• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.2
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• pp.111-124
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• 1996

The main purpose of this study is to develop an algorithm to solve the scheduling problems of FMS using Petri-net is well suited to model the dynamics of FMS and Petri-net is an ideal tool to formulate scheduling problems with routing flexibility and shared resources. By using the marking of Petri-net, We can model features of discrete even system, such as concurrency, asynchronous, conflict and non-determinism. The proposed algorithm in this paper can handle back-tracking using the marking of Petri-net. The results of the experiment show that marking is one of the best ways that describe exactly movement of the discrete event system. To show the effectiveness of the algorithm suggested here, we compare it with L1 algorithm using the Petri-net through the test on randomly generated test problems.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.364-364
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• 2000

Timed Petri Net(TPN) is one of methods to model and to analyze Discrete Event Dynamic Systems(DEDSs) with real time values. It has two time values, earliest firing time ($\alpha$$_{i}$) and latest firing time ($\beta$$_{I}$) for the each transition. A transition of TPN is fired at arbitrary time of time interval ($\alpha$$_{I}$, $\beta$$_{i}$). Uncertainty of firing time gives difficulty to analyze and estimate a modeled system. In this paper, we proposed the Fuzzy Transition Timed Petri Net(FTTPN) with fuzzy theory to determine the optimal transition time (${\gamma}$$_{i}$). The transition firing time (${\gamma}$$_{i}$) of FTTPN is determined from fuzzy controller which is modeled with information of state transition. Each of the traffic signal controllers are modeled using the proposed method and timed petri net. And its Performance is evaluated by simulation of traffic signal controller. controller.

• Nuclear Engineering and Technology
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• v.36 no.3
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• pp.219-228
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• 2004

[1] and [2] present an approach to diagnosing possible defects in the mechanical systems of a nuclear power plant. In this paper, by using a fault library as a database and training data, we develop a diagnostic algorithm 1) to decide whether an Air Operated Valve system is sound or not and 2) to identify the defect from which an Air-Operated Valve system suffers, if any. This algorithm is composed of three stages: a neural net stage, a non-neural net stage, and an integration stage. The neural net stage is a simple perceptron, a pattern-recognition module, using a neural net. The non-neural net stage is a simple pattern-matching algorithm, which translates the degree of matching into a corresponding number. The integration stage collects each output and makes a decision. We present a simulation result and confirm that the developed algorithm works accurately, if the input matches one in the database.

• Korean Journal of Computational Design and Engineering
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• v.12 no.4
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• pp.274-282
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• 2007

In this paper, a method of constructing a rectangular net from unorganized point cloud data is presented. In the method an implicit surface that fits the given point data is generated by using principal component analysis(PCA) and adaptive domain decomposition method(ADDM). Then a complete and quality rectangular net can be obtained by extracting voxel data from the implicit surface and projecting exterior faces of extracted voxels onto the implicit surface. The main advantage of the proposed method is that a quality rectangular net can be extracted from randomly scattered 3D points only without any further information. Furthermore the results of this works can be used to obtain many useful information including a slicing data, a solid STL model and a NURBS surface model in many areas involved in treatment of large amount of point data by proper processing of implicit surface and rectangular net generated previously.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.2 s.16
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• pp.109-116
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• 2000

GeoNet is java-based remotely sensed image processing system. It is based on java Ibject-oriented paradigm and features cross-platform, web-based execution and extensibility to client/server remotely sensed image processing model. Remotely sensed image processing softwares made by java programming language can suggest alternatives to meet readily demand on remotely sensed image processing in proportion to increasement of remotely sensed data.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.916-922
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• 2002

