• Proceedings of the Zoological Society Korea Conference
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• 1997.10b
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• pp.259.2-259
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• 1997

No Abstract, See Full Text

• Proceedings of the Korea Society of Design Studies Conference
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• 2005.05a
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• pp.114-115
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• 2005

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2483-2503
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• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.517-529
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• 1998

When the sample size is small the robust minimum Hellinger distance (HD) estimator can have substantially poor relative efficiency at the true model. Similarly, approximating the exact null distributions of the ordinary Hellinger distance tests with the limiting chi-square distributions can be quite inappropriate in small samples. To overcome these problems Harris and Basu (1994) and Basu et at. (1996) recommended using a modified HD called penalized Hellinger distance (PHD). Lindsay (1994) and Basu et al. (1997) showed that another density based distance, namely the negative exponential disparity (NED), is a major competitor to the Hellinger distance in producing an asymptotically fully efficient and robust estimator. In this paper we investigate the small sample performance of the estimates and tests based on the NED and penalized NED (PNED). Our results indicate that, in the settings considered here, the NED, unlike the HD, produces estimators that perform very well in small samples and penalizing the NED does not help. However, in testing of hypotheses, the deviance test based on a PNED appears to achieve the best small-sample level compared to tests based on the NED, HD and PHD.

• Journal of Advanced Navigation Technology
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• v.14 no.4
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• pp.504-511
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• 2010

The personal bio-information supplied from the PHD(Personal Health Device) for personal health management is very sensitive in relation to a personal living body in an aspect of privacy protection. On the assumption thai the information is about a patient, it is more serious problem if it is revealed to a third party. However. the established ISO (International Organizations for Standardization) standard protocol[1] in October 2009 has just considered a transmission part for mutual exchange of bio-information between individuals, but has never actually considered security elements. Accordingly, this paper is to show all sorts of security threats according to personal health management in the u-health environment and security requirements newly.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.361-363
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• 2013

본 논문에서는 최근 스마트 헬스케어가 보건의료서비스에 특화시켜 환자와 의사가 직 간접적으로 진료를 할 수 있게끔 하는 스마트폰 환경에서의 원격진료 서비스가 부각됨에 따라 유무선 통신 인프라를 기반으로 노인, 만성질환자, 회복중인 환자나 수술 후 환자 그리고 일반인 등이 일상생활을 하면서 불편하거나, 거추장스럽지 않게 신체 정보를 측정하고 건강상태의 변화에 대한 전문가의 진단을 즉각적으로 제공하기 위해 Bluetooth HDP(Health Device Profile)을 통해 IEEE11073 PHD 표준 기반의 홈 헬스케어 의료기기 연결성을 보장하며, HL7 CDA 기반의 정보 전달 구조로 의료진뿐만 아니라 다양한 스마트 앱 어플리케이션 간의 융합을 가능하게 하는 스마트 헬스케어 솔루션을 설계하고자 한다.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.625-632
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• 2014

The u-health service is using portable device such as smart device and it consists of small computing device. The u-health service carry out same performance with desktop computer. We designed message structure based on Bluetooth HDP. This message structure is used to transmit patient's biometric data on the smart device of medical team, patient and family over the mobile network environment. ISO/IEEE 11073 PHD standard was defined based on the method of communication between the agent and the manager. And We are confirmed the reliable transmission of biometric data at the smart device by implementing the android OS based patient information monitoring application to check the status of patient for medical team, patient and family.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.954-956
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• 2013

IOS/IEEE 11073 PHD 표준들은 u-헬스 측정기기와 u-헬스 게이트웨이간의 통신을 가능하게 하도록 설계되어 있다. 모바일 단말기를 데이터 취합을 위한 중계기로 활용하고 별도의 게이트웨이를 구성하여 헬스케어 의료기기를 연동하고 모니터링을 위한 인터페이스를 제공해 왔으나 스마트폰 애플리케이션 단계에서 IEEE 11073 플랫폼을 포함하여 헬스케어 의료기기를 활용하는 u-헬스케어 서비스를 제공하기에는 많은 제약이 있다. 이에 본 논문에서는 Android 4.0.x OS 스마트폰을 대상으로 Bluetooth HDP을 활용하여 u-헬스케어 시스템에서의 게이트웨이/서버 플랫폼 기능을 포함하는 헬스케어 의료기기의 모니터링 애플리케이션 시스템을 설계하였다.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.10-18
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• 2010

Due to a large number of classes in Hangul character recognition, it is usual to use the six-type preclassification stage. After the preclassification, the first consonent, vowel, and last consonent can be classified separately. Though each of three components has a few of classes, classification errors occurs often due to shape similarity such as 'ㅔ' and 'ㅖ'. So this paper proposes a hierarchical recognition method which adopts multi-stage tree structures for each of 6-types. In addition, to reduce the interference among three components, the method uses the recognition results of first consonents and vowel as features of vowel classifier. The recognition accuracy for the test set of PHD08 database was 98.96%.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.313-314
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• 2014

인구의 고령화로 만성질환자가 증가함에 따라 개인건강관리를 위한 U 헬스 서비스에 관심이 증대되고 있다. U 헬스 서비스를 활용하기 위해서는 다양한 생체정보를 간편하게 측정하는 개인건강기기(PHD, Personal Health Device)가 필요하다. 하지만 혈압, 심전도, 혈당, 산소포화도 등을 측정하는 개인건강기기는 제작 회사마다 서로 다른 프로토콜과 포맷으로 개발되어 기기간의 상호 운용성(Interoperability)이 보장되지 않는다. 또한 각기 다른 포맷으로 측정된 데이터를 병원정보시스템(HIS, Hospital Information System)간 공유하고 관리하는데 어려움이 존재한다. 이에 따라, 본 논문에서는 개인건강기기 국제 표준인 IEEE 11073 PHD 를 기반으로 다양한 개인건강기기와 실시간으로 통신하며, 측정된 생체정보를 관리하고 전송하는 모바일 헬스케어 매니저 설계를 제시한다. 제시한 매니저는 다양한 모바일 기기 중 스마트폰 기반으로 설계하였고, 각기 다른 포맷으로 측정된 데이터를 국제표준 메시지 교환방식인 HL7 (Health Level Seven)메시지로 변환하여 전달하는 게이트웨이 역할을 담당한다.