• 천문학회보
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• 제36권2호
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• pp.64-64
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• 2011

We present a new quasi-stellar object (QSO) selection algorithm using a Support Vector Machine, a supervised classification method, on a set of extracted time series features including period, amplitude, color, and autocorrelation value. We train a model that separates QSOs from variable stars, non-variable stars, and microlensing events using 58 known QSOs, 1629 variable stars, and 4288 non-variables in the MAssive Compact Halo Object (MACHO) database as a training set. To estimate the efficiency and the accuracy of the model, we perform a cross-validation test using the training set. The test shows that the model correctly identifies ~80% of known QSOs with a 25% false-positive rate. The majority of the false positives are Be stars. We applied the trained model to the MACHO Large Magellanic Cloud (LMC) data set, which consists of 40 million lightcurves, and found 1620 QSO candidates. During the selection, none of the 33,242 known MACHO variables were misclassified as QSO candidates. In order to estimate the true false-positive rate, we crossmatched the candidates with astronomical catalogs including the Spitzer Surveying the Agents of a Galaxy's Evolution (SAGE) LMC catalog and a few X-ray catalogs. The results further suggest that the majority of the candidates, more than 70%, are QSOs.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.316-321
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• 2008

Advanced computer network technology enables computers to be connected in 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, which makes it vulnerable to previously unidentified attack patterns and variations in attack and increases false negatives. Intrusion detection and analysis technologies are thus required. This paper investigates the asymmetric costs of false errors to enhance the performances the detection systems. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of anomaly traffic detection is enhanced by considering the costs of false errors.

• Imaging Science in Dentistry
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• 제48권2호
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• pp.121-125
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• 2018

Purpose: Detecting laryngeal cartilages (triticeous and thyroid cartilages) on panoramic radiographs is important because they may be confused with carotid artery calcifications in the bifurcation region, which are a risk factor for stroke. This study assessed the efficiency of panoramic radiography in the diagnosis of calcified laryngeal cartilages using cone-beam computed tomography (CBCT) as the reference standard. Materials and Methods: A total of 312 regions(142 bilateral, 10 left, 18 right) in 170 patients(140 males, 30 females) were examined. Panoramic radiographs were examined by an oral and maxillofacial radiologist with 11 years of experience. CBCT scans were reviewed by 2 other oral and maxillofacial radiologists. The kappa coefficient(${\kappa}$) was calculated to determine the level of intra-observer agreement and to determine the level of agreement between the 2 methods. Diagnostic indicators(sensitivity, specificity, accuracy, and false positive and false negative rates) were also calculated. P values <.05 were considered to indicate statistical significance. Results: Eighty-two images were re-examined to determine the intra-observer agreement level, and the kappa coefficient was calculated as 0.709 (P<.05). Statistically significant and acceptable agreement was found between the panoramic and CBCT images (${\kappa}=0.684$ and P<.05). The sensitivity, specificity, diagnostic accuracy rate, the false positive rate, and the false negative rate of the panoramic radiographs were 85.4%, 83.5%, 84.6%, 16.5%, and 14.6%, respectively. Conclusion: In most cases, calcified laryngeal cartilages could be diagnosed on panoramic radiographs. However, due to variation in the calcifications, diagnosis may be difficult.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3884-3910
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• 2016

