• Title/Summary/Keyword: domain knowledge

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Optimazation of Simulated Fuzzy Car Controller Using Genetic Algorithm (유전자 알고즘을 이용한 자동차 주행 제어기의 최적화)

  • Kim Bong-Gi
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.1
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    • pp.212-219
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    • 2006
  • The important problem in designing a Fuzzy Logic Controller(FLC) is generation of fuzzy control rules and it is usually the case that they are given by human experts of the problem domain. However, it is difficult to find an well-trained expert to any given problem. In this paper, I describes an application of genetic algorithm, a well-known global search algorithm to automatic generation of fuzzy control rules for FLC design. Fuzzy rules are automatically generated by evolving initially given fuzzy rules and membership functions associated fuzzy linguistic terms. Using genetic algorithm efficient fuzzy rules can be generated without any prior knowledge about the domain problem. In addition expert knowledge can be easily incorporated into rule generation for performance enhancement. We experimented genetic algorithm with a non-trivial vehicle controling problem. Our experimental results showed that genetic algorithm is efficient for designing any complex control system and the resulting system is robust.

Automatic Electronic Cleansing in Computed Tomography Colonography Images using Domain Knowledge

  • Manjunath, KN;Siddalingaswamy, PC;Prabhu, GK
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.18
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    • pp.8351-8358
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    • 2016
  • Electronic cleansing is an image post processing technique in which the tagged colonic content is subtracted from colon using CTC images. There are post processing artefacts, like: 1) soft tissue degradation; 2) incomplete cleansing; 3) misclassification of polyp due to pseudo enhanced voxels; and 4) pseudo soft tissue structures. The objective of the study was to subtract the tagged colonic content without losing the soft tissue structures. This paper proposes a novel adaptive method to solve the first three problems using a multi-step algorithm. It uses a new edge model-based method which involves colon segmentation, priori information of Hounsfield units (HU) of different colonic contents at specific tube voltages, subtracting the tagging materials, restoring the soft tissue structures based on selective HU, removing boundary between air-contrast, and applying a filter to clean minute particles due to improperly tagged endoluminal fluids which appear as noise. The main finding of the study was submerged soft tissue structures were absolutely preserved and the pseudo enhanced intensities were corrected without any artifact. The method was implemented with multithreading for parallel processing in a high performance computer. The technique was applied on a fecal tagged dataset (30 patients) where the tagging agent was not completely removed from colon. The results were then qualitatively validated by radiologists for any image processing artifacts.

Building and Applying Shipbuilding Ontology for BOM Data Interoperability in Heterogeneous Shipbuilding PLM Systems (이 기종 조선 PLM 시스템 간 BOM Data 교환을 위한 조선 온톨로지 Framework 구축)

  • Kim, Dae-Seok;Lee, Kyung-Ho;Lee, Jung-Min;Lee, Kwang;Kim, Jin-Ho
    • Korean Journal of Computational Design and Engineering
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    • v.16 no.3
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    • pp.197-206
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    • 2011
  • Shipbuilding is a complex industry which contains a lot of knowledge, technology, and utilities. Hence, the necessity of the PLM (Product Life-cycle Management) system which manages life-cycle information of marine product has been increased. So, many studies related to shipbuilding PLM have been preceded, and there are some cases to be built. To implement collaboration and concurrent engineering of ship designing and manufacturing, interoperability of product data in heterogeneous system is required. Also, sharing and reusing knowledge are important for innovation of business process and productivity of enterprises. Even though many studies related interoperability of product data are going on in varies domain, the application to shipbuilding is deficient. This paper proposes a methodology for management and interconnection of BOM data based on ontology in heterogeneous PLM system of shipbuilding. Using Prot$\'{e}$g$\'{e}$-OWL, we built simple domain ontology of shipbuilding industry, and then, we integrated product information of shipbuilding BOM which is represented with different ontologies. We verified possibility of integration of shipbuilding BOM in heterogeneous PLM, using ontology.

The Influence of Relationship-specificity of Invested Assets on Electronic Collaboration and Firm's Performance in Small and Medium Enterprises (기업간 관계자산 특유성이 전자적 협력과 성과에 미치는 영향)

  • Choi, Su-Jeong;Ko, Il-Sang
    • Asia pacific journal of information systems
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    • v.16 no.4
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    • pp.121-149
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    • 2006
  • This study tries to explain how the relationship-specificity of invested assets affects E-collaboration and consequently on performance of Small and Medium Enterprises (SMEs). We classify the relationship-specificity of invested assets into four types such as business process specificity, physical asset specificity, domain knowledge specificity, and site specificity. We define E-collaboration as composed of Electronic Information Sharing (EIS) and Electronic Cooperation (E-Co). In addition, we articulate firm's performance as operational and strategic one, and investigate the impacts of EIS and E-Co on its performance. The data were collected from 187 SMEs and used for analysis. Based on the survey results, we find the following: (1) EIS is directly influenced by business process specificity and physical asset specificity, (2) E-Co is affected by site specificity and domain knowledge specificity, (3) EIS has a positive and significant impact on E-Co, (4) EIS affects firm's operational performance, (5) E-Co influences on firm's strategic performance. In conclusions, the higher the level of EIS, SMEs seem to get greater operational performance, Respectively, the higher the level of E-Co, they tend to get greater strategic performance.

