• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2015.07a
• /
• pp.310-311
• /
• 2015

Ships' tracking data are being monitored and collected by vessel traffic service center in real time. In this paper, we intend to contribute to vessel traffic service operators' decision making through extracting ships' tracking patterns and models based on these data. Support Vector Machine algorithm was used for vessel track modeling to handle and process the data sets and k-fold cross validation was used to select the proper parameters. Proposed data processing methods could support vessel traffic service operators' decision making on case of anomaly detection, calculation ships' dead reckoning positions and etc.

• Journal of Internet Computing and Services
• /
• v.7 no.3
• /
• pp.119-132
• /
• 2006

The network based security techniques well-known until now have week points to be passive in attacks and susceptible to roundabout attacks so that the misuse detection based intrusion prevention system which enables positive correspondence to the attacks of inline mode are used widely. But because the Misuse detection based Intrusion prevention system is proportional to the detection rules, it causes excessive false alarm and is linked to wrong correspondence which prevents the regular network flow and is insufficient to detect transformed attacks, This study suggests an Intrusion prevention system which uses Support Vector machines(hereinafter referred to as SVM) as one of rule based Intrusion prevention system and Anomaly System in order to supplement these problems, When this compared with existing intrusion prevention system, show performance result that improve about 20% and could through intrusion prevention system that propose false positive minimize and know that can detect effectively about new variant attack.

• Journal of KIISE:Software and Applications
• /
• v.37 no.9
• /
• pp.712-721
• /
• 2010

This paper proposes a new fire-flame detection method using probabilistic membership function of visual features and Fuzzy Finite Automata (FFA). First, moving regions are detected by analyzing the background subtraction and candidate flame regions then identified by applying flame color models. Since flame regions generally have continuous and an irregular pattern continuously, membership functions of variance of intensity, wavelet energy and motion orientation are generated and applied to FFA. Since FFA combines the capabilities of automata with fuzzy logic, it not only provides a systemic approach to handle uncertainty in computational systems, but also can handle continuous spaces. The proposed algorithm is successfully applied to various fire videos and shows a better detection performance when compared with other methods.

• The Journal of the Korea Contents Association
• /
• v.9 no.2
• /
• pp.432-438
• /
• 2009

In this paper, we evaluated the performance of the automatic classifier applied for the discrimination of acute alcoholic liver injury and chronic liver fibrosis. The classifier uses the discriminant peaks of the preprocessed Raman spectrum as a feature set. In preprocessing step, we subtract baseline and apply Savitzky-Golay smoothing filter which is known to be useful at preserving peaks. After identifying discriminant peaks from the spectra, we carried out the classification experiments using MAP and neural networks. According to the experimental results, the classifier shows the promising results to diagnosis alcoholic liver injury and chronic liver fibrosis. Classification results over 80% means that the peaks used as a feature set is useful for diagnosing liver disease.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.3
• /
• pp.72-77
• /
• 2017

This paper focuses on the development of a supporting S/W tool for the automated design of an automotive press trim die. To define the die design process based on automation, we analyze the press die design process of the current industry and group repetitive works in the 3D modeling process. The proposed system consists of two modules, namely the template models of the trim steel parts and UI function for their auto-positioning. Four kinds of template models are developed to adapt to various situations and the rules of the interaction formula which are used for checking and correcting the directions of the datum point, datum curve, datum plane are implemented to eliminate errors. The system was developed using CATIA Knowledgeware, CAA(CATIA SDK) and Visual C++, in order for it to function as a plug-in module of CATIA V5, which is one of the major 3D CAD systems in the manufacturing industry. The developed system was tested by applying it to various panels of current automobiles and the results showed that it reduces the time-cost by 74% compared to the traditional method.

