• Title/Summary/Keyword: Semantic structure

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A Study on the Semantic Modeling of Manufacturing Facilities based on Status Definition and Diagnostic Algorithms (상태 정의 및 진단 알고리즘 기반 제조설비 시멘틱 모델링에 대한 연구)

  • Kwang-Jin, Kwak;Jeong-Min, Park
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.1
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    • pp.163-170
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    • 2023
  • This paper introduces the semantic modeling technology for autonomous control of manufacturing facilities and status definition algorithm. With the development of digital twin technology and various ICT technologies of the smart factory, a new production management model is being built in the manufacturing industry. Based on the advanced smart manufacturing technology, the status determination algorithm was presented as a methodology to quickly identify and respond to problems with autonomous control and facilities in the factory. But the existing status determination algorithm informs the user or administrator of error information through the grid map and is presented as a model for coping with it. However, the advancement and direction of smart manufacturing technology is diversifying into flexible production and production tailored to consumer needs. Accordingly, in this paper, a technology that can design and build a factory using a semantic-based Linked List data structure and provide only necessary information to users or managers through graph-based information is introduced to improve management efficiency. This methodology can be used as a structure suitable for flexible production and small-volume production of various types.

Deep Learning-based Pixel-level Concrete Wall Crack Detection Method (딥러닝 기반 픽셀 단위 콘크리트 벽체 균열 검출 방법)

  • Kang, Kyung-Su;Ryu, Han-Guk
    • Journal of the Korea Institute of Building Construction
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    • v.23 no.2
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    • pp.197-207
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    • 2023
  • Concrete is a widely used material due to its excellent compressive strength and durability. However, depending on the surrounding environment and the characteristics of the materials used in the construction, various defects may occur, such as cracks on the surface and subsidence of the structure. The detects on the surface of the concrete structure occur after completion or over time. Neglecting these cracks may lead to severe structural damage, necessitating regular safety inspections. Traditional visual inspections of concrete walls are labor-intensive and expensive. This research presents a deep learning-based semantic segmentation model designed to detect cracks in concrete walls. The model addresses surface defects that arise from aging, and an image augmentation technique is employed to enhance feature extraction and generalization performance. A dataset for semantic segmentation was created by combining publicly available and self-generated datasets, and notable semantic segmentation models were evaluated and tested. The model, specifically trained for concrete wall fracture detection, achieved an extraction performance of 81.4%. Moreover, a 3% performance improvement was observed when applying the developed augmentation technique.

Word Sense Distinction of Middle Verbs for Korean Verb Wordnet (한국어 동사의 어휘의미망 구축을 위한 중립동사의 의미분할)

  • Lee, Eunr-Young;Yoon, Ae-Sun
    • Language and Information
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    • v.9 no.2
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    • pp.23-48
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    • 2005
  • This study aims to discuss the word sense distinction of Korean middle verbs for restructuring KorLexVerb 1.0. Despite the duality of its meaning and syntactic structure, the word senses of middle verb are not clearly distinguished in current dictionaries. The underspecification causes very often mismatches that a same Korean word sense is used for two different English verb senses. A close examination on the syntactic and semantic properties of middle verb shows us that the word sense distinction and the reconstruction of hierarchical structure are indispensable. Finally, by doing this fine grained word sense distinction, we propose an alternative way of classification and description of the verb polysemy for KorLexVerb 1.0 as well as for dictionary-like language resources.

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A Cognitive Analysis on the Polysemous Perception Verbs (영어 지각동사의 인지적 연구)

  • 지인영
    • Lingua Humanitatis
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    • v.5
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    • pp.265-289
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    • 2003
  • This paper deals with the polysemous phenomenon of perception verbs in terms of metaphor and metonymy and suggest a model of cognitive semantic structure for them. English perception verbs are often used for representing a mental, cognitive activity as well as representing a physical, perceptive activity. This paper looks for a basis for the polysemous use in the creative system of metaphor and metonymy, especially in the meaning extension function of mind-as-body metaphor. English perception verbs show a good example of a metaphor of domain transfer from physical domain to mental or cognitive domain. This paper suggests the conceptual chain and the semantic structure for the perception verb to show the possibility of polysemy and contextual modulation.

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A Study on the Metadata Modeling for Research Result Information Using RDF/RDFS (RDF/RDFS를 이용한 연구성과물정보 메타데이터 모델링에 관한 연구)

  • Park, Dong-Jin
    • 한국디지털정책학회:학술대회논문집
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    • 2005.11a
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    • pp.383-389
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    • 2005
  • The purpose of this paper is to develop the metadata on the information of research result in Science and technology and to design the domain knowledge structure using semantic web technology for further implementation. In this paper, we first analyze the existing theories and techniques related to the metadata in such fields as R&D research result, international standard, and semantic web. Then, we extract and group the relevant factors from Dublin Core, CERIF, and the research results for building the integrated metadata framework. Based on our proposed metadata, we design a domain knowledge structure which employs RDF/RDFS as knowledge representation tool. Therefore, we can implement the ontology which produce the 'intelligent' information service and improve the interoperability between the research institutions. Also, the metadata can be used as the basis for developing National R&D Performance Information, and in terms of research institutions, can be used as tools for managing the their own research results information systematically and consistently.

