• 한국IT서비스학회지
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• 제9권3호
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• pp.179-191
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• 2010

Service identification and composition is one of the key characteristics for a successful Service-Oriented Computing, being receiving a lot of attention from researchers in recent years. In the Service-Oriented Analysis, the identification of business services has to be preceded before application services are identified. Most approaches addressing the derivation of business services are based on heuristic methods and human experts. The manual identification of business services is highly expensive and ambiguous task, and it may result in the service design with bad quality because of errors and misconception. Although a few of approaches of automatic service identification are proposed, most of them are in focus on technical architectures and application services. In this paper, we propose a model on the automatic identification of business services by horizontal and vertical service alignment using Enterprise Architecture as an ontology. We verify the effectiveness of the proposed model of business services identification through a case study based on Department of Defense Enterprise Architecture.

• 수산경영론집
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• 제38권1호
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• pp.115-132
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• 2007

Implementing the automatic identification in supply chain management is essential for effective and efficient process control. Though the GTIN based bar code system is generally used as an automatic identification method in most industries, it can not identify individual item, and is not appropriated for products' reliability and safety management. So the RFID system with EPC is considered as a better solution for resolving those problems. This study reviewed automatic identification code systems and the attributes and characteristics of RFID Gen 2 which became a global standard recently for supply chain management. Particularly, this study analyzed RFID Gen 2 systems' read rates on various conditions including distances between tags and readers and between antennas, condensation, and several packing materials in practical supply chain environment. The results of this study showed that the RFID Gen 2 had high read ratio in practical application and would be adopted as a new automatic identification means for traceability systems.

• 한국항해항만학회지
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• 제27권6호
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• pp.693-700
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• 2003

Universal AIS, which has been adopted officially for automatic identification systems among regulated ships by SOLAS, should be installed, for example, on all passenger ships over 300 tons engaged in international voyage and over 500 tons in domestic voyage, sequentially from 2002 to 2004. We must not overlook the fact than-ruled regions by regional authorities in the case of VTS. Actually a major portion of accidents have happened in small vessels like fishing vessels. However, they are not equipped with automatic identification tools, due to the high costs of the equipment for identifying purposes, as well as the absence of regulation In this paper, we researched the alternative of automatic identification for small vessel instead of universal AIS. We analyzed the requirement of automatic identification for small vessel about wireless communication method, traffic volume, etc. We proposed the identification system for small vessels in local areas and developed the Local Vessel Identification System (LVIS) interoperable with universal AIS using a PDA platform and wireless network.

• Journal of the Korean Wood Science and Technology
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• 제45권6호
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• pp.797-808
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• 2017

Automatic wood species identification systems have enabled fast and accurate identification of wood species outside of specialized laboratories with well-trained experts on wood species identification. Conventional automatic wood species identification systems consist of two major parts: a feature extractor and a classifier. Feature extractors require hand-engineering to obtain optimal features to quantify the content of an image. A Convolutional Neural Network (CNN), which is one of the Deep Learning methods, trained for wood species can extract intrinsic feature representations and classify them correctly. It usually outperforms classifiers built on top of extracted features with a hand-tuning process. We developed an automatic wood species identification system utilizing CNN models such as LeNet, MiniVGGNet, and their variants. A smartphone camera was used for obtaining macroscopic images of rough sawn surfaces from cross sections of woods. Five Korean softwood species (cedar, cypress, Korean pine, Korean red pine, and larch) were under classification by the CNN models. The highest and most stable CNN model was LeNet3 that is two additional layers added to the original LeNet architecture. The accuracy of species identification by LeNet3 architecture for the five Korean softwood species was 99.3%. The result showed the automatic wood species identification system is sufficiently fast and accurate as well as small to be deployed to a mobile device such as a smartphone.

• 대한인간공학회지
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• 제24권2호
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• pp.35-43
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• 2005

The purpose of this study is to suggest computer assisted neck-base's landmark identification algorithms and measurement extraction methods from three-dimensional human scan data. So we developed the algorithms for automatic identification of landmarks related to the neck-base types. The subjects were 58 women $18{\sim}24$ years of age. Their body were measured directly and indirectly by using camera and three-dimensional body scanner. They were measured during the months of October in 2001. Based on the characters of classified neck-base types, algorithms for the automatic identification of landmarks and methods of automatic measurement are developed. The three-dimensional automatic measuring program is made by $C^{++}$ language. Using this program, 4 landmarks are identified and 6 items are measured. In the verifying the precision of automatic measurement, the height measurements(cervicale, side neck point, front neck point) were relatively accurate, but neck-base width measurement was measured wide.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제54권10호
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• pp.492-496
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• 2005

An electronic ballast with automatic identification between HPS and MH lamps is proposed in this paper. The behavior of the lamp impedance is studied at both cold-starting and warm-starting. Lamp identification is carried out by taking into account the rate of impedance changing at constant current driving mode just after ignition. The ballast consists of 8-bit microcontroller and LCC resonant inverter.

