• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.69-74
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• 2011

In the curving detection method by using an accelerometer, the ride comfort in the first car is worse than one in the others due to spend the time to calculate the tilting command and drive the tilting mechanism after entering in the curve. In order to enhance the ride comfort in the first car, the preditive curve detection method which predicts the distance from a train to the starting point of curve by using the GPS, Tachometer, Ground balise and position DB for track. In this study, we predicted and evaluated the ride comfort for predictive curve detection method in transient curves according to the shape and dimension of transient curve and the various driving speed. Also, we predicted the improvement of the ride comfort for predictive curve detection method by comparing with the result of the ride comfort for predictive curve detection method and for curve detection method using an accelerometer in the short transient curve.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.169-171
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• 2004

This paper propose a new detection method of curve lane using Catmull-Rom spline for recognition various shape of the curve lane. To improve the accracy of lane detection, binarization and thinning process are firstly performed on the input image. Next, features on the curve lane such as curvature and orientation are extracted, and the control points of Catmull-Rom spline are detected to recognize the curve lane. Finally, Computer simulation results are given using a natural test image to show the efficiency of the proposed scheme.

• 한국식품과학회지
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• 제32권3호
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• pp.525-530
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• 2000

국내에서 생산된 농산물의 방사선 조사유무를 확인하기 위하여 TL을 측정하였다. 모든 시료의 first glow curve는 조사선량이 증가할수록 TL intensity도 증가하는 경향을 보여 주었다. 당근, 생강, 감자, 고구마의 상관계수는 0.8522, 0.9968, 0.9612, 0.9071의 높은 값을 나타내었으며, first glow curve의 최대발광온도점은 $176.16{\sim}190.08^{\circ}C$사이에 있었고, second glow curve는 $143.84{\sim}146.56^{\circ}C$ 사이에서 나타났다. Glow curve ratio 1은 감자와 고구마를 제외하고 모두 0.1보다 작은 수치를 보여 비조사시료로 확인되었으며, 감자(0.1840)와 고구마(0.1655)는 0.1보다 큰 수치를 보였으나 독특한 first glow curve가 나타나지 않은 점으로 보아 비조사시료로 확인되었다. 그리고 모든 시료의 glow curve ratio 2는 0.7159보다 높은 수치를 나타내어 조사시료로 확인되었다. Glow curve의 모양을 분석한 결과 second glow curve의 모양이 first glow curve의 유사하였고, 더 낮은 온도에서 나타났다. 따라서 glow curve ratio와 glow curve의 모양에 의해 정확하게 조사유무를 확인할 수 있었고 TL을 이용하여 방사선 조사된 농산물의 검지가 가능함을 확인할 수 있었다.

• Preventive Nutrition and Food Science
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• 제6권1호
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• pp.23-28
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• 2001

A study was carried out to establish a detection method of irradiated shellfish through thermoluminescence (TL). The TL intensity of first glow curves for irradiated bloody, freshwater, and short-neck shellfish increased from control until 5 kGy and increased slightly room 5 kGy until 10 kGy. Maximum TL temperatures of all irradiated samples tested were below 23$0^{\circ}C$, within temperature interval of 150~25$0^{\circ}C$ recommended for evaluation. Since just in control, glow curve ratios of G3 and G4 calculated from re-irradiated (1 kGy) bloody, freshwater and shortneck were over 0.5, detection in control was possible. However, as glow curve ratios after three months were below 0.5, detection by glow curve ratios after three months was impossible. Gl, which calculated from unirradiated samples, exhibited below 0.1, they were classified as unirradiated. In all samples, all the irradiated shellfish could be classified correctly as irradiated by hemaximum TL temperatures and shape of the second glow curve because those were shown in a lower temperature region than those of the first glow curve.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.5159-5178
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• 2018

Network Intrusion detection is a rapidly growing field of information security due to its importance for modern IT infrastructure. Many supervised and unsupervised learning techniques have been devised by researchers from discipline of machine learning and data mining to achieve reliable detection of anomalies. In this paper, a deep convolutional neural network (DCNN) based intrusion detection system (IDS) is proposed, implemented and analyzed. Deep CNN core of proposed IDS is fine-tuned using Randomized search over configuration space. Proposed system is trained and tested on NSLKDD training and testing datasets using GPU. Performance comparisons of proposed DCNN model are provided with other classifiers using well-known metrics including Receiver operating characteristics (RoC) curve, Area under RoC curve (AuC), accuracy, precision-recall curve and mean average precision (mAP). The experimental results of proposed DCNN based IDS shows promising results for real world application in anomaly detection systems.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.1577-1578
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• 2013