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Enhancing Text Document Clustering Using Non-negative Matrix Factorization and WordNet

  • Kim, Chul-Won;Park, Sun
    • Journal of information and communication convergence engineering
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    • v.11 no.4
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    • pp.241-246
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    • 2013
  • A classic document clustering technique may incorrectly classify documents into different clusters when documents that should belong to the same cluster do not have any shared terms. Recently, to overcome this problem, internal and external knowledge-based approaches have been used for text document clustering. However, the clustering results of these approaches are influenced by the inherent structure and the topical composition of the documents. Further, the organization of knowledge into an ontology is expensive. In this paper, we propose a new enhanced text document clustering method using non-negative matrix factorization (NMF) and WordNet. The semantic terms extracted as cluster labels by NMF can represent the inherent structure of a document cluster well. The proposed method can also improve the quality of document clustering that uses cluster labels and term weights based on term mutual information of WordNet. The experimental results demonstrate that the proposed method achieves better performance than the other text clustering methods.

A study on Framework for Sharable Metadata Interoperability (메타데이터 상호운용을 위한 프레임워크)

  • Choi, O-Hoon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2004.05a
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    • pp.1449-1452
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    • 2004
  • It is necessary to resolve the syntax, structure and semantic heterogeneity for sharing information resources. And the representative technologies are XML and Metadata. XML has been used to represent the syntax and structure, and metadata has been used to represent the semantic meaning of information resources. However, various metadata sets in one or more domains that have been developed by each independent organizations without any standards or guidelines, make it difficult to share their information resource. In this paper, we propose an interoperability framework (FSMI, Framework for Sharable Metadata Interoperability) on MDR (Metadata Registry) to increase the interoperability of XML encoded information resources between systems using different metadata sets.

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USER-DEFINED PROPERTY SETS-BASED IFC EXTENSION FOR BRIDGE APPLICATION INFORMATION MODEL

  • Sang-Ho Lee;Sang Il Park;Munsu Yang
    • International conference on construction engineering and project management
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    • 2013.01a
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    • pp.433-436
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    • 2013
  • This study suggests IFC-based bridge information modeling methods and its application model in BIM environment. Data model extension for bridge structure was achieved using user-defined property sets based on IFC framework. First, identification information was added. Bridge members are identified through physical and spatial semantic information added as property sets. Instances for semantic information were assigned according to standardized rules. Second, CO2 related factors were added for application information model. It can play a role to calculate and manage the quantity of CO2 emission. Third, properties for temporary structure to estimate and manage the construction cost were added. Finally, we investigated proposed methods through implementing the application information model of bridges.

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Intelligent Shopping Agents Using Finite Domain Constraint under Semantic Web (의미웹에서 한정도메인 제약식을 이용한 지능형 쇼핑에이전트 : CD 쇼핑몰의 경우를 중심으로)

  • Kim, Hak-Jin;Lee, Myung Jin
    • Journal of Intelligence and Information Systems
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    • v.12 no.4
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    • pp.73-90
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    • 2006
  • When a consumer intends to purchase products through Internet stores, many difficulties are met because of limitations of the current search engines and the current web structure, and lack of tools supporting decision-makings. This paper raises an Internet shopping problem and proposes a framework of decision making process to settle it with an intelligent agent based on Semantic Web and Finite Domain Constraint. The agent uses finite domain constraint programming as modeling and solution methods for the decision problem under the Semantic Web environment.

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Semantic Image Segmentation Combining Image-level and Pixel-level Classification (영상수준과 픽셀수준 분류를 결합한 영상 의미분할)

  • Kim, Seon Kuk;Lee, Chil Woo
    • Journal of Korea Multimedia Society
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    • v.21 no.12
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    • pp.1425-1430
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    • 2018
  • In this paper, we propose a CNN based deep learning algorithm for semantic segmentation of images. In order to improve the accuracy of semantic segmentation, we combined pixel level object classification and image level object classification. The image level object classification is used to accurately detect the characteristics of an image, and the pixel level object classification is used to indicate which object area is included in each pixel. The proposed network structure consists of three parts in total. A part for extracting the features of the image, a part for outputting the final result in the resolution size of the original image, and a part for performing the image level object classification. Loss functions exist for image level and pixel level classification, respectively. Image-level object classification uses KL-Divergence and pixel level object classification uses cross-entropy. In addition, it combines the layer of the resolution of the network extracting the features and the network of the resolution to secure the position information of the lost feature and the information of the boundary of the object due to the pooling operation.