• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1149-1151
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• 2003

We performed a validation study of the MODIS active fire detection algorithm using high resolution SPOT image as the reference data set. Fire with visible smoke plumes are detected in the SPOT scenes, while the hotspots in MODIS data are detected using NASA's new version 4 fire detection algorithm. The detection performance is characterized by the commission error rate (false alarms) and the omission error rate (undetected fires). In the Sumatra and Kalimantan study area, the commission rate and the omission rate are 27% and 34% respectively. False alarms are probably due to recently burnt areas with warm surfaces. False negative detection occur where there are long smoke plumes and where fires occur in densely vegetated areas.

• Journal of information and communication convergence engineering
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• 제7권1호
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• pp.7-12
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• 2009

The advanced computer network and Internet technology enables connectivity of computers through an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, making it vulnerable to previously unidentified attack patterns and variations in attack and increasing false negatives. Intrusion detection and prevention technologies are thus required. We proposed a network based hybrid Probe Intrusion Detection model using Fuzzy cognitive maps (PIDuF) that detects intrusion by DoS (DDoS and PDoS) attack detection using packet analysis. A DoS attack typically appears as a probe and SYN flooding attack. SYN flooding using FCM model captures and analyzes packet information to detect SYN flooding attacks. Using the result of decision module analysis, which used FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance evaluation, the "IDS Evaluation Data Set" created by MIT was used. From the simulation we obtained the max-average true positive rate of 97.064% and the max-average false negative rate of 2.936%. The true positive error rate of the PIDuF is similar to that of Bernhard's true positive error rate.

• Journal of the Optical Society of Korea
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• 제14권4호
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• pp.451-457
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• 2010

Increasing demands on the safety of public train services have led to the development of various types of security monitoring systems. Most of the surveillance systems are focused on the estimation of crowd level in the platform, thereby yielding too many false alarms. In this paper, we present a novel security monitoring system to detect critically dangerous situations such as when a passenger falls from the station platform, or when a passenger walks on the rail tracks. The method is composed of two stages of detecting dangerous situations. Objects falling over to the dangerous zone are detected by motion tracking. 3D depth information retrieved by the stereo vision is used to confirm fallen events. Experimental results show that virtually no error of either false positive or false negative is found while providing highly reliable detection performance. Since stereo matching is performed on a local image only when potentially dangerous situations are found; real-time operation is feasible without using dedicated hardware.

• 대한건축학회논문집:구조계
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• 제36권3호
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• pp.113-120
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• 2020

The purpose of this study is to compare the models of Deep Learning-based Convolution Neural Network(CNN) for concrete crack detection. The comparison models are AlexNet, GoogLeNet, VGG16, VGG19, ResNet-18, ResNet-50, ResNet-101, and SqueezeNet which won ImageNet Large Scale Visual Recognition Challenge(ILSVRC). To train, validate and test these models, we constructed 3000 training data and 12000 validation data with 256×256 pixel resolution consisting of cracked and non-cracked images, and constructed 5 test data with 4160×3120 pixel resolution consisting of concrete images with crack. In order to increase the efficiency of the training, transfer learning was performed by taking the weight from the pre-trained network supported by MATLAB. From the trained network, the validation data is classified into crack image and non-crack image, yielding True Positive (TP), True Negative (TN), False Positive (FP), False Negative (FN), and 6 performance indicators, False Negative Rate (FNR), False Positive Rate (FPR), Error Rate, Recall, Precision, Accuracy were calculated. The test image was scanned twice with a sliding window of 256×256 pixel resolution to classify the cracks, resulting in a crack map. From the comparison of the performance indicators and the crack map, it was concluded that VGG16 and VGG19 were the most suitable for detecting concrete cracks.

• 대한세포병리학회지
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• 제8권2호
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• pp.120-128
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• 1997

Fine needle aspiration cytology of breast lesion is well known as a simple, economic and effective diagnostic modality. For the evaluation of cytohistologic correlation, 256 cases of cytologic smears and subsequent histologic sections during 2-year period from Jan. 1995 to Dec. 1996 were reviewed. 1. Fifteen cases(5.9%) were proven as insufficient for evaluation, and 13 of them were fibrocystic change histologically. One case of carcinoma exhibiting sufficient amount of aspirates with no malignant cells on smear was regarded as inadequate. 2. Cytohistologic correlation of 240 cases revealed sensitivity 87.0%, specificity 100.0%, positive predictive value 100.0%, negative predictive value 97.0%, false positive rate 0.0% and false negative rate 13.0%. Total diagnostic accuracy is 95.7%. 3. Total 6 cases of negative were due to small amount of aspirates containing scantiness of malignant cells in two and underestimation in four. 4. Diagnostic concordance rates of fibrocystic change and fibroadenoma were 95.5% and 80.0%, respectively. Diagnostic discrepancies were noted in 7 cases of fibrocystic change and 6 cases of fibroadenoma, however, cytologic discrimination of two entities was not easy in seven of them. 5. In a case of phyllodes tumor and a case of duct ectasia, the discrepancy was due to targeting error. Other three cases(lymphoma, adenomyoepithelioma and granulomatous mastitis) were misinterpreted because of poor acquaintance with those entities. Diagnostic accuracy of fine needle aspiration cytology of breast lesions are relatively high. However, good technique on aspiration and adequate interpretation are necessary to reduce the false negative rate and the discrepancy between cytologic and histologic diagnoses.