Construction of the Concept-Based Faceted Framework for Thesaurus Integration (시소러스 통합을 위한 개념기반 패싯 프레임워크 구축)

  • Lee, Seung-Min
    • Journal of Korean Library and Information Science Society
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    • v.41 no.3
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    • pp.269-290
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    • 2010
  • Applying one specific thesaurus might cause several problems because each thesaurus has its own characteristics inherited from its construction process. Therefore, integration of thesauri can be an appropriate approach to overcome the difficulties. This current research selected physics as a domain and two thesauri in the domain: PACS and PIRA. By integrating these two heterogeneous thesauri, this research could construct a conceptual structure that covers the whole concepts related to physics. By constructing the conceptual structure with the use of facet analysis from integrated thesaurus, it provides knowledge base with hierarchical structure and clear relationships between concepts. It can be an alternate approach to effective and efficient information retrieval and knowledge discovery.

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A Framework for Q&A Community based Vertical Search (Q&A 커뮤니티 기반 전문영역 검색을 위한 프레임워크)

  • Jeong, Ok-Ran;Oh, Je-Hwan;Lee, Eun-Seok
    • The Journal of Society for e-Business Studies
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    • v.16 no.2
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    • pp.143-158
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    • 2011
  • This study suggests a framework which extracts features of collective intelligence from social Q&A community sites and takes advantage of those features upon vertical search for domain specific knowledge or information retrieval. One source of collective intelligence on the internet is the question and answer(Q&A) data available from many Q&A sites. Vertical search is focused on searching special areas or specific domains. This paper proposes a framework for extending the relevant terms by using Q&A information connected with query that the user wants to retrieve, and then applies them to specific domain field that requires professional and detailed knowledge.

Named Entity Recognition with Structural SVMs and Pegasos algorithm (Structural SVMs 및 Pegasos 알고리즘을 이용한 한국어 개체명 인식)

  • Lee, Chang-Ki;Jang, Myun-Gil
    • Korean Journal of Cognitive Science
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    • v.21 no.4
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    • pp.655-667
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    • 2010
  • The named entity recognition task is one of the most important subtasks in Information Extraction. In this paper, we describe a Korean named entity recognition using structural Support Vector Machines (structural SVMs) and modified Pegasos algorithm. Using the proposed approach, we could achieve an 85.43% F1 and an 86.79% F1 for 15 named entity types on TV domain and sports domain, respectively. Moreover, we reduced the training time to 4% without loss of performance compared to Conditional Random Fields (CRFs).

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Design of Markov Decision Process Based Dialogue Manager (마르코프 의사결정 과정에 기반한 대화 관리자 설계)

  • Choi, Joon-Ki;Eun, Ji-Hyun;Chang, Du-Seong;Kim, Hyun-Jeong;Koo, Myong-Wan
    • Proceedings of the KSPS conference
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    • 2006.11a
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    • pp.14-18
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    • 2006
  • The role of dialogue manager is to select proper actions based on observed environment and inferred user intention. This paper presents stochastic model for dialogue manager based on Markov decision process. To build a mixed initiative dialogue manager, we used accumulated user utterance, previous act of dialogue manager, and domain dependent knowledge as the input to the MDP. We also used dialogue corpus to train the automatically optimized policy of MDP with reinforcement learning algorithm. The states which have unique and intuitive actions were removed from the design of MDP by using the domain knowledge. The design of dialogue manager included the usage of natural language understanding and response generator to build short message based remote control of home networked appliances.

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A Study of Implementing Knowledge Management (KM) in Construction Domain (건설업 지식경영체제 구축에 관한 연구)

  • Park Min-Kyoo;Baek Jong-kun;Kim Dae-Ho;Kim Jae-Jun
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • autumn
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    • pp.273-278
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    • 2001
  • Since its introduction in mid 1990s, Financial Crisis in Korea, knowledge management (KM) has been considered as a new, optimal way of corporate management style. And a large number of researches, either theoretically or empirically, were carried out in order to find out what the key success factors will be in common. However, though key success factors are extracted, it can hardly be a successful project if those are not well matched for the unique industry characteristics, still more in construction industry. Even we can find some KM precedents in construction industry, it can hardly be revealed how far they exerted themselves in order to match key factors with industry characteristics. Hence, at the dawn of implementing KM, this research work will scrutinize key success factors (KSFs) derived from previous studies and funnel those KSFs into construction domain. Then rearranged KSFs will be proposed with each key issues. Therefore, this article can contribute to setting strategies for KM in construction sector.

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Reinforcement Learning Algorithm using Domain Knowledge for MAV (초소형 비행체 운항방법에 대한 환경 지식을 이용한 강화학습 방법)

  • Kim, Bong-Oh;Kong, Sung-Hak;Jang, Si-Young;Suh, Il-Hong;Oh, Sang-Rok
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2407-2409
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    • 2002
  • 강화학습이란 에이전트가 알려지지 않은 미지의 환경에서 행위와 보답을 주고받으며, 임의의 상태에서 가장 적절한 행위를 학습하는 방법이다. 만약 강화학습 중에 에이전트가 과거 문제들을 해결하면서 학습한 환경에 대한 지식을 이용할 수 있는 능력이 있다면 새로운 문제를 빠르게 해결할 수 있다. 이런 문제를 풀기 위한 방법으로 에이전트가 과거에 학습한 여러 문제들에 대한 환경 지식(Domain Knowledge)을 Local state feature라는 기억공간에 학습한 후 행위함수론 학습할 때 지식을 활용하는 방법이 연구되었다. 그러나 기존의 연구들은 주로 2차원 공간에 대한 연구가 진행되어 왔다. 본 논문에서는 환경 지식을 이용한 강화학습 알고리즘을 3차원 공간에 대해서도 수행 할 수 있도록하는 개선된 알고리즘을 제안하였으며, 제안된 알고리즘의 유효성을 검증하기 위해 초소형 비행체의 항공운항 학습에 대해 모의실험을 수행하였다.

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