Intrusion Detection System (IDS) in general considers a big amount of data that are highly redundant and irrelevant. This trait causes slow instruction, assessment procedures, high resource consumption and poor detection rate. Due to their expensive computational requirements during both training and detection, IDSs are mostly ineffective for real-time anomaly detection. This paper proposes a dimensionality reduction technique that is able to enhance the performance of IDSs up to constant time O(1) based on the Principle Component Analysis (PCA). Furthermore, the present study offers a feature selection approach for identifying major components in real time. The PCA algorithm transforms high-dimensional feature vectors into a low-dimensional feature space, which is used to determine the optimum volume of factors. The proposed approach was assessed using HTTP packet payload of ISCX 2012 IDS and DARPA 1999 dataset. The experimental outcome demonstrated that our proposed anomaly detection achieved promising results with 97% detection rate with 1.2% false positive rate for ISCX 2012 dataset and 100% detection rate with 0.06% false positive rate for DARPA 1999 dataset. Our proposed anomaly detection also achieved comparable performance in terms of computational complexity when compared to three state-of-the-art anomaly detection systems.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2006년도 한국컴퓨터종합학술대회 논문집 Vol.33 No.1 (B)
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• pp.55-57
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• 2006

본 논문에서는 컬러코드를 이용하여 증강현실 시스템에 사용 가능한 태그를 탐지하는 알고리즘을 설계하고 차단 현상에 강인한 알고리즘을 제안하였다. 기존의 ARToolkit에서 태그의 일부분이 사용자 또는 다른 물체에 의해 가려지게 될 경우 증강되었던 객체가 순간 사라져 버리는 불안정성 (Instability) 문제를 해결하기 위한 방법에 초점을 맞춘다. 불안정성의 문제는 이미지 안에 태그가 존재하지만 해당하는 객체를 증강시키지 못하는 False Negative 에러와 태그가 존재하지 않는 곳에 잘못된 객체를 증강시키는 False Positive 에러로 분류 될 수 있다. 제안된 탐지 알고리즘으로 특정 컬러 영역을 분리하여 모서리 여부를 판별하고 모서리인 경우 가려진 꼭지점의 위치를 추출하여 태그가 차단에 의하여 가려졌을 때에도 객체를 안정적으로 증강시킬 수 있다. 기존 AR 시스템들의 태그를 가지고 Daylight 65, Illuminant A. CWF, TL84의 4가지의 표준 조명하에 컬러코드 4종류, ARToolkit 태그 4개, ARTag 4개를 이용하여 실험을 진행하여 차단 현상이 발생하면 전혀 객체를 증강시킬 수 없었던 ARToolkit에서도 DayLight65의 경우 50%의 False Negative. False Positive rate을 보여 기존 증강현실 시스템에서 보였던 불안정성 문제를 개선하였다.

• Journal of Communications and Networks
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• 제12권1호
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• pp.74-85
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• 2010

For the purpose of compromising hosts, attackers including infected hosts initially perform a portscan using IP addresses in order to find vulnerable hosts. Considerable research related to portscan detection has been done and many algorithms have been proposed and implemented in the network intrusion detection system (NIDS). In order to distinguish portscanners from remote hosts, most portscan detection algorithms use a fixed threshold that is manually managed by the network manager. Because the threshold is a constant, even though the network environment or the characteristics of traffic can change, many false positives and false negatives are generated by NIDS. This reduces the efficiency of NIDS and imposes a high processing burden on a network management system (NMS). In this paper, in order to address this problem, we propose an automatic portscan detection system using an fast increase slow decrease (FISD) scheme, that will automatically and adaptively set the threshold based on statistical data for traffic during prior time periods. In particular, we focus on reducing false positives rather than false negatives, while the threshold is adaptively set within a range between minimum and maximum values. We also propose a new portscan detection algorithm, rate of increase in the number of failed connection request (RINF), which is much more suitable for our system and shows better performance than other existing algorithms. In terms of the implementation, we compare our scheme with other two simple threshold estimation methods for an adaptive threshold setting scheme. Also, we compare our detection algorithm with other three existing approaches for portscan detection using a real traffic trace. In summary, we show that FISD results in less false positives than other schemes and RINF can fast and accurately detect portscanners. We also show that the proposed system, including our scheme and algorithm, provides good performance in terms of the rate of false positives.