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권11호
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• pp.912-919
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• 2009

본 논문에서는 이차원 텐서보팅과 에지 기반 방법을 이용하여 자연영상에서 문자를 검출하는 새로운 방법을 제시한다. 텍스트의 문자들은 보통 연속적인 완만한 곡선 상에 배열되어 있고 서로 가깝게 위치하며, 이러한 특성은 텐서보팅에 의하여 효과적으로 검출될 수 있다. 이차원 텐서보팅은 토큰의 연속성을 curve saliency 로 산출하며 이러한 특성은 다양한 영상해석에 사용된다. 먼저 에지 검출을 이용하여 영상 내의 텍스트 영역이 위치할 가능성이 있는 텍스트 후보영역을 찾고 이러한 후보영역의 연속성을 텐서보팅에 의해 검증하여 잡음영역을 제거하고 텍스트 영역만을 구분한다. 실험 결과, 제안된 방법은 복잡한 자연영상에서 효과적으로 텍스트 영역을 검출함을 확인하였다.

• 제어로봇시스템학회논문지
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• 제21권2호
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• pp.130-136
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• 2015

In this paper, we propose a robust curved lane marking detection method. Several lane detection methods have been proposed, however most of them have considered only straight lanes. Compared to the number of straight lane detection researches, less number of curved-lane detection researches has been investigated. This paper proposes a new curved lane detection and tracking method which is robust to various illumination conditions. First, the proposed methods detect straight lanes using a robust road feature image. Using the geometric relation between a vehicle camera and the road plane, several circle models are generated, which are later projected as curved lane models on the camera images. On the top of the detected straight lanes, the curved lane models are superimposed to match with the road feature image. Then, each curve model is voted based on the distribution of road features. Finally, the curve model with highest votes is selected as the true curve model. The performance and efficiency of the proposed algorithm are shown in experimental results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권3호
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• pp.263-267
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• 2005

Building classifiers for financial real-world classification problems is often plagued by severely overlapping and highly skewed class distribution. New performance measures such as receiver operating characteristic (ROC) curve and area under ROC curve (AUC) have been recently introduced in evaluating and building classifiers for those kind of problems. They are, however, in-effective to evaluation of classifier's discrimination performance in a particular class of the classification problems that interests lie in only a local operating range of the classifier, In this paper, a new method is proposed that enables us to directly improve classifier's discrimination performance at a desired local operating range by defining and optimizing a partial area under ROC curve or domain-specific curve, which is difficult to achieve with conventional classification accuracy based learning methods. The effectiveness of the proposed approach is demonstrated in terms of fraud detection capability in a real-world fraud detection problem compared with the MSE-based approach.

• 디지털융복합연구
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• 제14권8호
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• pp.253-259
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• 2016

차선의 인식을 위한 연구는 차량의 자율 주행 또는 교통사고의 예방을 위하여 지속적인 연구가 진행되고 있으며, 최근에는 다양한 알고리즘이 등장하여 차선 인식과 검출은 비약적으로 발전하였다. 이들 연구는 주로 비전 시스템 기반의 연구이며 인식률 또한 상당히 좋아 졌다. 그러나 야간의 도로 또는 우천 시에는 그 인식률이 아직 만족할 수준까지 도달하지는 못하였다. 본 논문은 이러한 비전 시스템 기반의 차선 인식 및 검출의 단점을 개선하여 사고 발생 후 대응을 위한 센서 융합 기술을 적용하여 차선 검출에 대한 연구를 수행하였고, 차선 검출에 대한 연구 중 곡선차선의 검출에 대한 연구를 진행하였다. 도로는 직선도로 뿐만 아니라 다양한 곡선도로까지 검출 가능해야 하며 이는 교통사고 조사 시에 활용될 수 있다. 커브의 굽은 정도를 나타내는 곡률의 임계값을 0.001~0.06로 하여 곡선자선을 산출해 낼 수 있음을 보였다.