• 대한세포병리학회지
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• 제9권1호
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• pp.37-44
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• 1998

OBJECTIVE: False negatives of cervical smears due to screening errors pose a significant and persistent problem. AutoPap 300 QC System, an automated screening device, is designed to rescreen conventionally prepared Pap smears initially screened by cytotechnologists as normal. Clinical experience and sensitivity of the AutoPap 300 QC System were assessed and compared with current 10% random qualify control technique. MATERIALS AND METHODS: In clinical practice, a total of 18,592 "within normal limits" or "benign cellular changes" cases classified by The Bethesda System were rescreened by the Autopap System. In study for sensitivity of The AutoPap System to detect false negatives, a total of 1,680 "within normal limits" or "benign cellular changes" cases were rescreened both manually and by the AutoPap System. The sensitivity of the AutoPap System to these false negatives was assessed at 10% review rate to compare 10% random manual rescreen. RESULTS: In clinical practice, 38 false negatives were identified by the AutoPap System and we had achieved 0.2% reduction in the false negative rate of screening error. In study for sensitivity, 37 false negatives were identified by manual rescreening, and 23 cases(62.2%) of the abnormal squamous cytology were detected by the AutoPap System at 10% review rate. CONCLUSONS: The AutoPap 300 QC System is a sensitive automated rescreening device that can detect potential false negatives prior to reporting and can reduce false negative rates in the laboratory. The device is confirmed to be about eight times superior to the 10% random rescreen in detecting false negatives.

• 전자공학회논문지
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• 제53권7호
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• pp.49-55
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• 2016

디지털 포렌식 영상은 여러 가지 영상타입으로 위 변조되어 유통되는 심각한 문제가 대두되어 있다. 이러한 문제를 해결하기 위하여, 본 논문에서는 포렌식 영상의 분류 알고리즘을 제안한다. 제안된 알고리즘은 여러 가지 영상타입의 그레이 레벨 co-occurrence 행렬의 특성 중에서 콘트라스트와 에너지 그리고 영상의 엔트로피로 21-dim.의 특징벡터를 추출하고, 결정나무 플랜에서 분류학습을 위하여 PPCA를 이용하여 2-dim.으로 차원을 축소한다. 포렌식 영상의 분류 테스트는 영상 타입들의 전수조합에서 수행되었다. 실험을 통하여, TP (True Positive)와 FN (False Negative)을 검출하고, 제안된 알고리즘의 성능평가에서 민감도 (Sensitivity)와 1-특이도 (1-Specificity)의 AUROC (Area Under Receiver Operating Characteristic) 커브 면적은 0.9980으로 'Excellent(A)' 등급임을 확인하였다. 산출된 최소평균 판정에러 0.0179에서 분류할 포렌식 영상타입이 모두 포함되어 분류 효율성이 높다.

• Journal of Yeungnam Medical Science
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• 제3권1호
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• pp.179-183
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• 1986

영남대학교 영남의료원 해부병리과에 최근 3년간 의뢰된 동결 절편 809예를 검토한 결과, 임파절, 위장관계, 피부의 순으로 많았으며, 동결절편 진단의 정확도는 진단연기 예(0.9%)를 포함하면 98.1%였고 위음성율은 0.5%였으며 위양성은 1예도 없었다. 위음성의 예는 임파절, 피부, 난소, 갑상선 각 1예였고 부정확한 진단 명기 및 grading error가 0.5%였다.

• 정보처리학회논문지C
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• 제13C권1호
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• pp.45-54
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• 2006

현재까지 존재하는 무수한 악성 행위에 대응하기 위해서 다양한 기법들이 제안되었다 그러나 현존하는 악성행위 탐지 기법들은 기존의 행위에 대한 변종들과 새로운 형태의 악성행위에 대해서 적시 적절하게 대응하지 못하였고 긍정 오류(false positive)와 틀린 부정(negative false) 등을 해결하지 못한 한계점을 가지고 있다. 위와 같은 문제점을 개선하고자 한다. 여기서는 소스코드의 기본 단위(token)들을 개념화하여 악성행위 탐지에 응용하고자 한다. 악성 코드를 개념 그래프로 정의할 수 있고, 정의된 그래프를 통하여 정규화 표현으로 바꿔서 코드 내 악성행위 유사관계를 비교할 수 있다. 따라서 본 논문에서는, 소스코드를 개념 그래프화하는 방법을 제시하며, 정확한 악성행위 판별을 위한 유사도 측정방안을 제시한다. 실험결과, 향상된 악성 코드 탐지율을 얻었다.

• 한국산업보건학회지
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• 제21권4호
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• pp.222-226
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• 2011

This study was conducted to identify the characteristics of analytical errors shown in the Korean quality control program on bulk asbestos analyses using polarized light microscopy (PLM). 179 participating laboratories were required to analyze 4 samples respectively and asked to classify each test sample as asbestos-containing (positive) or non-asbestos-containing (negative). For positive samples, participants were also asked to identify the type and semiquantitate the contents of asbestos present. The test results showed 21 (4%) false negative errors among 562 samples, 9 (6%) false positive errors among 154 samples and 53 (9%) asbestos identification errors among 562 samples. Most of false negative and positive errors were observed in a few types of samples. Higher frequencies of asbestos identification errors were shown in samples containing two or more types of asbestos and samples containing anthophyllite, tremolite or actinolite asbestos. For semiquantitative analyses, the ratios of mean to nominal weight contents were 2.1 for chrysotile and 2.9 for amphiboles. A tendency of over-estimation was observed in semiquantitative analyses using the visual estimation technique and higher in case of analyzing samples containing amphiboles than chrysotile. Coefficients of variation (CVs) of semiquantitative analytical results were 0.44~0.83 and 0.5~1.14 for samples containing chrysotile and amphibole asbestos, respectively.