• Proceedings of the KSRS Conference
• /
• 2007.03a
• /
• pp.153-157
• /
• 2007

본 논문은 지표면 현상의 관측에 날씨의 영향을 거의 받지 않는 마이크로파 L-밴드(1.95 GHz)와 C-밴드(5.3 GHz) scatterometer 시스템을 이용하여 농업과학기술원 내의 논에서 자라는 추청벼를 대상으로 2006년 5월 29일부터 10월 9일까지 생육에 따른 군락의 후방산란계수를 관측한 데이터와 작물의 생육과의 관계를 살펴보고 또한，측정 시스템의 개요，측정 시스템의 보정 방법들을 기술하고자 한다. Scatterometer 시스템의 송 수신기로 HP 8753D 벡터 네트워크 분석기를 사용하며，타워 위에 안테나를 설치하여 3.4 m의 높이에서 측정하도록 하였다. L-밴 드와 C-밴드 scatterometer는 VV-, VH-, HV-, HH-편파를 측정하여 fully polarimetric한 데이터를 얻도록 설계된 레이더시스템으로 입사각을 $30^{\circ}{\sim}60^{\circ}$에서 $10^{\circ}$간격으로 각각 30개의 독립적인 샘플을 측정하여 통계적으로 후방산란계수를 얻었다. 타워에서 발생하는 전파 잡음과 안테나 패턴의 부엽에 의한 지면에서의 수직반사(coherent 성분) 전파를 제거하기 위해 네트워크 분석기의 time gating 기능을 사용하며，55 cm 크기의 trihedral 전파반사기를 보정용 반사기로 사용하고， STCT(single target calibration technique) 방법을 이용하여 시스템을 보정하였다. 측정 결과를 분석하여 주파수， 입사각도， 편파의 변화에 대한 벼의 후방산란 특성과 벼의 생육상태과의 관계를 살펴보았다. L-밴드와 C-밴드 모두 벼의 생육과 밀접한 결과를 나타내었으나，입사각이 작을 때는 C-밴드와의 상관이 높게 나타났고 입사각이 커질수록 L-밴드와의 상관이 높게 나타났다. 편파는 L-밴드 와 C-밴드 모두 hh 편파가，입사각은 50도에서 가장 생육의 변이를 잘 설명하는 것으로 나타났다. 생육 데이터 모두를 이용한 경우보다는 유수형성기 또는 출수기 등 벼 생육의 질적인 변화를 보이는 시기에 따라 나누어 분석하는 것이 변화추이를 더 잘 설명하는 것으로 나타났다.

• The Korean Journal of Applied Statistics
• /
• v.31 no.3
• /
• pp.353-366
• /
• 2018

This study uses mixed-effects models to predict thigh soft tissue artefact (STA), relative movement of soft tissue such as skin to femur occurring during hip joint motions. The random effects in the model were defined as STA and the fixed effects in the model were considered as skeletal motion. Five male subjects without musculoskeletal disease were selected to perform various hip joint rotational motions. Linear mixed-effects models were applied to markers' position vectors acquired from non-invasive method, photogrammetry. Predicted random effects showed similar patterns of STA among subjects. Large magnitudes of STA appeared on the points near the hip joint regardless of sides; however, small values appeared on the distal anterior.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.4
• /
• pp.256-265
• /
• 2003

To improve reliability and practicality, a fingerprint-based biometric system needs to be robust to rotations of an input fingerprint and the processing speed should be fast. Accordingly, this paper presents a new filterbank-based fingerprint feature extraction and matching method that is robust to diverse rotations and reasonably fast. The proposed method fast extracts fingerprint features using a directional filter bank, which effectively decomposes an image into several subband outputs Since matching is also performed rapidly based on the Euclidean distance between the corresponding feature vectors, the overall processing speed is so fast. To make the system robust to rotations, the proposed method generates a set of feature vectors considering various rotations of an input fingerprint and then matches these feature vectors with the enrolled single template feature vector. Experimental results demonstrated the high speed of the proposed method in feature extraction and matching, along with a comparable verification accuracy to that of other leading techniques.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.6
• /
• pp.141-148
• /
• 2003

This paper proposes a new algorithm that generates the smooth and realistic transition views from one viewpoint to another on the multi-panorama based navigation system. The proposed algorithm is composed of two steps. One is prewarping that aligns the viewing directions of two panoramic images, and the other is the bidirectional disparity morphing(BDM) that generates the intermediate scene from the aligned panoramic images. For prewarping, we compute the phase correlation between two images in order to obtain the information, such as translation, rotation, and scaling. Then we align the viewing directions of two original images using these information. Afterprewarping, we compute the block based disparity vector(DV) and smooth them using two occluding patterns. As we apply these DVs to the BDM, we can generate the elaborate intermediate scene. We make an experiment on the proposed algorithm with some real panoramic images and obtain good quality intermediate scenes.

• The Korean Journal of Applied Statistics
• /
• v.32 no.5
• /
• pp.671-681
• /
• 2019

Studies on predicting arrhythmia using machine learning have been actively conducted with increasing number of arrhythmia patients. Existing studies have predicted arrhythmia based on multivariate data of feature variables extracted from RR interval data at a specific time point. In this study, we consider that the pattern of the heart state changes with time can be important information for the arrhythmia prediction. Therefore, we investigate the usefulness of predicting the arrhythmia with multivariate time series data obtained by extracting and accumulating the multivariate vectors of the feature variables at various time points. When considering 1-nearest neighbor classification method and its ensemble for comparison, it is confirmed that the multivariate time series data based method can have better classification performance than the multivariate data based method if we select an appropriate time series distance function.