• 대한임베디드공학회논문지
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• 제19권1호
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• pp.1-8
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• 2024

Robotic arms have been widely utilized in various labor-intensive industries such as manufacturing, agriculture, and food services, contributing to increasing productivity. In the development of industrial robotic arms, camera sensors have many advantages due to their cost-effectiveness and small sizes. However, estimating object positions is a challenging problem, and it critically affects to the robustness of object manipulation functions. This paper proposes a method for estimating the 3D positions of objects, and it is applied to a pick-and-place task. A deep learning model is utilized to detect 2D bounding boxes in the image plane, and the pinhole camera model is employed to compute the object positions. To improve the robustness of measuring the 3D positions of objects, we analyze the effect of lens distortion and introduce a false positive filtering process. Experiments were conducted on a real-world scenario for moving medicine bottles by using a camera-based manipulator. Experimental results demonstrated that the distortion removal and false positive filtering are effective to improve the position estimation precision and the manipulation success rate.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (A)
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• pp.247-249
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• 2004

IDS에서 발생되는 경보의 수는 최근 인터넷 애플리케이션의 발달로 인하여 급격히 증가하고 있으며. 그로 인해 오 경보의 수도 함께 증가하고 있다. 발생된 경보들은 침입탐지 시스템의 성능저하와 alert flooding 의 원인이 된다. 따라서 이 논문에서는 다량의 경보 중에서 오 경보(False Alarm)의 발생을 감소시킬 수 있는 오 경보 분류 모델을 제안한다. 제안된 오 경보 분류 모델은 데이터 마이닝 기법들 중에서 분류 기법을 기반으로 구현되었다. 실험 을 통해서 IDS에서 발생하는 경보 중에서 정상데이터이나 공격으로 잘못 판단하여 발생하는 False Positive의 발생율이 현저히 감소됨을 확인할 수 있었다. 제안된 오 경보 분류 모델은 경보메시지 축약의 효과가 있으며 침입탐지 시스템의 탐지율을 높이는데 활용될 수 있다.

• Asian Pacific Journal of Cancer Prevention
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• 제13권1호
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• pp.237-241
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• 2012

Objective: Screening for colorectal cancer using guaiac-based fecal occult blood tests (gFOBT) is well established in Western populations, but is hampered by poor patient compliance due to the imposed dietary restrictions. Fecal immunochemical tests (FIT) do not require dietary restriction, but are more expensive than gFOBT and therefore restrict its use in developing countries in Asia. However, Asian diets being low in meat content may not require diet restriction for gFOBT to achieve equivalent results. The objective of this study was to evaluate and compare the validity and suitability of gFOBT and FIT or a combination of the two in screening for colorectal neoplasias without prior dietary restriction in an Asian population. Methods: Patients referred to the Endoscopic Unit for colonoscopy were recruited for the study. Stool samples were collected prior to bowel preparation, and tested for occult blood with both gFOBT and FIT. Dietary restriction was not imposed. To assess the validity of either tests or in combination to detect a neoplasm or cancer in the colon, their false positive rates, their sensitivity (true positive rate) and the specificity (true negative rate) were analyzed and compared. Results: One hundred and three patients were analysed. The sensitivity for picking up any neoplasia was 53% for FIT, 40% for gFOBT and 23.3% for the combination. The sensitivities for picking up only carcinoma were 77.8%, 66.7% and 55.5%, respectively. The specificity for excluding any neoplasia was 91.7% for FIT, 74% for gFOBT and 94.5% for a combination, whereas for excluding only carcinomas they were 84%, 73.4% and 93.6%. Of the 69 with normal colonoscopic findings, FOBT was positive in 4.3%, 23.2 %and 2.9% for FIT, gFOBT, or combination of tests respectively. Conclusion: FIT is the recommended method if we are to dispense with dietary restriction in our patients because of its relatively low-false positivity and better sensitivity and specificity rates.

• 대한예방의학회:학술대회논문집
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• 대한예방의학회 1995년도 제47차 추계 학술대회 연제집
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• pp.111-112
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• 1995