• 말소리와 음성과학
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• 제4권3호
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• pp.95-101
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• 2012

In this paper, we introduce the automatic speaker identification system 'SPO(Supreme Prosecutors Office) Verifier'. SPO Verifier is a GMM(Gaussian mixture model)-UBM(universal background model) based automatic speaker recognition system and has been developed using Korean speakers' utterances. This system uses a channel compensation algorithm to compensate recording device characteristics. The system can give the users the ability to manage reference models with utterances from various environments to get more accurate recognition results. To evaluate the performance of SPO Verifier on Korean speakers, we compared this system with one of the most widely used commercial systems in the forensic field. The results showed that SPO Verifier shows lower EER(equal error rate) than that of the commercial system.

• Journal of Ship and Ocean Technology
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• 제6권1호
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• pp.16-26
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• 2002

In this paper, a motion identification method using neural networks is applied to automatic ship berthing to overcome disturbance effects. Motion identification is used to estimate the effect of environmental disturbance. Two rule-based algorithms have been developed to over-come disturbance. The first rule based-algorithm was designed to overcome lateral disturbance when a ship's lateral speed is affected by it. The second rule-based algorithm was also designed to overcome longitudinal disturbance when a ship's angular velocity is changed by it. Finally, numerical simulations for automatic berthing are carried out, and the suggested control system is proved to be more practical under disturbance circumstances.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.43.4-43
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• 2001

This paper deals with motion identification using artificial neural network (ANN) and its application to automatic ship berthing. As ship motions are expressed by multi-term non-linear model, it is very difficult to find optimal methods for automatic ship berthing especially under environmental disturbances. In this paper, metier identification was used to estimate the effect of environmental disturbances and then the differences between values of identification and state variables are used to estimate the effect of environmental disturbances. A rule based-algorithm using the difference is suggested to cope with the effect of the disturbances. The algorithm adjusts the value of input units of ANN, which control a ship to keep desired route ...

• 정보처리학회논문지D
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• 제15D권6호
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• pp.861-872
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• 2008

컴퓨팅 환경이 발전함에 따라 다양한 물리적 객체와 디지털 정보를 연동하는 자동인식 연구가 활발히 진행 중이다. 이러한 자동인식시스템은 다양한 산업분야에서 활용되고 있음에도 불구하고 보건의료와 관련한 자동인식 기술의 접목은 아직까지 다른 산업기술 전반에 미치지 못하고 있는 실정이다. 이에 따라 의료장비, 혈액, 인체조직 등 보건의료 용품의 자동인식에 관한 여러 연구가 진행 중이다. 이 논문은 인간 유전체 연구의 필수 연구재료인 생물자원을 대상으로 자동인식 기술의 적용 방안을 제안한다. 먼저, 자동인식기술 도입을 위해 사용 환경상의 고려사항을 정의하고, 조사과정 또는 실험을 통하여 적합한 형태의 태그 인터페이스로서 바코드를 선택하였다. 바코드 심볼로지는 2차원 바코드 심볼로지인 Data Matrix를 사용하고, 데이터 스키마는 국제적 범용성 추구를 위하여 UCC/EAN-128 기반으로 설계하였다. 제안된 기술들이 실제 환경에 적용되는지를 보이기 위한 어플리케이션을 개발하고, 이에 대한 실험 및 평가를 다음의 방법으로 수행하였다. 생물자원이 실제 보존되는 영하 $196^{\circ}C$, 영하 $75^{\circ}C$의 초저온 보존환경에서 바코드 인식실험을 한 결과 1.6초 내외의 평균 인식시간을 보이며, 데이터 스키마는 생물자원 활용 분야의 요구사항을 만족하는 것으로 평가되었다. 따라서 제안한 방법으로 생물자원의 정보처리 과정에서 정확성과 데이터 입력의 신속성이 제공될 수 있다.