본 연구는 WfMS라는 사용환경 하에서, 워크플로우 프로세스라는 대상 객체를 BOM(bill of material) 정보로 부터 High Level Petri net 형식으로 자동적으로 생성할 수 있는 엔진의 개발을 궁극적인 목표로 설정하고 있다. BOM은 제조되는 제품의 구조에 대한 정보를 지니고 있다. 관리 및 생산이라는 두 도메인 사이의 차이점에도 불구하고, 생산 분야의 BOM 정보의 이용방식이 관리 프로세스의 설계에도 이용될 수 잇다는 사실을 먼저 설명한다. 워크플로우 프로세스는 Petri Net의 형식으로 표시한다. 주어진 BOM으로부터 이에 대응하는 petri net을 생성할 수 있는 매핑 알고리즘을 소개한다. 이러한 이론 및 알고리즘을 기반으로 하여, 주어진 BOM 정보로부터 이에 대응하는 Petri Net 정보를 자동으로 생성시키는 프로세스 디자이너의 프로토타입을 구현하여 소개한다.

• Annual Conference on Human and Language Technology
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• 2004.10d
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• pp.106-111
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• 2004

사람의 언어를 이해하는 자연언어처리 시스템을 개발하기 위해서는 의미처리를 위한 지식 베이스(knowledge base)가 필요하다. 지금까지 사람이 가진 지식 베이스를 컴퓨터에 도입하려는 많은 노력을 기울이고 있고 그 결과물로 온톨로지(ontology)와 시소러스(thesaurus)가 만들어지고 있다. 외국에서는 지식 베이스의 중요성을 알고 많은 연구를 수행하고 있으며 그 대표적인 사례들에는 Roget's Thesaurus, WordNet, EDR 개념사전, CYC, Euro WordNet 등이 있다. 이 중에서 가장 대표적이며 많은 활용을 보이는 것이 Princeton 대학의 WordNet이다. WordNet은 인간의 어휘지식에 대한 심리 언어학적인 연구의 결과물로써 심리학자와 언어학자들에 의해 10여 년 동안 구축되고 있는 영어에 대한 어휘데이터베이스이다. 본 논문에서는 WordNet을 기반으로 명사에 대해서 영한사전과 국어사전을 이용하여 구축한 한국어 워드넷을 소개하구 구축시 고려한 기본지침을 소개하도록 하겠다.

• Investigative Magnetic Resonance Imaging
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• v.22 no.2
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• pp.123-130
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• 2018

An ampulla of Vater neuroendocrine tumor (AOV-NET) is a rare subset of gastroenteropancreatic neuroendocrine tumors (GEP-NETs). Very few studies have been undertaken regarding MRI findings of an AOV-NET. We report on a case of a 59-year-old woman diagnosed with an AOV-NET with liver and lymph node metastasis, with an emphasis on the MRI findings. This case shows rare and precious typical MRI findings of an AOV-NET. The MRI visualized the AOV-NET very well and is helpful for the differentiation of an AOV-NET from other tumors in the ampullary area as well as with treatment planning.

• Proceedings of the Safety Management and Science Conference
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• 2003.05a
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• pp.185-193
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• 2003

This paper is intended as an investigation of Build-up Method of SCM Connection applying EC Standard(Rossetta-net) to reduce the integration effort, and improve extensibility and interoperability of an eBusiness infrastructure.-Intiative way for I-commerce applications to quickly incorporate new standards. Let me summarize the main points that have been made in this paper. The sharing information for connection and the Rosetta-net standard of the existing SCM system, and PIP 3A4, order management module, of the Rosetta-net specifications for connection by the Rosetta-net. Lastly, That shows the process of the gateway for connecting among the existing SCM systems.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.11-15
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• 2020

In a typical initial setup of a PCB component inspection system, operators should manually input various information such as category, position, and inspection area for each component to be inspected, thus causing much inconvenience and longer setup time. Although there are many deep learning based object detectors, RetinaNet is regarded as one of best object detectors currently available. In this paper, a method using an extended RetinaNet is proposed that automatically detects its component category and position for each component mounted on PCBs from a high-resolution color input image. We extended the basic RetinaNet feature pyramid network by adding a feature pyramid layer having higher spatial resolution to the basic feature pyramid. It was demonstrated by experiments that the extended RetinaNet can detect successfully very small components that could be missed by the basic RetinaNet. Using the proposed method could enable automatic generation of inspection areas, thus considerably reducing the setup time of PCB component inspection systems.