시스템의 하드웨어 구성은 Chopper, Filter Wheel, De-Rotator로 구성된 Wheel station과 CCD 카메라로 구성된다. Chopper는 CCD 영상에서 위성의 궤적을 자르는 역할을 하고 Filter Wheel은 관측대상의 파장 영역대를 선택하는 기능을 한다. 영상획득용 CCD카메라는 천문관측용 Full Frame 방식의 카메라를 사용하고 있으며 모델명 PL16803의 FLI 제품을 사용한다. 검출기시스템은 시스템 부팅 후 "Health check"를 통하여 검출기시스템의 상태를 점검하고 "과거이력관리" 및 "과거미처리 영상관리"를 점검하여 부팅 이전에 비상사태 등으로 인해, 비정상적으로 종료되어 처리되지 못한 명령이나 영상자료를 처리한다. 그리고 이에 대한 보고서를 기록하여 보관한다. 검출기시스템은 관측명령서(OCF: Observation Command File)를 받게 되면 자동 관측을 수행하며, 자동 관측 전에 "OCF 동기화"를 통하여 최신의 명령을 유지한다. 자동 관측이 종료된 후에는 획득한 영상을 처리하는 과정을 진행한다. 영상자료 처리과정 중에는 위성의 궤적을 "Line-Detection"을 통해 검출하고 World Coordinate System(WCS)를 계산 한 후, 이미지 상의 특정 위성 궤적의 좌표를 RA, DEC으로 표현되는 위치정보를 획득하도록 프로그램되어 있다. 이 외에도 운용 소프트웨어에는 자동 초점기능을 수행하는 기능도 포함하고 있다. 본 연구에서는 검출기 부분에 대한 설계 및 시험의 과정을 기술하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.938-941
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• 2010

Though a compiler checks memory errors, it is difficult for the compiler to detect function pointer errors in code level. Thus, in this paper, we propose a method for effectively detecting Invalid function pointer access errors, by analyzing assembly codes that are obtained by disassembling an executable file. To detect the errors, assembly codes in disassembled files are checked out based on the instruction transition diagrams which are constructed through analyzing normal usage patterns of function pointer access. When applying the proposed method to various programs having no compilation error, a total of about 500 potential errors including the ones of well-known open source programs such as Apache web server and PHP script interpreter are detected among 1 million lines of assembly codes corresponding to a total of about 10 thousand functions.

• Journal of Biomedical Engineering Research
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• v.6 no.2
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• pp.43-52
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• 1985

In this paper, the depth and attenuation coefficient are estimated from the mutilayered liver tissue which contained a inhomogeneous one using reflected ultrasonic signals and the abnormal one is detected quantitatively. Regarding a liver tissue as several reflectors, we analyzed each one by the frequency spectral difference method and discussed its attenuation characteristics. For the verification of this method, the liver pantom and acryle are used. And also we proved the usefulness through the experiment.